This study investigated the potential for the uranium mineral carnotite (K2(UO2)2(VO4)2·3H2O) to precipitate from evaporating groundwater in the Texas Panhandle region of the United States. The evolution of groundwater chemistry during evaporation was modeled with the USGS geochemical code PHREEQC using water-quality data from 100 groundwater wells downloaded from the USGS National Water Information System (NWIS) database. While most modeled groundwater compositions precipitated calcite upon evaporation, not all groundwater became saturated with respect to carnotite with the system open to CO2. Thus, the formation of calcite is not a necessary condition for carnotite to form. Rather, the determining factor in achieving carnotite saturation was the evolution of groundwater chemistry during evaporation following calcite precipitation. Modeling in this study showed that if the initial major-ion groundwater composition was dominated by calcium-magnesium-sulfate (>70 precent Ca + Mg and >50 percent SO4 + Cl) or calcium-magnesium-bicarbonate (>70 percent Ca + Mg and <70 percent HCO3 + CO3) and following the precipitation of calcite, the concentration of calcium was greater than the carbonate alkalinity (2mCa+2 > mHCO3− + 2mCO3−2) carnotite saturation was achieved. If, however, the initial major-ion groundwater composition is sodium-bicarbonate (varying amounts of Na, 40–100 percent Na), calcium-sodium-sulfate, or calcium-magnesium-bicarbonate composition (>70 percent HCO3 + CO3) and following the precipitation of calcite, the concentration of calcium was less than the carbonate alkalinity (2mCa+2 < mHCO3- + 2mCO3−2) carnotite saturation was not achieved. In systems open to CO2, carnotite saturation occurred in most samples in evaporation amounts ranging from 95 percent to 99 percent with the partial pressure of CO2 ranging from 10−3.5 to 10−2.5 atm. Carnotite saturation occurred in a few samples in evaporation amounts ranging from 98 percent to 99 percent with the partial pressure of CO2 equal to 10−2.0 atm. Carnotite saturation did not occur in any groundwater with the system closed to CO2.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.08.004","usgsCitation":"Ranalli, A.J., and Yager, D.B., 2016, Use of mineral/solution equilibrium calculations to assess the potential for carnotite precipitation from groundwater in the Texas Panhandle, USA: Applied Geochemistry, v. 73, p. 118-131, https://doi.org/10.1016/j.apgeochem.2016.08.004.","productDescription":"14 p.","startPage":"118","endPage":"131","ipdsId":"IP-069663","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":335173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.07373046875,\n 33.925129700072\n ],\n [\n -103.07373046875,\n 36.50963615733049\n ],\n [\n -99.97558593749999,\n 36.50963615733049\n ],\n [\n -99.97558593749999,\n 33.925129700072\n ],\n [\n -103.07373046875,\n 33.925129700072\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"589fff23e4b099f50d3e0450","contributors":{"authors":[{"text":"Ranalli, Anthony J. tranalli@usgs.gov","contributorId":1195,"corporation":false,"usgs":true,"family":"Ranalli","given":"Anthony","email":"tranalli@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":663275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Douglas B. 0000-0001-5074-4022 dyager@usgs.gov","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":798,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","email":"dyager@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":663274,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178310,"text":"70178310 - 2016 - Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction","interactions":[],"lastModifiedDate":"2019-09-06T11:17:58","indexId":"70178310","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction","docAbstract":"Land subsidence includes both gentle downwarping and sudden sinking of\nsegments of the land surface. Major anthropogenic causes of land subsidence\nare extraction of fluids including water, oil, and gas. Measurement and detec-\ntion of land subsidence include both ground-based and remotely sensed air-\nborne and space-based methods. Methods for measurement of subsidence at\npoints include differential leveling, global positioning system surveys, and\nextensometers. Satellite-borne differential interferometric synthetic aperture\nradar and airborne LiDAR techniques can detect land-surface movement over\nwide areas of interest. Aquifer-system compaction and subsidence owing to\ngroundwater extraction typically occurs in areas of unconsolidated alluvial or\nbasin-fill aquifer systems comprising aquifers and aquitards. Approaches to\nanalyzing and modeling deformation of aquifer systems follow from the basic\nrelations between head, stress, compressibility, and groundwater flow.\nAnalysis and simulation of aquifer-system compaction have been addressed\nprimarily using either an approach based on conventional groundwater flow\ntheory or an approach based on linear poroelasticity theory. Both approaches\nrely on the principle of effective stress outlined by Karl Terzaghi in 1925. In\nthe approach based on conventional groundwater flow theory, an aquitard\ndrainage model explains the compaction of fine grained material using the\nprinciple of effective stress and theory of hydrodynamic lag. Packages for the\nwidely-used MODFLOW groundwater model are available to simulate aqui-\nfer-system compaction and land subsidence using the aquitard-drainage\napproach. Poroelasticity theory describes the more fully coupled processes of\ngroundwater flow and three-dimensional deformation of aquifer systems.\nThe general theory accounts for compressible fluid, porous matrix and solid\ngrains. Simulation codes using the poroelastic theory include some commer-\ncial software products and a few research codes.","largerWorkTitle":"Handbook of applied hydrology","language":"English","publisher":"McGraw-Hill Education","isbn":"9780071835091","usgsCitation":"Galloway, D.L., and Leake, S.A., 2016, Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction, chap. of Handbook of applied hydrology, p. 56.1-56.11.","productDescription":"11 p.","startPage":"56.1","endPage":"56.11","ipdsId":"IP-066741","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":337768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58cba41ae4b0849ce97dc744","contributors":{"editors":[{"text":"Singh, Vijay P.","contributorId":176741,"corporation":false,"usgs":false,"family":"Singh","given":"Vijay","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":684832,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":653592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leake, Stanley A. 0000-0003-3568-2542 saleake@usgs.gov","orcid":"https://orcid.org/0000-0003-3568-2542","contributorId":1846,"corporation":false,"usgs":true,"family":"Leake","given":"Stanley","email":"saleake@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653593,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178430,"text":"70178430 - 2016 - Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","interactions":[],"lastModifiedDate":"2017-04-19T11:49:02","indexId":"70178430","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","docAbstract":"The east-central Great Basin near the Utah-Nevada border contains two great \ngroundwater flow systems. The first, the White River regional groundwater \nflow system, consists of a string of hydraulically connected hydrographic basins \nin Nevada spanning about 270 miles from north to south. The northernmost \nbasin is Long Valley and the southernmost basin is the Black Mountain area, a \nvalley bordering the Colorado River. The general regional groundwater flow \ndirection is north to south. The second flow system, the Great Salt Lake Desert \nregional groundwater flow system, consists of hydrographic basins that straddle\nthe Utah-Nevada border, with a length of about 150 miles from north to south. \nThe general regional groundwater flow direction is from south to north towards \nthe Great Salt Lake Desert.\n\nFor 15 years with support from the Southern Nevada Water Authority (SNWA), \nhydrologists, geologists, and geophysicists studied the basin connections and \nthe groundwater resources in these and adjacent flow systems over an area of \nabout 25,000 square miles. A major first part of the SNWA study was \nconstructing a 3-dimensional digital hydrogeologic framework based on \ngeologic maps and cross sections at 1:250,000 scale. This framework \ndocuments the presence of three major aquifers: (1) Paleozoic carbonate \nrocks, (2) Eocene to Miocene volcanic rocks, and (3) Miocene to Holocene \nbasin-fill sediments, as well as confining units that constrain flow. We \ninterpret that movement of most groundwater through and across basins is by \nfracture-dominated flow along faults/fractures, yet in most places flow is \nprevented or retarded across faults, so mapping structures gives a first \napproximation to conduits and barriers to flow.\n\nThe most important structures by far are high-angle normal faults of the \nbasin-range episode of east-west extensional deformation. This event \nbegan at about 20 Ma, although most deformation and the formation of the \npresent topography took place between 10 Ma and present. This topography \nconsists of north-trending basins (mostly grabens) that alternate with north-\ntrending ranges (mostly horsts); erosion of the ranges filled the basins with \nclastic alluvial basin-fill deposits.\n\nGeophysics provides data on the third dimension (cross sections) of the \nhydrogeologic framework. Audiomagnetotelluric profiles and gravity \ninversion located faults and enabled us to estimate thicknesses of basin-fill \ndeposits. To this framework, hydrologic studies addressed precipitation, \nsurface water, and springs, as well as groundwater levels, volumes, \ngeochemistry, water budgets, and monitoring. At nearly the same time as \nour study, the Utah Geological Survey (UGS) and U.S. Geological Survey \n(USGS) addressed the same issues in many of the same areas, and publication \nof the efforts by all three agencies reveals a surprising similarity of conclusions, \nwith some critical exceptions, which therefore demonstrates the great value of \nmany scientists independently studying the same complex scientific problem. \nThe differences in conclusions include directions and volumes of some ground-\nwater flow paths, such as one proposed by the USGS of unlikely groundwater \nflow from Steptoe Valley to southern Snake Valley, and another proposed by the \nUGS of unlikely significant groundwater recharge flow from the Snake Range to \nthe Fish Springs complex.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Resources and Geo- logy of Utah's West Desert","language":"English","publisher":"Utah Geologic Association","usgsCitation":"Rowley, P.D., Dixon, G.L., Watrus, J.M., Burns, A.G., Mankinen, E.A., McKee, E.H., Pari, K.T., Ekren, E.B., and Patrick, W.G., 2016, Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada, chap. of Resources and Geo- logy of Utah's West Desert, v. 45, p. 167-200.","productDescription":"34 p. 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\"}}]}","volume":"45","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f877b8e4b0b7ea54521c18","contributors":{"editors":[{"text":"Comer, John B.","contributorId":147613,"corporation":false,"usgs":false,"family":"Comer","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":692018,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Inkenbrandt, Paul C.","contributorId":191156,"corporation":false,"usgs":false,"family":"Inkenbrandt","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692019,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Krahulec, K.A.","contributorId":42429,"corporation":false,"usgs":true,"family":"Krahulec","given":"K.A.","affiliations":[],"preferred":false,"id":692020,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Pinnell, Michael L.","contributorId":191157,"corporation":false,"usgs":false,"family":"Pinnell","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":692021,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Rowley, Peter D.","contributorId":27435,"corporation":false,"usgs":true,"family":"Rowley","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":673660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dixon, Gary L.","contributorId":23571,"corporation":false,"usgs":true,"family":"Dixon","given":"Gary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":673661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watrus, James M.","contributorId":184152,"corporation":false,"usgs":false,"family":"Watrus","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":673662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Andrews G.","contributorId":184154,"corporation":false,"usgs":false,"family":"Burns","given":"Andrews","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":673663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":673664,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKee, Edwin H. mckee@usgs.gov","contributorId":3728,"corporation":false,"usgs":true,"family":"McKee","given":"Edwin","email":"mckee@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":673665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pari, Keith T.","contributorId":184155,"corporation":false,"usgs":false,"family":"Pari","given":"Keith","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":673666,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ekren, E. Bartlett","contributorId":47644,"corporation":false,"usgs":true,"family":"Ekren","given":"E.","email":"","middleInitial":"Bartlett","affiliations":[],"preferred":false,"id":673667,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Patrick, William G.","contributorId":184151,"corporation":false,"usgs":false,"family":"Patrick","given":"William","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":673668,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70182256,"text":"70182256 - 2016 - The effect of restored and native oxbows on hydraulic loads of nutrients and stream water quality","interactions":[],"lastModifiedDate":"2017-02-23T13:03:09","indexId":"70182256","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"The effect of restored and native oxbows on hydraulic loads of nutrients and stream water quality","docAbstract":"The use of oxbow wetlands has been identified as a potential strategy to reduce nutrient transport from agricultural drainage tiles to streams in Iowa. In 2013 and 2014, a study was conducted in north-central Iowa in a native oxbow in the Lyons Creek watershed and two restored oxbow wetlands in the Prairie Creek watershed (Smeltzer west and Smeltzer east) to assess their effectiveness at reducing nitrogen and phosphorus loads. The tile line inlets carrying agricultural runoff to the oxbows, the outfall from the oxbows, and the surface waters in the streams receiving the outfall water were monitored for discharge and nutrients from February 2013 to September 2015. Smeltzer west and east also had four monitoring wells each, two in the upland and two between the oxbow and Prairie Creek to monitor surface water-groundwater interaction. The Smeltzer west and east oxbow sites also were instrumented to continuously measure the nitrate concentration. Rainfall was measured at one Lyons Creek and one Smeltzer site. Daily mean nitrate-N concentrations in Lyons Creek in 2013 ranged from 11.8 mg/L to 40.9 mg/L, the median daily mean nitrate-N concentration was 33.0 mg/L. Daily mean nitrate-N concentrations in Prairie Creek in 2013 ranged from 0.07 mg/L in August to 32.2 mg/L in June. In 2014, daily mean nitrate-N concentrations in Prairie Creek ranged from 0.17 mg/L in April to 26.7 mg/L in July; the daily mean nitrate-N concentration for the sampled period was 9.78 mg/L. Nutrient load reduction occurred in oxbow wetlands in Lyons and Prairie Creek watersheds in north-central Iowa but efficiency of reduction was variable. Little nutrient reduction occurred in the native Lyons Creek oxbow during 2013. Concentrations of all nutrient constituents were not significantly (P>0.05, Wilcoxon rank sum) different in water discharging from the tile line than in water leaving the Lyons Creek oxbow. A combination of physical features and flow conditions suggest that the residence time of water in the oxbow may not have been sufficient to allow for removal of substantial amounts of nutrients. Approximately 54 percent less nitrate-N was measured leaving the Smeltzer west oxbow than was measured entering from a small 6-inch field tile. The efficiency of nitrate-N removal in the oxbow was not able to be definitively quantified as other hydrologic factors such as overland and groundwater flow into and through the oxbow were not addressed and may provide alternative routes for nutrient transport. Damage to the Smeltzer east oxbow outfall weir prevented analysis of its nutrient load reduction capability. The study provides important information to managers and land owners looking for strategies to reduce nutrient transport from fields. Additional research is needed to understand how increased discharge from larger field tiles and drainage district mains may influence the efficiency of nutrient reduction in relation to the size, type, and landscape setting of a wetland.","language":"English","publisher":"U.S. Environmental Protection Agency","collaboration":"U. S. Environmental Protection Agency ORD, NRMRL, Cincinnati, OH","usgsCitation":"Kalkhoff, S.J., Hubbard, L.E., and P.Schubauer-Berigan, J., 2016, The effect of restored and native oxbows on hydraulic loads of nutrients and stream water quality, xii., 83 p. .","productDescription":"xii., 83 p. ","ipdsId":"IP-077913","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":336108,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335923,"type":{"id":15,"text":"Index Page"},"url":"https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100PP42.txt"}],"country":"United States","state":"Iowa ","otherGeospatial":"Lyons Creek, Prairie Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.82083892822266,\n 42.47893393507777\n ],\n [\n -93.81895065307617,\n 42.47830090850463\n ],\n [\n -93.75577926635742,\n 42.47627518043613\n ],\n [\n -93.7114906311035,\n 42.49399807755323\n ],\n [\n -93.71011734008789,\n 42.52196471770537\n ],\n [\n -93.74221801757812,\n 42.522217752342236\n ],\n [\n -93.78650665283203,\n 42.52348291015486\n ],\n [\n -93.82650375366211,\n 42.51791602414797\n ],\n [\n -93.82083892822266,\n 42.47893393507777\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.18819427490234,\n 42.43980086209991\n ],\n [\n -94.21548843383789,\n 42.4417010906216\n ],\n [\n -94.22029495239258,\n 42.38441557693553\n ],\n [\n -94.19540405273438,\n 42.38504955243599\n ],\n [\n -94.14527893066406,\n 42.38555672822687\n ],\n [\n -94.14459228515624,\n 42.39988275145449\n ],\n [\n -94.15197372436523,\n 42.43904075455518\n ],\n [\n -94.18819427490234,\n 42.43980086209991\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b002c6e4b01ccd54fb27cd","contributors":{"authors":[{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":670254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":670255,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"P.Schubauer-Berigan, Joseph","contributorId":182023,"corporation":false,"usgs":false,"family":"P.Schubauer-Berigan","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":670256,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178695,"text":"70178695 - 2016 - Undergraduate research projects help promote diversity in the geosciences","interactions":[],"lastModifiedDate":"2017-01-20T10:26:11","indexId":"70178695","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Undergraduate research projects help promote diversity in the geosciences","docAbstract":"A workforce that draws from all segments of society and mirrors the ethnic, racial, and gender\r\ndiversity of the United States population is important. The geosciences (geology, hydrology,\r\ngeospatial sciences, environmental sciences) continue to lag far behind other science, technology,\r\nengineering and mathematical (STEM) disciplines in recruiting and retaining minorities (Valsco\r\nand Valsco, 2010). A report published by the National Science Foundation in 2015, “Women,\r\nMinorities, and Persons with Disabilities in Science and Engineering” states that from 2002 to\r\n2012, less than 2% of the geoscience degrees were awarded to African-American students. Data\r\nalso show that as of 2012, approximately 30% of African-American Ph.D. graduates obtained a\r\nbachelor’s degree from a Historic Black College or University (HBCU), indicating that HBCUs\r\nare a great source of diverse students for the geosciences. This paper reviews how an informal\r\npartnership between Tennessee State University (a HBCU), the U.S. Geological Survey, and\r\nMammoth Cave National Park engaged students in scientific research and increased the number\r\nof students pursuing employment or graduate degrees in the geosciences.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings for Celebrating the Diversity of Research in the Mammoth Cave Region: 11th Research Symposium at Mammoth Cave National Park","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","usgsCitation":"Young, D., Trimboli, S., Toomey, R.S., and Byl, T.D., 2016, Undergraduate research projects help promote diversity in the geosciences, in Proceedings for Celebrating the Diversity of Research in the Mammoth Cave Region: 11th Research Symposium at Mammoth Cave National Park, p. 108-113.","productDescription":"6 p.","startPage":"108","endPage":"113","ipdsId":"IP-072862","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":333526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":331450,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=1146&context=mc_reserch_symp"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58833023e4b0d00231637790","contributors":{"authors":[{"text":"Young, De’Etra","contributorId":177163,"corporation":false,"usgs":false,"family":"Young","given":"De’Etra","email":"","affiliations":[],"preferred":false,"id":654830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trimboli, Shannon","contributorId":177164,"corporation":false,"usgs":false,"family":"Trimboli","given":"Shannon","email":"","affiliations":[],"preferred":false,"id":654831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toomey, Rick S.","contributorId":177165,"corporation":false,"usgs":false,"family":"Toomey","given":"Rick","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":654832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byl, Thomas D. 0000-0001-6907-9149 tdbyl@usgs.gov","orcid":"https://orcid.org/0000-0001-6907-9149","contributorId":583,"corporation":false,"usgs":true,"family":"Byl","given":"Thomas","email":"tdbyl@usgs.gov","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654833,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189513,"text":"70189513 - 2016 - Estimating mercury emissions resulting from wildfire in forests of the Western United States","interactions":[],"lastModifiedDate":"2018-08-07T12:28:27","indexId":"70189513","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Estimating mercury emissions resulting from wildfire in forests of the Western United States","docAbstract":"Understanding the emissions of mercury (Hg) from wildfires is important for quantifying the global atmospheric Hg sources. Emissions of Hg from soils resulting from wildfires in the Western United States was estimated for the 2000 to 2013 period, and the potential emission of Hg from forest soils was assessed as a function of forest type and soil-heating. Wildfire released an annual average of 3100 ± 1900 kg-Hg y− 1 for the years spanning 2000–2013 in the 11 states within the study area. This estimate is nearly 5-fold lower than previous estimates for the study region. Lower emission estimates are attributed to an inclusion of fire severity within burn perimeters. Within reported wildfire perimeters, the average distribution of low, moderate, and high severity burns was 52, 29, and 19% of the total area, respectively. Review of literature data suggests that that low severity burning does not result in soil heating, moderate severity fire results in shallow soil heating, and high severity fire results in relatively deep soil heating (< 5 cm). Using this approach, emission factors for high severity burns ranged from 58 to 640 μg-Hg kg-fuel− 1. In contrast, low severity burns have emission factors that are estimated to be only 18–34 μg-Hg kg-fuel− 1. In this estimate, wildfire is predicted to release 1–30 g Hg ha− 1 from Western United States forest soils while above ground fuels are projected to contribute an additional 0.9 to 7.8 g Hg ha− 1. Land cover types with low biomass (desert scrub) are projected to release less than 1 g Hg ha− 1. Following soil sources, fuel source contributions to total Hg emissions generally followed the order of duff > wood > foliage > litter > branches.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.01.166","usgsCitation":"Webster, J., Kane, T., Obrist, D., Ryan, J.N., and Aiken, G.R., 2016, Estimating mercury emissions resulting from wildfire in forests of the Western United States: Science of Total Environment, v. 568, p. 578-586, https://doi.org/10.1016/j.scitotenv.2016.01.166.","productDescription":"9 p.","startPage":"578","endPage":"586","ipdsId":"IP-071233","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.01.166","text":"Publisher Index Page"},{"id":343855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"568","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5969d82be4b0d1f9f060a188","contributors":{"authors":[{"text":"Webster, Jackson","contributorId":172157,"corporation":false,"usgs":false,"family":"Webster","given":"Jackson","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":704982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kane, Tyler J. 0000-0003-2511-7312","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":194675,"corporation":false,"usgs":false,"family":"Kane","given":"Tyler J.","affiliations":[],"preferred":false,"id":704983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Obrist, Daniel","contributorId":172155,"corporation":false,"usgs":false,"family":"Obrist","given":"Daniel","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":704984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":704985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704986,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189515,"text":"70189515 - 2016 - A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity","interactions":[],"lastModifiedDate":"2020-09-01T14:28:24.754124","indexId":"70189515","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity","docAbstract":"A synthesis of published vegetation mercury (Hg) data across 11 contiguous states in the western United States showed that aboveground biomass concentrations followed the order: leaves (26 μg kg− 1) ~ branches (26 μg kg− 1) > bark (16 μg kg− 1) > bole wood (1 μg kg− 1). No spatial trends of Hg in aboveground biomass distribution were detected, which likely is due to very sparse data coverage and different sampling protocols. Vegetation data are largely lacking for important functional vegetation types such as shrubs, herbaceous species, and grasses.
Soil concentrations collected from the published literature were high in the western United States, with 12% of observations exceeding 100 μg kg− 1, reflecting a bias toward investigations in Hg-enriched sites. In contrast, soil Hg concentrations from a randomly distributed data set (1911 sampling points; Smith et al., 2013a) averaged 24 μg kg− 1 (A-horizon) and 22 μg kg− 1 (C-horizon), and only 2.6% of data exceeded 100 μg kg− 1. Soil Hg concentrations significantly differed among land covers, following the order: forested upland > planted/cultivated > herbaceous upland/shrubland > barren soils. Concentrations in forests were on average 2.5 times higher than in barren locations. Principal component analyses showed that soil Hg concentrations were not or weakly related to modeled dry and wet Hg deposition and proximity to mining, geothermal areas, and coal-fired power plants. Soil Hg distribution also was not closely related to other trace metals, but strongly associated with organic carbon, precipitation, canopy greenness, and foliar Hg pools of overlying vegetation. These patterns indicate that soil Hg concentrations are related to atmospheric deposition and reflect an overwhelming influence of plant productivity — driven by water availability — with productive landscapes showing high soil Hg accumulation and unproductive barren soils and shrublands showing low soil Hg values. Large expanses of low-productivity, arid ecosystems across the western U.S. result in some of the lowest soil Hg concentrations observed worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.11.104","usgsCitation":"Obrist, D., Pearson, C., Webster, J., Kane, T., Lin, C., Aiken, G.R., and Alpers, C.N., 2016, A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity: Science of the Total Environment, v. 568, p. 522-535, https://doi.org/10.1016/j.scitotenv.2015.11.104.","productDescription":"14 p.","startPage":"522","endPage":"535","ipdsId":"IP-070736","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2015.11.104","text":"Publisher Index Page"},{"id":343856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"568","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5969d82ae4b0d1f9f060a184","contributors":{"authors":[{"text":"Obrist, Daniel","contributorId":172155,"corporation":false,"usgs":false,"family":"Obrist","given":"Daniel","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":704988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, Christopher","contributorId":49278,"corporation":false,"usgs":true,"family":"Pearson","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":704989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webster, Jackson","contributorId":172157,"corporation":false,"usgs":false,"family":"Webster","given":"Jackson","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":704990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Tyler J. 0000-0003-2511-7312","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":194675,"corporation":false,"usgs":false,"family":"Kane","given":"Tyler J.","affiliations":[],"preferred":false,"id":704991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Che-Jen","contributorId":167257,"corporation":false,"usgs":false,"family":"Lin","given":"Che-Jen","email":"","affiliations":[{"id":24666,"text":"Lamar University","active":true,"usgs":false}],"preferred":false,"id":704992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704993,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704994,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70184238,"text":"70184238 - 2016 - Potential interactions among disease, pesticides, water quality and adjacent land cover in amphibian habitats in the United States","interactions":[],"lastModifiedDate":"2018-08-09T12:24:22","indexId":"70184238","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Potential interactions among disease, pesticides, water quality and adjacent land cover in amphibian habitats in the United States","docAbstract":"To investigate interactions among disease, pesticides, water quality, and adjacent land cover, we collected samples of water, sediment, and frog tissue from 21 sites in 7 States in the United States (US) representing a variety of amphibian habitats. All samples were analyzed for > 90 pesticides and pesticide degradates, and water and frogs were screened for the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd) using molecular methods. Pesticides and pesticide degradates were detected frequently in frog breeding habitats (water and sediment) as well as in frog tissue. Fungicides occurred more frequently in water, sediment, and tissue than was expected based upon their limited use relative to herbicides or insecticides. Pesticide occurrence in water or sediment was not a strong predictor of occurrence in tissue, but pesticide concentrations in tissue were correlated positively to agricultural and urban land, and negatively to forested land in 2-km buffers around the sites. Bd was detected in water at 45% of sites, and on 34% of swabbed frogs. Bd detections in water were not associated with differences in land use around sites, but sites with detections had colder water. Frogs that tested positive for Bd were associated with sites that had higher total fungicide concentrations in water and sediment, but lower insecticide concentrations in sediments relative to frogs that were Bd negative. Bd concentrations on frog swabs were positively correlated to dissolved organic carbon, and total nitrogen and phosphorus, and negatively correlated to pH and water temperature.
Data were collected from a range of locations and amphibian habitats and represent some of the first field-collected information aimed at understanding the interactions between pesticides, land use, and amphibian disease. These interactions are of particular interest to conservation efforts as many amphibians live in altered habitats and may depend on wetlands embedded in these landscapes to survive.
","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.scitotenv.2016.05.062","usgsCitation":"Battaglin, W.A., Smalling, K., Anderson, C.W., Calhoun, D.L., Chestnut, T.E., and Muths, E.L., 2016, Potential interactions among disease, pesticides, water quality and adjacent land cover in amphibian habitats in the United States: Science of the Total Environment, v. 566-567, p. 320-332, https://doi.org/10.1016/j.scitotenv.2016.05.062.","productDescription":"13 p.","startPage":"320","endPage":"332","ipdsId":"IP-073673","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":336833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Georgia, Idaho, 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The DAA H-3613i is a noncontact water-level sensor that uses pulsed radar to measure the distance between the radar and the water surface from 0.75 to 131 feet over a temperature range of −40 to 60 degrees Celsius (°C). Manufacturer accuracy specifications that were evaluated, the test procedures that followed, and the results obtained are described in this report. The sensor’s accuracy specification of ± 0.01 feet (± 3 millimeters) meets USGS requirements for a primary water-stage sensor used in the operation of a streamgage. The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during temperature testing at a distance of 8 feet from the target over its temperature-compensated operating range of −40 to 60 °C, except at 60 °C. At 60 °C, about half the measurements exceeded the manufacturer’s accuracy specification by not more than 0.005 feet.The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during distance-accuracy testing at the tested distances from 3 to 15 feet above the water surface at the HIF.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161124","usgsCitation":"Carnley, M.V., 2016, Laboratory evaluation of the Design Analysis Associates DAA H-3613i radar water-level sensor—Results of temperature, distance, and SDI-12 tests: U.S. Geological Survey Open-File Report 2016–1124, 7 p., https://dx.doi.org/10.3133/ofr20161124. ","productDescription":"iii, 7 p.","numberOfPages":"16","onlineOnly":"Y","ipdsId":"IP-071442","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":329212,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1124/coverthb.jpg"},{"id":329213,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1124/ofr20161124.pdf","text":"Report","size":"2.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1124"}],"contact":"Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
A daily watershed model of the Sacramento River Basin of northern California was developed to simulate streamflow and suspended sediment transport to the San Francisco Bay-Delta. To compensate for sparse data, a unique combination of model inputs was developed, including meteorological variables, potential evapotranspiration, and parameters defining hydraulic geometry. A slight decreasing trend of sediment loads and concentrations was statistically significant in the lowest 50% of flows, supporting the observed historical sediment decline. Historical changes in climate, including seasonality and decline of snowpack, contribute to changes in streamflow, and are a significant component describing the mechanisms responsible for the decline in sediment. Several wet and dry hypothetical climate change scenarios with temperature changes of 1.5 °C and 4.5 °C were applied to the base historical conditions to assess the model sensitivity of streamflow and sediment to changes in climate. Of the scenarios evaluated, sediment discharge for the Sacramento River Basin increased the most with increased storm magnitude and frequency and decreased the most with increases in air temperature, regardless of changes in precipitation. The model will be used to develop projections of potential hydrologic and sediment trends to the Bay-Delta in response to potential future climate scenarios, which will help assess the hydrological and ecological health of the Bay-Delta into the next century.
","language":"English","publisher":"Molecular Diversity Preservation International","publisherLocation":"Basel, Switzerland","doi":"10.3390/w8100432","usgsCitation":"Stern, M.A., Flint, L.E., Minear, J.T., Flint, A.L., and Wright, S., 2016, Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF): Water, v. 8, no. 10, https://doi.org/10.3390/w8100432.","startPage":"432","numberOfPages":"21","ipdsId":"IP-073991","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":462073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8100432","text":"Publisher Index Page"},{"id":329512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.5,\n 38.25\n ],\n [\n -123.5,\n 41\n ],\n [\n -121,\n 41\n ],\n [\n -121,\n 38.25\n ],\n [\n -123.5,\n 38.25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf4","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minear, Justin Toby jminear@usgs.gov","contributorId":3736,"corporation":false,"usgs":true,"family":"Minear","given":"Justin","email":"jminear@usgs.gov","middleInitial":"Toby","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650714,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650716,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175349,"text":"ofr20161127 - 2016 - Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California","interactions":[],"lastModifiedDate":"2016-10-03T11:36:18","indexId":"ofr20161127","displayToPublicDate":"2016-09-30T00:00:00","publicationYear":"2016","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":"2016-1127","title":"Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California","docAbstract":"In the spring of 2009, the U.S. Geological Survey, in cooperation with the San Bernardino Valley Municipal Water District, began working on a gravity survey in the Yucaipa area to explore the three-dimensional shape of the sedimentary fill (alluvial deposits) and the surface of the underlying crystalline basement rocks. As water use has increased in pace with rapid urbanization, water managers have need for better information about the subsurface geometry and the boundaries of groundwater subbasins in the Yucaipa area. The large density contrast between alluvial deposits and the crystalline basement complex permits using modeling of gravity data to estimate the thickness of alluvial deposits. The bottom of the alluvial deposits is considered to be the top of crystalline basement rocks. The gravity data, integrated with geologic information from surface outcrops and 51 subsurface borings (15 of which penetrated basement rock), indicated a complex basin configuration where steep slopes coincide with mapped faults―such as the Crafton Hills Fault and the eastern section of the Banning Fault―and concealed ridges separate hydrologically defined subbasins.
Gravity measurements and well logs were the primary data sets used to define the thickness and structure of the groundwater basin. Gravity measurements were collected at 256 new locations along profiles that totaled approximately 104.6 km (65 mi) in length; these data supplemented previously collected gravity measurements. Gravity data were reduced to isostatic anomalies and separated into an anomaly field representing the valley fill. The ‘valley-fill-deposits gravity anomaly’ was converted to thickness by using an assumed, depth-varying density contrast between the alluvial deposits and the underlying bedrock.
To help visualize the basin geometry, an animation of the elevation of the top of the basement-rocks was prepared. The animation “flies over” the Yucaipa groundwater basin, viewing the land surface, geology, faults, and ridges and valleys of the shaded-relief elevation of the top of the basement complex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161127","collaboration":"Prepared in cooperation with the San Bernardino Valley Municipal Water District","usgsCitation":"Mendez, G.O., Langenheim, V.E., Morita, Andrew, and Danskin, W.R., 2016, Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California: U.S. Geological Survey Open-File Report 2016–1127, 22 p., https://dx.doi.org/10.3133/ofr20161127.","productDescription":"Report: vii, 23 p.; Video Animation","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077241","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":329070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1127"},{"id":329071,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127_gravity.mp4","text":"Video animation","size":"47.3 MB mp4","description":"OFR 2016-1127 Video Animation","linkHelpText":"Land surface, geology, faults, wells, and elevation of the basement rocks in the Yucaipa area, California."},{"id":329069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1127/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County, Riverside County","otherGeospatial":"Yucaipa Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.15888977050781,\n 33.96842016198477\n ],\n [\n -117.15888977050781,\n 34.08962997133382\n ],\n [\n -116.97212219238281,\n 34.08962997133382\n ],\n [\n -116.97212219238281,\n 33.96842016198477\n ],\n [\n -117.15888977050781,\n 33.96842016198477\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data.
The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the event that a station does malfunction, ADAM provides an accurate estimate for the period of missing data. The ADAM software also is used in the quality assurance and quality control of the data. The virtual signals are compared to the real-time data, and if the difference between the two signals exceeds a certain tolerance, corrective action to the data and (or) the gaging station can be taken. The ADAM software is automated so that, each morning, the real-time EDEN data are compared to the inferential sensor signals and digital reports highlighting potential erroneous real-time data are generated for appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165094","collaboration":"Greater Everglades Priority Ecosystems Science","usgsCitation":"Petkewich, M.D., Daamen, R.C., Roehl, E.A., and Conrads, P.A., 2016, Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data: U.S. Geological Survey Scientific Investigations Report 2016–5094, 25 p., https://dx.doi.org/10.3133/sir20165094.","productDescription":"v, 25 p.","onlineOnly":"Y","ipdsId":"IP-066447","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329015,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161116","text":"Open-File Report 2016–1116","description":"Open-File Report 2016–1116","linkHelpText":"- User’s Manual for the Automated Data Assurance and Management Application Developed for Quality Control of Everglades Depth Estimation Network Water-Level Data"},{"id":329013,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5094/coverthb.jpg"},{"id":329014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5094/sir20165094.pdf","text":"Report","size":"14.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5094"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.36749267578125,\n 25.916055815010868\n ],\n [\n -81.3482666015625,\n 26.25893609446839\n ],\n [\n -80.88958740234375,\n 26.261399213411483\n ],\n [\n -80.88134765625,\n 26.152972606566966\n ],\n [\n -80.84564208984375,\n 26.09625490696853\n ],\n [\n -80.82916259765625,\n 26.335268473041793\n ],\n [\n -80.53802490234375,\n 26.337729970839195\n ],\n [\n -80.4583740234375,\n 26.477948705162902\n ],\n [\n -80.45562744140625,\n 26.681821407205977\n ],\n [\n -80.35400390625,\n 26.681821407205977\n ],\n [\n -80.34576416015625,\n 26.64745870265938\n ],\n [\n -80.2716064453125,\n 26.5958952526538\n ],\n [\n -80.22491455078125,\n 26.519735305660795\n ],\n [\n -80.2166748046875,\n 26.423849388805877\n ],\n [\n -80.233154296875,\n 26.369724677109726\n ],\n [\n -80.2880859375,\n 26.35988109485539\n ],\n [\n -80.299072265625,\n 26.194876675795218\n ],\n [\n -80.3594970703125,\n 26.123384198664976\n ],\n [\n -80.4364013671875,\n 26.14804172600284\n ],\n [\n -80.43090820312499,\n 25.94816628853973\n ],\n [\n -80.48309326171875,\n 25.8962911755466\n ],\n [\n -80.4913330078125,\n 25.668760323272966\n ],\n [\n -80.5572509765625,\n 25.57465306409282\n ],\n [\n -80.4803466796875,\n 25.29437116258816\n ],\n [\n -80.75225830078125,\n 25.227304826281653\n ],\n [\n -81.36749267578125,\n 25.916055815010868\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
Stephenson Center, Suite 129
Gracern Road
Columbia, SC 29210
https://www2.usgs.gov/water/southatlantic/
A hydrogeologic framework was constructed to represent the altitudes and thicknesses of hydrogeologic units within the Ozark Plateaus aquifer system as part of a regional groundwater-flow model supported by the U.S. Geological Survey Water Availability and Use Science Program. The Ozark Plateaus aquifer system study area is nearly 70,000 square miles and includes parts of Arkansas, Kansas, Missouri, and Oklahoma. Nine hydrogeologic units were selected for delineation within the aquifer system and include the Western Interior Plains confining system, the Springfield Plateau aquifer, the Ozark confining unit, the Ozark aquifer, which was divided into the upper, middle, and lower Ozark aquifers to better capture the spatial variation in the hydrologic properties, the St. Francois confining unit, the St. Francois aquifer, and the basement confining unit. Geophysical and well-cutting logs, along with lithologic descriptions by well drillers, were compiled and interpreted to create hydrologic altitudes for each unit. The final compiled dataset included more than 23,000 individual altitude points (excluding synthetic points) representing the nine hydrogeologic units within the Ozark Plateaus aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165130","collaboration":"Water Availability and Use Science Program","usgsCitation":"Westerman, D.A., Gillip, J.A., Richards, J.M., Hays, P.D., Clark, B.R., 2016, Altitudes and thicknesses of hydrogeologic units of the Ozark Plateaus aquifer system in Arkansas, Kansas, Missouri, and Oklahoma: U.S. Geological Survey Scientific Investigations Report 2016–5130, 32 p., https://dx.doi.org/10.3133/sir20165130. 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U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
This is the eighth annual report highlighting U.S. Geological Survey (USGS) science and decision-support activities conducted for the Wyoming Landscape Conservation Initiative (WLCI). The activities address specific management needs identified by WLCI partner agencies. In 2015, USGS scientists continued 24 WLCI projects in 5 categories: (1) acquiring and analyzing resource-condition data to form a foundation for understanding and monitoring landscape conditions and projecting changes; (2) using new technologies to improve the scope and accuracy of landscape-scale monitoring and assessments, and applying them to monitor indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms that drive wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them to use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. Of the 24 projects, 21 were ongoing, including those that entered new phases or more in-depth lines of inquiry, 2 were new, and 1 was completed.
A highlight of 2015 was the WLCI science conference sponsored by the USGS, Bureau of Land Management, and National Park Service in coordination with the Wyoming chapter of The Wildlife Society. Of 260 participants, 41 were USGS professionals representing 13 USGS science centers, field offices, and Cooperative Wildlife Research Units. Major themes of USGS presentations included using new technologies for developing more efficient research protocols for modeling and monitoring natural resources, researching effects of energy development and other land uses on wildlife species and habitats of concern, and modeling species distributions, population trends, habitat use, and effects of land-use changes. There was also a special session on the effectiveness of Wyoming’s Sage-Grouse Executive Order. Combined, USGS presentations provided WLCI partners with a wealth of information and conservation tools.
The project completed in 2015 yielded an index of important agricultural lands in the WLCI region. The index improves upon existing measures of agricultural productivity and provides planners and managers with additional values to consider when making decisions about land use and conservation actions. The two new projects include an analysis of satellite imagery to quantify sagebrush productivity and mortality, and an evaluation of how groundwater and small streams interact in the upper Green River Basin. Initiated in response to concern among WLCI partners that large areas of sagebrush appear to have died recently, the sagebrush study objectives are to assess effects of these mortality events on overall sagebrush ecosystem productivity, evaluate the feasibility of using satellite imagery to detect patterns in sagebrush mortality over time, and identify factors driving these mortality events. The groundwater-streamflow interaction study is being conducted by hydrologists and fish ecologists to better understand how groundwater-streamflow interactions are affected by energy-resource development and how native fish communities are affected by these factors. Expected outcomes of both new projects will provide WLCI partners with additional information and decision-support tools.
Highlights of ongoing science foundation activities included simulations of nine alternative build-out scenarios for oil and gas development and an associated online fact sheet that explains how the simulations were conducted, with an applied example for the Atlantic Rim. Also completed in 2015 was an update of the USGS online inventory of mineral resources data, and publication of a USGS uranium resource survey for the WLCI region. Combined, the outcomes of this work provide decisionmakers and managers with important baseline information for existing and (or) future planning and monitoring efforts.
Terrestrial monitoring activities in 2015 emphasized the use of satellite data in combination with other technologies and field data to monitor, assess, and (or) forecast distribution patterns and (or) trends in sagebrush ecosystems, seasonal and migration stopover habitats used by mule deer and elk, and semi-arid aspen woodlands. Several professional papers detailing new monitoring models and results have been published. Combined, this and related work will help managers understand distribution patterns and trends among priority habitats, identify areas in need of restoration or conservation, and monitor the effectiveness of habitat-management actions.
Aquatic monitoring activities entailed not only the new groundwater-streamflow interaction study already mentioned, but also continued monitoring with streamgages paired with nearby wells in the Green River Basin to assess groundwater effects on streamflow and surface water temperatures. A map that portrays groundwater levels and general direction of flow in the Green River Basin was published as well. Overall, outcomes of USGS hydrological research and monitoring will inform WLCI partners about water resources in the WLCI region and help to explain fish-community responses to energy-resource development.
In 2015, USGS terrestrial wildlife ecologists continued to make crucial strides towards better understanding wildlife species responses to energy-resource development and other land-use changes. This body of research includes six taxa that require or heavily depend on sagebrush habitats: sage-grouse, pygmy rabbits, 3 songbird species, and mule deer. Native fish communities are also being evaluated. Approaches include modeling and mapping wildlife species distributions, abundances, and trends; using satellite and other technologies to track wildlife seasonal movements; conducting successive phases of research that build on the knowledge gained through prior phases to reveal the specific factors or thresholds that drive population- or individual-level responses to changes; and conducting population viability analyses. Additionally, wildlife habitat association models for pygmy rabbit and sage-grouse were combined with the oil and gas build-out scenarios to project species responses to alternative energy development scenarios. Outcomes of the wildlife response research are helping decisionmakers and managers identify specific factors that contribute to species population trends, the potential for spatial overlap between important wildlife habitats and proposed energy-resource development, locations of priority habitats for restoration and conservation, and more.
Data and WLCI Web site management highlights of 2015 included not only ongoing software upgrades, but also an update of the datasets displayed in two of the online products developed for the WLCI effort: (1) a map of 15,532 oil and natural gas well pad scars and other features associated with oil and gas extraction, and (2) a map of oil and gas, oil shale, uranium, and solar energy production, both for southwestern Wyoming. In addition, a map viewer was developed for a previously published map of coal and wind production in relation to sage-grouse distribution and core management areas in southwestern Wyoming. Combined, these maps place valuable decision-support tools in the hands of WLCI partners.
The USGS coordination efforts on behalf of the WLCI in 2015 included significant work on planning and executing the WLCI science conference. They also included ongoing efforts to support Local Project Development Teams and the WLCI Coordination Team (CT) with developing conservation priorities and strategies, identifying priority areas for future conservation actions, supporting the evaluation and ranking of conservation projects, and evaluating the ways in which proposed habitat projects relate to WLCI priorities. In 2015, the USGS also assisted the WLCI CT with updating the WLCI Conservation Action Plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161141","usgsCitation":"Bowen, Z.H., Aldridge, C.L., Anderson, P.J., Assal, T.J., Bartos, T.T., Chalfoun, A.D., Chong, G.W., Dematatis, M.K., Eddy-Miller, C.A., Garman, S.L., Germaine, S.S., Homer, C.G., Huber, C.C., Kauffman, M.J., Manier, D.J., Melcher, C.P., Miller, K.A., Norkin, Tamar, Sanders, L.E., Walters, A.W., Wilson, A.B., and Wyckoff, T.B., 2016, U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2015 annual report: U.S. Geological Survey Open-File Report 2016–1141, 59 p., https://dx.doi.org/10.3133/ofr20161141.","productDescription":"viii, 59 p.","onlineOnly":"Y","ipdsId":"IP-075182","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":329020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1141/coverthb.jpg"},{"id":329021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1141/ofr20161141.pdf","text":"Report","size":"36.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1141"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.07177734375,\n 43.40504748787035\n ],\n [\n -111.0498046875,\n 41\n ],\n [\n -105.99609375,\n 41\n ],\n [\n -105.99609375,\n 41.80407814427234\n ],\n [\n -105.35888671875,\n 41.82045509614034\n ],\n [\n -105.380859375,\n 42.47209690919285\n ],\n [\n -106.5673828125,\n 42.52069952914966\n ],\n [\n -107.20458984375,\n 42.48830197960227\n ],\n [\n -107.70996093749999,\n 42.53689200787315\n ],\n [\n -108.5009765625,\n 42.779275360241904\n ],\n [\n -108.80859375,\n 42.98857645832184\n ],\n [\n -109.22607421875,\n 43.229195113965005\n ],\n [\n -109.3798828125,\n 43.42100882994726\n ],\n [\n -109.79736328125,\n 43.5326204268101\n ],\n [\n -110.41259765625,\n 43.56447158721811\n ],\n [\n -111.07177734375,\n 43.40504748787035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Assessments of streamflow (discharge) parameters, water quality, physical habitat, and biological communities were completed between May and September 2014 as part of a monitoring program in the Big Wood River watershed of south-central Idaho. The sampling was conducted by the U.S. Geological Survey in cooperation with Blaine County, Trout Unlimited, the Nature Conservancy, and the Wood River Land Trust to help identify the status of aquatic resources at selected locations in the watershed. Information in this report provides a basis with which to evaluate and monitor the long-term health of the Big Wood River and its major tributaries. Sampling sites were co-located with existing U.S. Geological Survey streamgaging stations: three on the main stem Big Wood River and four on the North Fork Big Wood River (North Fork), Warm Springs Creek (Warm Sp), Trail Creek (Trail Ck), and East Fork Big Wood River (East Fork) tributaries.
The analytical results and quality-assurance information for water quality, physical habitat, and biological community samples collected at study sites during 2 weeks in September 2014 are summarized. Water-quality data include concentrations of major nutrients, suspended sediment, dissolved oxygen, and fecal-coliform bacteria. To assess the potential effects of nutrient enrichment on algal growth, concentrations of periphyton biomass (chlorophyll-a and ash free dry weight) in riffle habitats were determined at each site. Physical habitat parameters include stream channel morphology, habitat volume, instream structure, substrate composition, and riparian vegetative cover. Biological data include taxa richness, abundance, and stream-health indicator metrics for macroinvertebrate and fish communities. Statistical summaries of the water-quality, habitat, and biological data are provided along with discussion of how these findings relate to the health of aquatic resources in the Big Wood River watershed.
Seasonal discharge patterns using statistical summaries of daily discharge from selected sites are reported for water years 2012–15. Results showed that annual average daily mean discharge increased from the Big Wood River near Ketchum, ID (BW Ketchum) downstream to the Big Wood River at Hailey, ID (BW Hailey), but decreased by nearly 50 percent from BW Hailey downstream to Big Wood River at Stanton Crossing near Bellevue, ID (BW Stanton). Annual variability in daily mean discharge among main-stem sites was highest at BW Stanton, suggesting that this part of the river may be subject to some level of flow alteration.
Hydrologic alterations resulting in flow reduction can contribute to higher water temperature, especially during the summer months when conditions are often most stressful to fish and other stream organisms. Daily water temperature and water temperature trends from June to September 2014 are reported for select tributary and main-stem sites on the Big Wood River and can be used to assess the potential for biological impairment based on aquatic life temperature criteria for cold-water streams. The State of Idaho maximum temperature criteria for protection of cold-water aquatic life of 22 °C was exceeded at Warm Sp and BW Stanton during summer 2014, but at none of the other main-stem or tributary sites. The 13 °C critical temperature criterion for salmonid spawning was exceeded in early July 2014 at BW Ketchum and BW Hailey near the end of the rainbow trout critical spawning and rearing period. Temperature exceedances were most frequent at BW Stanton, where exceedances for rainbow trout and brown trout occurred from May through early July 2014 during most of the critical spawning and rearing period.
Water quality and habitat availability did not seem to be limiting for fish or other aquatic organisms at most sites in the Big Wood River watershed. Water quality assessments in September 2014 determined no exceedances of total maximum daily load target levels. The availability and quality of habitat was limited at BW Stanton, where shallow-water habitat conditions prevailed.
Macroinvertebrate community diversity was high at all sites except for BW Stanton, where low community diversity was attributed to low species richness and high abundances of a few tolerant taxa. Presence of low species diversity and high macroinvertebrate tolerance values at BW Stanton indicates that benthic community condition and stream health were reduced at that location.
Fish surveys done in September 2014 did not indicate any significant reductions in native fish communities in the Big Wood River or its tributaries. Native rainbow trout (Oncorhynchus mykiss) and Wood River sculpin (Cottus leiopomus) were the dominant fish species in the drainage and were found at all tributary and main-stem sites. Non-native brown (Salmo trutta) and brook trout (Salvelinus fontinalis) were limited to lower drainage sites on the Big Wood River (BW Hailey and BW Stanton), and occurred in relatively low numbers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165128","collaboration":"Prepared in cooperation with Blaine County, Trout Unlimited, The Nature Conservancy, and the Wood River Land Trust","usgsCitation":"MacCoy, D.E., and Short, T.M., 2016, Aquatic biological communities and associated habitats at selected sites in the Big Wood River watershed, south-central Idaho, 2014: U.S. Geological Survey Scientific Investigations Report 2016–5128, 37 p., https://dx.doi.org/10.3133/sir20165128.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-061251","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":329075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5128/sir20165128.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5128"},{"id":329074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5128/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Wood River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.58465576171875,\n 43.2622061978402\n ],\n [\n -114.58465576171875,\n 43.81471121600004\n ],\n [\n -114.01473999023438,\n 43.81471121600004\n ],\n [\n -114.01473999023438,\n 43.2622061978402\n ],\n [\n -114.58465576171875,\n 43.2622061978402\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Warm Mineral Springs, located in southern Sarasota County, Florida, is a warm, highly mineralized, inland spring. Since 1946, a bathing spa has been in operation at the spring, attracting vacationers and health enthusiasts. During the winter months, the warm water attracts manatees to the adjoining spring run and provides vital habitat for these mammals. Well-preserved late Pleistocene to early Holocene-age human and animal bones, artifacts, and plant remains have been found in and around the spring, and indicate the surrounding sinkhole formed more than 12,000 years ago. The spring is a multiuse resource of hydrologic importance, ecological and archeological significance, and economic value to the community.
The pool of Warm Mineral Springs has a circular shape that reflects its origin as a sinkhole. The pool measures about 240 feet in diameter at the surface and has a maximum depth of about 205 feet. The sinkhole developed in the sand, clay, and dolostone of the Arcadia Formation of the Miocene-age to Oligocene-age Hawthorn Group. Underlying the Hawthorn Group are Oligocene-age to Eocene-age limestones and dolostones, including the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. Mineralized groundwater, under artesian pressure in the underlying aquifers, fills the remnant sink, and the overflow discharges into Warm Mineral Springs Creek, to Salt Creek, and subsequently into the Myakka River. Aquifers described in the vicinity of Warm Mineral Springs include the surficial aquifer system, the intermediate aquifer system within the Hawthorn Group, and the Upper Floridan aquifer in the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. The Hawthorn Group acts as an upper confining unit of the Upper Floridan aquifer.
Groundwater flow paths are inferred from the configuration of the potentiometric surface of the Upper Floridan aquifer for September 2010. Groundwater flow models indicate the downward flow of water into the Upper Floridan aquifer in inland areas, and upward flow toward the surface in coastal areas, such as at Warm Mineral Springs. Warm Mineral Springs is located in a discharge area. Changes in water use in the region have affected the potentiometric surface of the Upper Floridan aquifer. Historical increase in groundwater withdrawals resulted in a 10- to 20-foot regional decline in the potentiometric surface of the Upper Floridan aquifer by May 1975 relative to predevelopment levels and remained at approximately that level in May 2007 in the area of Warm Mineral Springs. Discharge measurements at Warm Mineral Springs (1942–2014) decreased from about 11–12 cubic feet per second in the 1940s to about 6–9 cubic feet per second in the 1970s and remained at about that level for the remainder of the period of record. Similarity of changes in regional water use and discharge at Warm Mineral Springs indicates that basin-scale changes to the groundwater system have affected discharge at Warm Mineral Springs. Water temperature had no significant trend in temperature over the period of record, 1943–2015, and outliers were identified in the data that might indicate inconsistencies in measurement methods or locations.
Within the regional groundwater basin, Warm Mineral Springs is influenced by deep Upper Floridan aquifer flow paths that discharge toward the coast. Associated with these flow paths, the groundwater temperatures increase with depth and toward the coast. Multiple lines of evidence indicate that a source of warm groundwater to Warm Mineral Springs is likely the permeable zone of the Avon Park Formation within the Upper Floridan aquifer at a depth of about 1,400 to 1,600 feet, or deeper sources. The permeable zone contains saline groundwater with water temperatures of at least 95 degrees Fahrenheit.
The water quality of Warm Mineral Springs, when compared with other springs in Florida had the highest temperature and the greatest mineralized content. Warm Mineral Springs water is characterized by a slight-green color, with varying water clarity, low dissolved oxygen (indicative of deep groundwater), and a hydrogen sulfide odor. Water-quality samples detected ammonium-nitrogen and nitrates, but at low concentrations. The drinking water standard for nitrate adopted by the U.S. Environmental Protection Agency is 10 milligrams per liter, measured as nitrogen. Water samples collected at spring vents by divers on April 29, 2015, had concentrations of 0.9 milligram per liter nitrate-nitrogen at vent A and 0.04–0.05 milligram per liter at vents B, C, and D. Typically, the water clarity is highest in the morning (about 30 feet Secchi depth) and often decreases throughout the day.
Analysis of existing data provided some insight into the hydrologic processes affecting Warm Mineral Springs; however, data have been sparsely and discontinuously collected since the 1940s. Continuous monitoring of hydrologic characteristics such as discharge, water temperature, specific conductance, and water-quality indicators, such as nitrate and turbidity (water clarity), would be valuable for monitoring and development of models of spring discharge and water quality. In addition, water samples could be analyzed for isotopic tracers, such as strontium, and the results used to identify and quantify the sources of groundwater that discharge at Warm Mineral Springs. Groundwater flow/transport models could be used to evaluate the sensitivity of the quality and quantity of water flowing from Warm Mineral Springs to changes in climate, aquifer levels, and water use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161166","collaboration":"Prepared in cooperation with the City of North Port and Sarasota County ","usgsCitation":"Metz, P.A., 2016, Discharge, water temperature, and water quality of Warm Mineral Springs, Sarasota County, Florida: A retrospective analysis: U.S. Geological Survey Open-File Report 2016–1166, 31 p., https://dx.doi.org/10.3133/ofr20161166.","productDescription":"vi, 31 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-066216","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":328877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1166/coverthb2.jpg"},{"id":328878,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1166/ofr20161166.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1166"}],"country":"United States","state":"Florida","county":"Sarasota County","otherGeospatial":"Warm Mineral Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.26177334785461,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.058867814427533\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
(813) 498-5000
Or visit the Caribbean-Florida Water Science Center Web page at
http://fl.water.usgs.gov
The Northern Arizona Regional Groundwater Flow Model was used to estimate the hydrologic changes, including water-level change and groundwater discharge to streams and springs, that may result from future changes in groundwater withdrawals in and near the Coconino Plateau Water Advisory Council study area, Coconino and Navajo Counties, Arizona. Three future groundwater withdrawal scenarios for tribal and nontribal uses were developed by the Coconino Plateau Water Advisory Council and were simulated for the period representing the years from 2006 through 2105. Scenario 1 assumes no major changes in groundwater use except for increased demand based on population projections. Scenario 2 assumes that a pipeline will provide a source of surface water from Lake Powell to areas near Cameron and Moenkopi that would replace local groundwater withdrawals. Scenario 3 assumes that the pipeline extends to the Flagstaff and Williams areas, and would replace groundwater demands for water in the area.
The Coconino Plateau Water Advisory Council withdrawal scenarios primarily influence water levels and groundwater discharge in the Coconino Plateau basin, near the western margin of the Little Colorado River Plateau basin, and the Verde Valley subbasin. Simulated effects of the withdrawal scenarios are superimposed on effects of previous variations in groundwater withdrawals and artificial and incidental recharge. Pre-scenario variations include changes in water-levels in wells; groundwater storage; discharge to streams and springs; and evapotranspiration by plants that use groundwater. Future variations in groundwater discharge and water-levels in wells will continue to occur as a result of both the past and any future changes.
Water-level variations resulting from post-2005 stresses, including groundwater withdrawals and incidental and artificial recharge, in the area of the withdrawal scenarios are primarily localized and superimposed on the regional changes caused by variations in stresses that occurred since the beginning of the initial stresses in the early 1900s through 2005. Withdrawal scenario 1 produced a broad region on the Coconino Plateau where water-levels declined 3–5 feet by 2105, and local areas with water-level declines of 100 feet or more where groundwater withdrawals are concentrated, near the City of Flagstaff Woody Mountain and Lake Mary well fields, and the towns of Tusayan, Williams, and Moenkopi. Water-level rises of 100 feet or more were simulated at areas of incidental recharge near wastewater treatment facilities near Flagstaff, Tusayan, Grand Canyon South Rim, Williams, and Munds Park.
Simulated water-level change from 2006 through 2105 for scenarios 2 and 3 is mostly different from water-level change simulated for scenario 1 at the local level. For scenarios 2 and 3, water levels near Cameron in 2105 where 1–3 feet higher than simulated for scenario 1. Water levels at Moenkopi are more than 100 feet higher due to the elimination of a proposed withdrawal well that was simulated in scenario 1. Scenario 3 eliminates more groundwater withdrawals in the Flagstaff and Williams areas, simulates 1–3 feet less water-level decline than scenario 1 across much of the Coconino Plateau, and water levels that are as much as 50 feet higher than simulated by scenario 1 near withdrawal wells in the Williams and Flagstaff areas.
Scenario 1 simulated the most change in groundwater discharge for the Little Colorado River below Cameron and for Oak Creek above Page Springs where declines in discharge of about 1.3 and 0.9 cubic feet per second (ft3/s), respectively, were simulated. Other simulated changes in discharge through 2105 in scenario 1 are losses of less than 0.4 ft3/s at the Upper Verde River, losses of less than 0.3 ft3/s at Havasu Creek and at Colorado River below Havasu Creek, losses of less than 0.1 ft3/s at Clear Creek, and increases in flow at the south rim springs and Chevelon Creek of less than 0.1 and 0.3 ft3/s, respectively. Simulated changes in discharge for scenarios 2 and 3 are less than for scenario 1 because of lower rates of groundwater withdrawal. Scenario 3 resulted in greater groundwater discharge than scenarios 1 and 2 at all major groundwater discharge features from 2006 through 2105 except for Clear and Chevelon Creeks, where the same groundwater discharge was simulated by each of the three scenarios.
Changes in groundwater discharge are expected to occur after 2105 to all major surface features that discharge from the Redwall-Muav and Coconino aquifers because change in aquifer storage was occurring at the end of the simulation in 2105. The accuracy of simulated changes resulting from the Coconino Plateau Water Advisory Council groundwater withdrawal scenarios is dependent on the persistence of several hydrologic assumptions that are inherent in the Northern Arizona Regional Groundwater Flow Model including, but not limited to, the reasonably accurate simulation of (1) transmissivity distributions, (2) distributions of vertical hydraulic properties, (3) distributions of spatial rates of withdrawal and incidental recharge, (4) aquifer extents, and (5) hydrologic barriers and conduits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165115","collaboration":"Prepared in cooperation with the Arizona Department of Water Resources and Yavapai County","usgsCitation":"Pool, D.R., 2016, Simulation of groundwater withdrawal scenarios for the Redwall-Muav and Coconino aquifer systems of northern and central Arizona: U.S. Geological Survey Scientific Investigations Report 2016–5115, 38 p., https://dx.doi.org/10.3133/sir20165115.","productDescription":"vi, 38 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-072545","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":328682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5115/coverthb.jpg"},{"id":328683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5115/sir20165115.pdf","text":"Report","size":"7.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5115"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5384521484375,\n 34.511083202999714\n ],\n [\n -112.5384521484375,\n 36.9806150652861\n ],\n [\n -110.50048828124999,\n 36.9806150652861\n ],\n [\n -110.50048828124999,\n 34.511083202999714\n ],\n [\n -112.5384521484375,\n 34.511083202999714\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
Understanding karst aquifers, for purposes of their management and protection, poses unique challenges. Karst aquifers are characterized by groundwater flow through conduits (tertiary porosity), and (or) layers with interconnected pores (secondary porosity) and through intergranular porosity (primary or matrix porosity). Since the late 1960s, advances have been made in the development of numerical computer codes and the use of mathematical model applications towards the understanding of dual (primary [matrix] and secondary [fractures and conduits]) porosity groundwater flow processes, as well as characterization and management of karst aquifers. The Floridan aquifer system (FAS) in Florida and parts of Alabama, Georgia, and South Carolina is composed of a thick sequence of predominantly carbonate rocks. Karst features are present over much of its area, especially in Florida where more than 30 first-magnitude springs occur, numerous sinkholes and submerged conduits have been mapped, and numerous circular lakes within sinkhole depressions are present. Different types of mathematical models have been applied for simulation of the FAS. Most of these models are distributed parameter models based on the assumption that, like a sponge, water flows through connected pores within the aquifer system and can be simulated with the same mathematical methods applied to flow through sand and gravel aquifers; these models are usually referred to as porous-equivalent media models. The partial differential equation solved for groundwater flow is the potential flow equation of fluid mechanics, which is used when flow is dominated by potential energy and has been applied for many fluid problems in which kinetic energy terms are dropped from the differential equation solved. In many groundwater model codes (basic MODFLOW), it is assumed that the water has a constant temperature and density and that flow is laminar, such that kinetic energy has minimal impact on flow. Some models have been developed that incorporate the submerged conduits as a one-dimensional pipe network within the aquifer rather than as discrete, extremely transmissive features in a porous-equivalent medium; these submerged conduit models are usually referred to as hybrid models and may include the capability to simulate both laminar and turbulent flow in the one-dimensional pipe network. Comparisons of the application of a porous-equivalent media model with and without turbulence (MODFLOW-Conduit Flow Process mode 2 and basic MODFLOW, respectively) and a hybrid (MODFLOW-Conduit Flow Process mode 1) model to the Woodville Karst Plain near Tallahassee, Florida, indicated that for annual, monthly, or seasonal average hydrologic conditions, all methods met calibration criteria (matched observed groundwater levels and average flows). Thus, the increased effort required, such as the collection of data on conduit location, to develop a hybrid model and its increased computational burden, is not necessary for simulation of average hydrologic conditions (non-laminar flow effects on simulated head and spring discharge were minimal). However, simulation of a large storm event in the Woodville Karst Plain with daily stress periods indicated that turbulence is important for matching daily springflow hydrographs. Thus, if matching streamflow hydrographs over a storm event is required, the simulation of non-laminar flow and the location of conduits are required. The main challenge in application of the methods and approaches for developing hybrid models relates to the difficulty of mapping conduit networks or having high-quality datasets to calibrate these models. Additionally, hybrid models have long simulation times, which can preclude the use of parameter estimation for calibration. Simulation of contaminant transport that does not account for preferential flow through conduits or extremely permeable zones in any approach is ill-advised. Simulation results in other karst aquifers or other parts of the FAS may differ from the comparison demonstrated herein.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165116","collaboration":"A product of the Water Use and Availability Science Program","usgsCitation":"Kuniansky, E.L., 2016, Simulating groundwater flow in karst aquifers with distributed parameter models—Comparison of porous-equivalent media and hybrid flow approaches: U.S. Geological Survey Scientific Investigations Report 2016–5116, 14 p., https://dx.doi.org/10.3133/sir20165116.","productDescription":"Report: v, 14 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-071317","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":328727,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5116/sir20165116.pdf","text":"Report","size":"3.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5116"},{"id":328833,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7PK0D87","text":"USGS data release - MODFLOW and MODFLOW Conduit Flow Process data sets for simulation experiments of the Woodville Karst Plain, near Tallahassee, Florida with three different approaches and different stress periods","description":"SIR 2016–5116 Data Release"},{"id":328726,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5116/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Woodville Karst Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.4903564453125,\n 30.04532159026885\n ],\n [\n -84.4903564453125,\n 30.456368670179007\n ],\n [\n -84.06875610351562,\n 30.456368670179007\n ],\n [\n -84.06875610351562,\n 30.04532159026885\n ],\n [\n -84.4903564453125,\n 30.04532159026885\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Caribbean-Florida Water Science Center-Florida
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559–6302
The study region encompasses the nearshore, coastal waters off west Maui, Hawaii. Here abundant groundwater—that carries with it a strong land-based fingerprint—discharges into the coastal waters and over a coral reef.
Coastal groundwater discharge is a ubiquitous hydrologic feature that has been shown to impact nearshore ecosystems and material budgets. A unique combined geochemical tracer and oceanographic time-series study addressed rates and oceanic forcings of submarine groundwater discharge at a submarine spring site off west Maui, Hawaii.
Estimates of submarine groundwater discharge were derived for a primary vent site and surrounding coastal waters off west Maui, Hawaii using an excess 222Rn (t1/2 = 3.8 d) mass balance model. Such estimates were complemented with a novel thoron (220Rn,t1/2 = 56 s) groundwater discharge tracer application, as well as oceanographic time series and thermal infrared imagery analyses. In combination, this suite of techniques provides new insight into the connectivity of the coastal aquifer with the near-shore ocean and examines the physical drivers of submarine groundwater discharge. Lastly, submarine groundwater discharge derived constituent concentrations were tabulated and compared to surrounding seawater concentrations. Such work has implications for the management of coastal aquifers and downstream nearshore ecosystems that respond to sustained constituent loadings via this submarine route.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2015.12.056","usgsCitation":"Swarzenski, P.W., Dulai, H., Kroeger, K., Smith, C.G., Dimova, N., Storlazzi, C., Prouty, N., Gingerich, S.B., and Glenn, C.R., 2016, Observations of nearshore groundwater discharge: Kahekili Beach Park submarine springs, Maui, Hawaii: Journal of Hydrology: Regional Studies, v. 11, p. 147-165, https://doi.org/10.1016/j.ejrh.2015.12.056.","productDescription":"19 p.","startPage":"147","endPage":"165","ipdsId":"IP-068143","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328777,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":470561,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2015.12.056","text":"Publisher Index Page"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.69799804687497,\n 20.92604896920106\n ],\n [\n -156.69799804687497,\n 20.94685150573486\n ],\n [\n -156.6826343536377,\n 20.94685150573486\n ],\n [\n -156.6826343536377,\n 20.92604896920106\n ],\n [\n -156.69799804687497,\n 20.92604896920106\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c87c","contributors":{"authors":[{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":649120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dulai, H.","contributorId":174725,"corporation":false,"usgs":false,"family":"Dulai","given":"H.","email":"","affiliations":[],"preferred":false,"id":649121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, K.D.","contributorId":26060,"corporation":false,"usgs":true,"family":"Kroeger","given":"K.D.","email":"","affiliations":[],"preferred":false,"id":649122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":649123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dimova, N.","contributorId":66051,"corporation":false,"usgs":true,"family":"Dimova","given":"N.","affiliations":[],"preferred":false,"id":649124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Storlazzi, C. D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":127154,"corporation":false,"usgs":true,"family":"Storlazzi","given":"C. D.","affiliations":[],"preferred":false,"id":649125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prouty, N.G.","contributorId":36766,"corporation":false,"usgs":true,"family":"Prouty","given":"N.G.","email":"","affiliations":[],"preferred":false,"id":649126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gingerich, S. B.","contributorId":83958,"corporation":false,"usgs":true,"family":"Gingerich","given":"S.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":649127,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Glenn, C. R.","contributorId":174726,"corporation":false,"usgs":false,"family":"Glenn","given":"C.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":649128,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70174983,"text":"sir20165108 - 2016 - Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky","interactions":[],"lastModifiedDate":"2016-09-19T13:57:31","indexId":"sir20165108","displayToPublicDate":"2016-09-19T10:45:00","publicationYear":"2016","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":"2016-5108","title":"Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky","docAbstract":"Digital flood inundation maps for a 17-mile reach of Licking River and 4-mile reach of South Fork Licking River near Falmouth, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with Pendleton County and the U.S. Army Corps of Engineers–Louisville District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://wim.usgs.gov/FIMI/FloodInundationMapper.html, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Licking River at Catawba, Ky., (station 03253500) and the USGS streamgage on the South Fork Licking River at Hayes, Ky., (station 03253000). Current conditions (2015) for the USGS streamgages may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis). In addition, the streamgage information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The flood hydrograph forecasts provided by the NWS are usually collocated with USGS streamgages. The forecasted peak-stage information, also available on the NWS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
In this study, flood profiles were computed for the Licking River reach and South Fork Licking River reach by using a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current (2015) stage-discharge relations for the Licking River at Catawba, Ky., and the South Fork Licking River at Hayes, Ky., USGS streamgages. The calibrated model was then used to calculate 60 water-surface profiles for a sequence of flood stages, at 2-foot intervals, referenced to the streamgage datum and ranging from an elevation near bankfull to the elevation associated with a major flood that occurred in the region in 1997. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model of the study area by using geographic information system software.
The availability of these flood inundation maps for Falmouth, Ky., along with online information regarding current stages from the USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with information that is critical for flood response activities such as evacuations, road closures, and post-flood recovery efforts.
Director, USGS Indiana-Kentucky Water Science Center
9818 Bluegrass Parkway
Louisville, KY 40299
Snow sublimation can be an important component of the snow-cover mass balance, and there is considerable interest in quantifying the role of this process within the water and energy balance of snow-covered regions. In recent years, robust eddy covariance (EC) instrumentation has been used to quantify snow sublimation over snow-covered surfaces in complex mountainous terrain. However, EC can be challenging for monitoring turbulent fluxes in snow-covered environments because of intensive data, power, and fetch requirements, and alternative methods of estimating snow sublimation are often relied upon. To evaluate the relative merits of methods for quantifying surface sublimation, fluxes calculated by the EC, Bowen ratio–energy balance (BR), bulk aerodynamic flux (BF), and aerodynamic profile (AP) methods and their associated uncertainty were compared at two forested openings in the Colorado Rocky Mountains. Biases between methods are evaluated over a range of environmental conditions, and limitations of each method are discussed. Mean surface sublimation rates from both sites ranged from 0.33 to 0.36 mm day−1, 0.14 to 0.37 mm day−1, 0.10 to 0.17 mm day−1, and 0.03 to 0.10 mm day−1 for the EC, BR, BF and AP methods, respectively. The EC and/or BF methods are concluded to be superior for estimating surface sublimation in snow-covered forested openings. The surface sublimation rates quantified in this study are generally smaller in magnitude compared with previously published studies in this region and help to refine sublimation estimates for forested openings in the Colorado Rocky Mountains.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10864","usgsCitation":"Sexstone, G.A., Clow, D.W., Stannard, D.I., and Fassnacht, S.R., 2016, Comparison of methods for quantifying surface sublimation over seasonally snow-covered terrain: Hydrological Processes, v. 30, no. 19, p. 3373-3389, https://doi.org/10.1002/hyp.10864.","productDescription":"17 p.","startPage":"3373","endPage":"3389","ipdsId":"IP-071074","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":331427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"19","noUsgsAuthors":false,"publicationDate":"2016-06-06","publicationStatus":"PW","scienceBaseUri":"584144e0e4b04fc80e5073a8","contributors":{"authors":[{"text":"Sexstone, Graham A. 0000-0001-8913-0546 sexstone@usgs.gov","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":5159,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham","email":"sexstone@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stannard, David I. distanna@usgs.gov","contributorId":562,"corporation":false,"usgs":true,"family":"Stannard","given":"David","email":"distanna@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":654743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fassnacht, Steven R.","contributorId":177135,"corporation":false,"usgs":false,"family":"Fassnacht","given":"Steven","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":654744,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176453,"text":"70176453 - 2016 - Prerequisites for understanding climate-change impacts on northern prairie wetlands","interactions":[],"lastModifiedDate":"2017-01-03T16:13:01","indexId":"70176453","displayToPublicDate":"2016-09-14T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Prerequisites for understanding climate-change impacts on northern prairie wetlands","docAbstract":"The Prairie Pothole Region (PPR) contains ecosystems that are typified by an extensive matrix of grasslands and depressional wetlands, which provide numerous ecosystem services. Over the past 150 years the PPR has experienced numerous landscape modifications resulting in agricultural conversion of 75–99 % of native prairie uplands and drainage of 50–90 % of wetlands. There is concern over how and where conservation dollars should be spent within the PPR to protect and restore wetland basins to support waterbird populations that will be robust to a changing climate. However, while hydrological impacts of landscape modifications appear substantial, they are still poorly understood. Previous modeling efforts addressing impacts of climate change on PPR wetlands have yet to fully incorporate interacting or potentially overshadowing impacts of landscape modification. We outlined several information needs for building more informative models to predict climate change effects on PPR wetlands. We reviewed how landscape modification influences wetland hydrology and present a conceptual model to describe how modified wetlands might respond to climate variability. We note that current climate projections do not incorporate cyclical variability in climate between wet and dry periods even though such dynamics have shaped the hydrology and ecology of PPR wetlands. We conclude that there are at least three prerequisite steps to making meaningful predictions about effects of climate change on PPR wetlands. Those evident to us are: 1) an understanding of how physical and watershed characteristics of wetland basins of similar hydroperiods vary across temperature and moisture gradients; 2) a mechanistic understanding of how wetlands respond to climate across a gradient of anthropogenic modifications; and 3) improved climate projections for the PPR that can meaningfully represent potential changes in climate variability including intensity and duration of wet and dry periods. Once these issues are addressed, we contend that modeling efforts will better inform and quantify ecosystem services provided by wetlands to meet needs of waterbird conservation and broader societal interests such as flood control and water quality.","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0811-2","usgsCitation":"Anteau, M.J., Wiltermuth, M.T., Post van der Burg, M., and Pearse, A.T., 2016, Prerequisites for understanding climate-change impacts on northern prairie wetlands: Wetlands, v. 36, no. s2, p. 299-307, https://doi.org/10.1007/s13157-016-0811-2.","productDescription":"9 p.","startPage":"299","endPage":"307","ipdsId":"IP-073902","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"s2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-08","publicationStatus":"PW","scienceBaseUri":"57da66a5e4b090824ffb164c","chorus":{"doi":"10.1007/s13157-016-0811-2","url":"http://dx.doi.org/10.1007/s13157-016-0811-2","publisher":"Springer Nature","authors":"Anteau Michael J., Wiltermuth Mark T., van der Burg Max Post, Pearse Aaron T.","journalName":"Wetlands","publicationDate":"9/8/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"9/8/2016"},"contributors":{"authors":[{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":648804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648806,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176448,"text":"ofr20161159 - 2016 - Water temperature effects from simulated dam operations and structures in the Middle Fork Willamette River, western Oregon","interactions":[],"lastModifiedDate":"2016-09-15T08:09:53","indexId":"ofr20161159","displayToPublicDate":"2016-09-14T00:00:00","publicationYear":"2016","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":"2016-1159","title":"Water temperature effects from simulated dam operations and structures in the Middle Fork Willamette River, western Oregon","docAbstract":"Streamflow and water temperature in the Middle Fork Willamette River (MFWR), western Oregon, have been regulated and altered since the construction of Lookout Point, Dexter, and Hills Creek Dams in 1954 and 1961, respectively. Each year, summer releases from the dams typically are cooler than pre-dam conditions, with the reverse (warmer than pre-dam conditions) occurring in autumn. This pattern has been detrimental to habitat of endangered Upper Willamette River (UWR) Chinook salmon (Oncorhynchus tshawytscha) and UWR winter steelhead (O. mykiss) throughout multiple life stages. In this study, scenarios testing different dam-operation strategies and hypothetical dam-outlet structures were simulated using CE-QUAL-W2 hydrodynamic/temperature models of the MFWR system from Hills Creek Lake (HCR) to Lookout Point (LOP) and Dexter (DEX) Lakes to explore and understand the efficacy of potential flow and temperature mitigation options.
Model scenarios were run in constructed wet, normal, and dry hydrologic calendar years, and designed to minimize the effects of Hills Creek and Lookout Point Dams on river temperature by prioritizing warmer lake surface releases in May–August and cooler, deep releases in September–December. Operational scenarios consisted of a range of modified release rate rules, relaxation of power-generation constraints, variations in the timing of refill and drawdown, and maintenance of different summer maximum lake levels at HCR and LOP. Structural scenarios included various combinations of hypothetical floating outlets near the lake surface and hypothetical new outlets at depth. Scenario results were compared to scenarios using existing operational rules that give temperature management some priority (Base), scenarios using pre-2012 operational rules that prioritized power generation over temperature management (NoBlend), and estimated temperatures from a without-dams condition (WoDams).
Results of the tested model scenarios led to the following conclusions:
Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed regional-regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, 0.2-percent annual exceedance-probability discharge (AEPD) for natural streamflow in eastern Colorado. A total of 188 streamgages, consisting of 6,536 years of record and a mean of approximately 35 years of record per streamgage, were used to develop the peak-streamflow regional-regression equations. The estimated AEPDs for each streamgage were computed using the USGS software program PeakFQ. The AEPDs were determined using systematic data through water year 2013. Based on previous studies conducted in Colorado and neighboring States and on the availability of data, 72 characteristics (57 basin and 15 climatic characteristics) were evaluated as candidate explanatory variables in the regression analysis. Paleoflood and non-exceedance bound ages were established based on reconnaissance-level methods. Multiple lines of evidence were used at each streamgage to arrive at a conclusion (age estimate) to add a higher degree of certainty to reconnaissance-level estimates. Paleoflood or nonexceedance bound evidence was documented at 41 streamgages, and 3 streamgages had previously collected paleoflood data.To determine the peak discharge of a paleoflood or non-exceedanc bound, two different hydraulic models were used.
The mean standard error of prediction (SEP) for all 8 AEPDs was reduced approximately 25 percent compared to the previous flood-frequency study. For paleoflood data to be effective in reducing the SEP in eastern Colorado, a larger ratio than 44 of 188 (23 percent) streamgages would need paleoflood data and that paleoflood data would need to increase the record length by more than 25 years for the 1-percent AEPD. The greatest reduction in SEP for the peak-streamflow regional-regression equations was observed when additional new basin characteristics were included in the peak-streamflow regional-regression equations and when eastern Colorado was divided into two separate hydrologic regions. To make further reductions in the uncertainties of the peak-streamflow regional-regression equations in the Foothills and Plains hydrologic regions, additional streamgages or crest-stage gages are needed to collect peak-streamflow data on natural streams in eastern Colorado.
Generalized-Least Squares regression was used to compute the final peak-streamflow regional-regression equations for peak-streamflow. Dividing eastern Colorado into two new individual regions at –104° longitude resulted in peak-streamflow regional-regression equations with the smallest SEP. The new hydrologic region located between –104° longitude and the Kansas-Nebraska State line will be designated the Plains hydrologic region and the hydrologic region comprising the rest of eastern Colorado located west of the –104° longitude and east of the Rocky Mountains and below 7,500 feet in the South Platte River Basin and below 9,000 feet in the Arkansas River Basin will be designated the Foothills hydrologic region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165099","collaboration":"Prepared in cooperation with the Colorado Department of Transportation","usgsCitation":"Kohn, M.S., Stevens, M.R., Harden, T.M., Godaire, J.E., Klinger, R.E., and Mommandi, Amanullah, 2016, Paleoflood investigations to improve peak-streamflow regional-regression equations for natural streamflow in eastern Colorado, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5099, 58 p., https://dx.doi.org/10.3133/sir20165099.","productDescription":"Report: ix, 57 p.; 3 Appendixes","onlineOnly":"Y","ipdsId":"IP-064605","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":328604,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099_Appendix6.zip","text":"Appendix 6","size":"10.6 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5099 Appendix 6"},{"id":328603,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099_Appendix5.zip","text":"Appendix 5","size":"540 kB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5099 Appendix 5"},{"id":328602,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099_Appendix4.zip","text":"Appendix 4","size":"15.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5099 Appendix 4"},{"id":328354,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099.pdf","text":"Report","size":"127 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5099"},{"id":328353,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5099/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.5,\n 42\n ],\n [\n -110.5,\n 36\n ],\n [\n -100.5,\n 36\n ],\n [\n -100.5,\n 42\n ],\n [\n -110.5,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225
In the past decade, difficulties encountered in reproducing the results of a cancer study at Duke University resulted in a scandal and an investigation which concluded that tools used for data management, analysis, and modeling were inappropriate for the documentation of the study, let alone the reproduction of the results. New protocols were developed which require that data analysis and modeling be carried out with scripts that can be used to reproduce the results and are a record of all decisions and interpretations made during an analysis or a modeling effort. In the hydrological sciences, we face similar challenges and need to develop similar standards for transparency and repeatability of results. A promising route is to start making use of open-source languages (such as R and Python) to write scripts and to use collaborative coding environments (such as Git) to share our codes for inspection and use by the hydrological community. An important side-benefit to adopting such protocols is consistency and efficiency among collaborators.
","language":"English","publisher":"EGU","doi":"10.5194/hess-20-3739-2016","usgsCitation":"Fienen, M., and Bakker, M., 2016, HESS Opinions: Repeatable research: what hydrologistscan learn from the Duke cancer research scandal: Hydrology and Earth System Sciences, v. 20, p. 3739-3743, https://doi.org/10.5194/hess-20-3739-2016.","productDescription":"5 p.","startPage":"3739","endPage":"3743","ipdsId":"IP-075419","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":462083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-3739-2016","text":"Publisher Index Page"},{"id":328593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-12","publicationStatus":"PW","scienceBaseUri":"57d91527e4b090824ff9fa36","contributors":{"authors":[{"text":"Fienen, Michael 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":174604,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bakker, Mark","contributorId":56137,"corporation":false,"usgs":true,"family":"Bakker","given":"Mark","email":"","affiliations":[],"preferred":false,"id":648710,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}