Substantive changes to physical habitat in the Lower Missouri River, resulting from intensive management, have been implicated in the decline of pallid (Scaphirhynchus albus) and shovelnose (S. platorynchus) sturgeon. To aid in habitat rehabilitation efforts, we evaluated habitat selection of gravid, female shovelnose sturgeon during the spawning season in two sections (lower and upper) of the Lower Missouri River in 2005 and in the upper section in 2007. We fit discrete choice models within an information theoretic framework to identify selection of means and variability in three components of physical habitat. Characterizing habitat within divisions around fish better explained selection than habitat values at the fish locations. In general, female shovelnose sturgeon were negatively associated with mean velocity between them and the bank and positively associated with variability in surrounding depths. For example, in the upper section in 2005, a 0.5 m s−1 decrease in velocity within 10 m in the bank direction increased the relative probability of selection 70%. In the upper section fish also selected sites with surrounding structure in depth (e.g., change in relief). Differences in models between sections and years, which are reinforced by validation rates, suggest that changes in habitat due to geomorphology, hydrology, and their interactions over time need to be addressed when evaluating habitat selection. Because of the importance of variability in surrounding depths, these results support an emphasis on restoring channel complexity as an objective of habitat restoration for shovelnose sturgeon in the Lower Missouri River.
","language":"English","publisher":"Springer- Verlag","doi":"10.1111/j.1439-0426.2010.01637.x","usgsCitation":"Bonnot, T., Wildhaber, M.L., Millspaugh, J., Delonay, A.J., Jacobson, R.B., and Bryan, J., 2011, Discrete choice modeling of shovelnose sturgeon habitat selection in the Lower Missouri River: Journal of Applied Ichthyology, v. 27, no. 2, p. 291-300, https://doi.org/10.1111/j.1439-0426.2010.01637.x.","productDescription":"10 p.","startPage":"291","endPage":"300","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":474974,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1439-0426.2010.01637.x","text":"Publisher Index Page"},{"id":243317,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215507,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1439-0426.2010.01637.x"}],"country":"United States","state":"Kansas, Missouri, Nebraska, South Dakota","otherGeospatial":"Lower Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.2197265625,\n 38.87392853923629\n ],\n [\n -91.77978515625,\n 39.487084981687495\n ],\n [\n -93.33984375,\n 39.50404070558415\n ],\n [\n -94.7021484375,\n 39.232253141714885\n ],\n [\n -94.7021484375,\n 38.75408327579141\n ],\n [\n -91.95556640625,\n 38.238180119798635\n ],\n [\n -90.263671875,\n 38.39333888832238\n ],\n [\n -90.2197265625,\n 38.87392853923629\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {\n \"stroke\": \"#555555\",\n \"stroke-width\": 2,\n \"stroke-opacity\": 1,\n \"fill\": \"#555555\",\n \"fill-opacity\": 0.5\n },\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.73486328124999,\n 41.32732632036622\n ],\n [\n -96.0479736328125,\n 42.020732852644294\n ],\n [\n -96.3555908203125,\n 42.593532625649935\n ],\n [\n -96.6412353515625,\n 42.52879629320373\n ],\n [\n -96.2127685546875,\n 41.53736603550382\n ],\n [\n -95.91064453125,\n 41.376808565702355\n ],\n [\n -95.73486328124999,\n 41.32732632036622\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.229248046875,\n 42.512601715736665\n ],\n [\n -97.294921875,\n 43.03677585761058\n ],\n [\n -97.62451171875,\n 42.871938424448466\n ],\n [\n -97.2454833984375,\n 42.5733097370664\n ],\n [\n -96.5478515625,\n 42.431565872579185\n ],\n [\n -96.229248046875,\n 42.512601715736665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-03-28","publicationStatus":"PW","scienceBaseUri":"505a01f5e4b0c8380cd4fdf8","contributors":{"authors":[{"text":"Bonnot, T.W.","contributorId":52705,"corporation":false,"usgs":true,"family":"Bonnot","given":"T.W.","email":"","affiliations":[],"preferred":false,"id":448925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":448926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Millspaugh, J.J.","contributorId":99105,"corporation":false,"usgs":true,"family":"Millspaugh","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":448928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeLonay, Aaron J. 0000-0002-3752-2799 adelonay@usgs.gov","orcid":"https://orcid.org/0000-0002-3752-2799","contributorId":2725,"corporation":false,"usgs":true,"family":"DeLonay","given":"Aaron","email":"adelonay@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":448924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":448927,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bryan, J.L.","contributorId":15328,"corporation":false,"usgs":true,"family":"Bryan","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":448923,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046492,"text":"70046492 - 2011 - Isotopic tracing of perchlorate in the environment","interactions":[],"lastModifiedDate":"2018-08-29T09:42:42","indexId":"70046492","displayToPublicDate":"2011-06-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Isotopic tracing of perchlorate in the environment","docAbstract":"Isotopic measurements can be used for tracing the sources and behavior of environmental contaminants. Perchlorate (ClO 4 − ) has been detected widely in groundwater, soils, fertilizers, plants, milk, and human urine since 1997, when improved analytical methods for analyzing ClO 4 −concentration became available for routine use. Perchlorate ingestion poses a risk to human health because of its interference with thyroidal hormone production. Consequently, methods for isotopic analysis of ClO 4 − have been developed and applied to assist evaluation of the origin and migration of this common contaminant. Isotopic data are now available for stable isotopes of oxygen and chlorine, as well as 36Cl isotopic abundances, in ClO 4 − samples from a variety of natural and synthetic sources. These isotopic data provide a basis for distinguishing sources of ClO 4 − found in the environment, and for understanding the origin of natural ClO 4 − . In addition, the isotope effects of microbial ClO 4 − reduction have been measured in laboratory and field experiments, providing a tool for assessing ClO 4 − attenuation in the environment. Isotopic data have been used successfully in some areas for identifying major sources of ClO 4 − contamination in drinking water supplies. Questions about the origin and global biogeochemical cycle of natural ClO 4 − remain to be addressed; such work would benefit from the development of methods for preparation and isotopic analysis of ClO 4 − in samples with low concentrations and complex matrices.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of environmental isotope geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-642-10637-8_22","isbn":"978-3-642-10636-1","usgsCitation":"Sturchio, N.C., Bohlke, J., Gu, B., Hatzinger, P., and Jackson, W.A., 2011, Isotopic tracing of perchlorate in the environment, chap. of Handbook of environmental isotope geochemistry, p. 437-452, https://doi.org/10.1007/978-3-642-10637-8_22.","productDescription":"16 p.","startPage":"437","endPage":"452","ipdsId":"IP-022737","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":342101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2011-06-30","publicationStatus":"PW","scienceBaseUri":"59366dade4b0f6c2d0d7d648","contributors":{"editors":[{"text":"Baskaran, Mark","contributorId":87867,"corporation":false,"usgs":false,"family":"Baskaran","given":"Mark","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":697108,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Sturchio, Neil C.","contributorId":149375,"corporation":false,"usgs":false,"family":"Sturchio","given":"Neil","email":"","middleInitial":"C.","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":697103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":697104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gu, Baohua","contributorId":15504,"corporation":false,"usgs":true,"family":"Gu","given":"Baohua","affiliations":[],"preferred":false,"id":697105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatzinger, Paul B.","contributorId":43204,"corporation":false,"usgs":true,"family":"Hatzinger","given":"Paul B.","affiliations":[],"preferred":false,"id":697106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, W. Andrew","contributorId":191113,"corporation":false,"usgs":false,"family":"Jackson","given":"W.","email":"","middleInitial":"Andrew","affiliations":[],"preferred":false,"id":697107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207965,"text":"70207965 - 2011 - Seasonal dynamics of CO2 profiles across a soil chronosequence, Santa Cruz, California","interactions":[],"lastModifiedDate":"2020-01-21T14:53:31","indexId":"70207965","displayToPublicDate":"2011-06-21T14:46:19","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal dynamics of CO2 profiles across a soil chronosequence, Santa Cruz, California","docAbstract":"Concentrations of CO2 in soil atmosphere and CO2 efflux were measured across a marine terrace soil chronosequence near Santa Cruz, California. Soil development, specifically the formation of an argillic horizon, has created a two-tier soil gas profile in the older terrace soils. The soil above the argillic horizon has seasonal variations in soil CO2 associated with plant respiration. The older soils with dense argillic horizons maintain a year round ∼1%CO2 below the argillic horizon. The CO2efflux during the growing season is higher on the older terraces.
To investigate rainfall-runoff conditions that generate post-wildfire debris flows, we instrumented and surveyed steep, small watersheds along the tectonically active front of the San Gabriel Mountains, California. Fortuitously, we recorded runoff-generated debris-flows triggered by one spatially restricted convective event with 28 mm of rainfall falling over 62 minutes. Our rain gages, nested hillslope overland-flow sensors and soil-moisture probes, as well as a time series of terrestrial laser scanning (TLS) revealed the effects of the storm. Hillslope overland-flow response, along two ~10-m long flow lines perpendicular to and originating from a drainage divide, displayed only a 10 to 20 minute delay from the onset of rainfall with accumulated totals of merely 5-10 mm. Depth-stratified soil-moisture probes displayed a greater time delay, roughly 20- 30 minutes, indicating that initial overland flow was Hortonian. Furthermore, a downstream channel-monitoring array recorded a pronounced discharge peak generated by the passage of a debris flow after 18 minutes of rainfall. At this time, only four of the eleven hillslope overlandflow sensors confirmed the presence of surface-water flow. Repeat TLS and detailed field mapping using GPS document how patterns of rainsplash, overland-flow scour, and rilling contributed to the generation of meter-scale debris flows. In response to a single small storm, the debris flows deposited irregular levees and lobate terminal snouts on hillslopes and caused widespread erosion of the valley axis with ground surface lowering exceeding 1.5 m.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Debris-flow hazards: Mitigation, mechanics, prediction, and assessment: Proceedings of 5th international conference: Padua, Italy, 14-17 June 2011","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"5th International Conference on Debris-Flow Hazards: Mitigation, Mechanics, Prediction and Assessment","conferenceDate":"June 14-17, 2011","conferenceLocation":"Padua, Italy","language":"English","publisher":"Università La Sapienza","usgsCitation":"Schmidt, K.M., Hanshaw, M.N., Howle, J.F., Kean, J.W., Staley, D.M., Stock, J., and Bawden, G.W., 2011, Hydrologic conditions and terrestrial laser scanning of post-fire debris flows in the San Gabriel Mountains, CA, U.S.A., in Debris-flow hazards: Mitigation, mechanics, prediction, and assessment: Proceedings of 5th international conference: Padua, Italy, 14-17 June 2011, Padua, Italy, June 14-17, 2011, 11 p.","productDescription":"11 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":307687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gabriel Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.41294849142349,\n 34.17134863412667\n ],\n [\n -117.38533697577557,\n 34.20370576214499\n ],\n [\n -117.44976384562082,\n 34.27028427873003\n ],\n [\n -117.46126864380744,\n 34.323509168688005\n ],\n [\n -117.54180223111402,\n 34.37100288463023\n ],\n [\n -117.74428667919865,\n 34.45073173493678\n ],\n [\n -117.93986824837137,\n 34.4621153654533\n ],\n [\n -117.97208168329401,\n 34.511426493466885\n ],\n [\n -118.09403254407232,\n 34.528488936462225\n ],\n [\n -118.14925557536819,\n 34.486774573614554\n ],\n [\n -118.2435949204986,\n 34.50573823590351\n ],\n [\n -118.30111891143193,\n 34.47729112517355\n ],\n [\n -118.42306977221028,\n 34.42795981878015\n ],\n [\n -118.48979760169273,\n 34.37290207362\n ],\n [\n -118.48979760169273,\n 34.33110997098939\n ],\n [\n -118.3540409830903,\n 34.289297039240125\n ],\n [\n -118.1952747681149,\n 34.20370576214499\n ],\n [\n -118.09863446334703,\n 34.17325233818043\n ],\n [\n -117.98588744111811,\n 34.14088353007017\n ],\n [\n -117.72357804246263,\n 34.11802749074337\n ],\n [\n -117.67985980935366,\n 34.138979096174396\n ],\n [\n -117.57171470639916,\n 34.14469226909128\n ],\n [\n -117.41294849142349,\n 34.17134863412667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e18634e4b05561fa206ac3","contributors":{"authors":[{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":570653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanshaw, M. 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These trails can remove vegetation, displace wildlife, alter hydrology, alter habitat, spread invasive species, and fragment landscapes. This study examines informal and formal trails within Great Falls Park, VA, a sub-unit of the George Washington Memorial Parkway, managed by the U.S. National Park Service. This study sought to answer three specific questions: 1) Are the physical characteristics and topographic alignments of informal trails significantly different from formal trails, 2) Can landscape fragmentation metrics be used to summarize the relative impacts of formal and informal trail networks on a protected natural area? and 3) What can we learn from examining the spatial distribution of the informal trails within protected natural areas? Statistical comparisons between formal and informal trails in this park indicate that informal trails have less sustainable topographic alignments than their formal counterparts. Spatial summaries of the lineal and areal extent and fragmentation associated with the trail networks by park management zones compare park management goals to the assessed attributes. 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Flood-frequency flows also are presented for 275 Florida streamgages used in the regional regression analysis. Regression relations used generalized least-squares regression techniques to estimate flood magnitude and frequency on ungaged streams as a function of basin drainage area and a storage factor. These regression equations were developed for four different hydrologic regions in Florida. The flood regions were delineated based on plotted residuals, previous flood-frequency studies, and geologic, physiographic, and drainage-area maps. The methods used in this report are based on flood-frequency characteristics for 305 streamgages including 275 in Florida and 30 in the adjacent states of Georgia and Alabama, all having at least 10 years of record through September 2006. For the larger streams outside the limits of the regression equations-the Apalachicola River and Suwannee River at Ellaville and below-the report includes graphical relations of peak flow to drainage area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115034","usgsCitation":"Verdi, R.J., and Dixon, J.F., 2011, Magnitude and frequency of floods for rural streams in Florida, 2006: U.S. Geological Survey Scientific Investigations Report 2011-5034, v, 20 p.; Appendices; 1 Plate: 36.00 x 36.00 inches; Supplementary Files, https://doi.org/10.3133/sir20115034.","productDescription":"v, 20 p.; Appendices; 1 Plate: 36.00 x 36.00 inches; Supplementary Files","startPage":"i","endPage":"20","numberOfPages":"25","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":116282,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5034.jpg"},{"id":21824,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5034/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","projection":"Universal Transverse Mercator projection","country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89,24 ], [ -89,31.5 ], [ -79,31.5 ], [ -79,24 ], [ -89,24 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db649521","contributors":{"authors":[{"text":"Verdi, Richard J. 0000-0002-7093-9203 rverdi@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9203","contributorId":1098,"corporation":false,"usgs":true,"family":"Verdi","given":"Richard","email":"rverdi@usgs.gov","middleInitial":"J.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dixon, Joann F. 0000-0001-9200-6407 jdixon@usgs.gov","orcid":"https://orcid.org/0000-0001-9200-6407","contributorId":1756,"corporation":false,"usgs":true,"family":"Dixon","given":"Joann","email":"jdixon@usgs.gov","middleInitial":"F.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true},{"id":269,"text":"FLWSC-Ft. 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Most suspended-sediment transport occurred during flooding caused by winter storms; 55 percent of the sediment load was transported by the river during a three-day flood in January 2010. Concentrations of polyaromatic hydrocarbons can exceed regulatory criteria during high-flow events in the San Lorenzo River. These results highlight the importance of episodic sediment and contaminant transport in steep, mountainous, coastal watersheds and emphasize the importance of understanding physical processes and quantifying chemical constituents in discharge from coastal watersheds on event-scale terms.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111120","usgsCitation":"Draut, A.E., Conaway, C., Echols, K.R., Storlazzi, C., and Ritchie, A., 2011, Suspended sediment and organic contaminants in the San Lorenzo River, California, water years 2009-2010: U.S. Geological Survey Open-File Report 2011-1120, iv, 24 p.; Tables Folder, https://doi.org/10.3133/ofr20111120.","productDescription":"iv, 24 p.; Tables Folder","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-10-01","temporalEnd":"2010-09-30","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":116284,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1120.gif"},{"id":21840,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1120/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.25,36.833333333333336 ], [ -122.25,37.416666666666664 ], [ -121.83333333333333,37.416666666666664 ], [ -121.83333333333333,36.833333333333336 ], [ -122.25,36.833333333333336 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae0e4b07f02db687ff6","contributors":{"authors":[{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":350709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conaway, Christopher H.","contributorId":52620,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[],"preferred":false,"id":350707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Echols, Kathy R. 0000-0003-2631-9143 kechols@usgs.gov","orcid":"https://orcid.org/0000-0003-2631-9143","contributorId":2799,"corporation":false,"usgs":true,"family":"Echols","given":"Kathy","email":"kechols@usgs.gov","middleInitial":"R.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":350705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":77889,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[],"preferred":false,"id":350708,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ritchie, Andrew","contributorId":35443,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","affiliations":[],"preferred":false,"id":350706,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157330,"text":"70157330 - 2011 - The role of critical zone processes in the evolution of the Prairie Pothole Region wetlands","interactions":[],"lastModifiedDate":"2021-10-27T16:07:30.335341","indexId":"70157330","displayToPublicDate":"2011-06-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"The role of critical zone processes in the evolution of the Prairie Pothole Region wetlands","docAbstract":"The Prairie Pothole Region, which occupies 900,000 km2 of the north central USA and south central Canada, is one of the most important ecosystems in North America. It is characterized by millions of small wetlands whose chemistry is highly variable over short distances. The study involved the geochemistry of surface sediments, wetland water, and groundwater in the Cottonwood Lakes area of North Dakota, USA, whose 92 ha includes the dominant wetland hydrologic settings. The data show that oxygenated groundwater interacting with pyrite resident in a component of surficial glacial till derived from the marine Pierre Shale Formation has, over long periods of time, focused SO 4 2 - -bearing fluids from upland areas to topographically low areas. In these low areas, SO 4 2 - -enriched groundwater and wetlands have evolved, as has the CaSO4 mineral gypsum. Sulfur isotope data support the conclusion that isotopically light pyrite from marine shale is the source of SO 4 2 - . Literature data on wetland water composition suggests that this process has taken place over a large area in North Dakota.
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It has long been considered a cold-water species, but has recently spread to lower latitudes and warmer waters, and increasingly forms large blooms that cover streambeds. We used a comprehensive monitoring data set from the National Park Service (NPS) and USGS models of stream temperatures to explore the drivers of didymo abundance in Glacier National Park. We estimate that approximately 64% of the stream length in the park contains didymo, with around 5% in a bloom state. Results suggest that didymo abundance likely increased over the study period (2007–2009), with blooms becoming more common. Our models suggest that didymo abundance is positively related to summer stream temperatures and negatively related to total nitrogen and the distance downstream from lakes. Regional climate model simulations indicate that stream temperatures in the park will likely continue to increase over the coming decades, which may increase the extent and severity of didymo blooms. As a result, didymo may be a useful indicator of thermal and hydrological modification associated with climate warming, especially in a relatively pristine system like Glacier where proximate human-related disturbances are absent or reduced. Glacier National Park plays an important role as a sentinel for climate change and associated education across the Rocky Mountain region.
","language":"English","publisher":"Park Science","usgsCitation":"Muhlfeld, C.C., Jones, L.A., E. William Schweiger, Ashton, I.W., and Bahls, L.L., 2011, The distribution and abundance ofa nuisance native alga, Didymosphenia geminata,in streams of Glacier National Park: Climate drivers and management implications: Park Science, v. 28, no. 2, p. 88-91.","productDescription":"4 p. ","startPage":"88","endPage":"91","ipdsId":"IP-028364","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":328407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.147705078125,\n 48.98382212608503\n ],\n [\n -113.54919433593749,\n 48.99103162515997\n ],\n [\n -113.0987548828125,\n 48.352598707539286\n ],\n [\n -113.741455078125,\n 48.19904897935913\n ],\n [\n -115.147705078125,\n 48.929717630629554\n ],\n [\n -115.147705078125,\n 48.98382212608503\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d28bafe4b0571647d0f94c","contributors":{"authors":[{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Leslie A. 0000-0002-4953-7189 lajones@usgs.gov","orcid":"https://orcid.org/0000-0002-4953-7189","contributorId":4599,"corporation":false,"usgs":true,"family":"Jones","given":"Leslie","email":"lajones@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"E. 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William Schweiger","affiliations":[{"id":16277,"text":"NPS Rocky Mountain Inventory & Monitoring Network","active":true,"usgs":false}],"preferred":false,"id":565543,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ashton, Isabel W.","contributorId":145875,"corporation":false,"usgs":false,"family":"Ashton","given":"Isabel","email":"","middleInitial":"W.","affiliations":[{"id":16277,"text":"NPS Rocky Mountain Inventory & Monitoring Network","active":true,"usgs":false}],"preferred":false,"id":565544,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bahls, Loren L.","contributorId":145876,"corporation":false,"usgs":false,"family":"Bahls","given":"Loren","email":"","middleInitial":"L.","affiliations":[{"id":16278,"text":"Montana Diatom Collection","active":true,"usgs":false}],"preferred":false,"id":565545,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70003319,"text":"70003319 - 2011 - Statistical Comparisons of watershed scale response to climate change in selected basins across the United States","interactions":[],"lastModifiedDate":"2019-06-21T15:48:51","indexId":"70003319","displayToPublicDate":"2011-05-31T13:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Statistical Comparisons of watershed scale response to climate change in selected basins across the United States","docAbstract":"In an earlier global climate-change study, air temperature and precipitation data for the entire twenty-first century simulated from five general circulation models were used as input to precalibrated watershed models for 14 selected basins across the United States. Simulated daily streamflow and energy output from the watershed models were used to compute a range of statistics. With a side-by-side comparison of the statistical analyses for the 14 basins, regional climatic and hydrologic trends over the twenty-first century could be qualitatively identified. Low-flow statistics (95% exceedance, 7-day mean annual minimum, and summer mean monthly streamflow) decreased for almost all basins. Annual maximum daily streamflow also decreased in all the basins, except for all four basins in California and the Pacific Northwest. An analysis of the supply of available energy and water for the basins indicated that ratios of evaporation to precipitation and potential evapotranspiration to precipitation for most of the basins will increase. Probability density functions (PDFs) were developed to assess the uncertainty and multimodality in the impact of climate change on mean annual streamflow variability. Kolmogorov?Smirnov tests showed significant differences between the beginning and ending twenty-first-century PDFs for most of the basins, with the exception of four basins that are located in the western United States. Almost none of the basin PDFs were normally distributed, and two basins in the upper Midwest had PDFs that were extremely dispersed and skewed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth Interactions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Meteorological Society","doi":"10.1175/2010EI364.1","usgsCitation":"Risley, J., Moradkhani, H., Hay, L.E., and Markstrom, S., 2011, Statistical Comparisons of watershed scale response to climate change in selected basins across the United States: Earth Interactions, v. 15, no. 14, p. 1-26, https://doi.org/10.1175/2010EI364.1.","productDescription":"26 p.","startPage":"1","endPage":"26","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":474997,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/2010ei364.1","text":"Publisher Index Page"},{"id":204268,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":110886,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1175/2010EI364.1"}],"country":"United States","volume":"15","issue":"14","noUsgsAuthors":false,"publicationDate":"2011-05-01","publicationStatus":"PW","scienceBaseUri":"4f4e49dee4b07f02db5e2a24","contributors":{"authors":[{"text":"Risley, John","contributorId":38128,"corporation":false,"usgs":true,"family":"Risley","given":"John","affiliations":[],"preferred":false,"id":346880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moradkhani, Hamid","contributorId":42344,"corporation":false,"usgs":true,"family":"Moradkhani","given":"Hamid","email":"","affiliations":[],"preferred":false,"id":346881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":346882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steve","contributorId":23682,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steve","affiliations":[],"preferred":false,"id":346879,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004514,"text":"sir20115008 - 2011 - Precipitation-runoff relations and water-quality characteristics at edge-of-field stations, Discovery Farms and Pioneer Farm, Wisconsin, 2003-8","interactions":[],"lastModifiedDate":"2015-12-23T11:51:14","indexId":"sir20115008","displayToPublicDate":"2011-05-27T19:09:29","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5008","title":"Precipitation-runoff relations and water-quality characteristics at edge-of-field stations, Discovery Farms and Pioneer Farm, Wisconsin, 2003-8","docAbstract":"A cooperative study between the U.S. Geological Survey, the University of Wisconsin (UW)-Madison Discovery Farms program (Discovery Farms), and the UW-Platteville Pioneer Farm program (Pioneer Farm) was developed to identify typical ranges and magnitudes, temporal distributions, and principal factors affecting concentrations and yields of sediment, nutrients, and other selected constituents in runoff from agricultural fields. Hydrologic and water-quality data were collected year-round at 23 edge-of-field monitoring stations on 5 privately owned Discovery Farms and on Pioneer Farm during water years 2003-8. The studied farms represented landscapes, soils, and farming systems typical of livestock farms throughout southern Wisconsin. Each farm employed a variety of soil, nutrient, and water-conservation practices to help minimize sediment and nutrient losses from fields and to improve crop productivity. This report summarizes the precipitation-runoff relations and water-quality characteristics measured in edge-of-field runoff for 26 \"farm years\" (aggregate years of averaged station data from all 6 farms for varying monitoring periods). A relatively wide range of constituents typically found in agricultural runoff were measured: suspended sediment, phosphorus (total, particulate, dissolved reactive, and total dissolved), and nitrogen (total, nitrate plus nitrite, organic, ammonium, total Kjeldahl and total Kjeldahl-dissolved), chloride, total solids, total suspended solids, total volatile suspended solids, and total dissolved solids.\n\nMean annual precipitation was 32.8 inches for the study period, about 3 percent less than the 30-year mean. Overall mean annual runoff was 2.55 inches per year (about 8 percent of precipitation) and the distribution was nearly equal between periods of frozen ground (54 percent) and unfrozen ground (46 percent). Mean monthly runoff was highest during two periods: February to March and May to June. Ninety percent of annual runoff occurred between January and the end of June.\n\nEvent mean concentrations of suspended sediment in runoff during unfrozen-ground periods were significantly higher (p<0.05) than those during frozen-ground periods. Mean annual suspended-sediment yields ranged from about 3 to nearly 5,000 pounds per acre (lb/acre), with a mean yield of 667 lb/acre. Ninety percent of suspended sediment was yielded in runoff during unfrozen-ground periods. May and June alone contributed more than 80 percent of the overall yield.\n\nPhosphorus concentrations and yields were also affected by the ground conditions at the time of runoff; however, unlike suspended sediment, phosphorus was usually available for transport in runoff regardless of ground condition. Mean annual total-phosphorus yields ranged from 0.03 to 7.0 lb/acre, with a mean yield of about 2.0 lb/acre. Nitrogen in runoff followed similar patterns to phosphorus in that concentrations were highest during unfrozen-ground periods, yields were highest during months of highest runoff, and speciation was affected by the ground conditions at the time of runoff. Mean annual total-nitrogen yields ranged from 0.11 to 19.2 lb/acre, and the mean was 7.2 lb/acre. Mean monthly total-nitrogen yields were strongly correlated with mean monthly total-phosphorus yields (r2= 0.92), indicating that the sources of nitrogen and phosphorus in runoff were likely similar.\n\nAnalysis of runoff, concentration, and yield data on annual, monthly, and seasonal time scales, when combined with precipitation, soil moisture, soil temperature, and on-farm field-activity information, revealed conditions in which runoff was most likely. The analysis also revealed the effects that field conditions and the timing of field-management activities-most notably, manure applications and tillage-had on the quantity and quality of surface runoff from agricultural fields.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115008","usgsCitation":"Stuntebeck, T.D., Komiskey, M.J., Peppler, M.C., Owens, D., and Frame, D.R., 2011, Precipitation-runoff relations and water-quality characteristics at edge-of-field stations, Discovery Farms and Pioneer Farm, Wisconsin, 2003-8: U.S. Geological Survey Scientific Investigations Report 2011-5008, vii, 46 p.; Appendices 1-5 in Excel format and Excel Comma Separated Values format, https://doi.org/10.3133/sir20115008.","productDescription":"vii, 46 p.; Appendices 1-5 in Excel format and Excel Comma Separated Values format","startPage":"i","endPage":"46","numberOfPages":"53","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":116609,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5008.jpg"},{"id":21817,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5008/","linkFileType":{"id":5,"text":"html"}}],"state":"Wisconsin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93,42 ], [ -93,48 ], [ -87,48 ], [ -87,42 ], [ -93,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad0e4b07f02db680852","contributors":{"authors":[{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Komiskey, Matthew J. 0000-0003-2962-6974 mjkomisk@usgs.gov","orcid":"https://orcid.org/0000-0003-2962-6974","contributorId":1776,"corporation":false,"usgs":true,"family":"Komiskey","given":"Matthew","email":"mjkomisk@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peppler, Marie C. 0000-0002-1120-9673 mpeppler@usgs.gov","orcid":"https://orcid.org/0000-0002-1120-9673","contributorId":825,"corporation":false,"usgs":true,"family":"Peppler","given":"Marie","email":"mpeppler@usgs.gov","middleInitial":"C.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":350537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owens, David W. dwowens@usgs.gov","contributorId":3745,"corporation":false,"usgs":true,"family":"Owens","given":"David W.","email":"dwowens@usgs.gov","affiliations":[{"id":676,"text":"Wisconsin Water Resource Division","active":false,"usgs":true}],"preferred":false,"id":350539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frame, Dennis R.","contributorId":77282,"corporation":false,"usgs":true,"family":"Frame","given":"Dennis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":350541,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157546,"text":"70157546 - 2011 - Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley","interactions":[],"lastModifiedDate":"2021-11-09T17:55:54.596127","indexId":"70157546","displayToPublicDate":"2011-05-26T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley","docAbstract":"California's Central Valley has been one of the most productive agricultural regions in the world for more than 50 years. To better understand the groundwater availability in the valley, the U.S. Geological Survey (USGS) developed the Central Valley hydrologic model (CVHM). Because of recent water-level declines and renewed subsidence, the CVHM is being updated to better simulate the geohydrologic system. The CVHM updates and refinements can be grouped into two general categories: (1) model code changes and (2) data updates. The CVHM updates and refinements will require that the model be recalibrated. The updated CVHM will provide a detailed transient analysis of changes in groundwater availability and flow paths in relation to climatic variability, urbanization, stream flow, and changes in irrigated agricultural practices and crops. The updated CVHM is particularly focused on more accurately simulating the locations and magnitudes of land subsidence. The intent of the updated CVHM is to help scientists better understand the availability and sustainability of water resources and the interaction of groundwater levels with land subsidence.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World environmental and water resources congress 2011: Bearing knowledge for sustainability","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2011","conferenceDate":"May 22-26 2011","conferenceLocation":"Palm Springs, California","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/41173(414)88","usgsCitation":"Faunt, C., Hanson, R.T., Martin, P., and Schmid, W., 2011, Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley, in World environmental and water resources congress 2011: Bearing knowledge for sustainability, Palm Springs, California, May 22-26 2011, p. 864-870, https://doi.org/10.1061/41173(414)88.","productDescription":"7 p.","startPage":"864","endPage":"870","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026942","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":308612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.11376953125,\n 35.17380831799959\n ],\n [\n -118.47656249999999,\n 36.35052700542763\n ],\n [\n -120.76171875,\n 38.87392853923629\n ],\n [\n -121.728515625,\n 40.17887331434696\n ],\n [\n -122.32177734375,\n 40.48038142908172\n ],\n [\n -122.56347656249999,\n 39.57182223734374\n ],\n [\n -121.6845703125,\n 37.94419750075404\n ],\n [\n -120.10253906249999,\n 36.01356058518153\n ],\n [\n -119.11376953125,\n 35.17380831799959\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2012-04-26","publicationStatus":"PW","scienceBaseUri":"56067036e4b058f706e51945","contributors":{"authors":[{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":1491,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":573555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":573558,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70005228,"text":"70005228 - 2011 - Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA","interactions":[],"lastModifiedDate":"2020-01-28T09:35:43","indexId":"70005228","displayToPublicDate":"2011-05-25T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA","docAbstract":"Effective monitoring programs are designed to track changes in the distribution, occurrence, and abundance of species. We developed an extension of Royle and Kéry's (2007) single species model to estimate simultaneously temporal changes in probabilities of detection, occupancy, colonization, extinction, and species turnover using data on calling anuran amphibians, collected from 2002 to 2006 in the Lower Mississippi Alluvial Valley of Louisiana, USA. During our 5-year study, estimates of occurrence probabilities declined for all 12 species detected. These declines occurred primarily in conjunction with variation in estimates of local extinction probabilities (cajun chorus frog [Pseudacris fouquettei], spring peeper [P. crucifer], northern cricket frog [Acris crepitans], Cope's gray treefrog [Hyla chrysoscelis], green treefrog [H. cinerea], squirrel treefrog [H. squirella], southern leopard frog [Lithobates sphenocephalus], bronze frog [L. clamitans], American bullfrog [L. catesbeianus], and Fowler's toad [Anaxyrus fowleri]). For 2 species (eastern narrowmouthed toad [Gastrophryne carolinensis] and Gulf Coast toad [Incilius nebulifer]), declines in occupancy appeared to be a consequence of both increased local extinction and decreased colonization events. The eastern narrow-mouthed toad experienced a 2.5-fold increase in estimates of occupancy in 2004, possibly because of the high amount of rainfall received during that year, along with a decrease in extinction and increase in colonization of new sites between 2003 and 2004. Our model can be incorporated into monitoring programs to estimate simultaneously the occupancy dynamics for multiple species that show similar responses to ecological conditions. It will likely be an important asset for those monitoring programs that employ the same methods to sample assemblages of ecologically similar species, including those that are rare. By combining information from multiple species to decrease the variance on estimates of individual species, our results are advantageous compared to single-species models. This feature enables managers and researchers to use an entire community, rather than just one species, as an ecological indicator in monitoring programs.","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.97","usgsCitation":"Walls, S., Waddle, J., and Dorazio, R.M., 2011, Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA: Journal of Wildlife Management, v. 75, no. 4, p. 751-761, https://doi.org/10.1002/jwmg.97.","productDescription":"11 p.","startPage":"751","endPage":"761","temporalStart":"2002-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":204251,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya Basin, Lower Mississippi Alluvial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.8731689453125,\n 29.89304338543419\n ],\n [\n -91.8731689453125,\n 30.576450026618076\n ],\n [\n -91.373291015625,\n 30.576450026618076\n ],\n [\n -91.373291015625,\n 29.89304338543419\n ],\n [\n -91.8731689453125,\n 29.89304338543419\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-05-25","publicationStatus":"PW","scienceBaseUri":"4f4e4a0ce4b07f02db5fc9db","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":52284,"corporation":false,"usgs":true,"family":"Walls","given":"Susan C.","affiliations":[],"preferred":false,"id":352105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":89982,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[],"preferred":false,"id":352106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorazio, Robert M. 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":1668,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":352104,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":99271,"text":"ofr20111073 - 2011 - Global multi-resolution terrain elevation data 2010 (GMTED2010)","interactions":[],"lastModifiedDate":"2012-02-10T00:11:58","indexId":"ofr20111073","displayToPublicDate":"2011-05-20T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1073","title":"Global multi-resolution terrain elevation data 2010 (GMTED2010)","docAbstract":"In 1996, the U.S. Geological Survey (USGS) developed a global topographic elevation model designated as GTOPO30 at a horizontal resolution of 30 arc-seconds for the entire Earth. Because no single source of topographic information covered the entire land surface, GTOPO30 was derived from eight raster and vector sources that included a substantial amount of U.S. Defense Mapping Agency data. The quality of the elevation data in GTOPO30 varies widely; there are no spatially-referenced metadata, and the major topographic features such as ridgelines and valleys are not well represented. Despite its coarse resolution and limited attributes, GTOPO30 has been widely used for a variety of hydrological, climatological, and geomorphological applications as well as military applications, where a regional, continental, or global scale topographic model is required. These applications have ranged from delineating drainage networks and watersheds to using digital elevation data for the extraction of topographic structure and three-dimensional (3D) visualization exercises (Jenson and Domingue, 1988; Verdin and Greenlee, 1996; Lehner and others, 2008). Many of the fundamental geophysical processes active at the Earth's surface are controlled or strongly influenced by topography, thus the critical need for high-quality terrain data (Gesch, 1994). U.S. Department of Defense requirements for mission planning, geographic registration of remotely sensed imagery, terrain visualization, and map production are similarly dependent on global topographic data.\r\n\r\nSince the time GTOPO30 was completed, the availability of higher-quality elevation data over large geographic areas has improved markedly. New data sources include global Digital Terrain Elevation Data (DTEDRegistered) from the Shuttle Radar Topography Mission (SRTM), Canadian elevation data, and data from the Ice, Cloud, and land Elevation Satellite (ICESat). Given the widespread use of GTOPO30 and the equivalent 30-arc-second DTEDRegistered level 0, the USGS and the National Geospatial-Intelligence Agency (NGA) have collaborated to produce an enhanced replacement for GTOPO30, the Global Land One-km Base Elevation (GLOBE) model and other comparable 30-arc-second-resolution global models, using the best available data. The new model is called the Global Multi-resolution Terrain Elevation Data 2010, or GMTED2010 for short. This suite of products at three different resolutions (approximately 1,000, 500, and 250 meters) is designed to support many applications directly by providing users with generic products (for example, maximum, minimum, and median elevations) that have been derived directly from the raw input data that would not be available to the general user or would be very costly and time-consuming to produce for individual applications. The source of all the elevation data is captured in metadata for reference purposes. It is also hoped that as better data become available in the future, the GMTED2010 model will be updated.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111073","usgsCitation":"Danielson, J.J., and Gesch, D.B., 2011, Global multi-resolution terrain elevation data 2010 (GMTED2010): U.S. Geological Survey Open-File Report 2011-1073, iv, 23 p.; Appendix, https://doi.org/10.3133/ofr20111073.","productDescription":"iv, 23 p.; Appendix","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116894,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1073.jpg"},{"id":204774,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1073/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abee4b07f02db674b19","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":307951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":307950,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":99270,"text":"sir20115046 - 2011 - Gulkana Glacier, Alaska-Mass balance, meteorology, and water measurements-1997-2001","interactions":[],"lastModifiedDate":"2024-01-16T22:51:26.939831","indexId":"sir20115046","displayToPublicDate":"2011-05-17T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5046","title":"Gulkana Glacier, Alaska-Mass balance, meteorology, and water measurements-1997-2001","docAbstract":"The measured winter snow, maximum winter snow, net, and annual balances for 1997-2001 in the Gulkana Glacier basin are determined at specific points and over the entire glacier area using the meteorological, hydrological, and glaciological data. We provide descriptions of glacier geometry to aid in estimation of conventional and reference surface mass balances and descriptions of ice motion to aid in the understanding of the glacier's response to its changing geometry. These data provide annual estimates for area altitude distribution, equilibrium line altitude, and accumulation area ratio during the study interval. New determinations of historical area altitude distributions are given for 1900 and annually from 1966 to 2001. As original weather instrumentation is nearing the end of its deployment lifespan, we provide new estimates of overlap comparisons and precipitation catch efficiency.\n\nDuring 1997-2001, Gulkana Glacier showed a continued and accelerated negative mass balance trend, especially below the equilibrium line altitude where thinning was pronounced. Ice motion also slowed, which combined with the negative mass balance, resulted in glacier retreat under a warming climate. Average annual runoff augmentation by glacier shrinkage for 1997-2001 was 25 percent compared to the previous average of 13 percent, in accordance with the measured glacier volume reductions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115046","usgsCitation":"March, R.S., and O’Neel, S., 2011, Gulkana Glacier, Alaska-Mass balance, meteorology, and water measurements-1997-2001: U.S. Geological Survey Scientific Investigations Report 2011-5046, viii, 70 p., https://doi.org/10.3133/sir20115046.","productDescription":"viii, 70 p.","additionalOnlineFiles":"N","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":424458,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_95192.htm","linkFileType":{"id":5,"text":"html"}},{"id":115729,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5046/","linkFileType":{"id":5,"text":"html"}},{"id":116114,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5046.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulkana Glacier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -145.33928137695307,\n 63.2999444760608\n ],\n [\n -145.5156977043993,\n 63.2999444760608\n ],\n [\n -145.5156977043993,\n 63.25130158823154\n ],\n [\n -145.33928137695307,\n 63.25130158823154\n ],\n [\n -145.33928137695307,\n 63.2999444760608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae5e4b07f02db68a792","contributors":{"authors":[{"text":"March, Rod S. rsmarch@usgs.gov","contributorId":416,"corporation":false,"usgs":true,"family":"March","given":"Rod","email":"rsmarch@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":307948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307949,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":99265,"text":"sir20115018 - 2011 - Recent (2008-10) concentrations and isotopic compositions of nitrate and concentrations of wastewater compounds in the Barton Springs zone, south-central Texas, and their potential relation to urban development in the contributing zone","interactions":[],"lastModifiedDate":"2016-08-11T15:47:08","indexId":"sir20115018","displayToPublicDate":"2011-05-17T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5018","title":"Recent (2008-10) concentrations and isotopic compositions of nitrate and concentrations of wastewater compounds in the Barton Springs zone, south-central Texas, and their potential relation to urban development in the contributing zone","docAbstract":"During 2008–10, the U.S. Geological Survey, in cooperation with the City of Austin, the City of Dripping Springs, the Barton Springs/Edwards Aquifer Conservation District, the Lower Colorado River Authority, Hays County, and Travis County, collected and analyzed water samples from five streams (Barton, Williamson, Slaughter, Bear, and Onion Creeks), two groundwater wells (Marbridge well [YD–58–50–704] and Buda well [LR–58–58–403]), and the main orifice of Barton Springs in Austin, Texas, with the objective of characterizing concentrations and isotopic compositions of nitrate and concentrations of wastewater compounds in the Barton Springs zone. The Barton Springs zone is in south-central Texas, an area undergoing rapid growth in population and in land area affected by development, with associated increases in wastewater generation. Over a period of 17 months, during which the hydrologic conditions transitioned from dry to wet, samples were collected routinely from the streams, wells, and spring and, in response to storms, from the streams and spring; some or all samples were analyzed for nitrate, nitrogen and oxygen isotopes of nitrate, and wastewater compounds. The median nitrate concentrations in routine samples from all sites were higher in samples collected during the wet period than in samples collected during the dry period, with the greatest difference for stream samples (0.05 milligram per liter during the dry period to 0.96 milligram per liter for the wet period). Nitrate concentrations in recent (2008–10) samples were elevated relative to concentrations in historical (1990–2008) samples from streams and from Barton Springs under medium- and high-flow conditions. Recent nitrate concentrations were higher than historical concentrations at the Marbridge well but the reverse was true at the Buda well. The elevated concentrations likely are related to the cessation of dry conditions coupled with increased nitrogen loading in the contributing watersheds. An isotopic composition of nitrate (delta nitrogen–15) greater than 8 per mil in many of the samples indicated there was a contribution of nitrate with a biogenic (human and or animal waste, or both) origin. Wastewater compounds measured in routine samples were detected infrequently (3 percent of cases), and concentrations were very low (less than the method reporting level in most cases). There was no correlation between nitrate concentrations and the frequency of detection of wastewater compounds, indicating that wastewater compounds might be undergoing removal during such processes as infiltration through soil. Three potential sources of biogenic nitrate to the contributing zone were considered: septic systems, land application of treated wastewater, and domesticated dogs and cats. During 2001–10, the estimated densities of septic systems and domesticated dogs and cats (number per acre) increased in the watersheds of all five creeks, and the rate of land application of treated wastewater (gallons per day per acre) increased in the watersheds of Barton, Bear, and Onion Creeks. Considering the timing and location of the increases in the three sources, septic systems were considered a likely source of increased nitrate to Bear Creek; land application of treated wastewater a likely source to Barton, Bear, and Onion Creeks; and domestic dogs and cats a potential source principally to Williamson Creek. The results of this investigation indicate that baseline water quality, in terms of nitrate, has shifted upward between 2001 and 2010, even without any direct discharges of treated wastewater to the creeks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115018","collaboration":"In cooperation with the City of Austin, City of Dripping Springs, Barton Springs/Edwards Aquifer Conservation District, Lower Colorado River Authority, Hays County, and Travis County","usgsCitation":"Mahler, B., Musgrove, M., Herrington, C., and Sample, T.L., 2011, Recent (2008-10) concentrations and isotopic compositions of nitrate and concentrations of wastewater compounds in the Barton Springs zone, south-central Texas, and their potential relation to urban development in the contributing zone: U.S. Geological Survey Scientific Investigations Report 2011-5018, vi, 39 p., https://doi.org/10.3133/sir20115018.","productDescription":"vi, 39 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":116955,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5018.gif"},{"id":115731,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5018/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","otherGeospatial":"Central Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.76458740234375,\n 30.267370168467806\n ],\n [\n -97.85385131835938,\n 30.322507751454424\n ],\n [\n -97.9266357421875,\n 30.322507751454424\n ],\n [\n -97.96783447265625,\n 30.31895142366329\n ],\n [\n -98.09074401855469,\n 30.30294635121175\n ],\n [\n -98.16215515136719,\n 30.278044377800153\n ],\n [\n -98.21090698242188,\n 30.234154095850688\n ],\n [\n -98.23219299316406,\n 30.17599895913958\n ],\n [\n -98.14224243164062,\n 30.073253543030656\n ],\n [\n -97.88200378417969,\n 30.023921574501376\n ],\n [\n -97.73574829101562,\n 30.248984087355694\n ],\n [\n -97.76458740234375,\n 30.267370168467806\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a7ee4b07f02db64864e","contributors":{"authors":[{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":307936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrington, Chris","contributorId":9221,"corporation":false,"usgs":true,"family":"Herrington","given":"Chris","email":"","affiliations":[],"preferred":false,"id":307934,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sample, Thomas L.","contributorId":24902,"corporation":false,"usgs":true,"family":"Sample","given":"Thomas","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":307935,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":99264,"text":"fs20113014 - 2011 - Using models for the optimization of hydrologic monitoring","interactions":[],"lastModifiedDate":"2012-03-08T17:16:13","indexId":"fs20113014","displayToPublicDate":"2011-05-17T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-3014","title":"Using models for the optimization of hydrologic monitoring","docAbstract":"Hydrologists are often asked what kind of monitoring network can most effectively support science-based water-resources management decisions. Currently (2011), hydrologic monitoring locations often are selected by addressing observation gaps in the existing network or non-science issues such as site access. A model might then be calibrated to available data and applied to a prediction of interest (regardless of how well-suited that model is for the prediction). However, modeling tools are available that can inform which locations and types of data provide the most 'bang for the buck' for a specified prediction. Put another way, the hydrologist can determine which observation data most reduce the model uncertainty around a specified prediction.\r\n\r\nAn advantage of such an approach is the maximization of limited monitoring resources because it focuses on the difference in prediction uncertainty with or without additional collection of field data. Data worth can be calculated either through the addition of new data or subtraction of existing information by reducing monitoring efforts (Beven, 1993). The latter generally is not widely requested as there is explicit recognition that the worth calculated is fundamentally dependent on the prediction specified. If a water manager needs a new prediction, the benefits of reducing the scope of a monitoring effort, based on an old prediction, may be erased by the loss of information important for the new prediction.\r\n\r\nThis fact sheet focuses on the worth or value of new data collection by quantifying the reduction in prediction uncertainty achieved be adding a monitoring observation. This calculation of worth can be performed for multiple potential locations (and types) of observations, which then can be ranked for their effectiveness for reducing uncertainty around the specified prediction. This is implemented using a Bayesian approach with the PREDUNC utility in the parameter estimation software suite PEST (Doherty, 2010).\r\n\r\nThe techniques briefly described earlier are described in detail in a U.S. Geological Survey Scientific Investigations Report available on the Internet (Fienen and others, 2010; http://pubs.usgs.gov/sir/2010/5159/). This fact sheet presents a synopsis of the techniques as applied to a synthetic model based on a model constructed using properties from the Lake Michigan Basin (Hoard, 2010).","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20113014","collaboration":"National Water Availability and Use Pilot Program","usgsCitation":"Fienen, M., Hunt, R.J., Doherty, J.E., and Reeves, H.W., 2011, Using models for the optimization of hydrologic monitoring: U.S. Geological Survey Fact Sheet 2011-3014, 6 p., https://doi.org/10.3133/fs20113014.","productDescription":"6 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":116954,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3014.jpg"},{"id":204768,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3014/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db602eb1","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":307929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, John E.","contributorId":8817,"corporation":false,"usgs":false,"family":"Doherty","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":7046,"text":"Watermark Numerical Computing","active":true,"usgs":false}],"preferred":false,"id":307932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307931,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":9001500,"text":"sir20095120 - 2011 - Borehole geophysical investigation of a formerly used defense site, Machiasport, Maine, 2003-2006","interactions":[],"lastModifiedDate":"2019-10-24T14:19:42","indexId":"sir20095120","displayToPublicDate":"2011-05-12T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5120","title":"Borehole geophysical investigation of a formerly used defense site, Machiasport, Maine, 2003-2006","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, collected borehole geophysical logs in 18 boreholes and interpreted the data along with logs from 19 additional boreholes as part of an ongoing, collaborative investigation at three environmental restoration sites in Machiasport, Maine. These sites, located on hilltops overlooking the seacoast, formerly were used for military defense. At each of the sites, chlorinated solvents, used as part of defense-site operations, have contaminated the fractured-rock aquifer. Borehole geophysical techniques and hydraulic methods were used to characterize bedrock lithology, fractures, and hydraulic properties. In addition, each geophysical method was evaluated for effectiveness for site characterization and for potential application for further aquifer characterization and (or) evaluation of remediation efforts. Results of borehole geophysical logging indicate the subsurface is highly fractured, metavolcanic, intrusive, metasedimentary bedrock. Selected geophysical logs were cross-plotted to assess correlations between rock properties. These plots included combinations of gamma, acoustic reflectivity, electromagnetic induction conductivity, normal resistivity, and single-point resistance. The combined use of acoustic televiewer (ATV) imaging and natural gamma logs proved to be effective for delineating rock types. Each of the rock units in the study area could be mapped in the boreholes, on the basis of the gamma and ATV reflectivity signatures. The gamma and mean ATV reflectivity data were used along with the other geophysical logs for an integrated interpretation, yielding a determination of quartz monzonite, rhyolite, metasedimentary units, or diabase/gabbro rock types. The interpretation of rock types on the basis of the geophysical logs compared well to drilling logs and geologic mapping. These results may be helpful for refining the geologic framework at depth. A stereoplot of all fractures intersecting the boreholes indicates numerous fractures, a high proportion of steeply dipping fractures, and considerable variation in fracture orientation. Low-dip-angle fractures associated with unloading and exfoliation are also present, especially at a depth of less than 100 feet below the top of casing. These sub-horizontal fractures help to connect the steeply dipping fractures, making this a highly connected fracture network. The high variability in the fracture orientations also increases the connectivity of the fracture network. A preliminary comparison of all fracture data from all the boreholes suggests fracturing decreases with depth. Because all the boreholes were not drilled to the same depth, however, there is a clear sampling bias. Hence, the deepest boreholes are analyzed separately for fracture density. For the deepest boreholes in the study, the intensity of fracturing does not decline significantly with depth. It is possible the fractures observed in these boreholes become progressively tighter or closed with depth, but this is difficult to verify with the borehole methods used in this investigation. The fact that there are more sealed fractures at depth (observed in optical televiewer logs in some of the boreholes) may indicate less opening of the sealed fractures, less water moving through the rock, and less weathering of the fracture infilling minerals. Although the fracture orientation remained fairly constant with depth, differences in the fracture patterns for the three restoration sites indicate the orientation of fractures varies across the study area. The fractures in boreholes on Miller Mountain predominantly strike northwest-southeast, and to a lesser degree they strike northeast. The fractures on or near the summit of Howard Mountain strike predominantly east-west and dip north and south, and the fractures near the Transmitter Site strike northeast-southwest and dip northwest and southeast. The fracture populations for the boreholes on or near the summit of Howard Mountain show more variation than at the other two sites. This variation may be related to the proximity of the fault, which is northeast of the summit of Howard Mountain. In a side-by-side comparison of stereoplots from selected boreholes, there was no clear correspondence between fracture orientation and proximity to the fault. There is, however, a difference in the total populations of fractures for the boreholes on or near the summit of Howard Mountain and the boreholes near the Transmitter Site. Further to the southwest and further away from the fault, the fractures at the Transmitter Site predominantly strike northeast-southwest and northwest-southeast.Heat-pulse flowmeter (HPFM) logging was used to identify transmissive fractures and to estimate the hydraulic properties along the boreholes. Ambient downflow was measured in 13 boreholes and ambient upflow was measured in 9 boreholes. In nine other bedrock boreholes, the HPFM did not detect measurable vertical flow. The observed direction of vertical flow in the boreholes generally was consistent with the conceptual flow model of downward movement in recharge locations and upward flow in discharge locations or at breaks in the slope of land surface. Under low-rate pumping or injection rates [0.25 to 1 gallon per minute (gal/min)], one to three inflow zones were identified in each borehole. Two limitations of HPFM methods are (1) the HPFM can only identify zones within 1.5 to 2 orders of magnitude of the most transmissive zone in each borehole, and (2) the HPFM cannot detect flow rates less than 0.010 + or - 0.005 gal/min, which corresponds to a transmissivity of about 1 foot squared per day (ft2/d). Consequently, the HPFM is considered an effective tool for identifying the most transmissive fractures in a borehole, down to its detection level. Transmissivities below that cut-off must be measured with another method, such as packer testing or fluid-replacement logging. Where sufficient water-level and flowmeter data were available, HPFM results were numerically modeled. For each borehole model, the fracture location and measured flow rates were specified, and the head and transmissivity of each fracture zone were adjusted until a model fit was achieved with the interpreted ambient and stressed flow profiles. The transmissivities calculated by this method are similar to the results of an open-hole slug test; with the added information from the flowmeter, however, the head and transmissivity of discrete zones also can be determined. The discrete-interval transmissivities ranged from 0.16 to 330 ft2/d. The flowmeter-derived open-hole transmissivity, which is the combined total of each of the transmissive zones, ranged from 1 to 511 ft2/d. The whole-well open-hole transmissivity values determined with HPFM methods were compared to the results of open-hole hydraulic tests. Despite the fact that the flowmeter-derived transmissivities consistently were lower than the estimates derived from open-hole hydraulic tests alone, the correlation was very strong (with a coefficient of determination, R2, of 0.9866), indicating the HPFM method provides a reasonable estimate of transmissivities for the most transmissive fractures in the borehole. Geologic framework, fracture characterization, and estimates of hydraulic properties were interpreted together to characterize the fracture network. The data and interpretation presented in this report should provide information useful for site investigators as the conceptual site groundwater flow model is refined. Collectively, the results and the conceptual site model are important for evaluating remediation options and planning or implementing the design of a well field and borehole completions that will be adequate for monitoring flow, remediation efforts, groundwater levels, and (or) water quality. Similar kinds of borehole geophysical logging (specifically the borehole imaging, gamma, fluid logs, and HPFM) should be conducted in any newly installed boreholes and integrated with interpretations of any nearby boreholes. If boreholes are installed close to existing or other new boreholes, cross-hole flowmeter surveys may be appropriate and may help characterize the aquifer properties and connections between the boreholes.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095120","collaboration":"Prepared in cooperation with the\r\nU.S. Army Corps of Engineers, New England District","usgsCitation":"Johnson, C.D., Mondazzi, R.A., and Joesten, P.K., 2011, Borehole geophysical investigation of a formerly used defense site, Machiasport, Maine, 2003-2006: U.S. Geological Survey Scientific Investigations Report 2009-5120, Report: viii, 75 p.; 6 Appendixes, https://doi.org/10.3133/sir20095120.","productDescription":"Report: viii, 75 p.; 6 Appendixes","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2003-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":37277,"text":"WMA - 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Researchers gathered baseline information on hydrology, temperature, habitat, nearshore wetlands, and macroinvertebrate and fish communities and assessed the behavior and thermoregulation of stocked brown trout in study reaches from both rivers and from a control river. The effects of recreational-flow releases (releases) were assessed by comparing data from affected reaches with data from the same reaches during nonrelease days, control reaches in a nearby run-of-the-river system (the Cedar River), and one reach in the Hudson River upstream from the confluence with the Indian River. A streamgage downstream from Lake Abanakee transmitted data by satellite from November 2004 to November 2006; these data were used as the basis for developing a rating curve that was used to estimate discharges for the study period. River habitat at most study reaches was delineated by using Global Positioning System and ArcMap software on a handheld computer, and wetlands were mapped by ground-based measurements of length, width, and areal density. River temperature in the Indian and Hudson Rivers was monitored continuously at eight sites during June through September of 2005 and 2006; temperature was mapped in 2005 by remote imaging made possible through collaboration with the Rochester Institute of Technology. Fish communities at all study reaches were surveyed and characterized through quantitative, nearshore electrofishing surveys. Macroinvertebrate communities in all study reaches were sampled using the traveling-kick method and characterized using standard indices. Radio telemetry was used to track the movement and persistence of stocked brown trout (implanted with temperature-sensitive transmitters) in the Indian and Hudson Rivers during the summer of 2005 and in all three rivers during the summer of 2006. The releases had little effect on river temperatures, but increased discharges by about one order of magnitude. Regardless of the releases, river temperatures at all study sites commonly exceeded the threshold known to be stressful to brown trout. At most sites, mean and median water temperatures on release days were not significantly different, or slightly lower, than water temperatures on nonrelease days. Most differences were very small and, thus, were probably not biologically meaningful. The releases generally increased the total surface area of fast-water habitat (rapids, runs, and riffles) and decreased the total surface area of slow-water habitat (pools, glides, backwater areas, and side channels). The total surface areas of wetlands bordering the Indian River were substantially smaller than the surface areas bordering the Cedar River; however, no channel geomorphology or watershed soil and topographic data were assessed to determine whether the releases or other factors were mainly responsible for observed differences. Results from surveys of resident biota indicate that the releases generally had a limited effect on fish and macroinvertebrate communities in the Indian River and had no effect on communities in the Hudson River. Compared to fish data from Cedar River control sites, the impoundment appeared to reduce total density, biomass, and richness in the Indian River at the first site downstream from Lake Abanakee, moderately reduce the indexes at the other two sites on the Indian River, and slightly reduce the indexes at the first Hudson River site downstream from the confluence with the Indian River. The densities of individual fish populations at all Indian River sites were also reduced, but related effects on fish populations in the Hudson River were less evident. Altho
","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105223","collaboration":"Prepared in cooperation with the\r\nNew York State Department of Environmental Conservation","usgsCitation":"Baldigo, B., Mulvihill, C., Ernst, A., and Boisvert, B., 2011, Effects of recreational flow releases on natural resources of the Indian and Hudson Rivers in the Central Adirondack Mountains, New York, 2004-06: U.S. Geological Survey Scientific Investigations Report 2010-5223, xix, 72 p., https://doi.org/10.3133/sir20105223.","productDescription":"xix, 72 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":116926,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5223.gif"},{"id":14669,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5223/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a29e4b07f02db611998","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":25174,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulvihill, C.I.","contributorId":17350,"corporation":false,"usgs":true,"family":"Mulvihill","given":"C.I.","email":"","affiliations":[],"preferred":false,"id":307876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ernst, A.G.","contributorId":8973,"corporation":false,"usgs":true,"family":"Ernst","given":"A.G.","email":"","affiliations":[],"preferred":false,"id":307875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boisvert, B.A.","contributorId":79601,"corporation":false,"usgs":true,"family":"Boisvert","given":"B.A.","email":"","affiliations":[],"preferred":false,"id":307878,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":99252,"text":"fs20103105 - 2011 - Understanding processes affecting mineral deposits in humid environments","interactions":[],"lastModifiedDate":"2018-10-15T09:05:09","indexId":"fs20103105","displayToPublicDate":"2011-05-10T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-3105","title":"Understanding processes affecting mineral deposits in humid environments","docAbstract":"Recent interdisciplinary studies by the U.S. Geological Survey have resulted in substantial progress toward understanding the influence that climate and hydrology have on the geochemical signatures of mineral deposits and the resulting mine wastes in the eastern United States. Specific areas of focus include the release, transport, and fate of acid, metals, and associated elements from inactive mines in temperate coastal areas and of metals from unmined mineral deposits in tropical to subtropical areas; the influence of climate, geology, and hydrology on remediation options for abandoned mines; and the application of radiogenic isotopes to uniquely apportion source contributions that distinguish natural from mining sources and extent of metal transport.\r\n\r\nThe environmental effects of abandoned mines and unmined mineral deposits result from a complex interaction of a variety of chemical and physical factors. These include the geology of the mineral deposit, the hydrologic setting of the mineral deposit and associated mine wastes, the chemistry of waters interacting with the deposit and associated waste material, the engineering of a mine as it relates to the reactivity of mine wastes, and climate, which affects such factors as temperature and the amounts of precipitation and evapotranspiration; these factors, in turn, influence the environmental behavior of mineral deposits. The role of climate is becoming increasingly important in environmental investigations of mineral deposits because of the growing concerns about climate change. ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103105","usgsCitation":"Seal, R., and Ayuso, R.A., 2011, Understanding processes affecting mineral deposits in humid environments: U.S. Geological Survey Fact Sheet 2010-3105, 6 p., https://doi.org/10.3133/fs20103105.","productDescription":"6 p.","additionalOnlineFiles":"N","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":116947,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3105.gif"},{"id":14668,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3105/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49dde4b07f02db5e2433","contributors":{"authors":[{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":307873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":307874,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":99249,"text":"fs20113037 - 2011 - Enhancement of USGS scientific investigations in Texas by using geophysical techniques, 2005-10","interactions":[],"lastModifiedDate":"2016-08-11T15:48:55","indexId":"fs20113037","displayToPublicDate":"2011-05-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-3037","title":"Enhancement of USGS scientific investigations in Texas by using geophysical techniques, 2005-10","docAbstract":"Geophysical techniques are an increasingly important tool for scientific investigations, environmental planning, and resource management. During 2005-10 the U.S. Geological Survey Texas Water Science Center greatly expanded its capabilities of using surface and borehole geophysical techniques to gain insights into how groundwater systems work and the occurrence and distribution of certain contaminants. Geophysical techniques provide a relatively quick and inexpensive means to characterize the subsurface hydrology and lithology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Virginia","doi":"10.3133/fs20113037","usgsCitation":"Stanton, G.P., Payne, J., Teeple, A., and Thomas, J.V., 2011, Enhancement of USGS scientific investigations in Texas by using geophysical techniques, 2005-10: U.S. Geological Survey Fact Sheet 2011-3037, 4 p., https://doi.org/10.3133/fs20113037.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":116082,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3037.gif"},{"id":14665,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3037/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db6026b0","contributors":{"authors":[{"text":"Stanton, Gregory P. 0000-0001-8622-0933 gstanton@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-0933","contributorId":1583,"corporation":false,"usgs":true,"family":"Stanton","given":"Gregory","email":"gstanton@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":307864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Payne, Jason 0000-0003-4294-7924 jdpayne@usgs.gov","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":1062,"corporation":false,"usgs":true,"family":"Payne","given":"Jason ","email":"jdpayne@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":307862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":1399,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew ","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":307863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307865,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}