The Sparta aquifer is used in 15 parishes in north-central Louisiana, primarily for public supply and industrial purposes. Of those parishes, eight (Bienville, Claiborne, Jackson, Lincoln, Ouachita, Union, Webster, and Winn) rely on the Sparta aquifer as their principal source of groundwater. In 2010, withdrawals from the Sparta aquifer in Louisiana totaled 63.11 million gallons per day (Mgal/d), a reduction of more than 11 percent from 1995, when the highest rate of withdrawals (71.32 Mgal/d) from the Sparta aquifer were documented. The Sparta aquifer provides water for a variety of purposes which include public supply (34.61 Mgal/d), industrial (25.60 Mgal/d), rural domestic (1.50 Mgal/d), and various agricultural (1.40 Mgal/d). Of the 13 major aquifers or aquifer systems in Louisiana, the Sparta aquifer is currently (2012) the sixth most heavily pumped. The Sparta aquifer is the second most heavily pumped aquifer in Arkansas, which borders Louisiana to the north. In 2005, 170 Mgal/d were withdrawn from the Sparta aquifer in eastern and southern Arkansas; of that total, about 15.55 Mgal/d were withdrawn from the aquifer in Union County, which borders Claiborne and Union Parishes to the north. By 1997, a large cone of depression (a cone-shaped depression in the potentiometric surface caused by and centered on a pumping well or wells) in the Sparta aquifer centered over Union County had merged with the cone of depression at West Monroe. In 2004, the rate of withdrawal from the Sparta aquifer in Union County began to decline and water levels in the aquifer began to rise in nearby areas of Arkansas and Louisiana.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3313","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"McGee, B.D., and Brantly, J.A., 2015, Potentiometric surface, 2012, and water-level differences, 2005-12, of the Sparta Aquifer in north-central Louisiana: U.S. Geological Survey Scientific Investigations Map 3313, 2 Sheets: 44.00 x 34.00 inches, https://doi.org/10.3133/sim3313.","productDescription":"2 Sheets: 44.00 x 34.00 inches","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-048894","costCenters":[{"id":369,"text":"Louisiana Water Science 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55570a9fe4b0a92fa7e9cffd","contributors":{"authors":[{"text":"McGee, Benton D. bdmcgee@usgs.gov","contributorId":2899,"corporation":false,"usgs":true,"family":"McGee","given":"Benton","email":"bdmcgee@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brantly, Jeffrey A. jbrantly@usgs.gov","contributorId":5405,"corporation":false,"usgs":true,"family":"Brantly","given":"Jeffrey","email":"jbrantly@usgs.gov","middleInitial":"A.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546994,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148166,"text":"70148166 - 2015 - Composition, shell strength, and metabolizable energy of Mulinia lateralis and Ischadium recurvum as food for wintering surf scoters (Melanitta perspicillata)","interactions":[],"lastModifiedDate":"2015-05-26T12:43:02","indexId":"70148166","displayToPublicDate":"2015-05-15T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Composition, shell strength, and metabolizable energy of Mulinia lateralis and Ischadium recurvum as food for wintering surf scoters (Melanitta perspicillata)","docAbstract":"Decline in surf scoter (Melanitta perspicillata) waterfowl populations wintering in the Chesapeake Bay has been associated with changes in the availability of benthic bivalves. The Bay has become more eutrophic, causing changes in the benthos available to surf scoters. The subsequent decline in oyster beds (Crassostrea virginica) has reduced the hard substrate needed by the hooked mussel (Ischadium recurvum), one of the primary prey items for surf scoters, causing the surf scoter to switch to a more opportune species, the dwarf surfclam (Mulinia lateralis). The composition (macronutrients, minerals, and amino acids), shell strength (N), and metabolizable energy (kJ) of these prey items were quantified to determine the relative foraging values for wintering scoters. Pooled samples of each prey item were analyzed to determine composition. Shell strength (N) was measured using a shell crack compression test. Total collection digestibility trials were conducted on eight captive surf scoters. For the prey size range commonly consumed by surf scoters (6-12 mm for M. lateralis and 18-24 mm for I. recurvum), I. recurvum contained higher ash, protein, lipid, and energy per individual organism than M. lateralis. I. recurvum required significantly greater force to crack the shell relative to M. lateralis. No difference in metabolized energy was observed for these prey items in wintering surf scoters, despite I. recurvum's higher ash content and harder shell than M. lateralis. Therefore, wintering surf scoters were able to obtain the same amount of energy from each prey item, implying that they can sustain themselves if forced to switch prey.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0119839","usgsCitation":"Berlin, A., Perry, M.C., Kohn, R., Paynter, K., and Ottinger, M.A., 2015, Composition, shell strength, and metabolizable energy of Mulinia lateralis and Ischadium recurvum as food for wintering surf scoters (Melanitta perspicillata): PLoS ONE, v. 10, no. 5, p. 1-17, https://doi.org/10.1371/journal.pone.0119839.","productDescription":"17 p.","startPage":"1","endPage":"17","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049373","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0119839","text":"Publisher Index Page"},{"id":300792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-15","publicationStatus":"PW","scienceBaseUri":"55659935e4b0d9246a9eb610","contributors":{"authors":[{"text":"Berlin, Alicia aberlin@usgs.gov","contributorId":4139,"corporation":false,"usgs":true,"family":"Berlin","given":"Alicia","email":"aberlin@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Matthew C. mperry@usgs.gov","contributorId":429,"corporation":false,"usgs":true,"family":"Perry","given":"Matthew","email":"mperry@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kohn, R.A.","contributorId":140930,"corporation":false,"usgs":false,"family":"Kohn","given":"R.A.","email":"","affiliations":[],"preferred":false,"id":547620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paynter, K.T. Jr.","contributorId":140931,"corporation":false,"usgs":false,"family":"Paynter","given":"K.T.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":547621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ottinger, Mary Ann","contributorId":26422,"corporation":false,"usgs":false,"family":"Ottinger","given":"Mary","email":"","middleInitial":"Ann","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":547622,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147790,"text":"sir20155069 - 2015 - Water-quality characteristics of stormwater runoff in Rapid City, South Dakota, 2008-14","interactions":[],"lastModifiedDate":"2017-10-12T20:04:04","indexId":"sir20155069","displayToPublicDate":"2015-05-15T12:00:00","publicationYear":"2015","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":"2015-5069","title":"Water-quality characteristics of stormwater runoff in Rapid City, South Dakota, 2008-14","docAbstract":"The water quality of Rapid Creek is important because the reach that flows through Rapid City, South Dakota, is a valuable spawning area for a self-sustaining trout fishery, actively used for recreation, and a seasonal municipal water supply for the City of Rapid City. This report presents the current (2008–14) water-quality characteristics of urban stormwater runoff in selected drainage networks within the City of Rapid City, and provides an evaluation of the pollutant reductions of wetland channels implemented as a best-management practice. Stormwater runoff data were collected at nine sites in three drainage basins within Rapid City: the Arrowhead (2 monitoring sites), Meade-Hawthorne (1 monitoring site), and Downtown (6 monitoring sites) drainage basins. Stormwater runoff was evaluated for concentrations of total suspended solids (TSS) and bacteria at sites in the Arrowhead and Meade-Hawthorne drainage basins, and for concentrations of TSS, chloride, bacteria, nutrients, and metals at sites in the Downtown drainage basin.
\nFor the Arrowhead and Meade-Hawthorne sites, event-mean concentrations typically exceeded the TSS and bacteria beneficial-use criteria for Rapid Creek by 1–2 orders of magnitude. Comparing the two drainage basins, median TSS event-mean concentrations were more than two times greater at the Meade-Hawthorne outlet (520 milligrams per liter) than the Arrowhead outlet (200 milligrams per liter). Median fecal coliform bacteria event-mean concentrations also were greater at the Meade-Hawthorne outlet site (30,000 colony forming units per 100 milliliters) than the Arrowhead outlet site (17,000 colony forming units per 100 milliliters). A comparison to relevant standards indicates that stormwater runoff from the Downtown drainage basin exceeded criteria for bacteria and TSS, but concentrations generally were below standards for nutrients and metals. Stormwater-quality conditions from the Downtown drainage basin outfalls were similar to or better than stormwater-quality conditions observed in the Arrowhead and Meade-Hawthorne drainage basins. Three wetland channels located at the outlet of the Downtown drainage basin were evaluated for their pollutant reduction capability. Mean reductions in TSS and lead concentrations were greater than 40 percent for all three wetland channels. Total nitrogen, phosphorus, copper, and zinc concentrations also were reduced by at least 20 percent at all three wetlands. Fecal coliform bacteria concentrations typically were reduced by about 21 and 36 percent at the 1st and 2nd Street wetlands, respectively, but the reduction at the 3rd Street wetland channel was nearly zero percent. Total wetland storage volume affected pollutant reductions because TSS, phosphorus, and ammonia reductions were greatest in the wetland with the greatest volume. Chloride concentrations typically increased from inflow to outflow at the 2nd and 3rd Street wetland channels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155069","collaboration":"Prepared in cooperation with the City of Rapid City","usgsCitation":"Hoogestraat, G., 2015, Water-quality characteristics of stormwater runoff in Rapid City, South Dakota, 2008-14: U.S. Geological Survey Scientific Investigations Report 2015-5069, Report: vi, 27 p.; 1 Appendix, https://doi.org/10.3133/sir20155069.","productDescription":"Report: vi, 27 p.; 1 Appendix","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-062139","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":300426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155069.jpg"},{"id":300424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5069/pdf/sir2015-5069.pdf","size":"2.37 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":300425,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5069/downloads/sir2015-5069_appendix1.xlsx","text":"Appendix 1","size":"65 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":300423,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5069/"}],"projection":"Universal Transverse Mercator projection, Zone 13 North","country":"United States","state":"South Dakota","city":"Rapid City","otherGeospatial":"Arrowhead drainage basin, Meade-Hawthorne drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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44.06674358495704\n ],\n [\n -103.18260669708252,\n 44.06535595018047\n ],\n [\n -103.1815767288208,\n 44.06402995766841\n ],\n [\n -103.18110466003418,\n 44.062919801560184\n ],\n [\n -103.18119049072266,\n 44.0623338774432\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55570aa1e4b0a92fa7e9cfff","contributors":{"authors":[{"text":"Hoogestraat, Galen K. ghoogest@usgs.gov","contributorId":2336,"corporation":false,"usgs":true,"family":"Hoogestraat","given":"Galen K.","email":"ghoogest@usgs.gov","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":546295,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144367,"text":"70144367 - 2015 - The effects of geomorphic changes during Hurricane Sandy on water levels in Great South Bay","interactions":[],"lastModifiedDate":"2022-12-22T15:09:43.069217","indexId":"70144367","displayToPublicDate":"2015-05-15T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The effects of geomorphic changes during Hurricane Sandy on water levels in Great South Bay","docAbstract":"Hurricane Sandy caused record coastal flooding along the south shore of Long Island, NY, and led to significant geomorphic changes. These included severe dune erosion along the length of Fire Island and the formation of the Wilderness Breach. This study attempts to use numerical models to quantify how these changes affected water levels inside Great South Bay during and after Hurricane Sandy. The results suggest that overwash along Fire Island may have locally increased peak surge levels in the bay by 20 cm during the storm. There is however large uncertainty surrounding the overwash fluxes. The model results suggest that the development of the Wilderness Breach had locally led to an increase in peak water levels of approximately 7 percent at Lindenhurst by mid-2014, and an increase in tidal amplitudes here of 15 percent. The models predict that the largest changes have occurred in the central part of Great South Bay.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The proceedings of the coastal sediments 2015","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2015","conferenceDate":"May 11-15, 2015","conferenceLocation":"San Diego, CA","language":"English","publisher":"World Scientific","doi":"10.1142/9789814689977_0221","usgsCitation":"van Ormondt, M., Hapke, C., Roelvink, D., and Nelson, T., 2015, The effects of geomorphic changes during Hurricane Sandy on water levels in Great South Bay, in The proceedings of the coastal sediments 2015, San Diego, CA, May 11-15, 2015, 14 p., https://doi.org/10.1142/9789814689977_0221.","productDescription":"14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062930","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":311667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Great South Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.27880859375,\n 40.686886382151116\n ],\n [\n -73.26026916503906,\n 40.65511782196881\n ],\n [\n -73.2293701171875,\n 40.66136857063696\n ],\n [\n -73.22113037109375,\n 40.64886648762003\n ],\n [\n -73.26026916503906,\n 40.635319920747456\n ],\n [\n -73.25889587402344,\n 40.629587853312174\n ],\n [\n -73.19503784179688,\n 40.64469860601901\n ],\n [\n -73.13323974609374,\n 40.65720146993478\n ],\n [\n -73.004150390625,\n 40.687407052121316\n ],\n [\n -72.95951843261719,\n 40.71031250340588\n ],\n [\n -72.91213989257812,\n 40.73112880602221\n ],\n [\n -72.88742065429688,\n 40.749337730454826\n ],\n [\n -72.8887939453125,\n 40.760260692426186\n ],\n [\n -72.91900634765625,\n 40.758700379161034\n ],\n [\n -72.93960571289062,\n 40.745696344339564\n ],\n [\n -73.00552368164062,\n 40.747777160820704\n ],\n [\n -73.03298950195312,\n 40.734770989672406\n ],\n [\n -73.07899475097655,\n 40.72124187397379\n ],\n [\n -73.11813354492186,\n 40.72332345541449\n ],\n [\n -73.13461303710938,\n 40.7202010588415\n ],\n [\n -73.14216613769531,\n 40.703545803451426\n ],\n [\n -73.15658569335936,\n 40.69521661351717\n ],\n [\n -73.20121765136719,\n 40.70823051511181\n ],\n [\n -73.23280334472656,\n 40.70927151739564\n ],\n [\n -73.23348999023438,\n 40.714476284709335\n ],\n [\n -73.25752258300781,\n 40.697299008636755\n ],\n [\n -73.2733154296875,\n 40.68844837985795\n ],\n [\n -73.27880859375,\n 40.686886382151116\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-15","publicationStatus":"PW","scienceBaseUri":"565446c6e4b071e7ea53d4db","contributors":{"authors":[{"text":"van Ormondt, Maarten","contributorId":50181,"corporation":false,"usgs":true,"family":"van Ormondt","given":"Maarten","affiliations":[],"preferred":false,"id":543546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":139949,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":543545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roelvink, Dano","contributorId":139950,"corporation":false,"usgs":false,"family":"Roelvink","given":"Dano","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":543547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Timothy R. 0000-0002-5005-7617 trnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-5005-7617","contributorId":5814,"corporation":false,"usgs":true,"family":"Nelson","given":"Timothy R.","email":"trnelson@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":543548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70147397,"text":"ofr20151055 - 2015 - Effects of proposed sediment borrow pits on nearshore wave climate and longshore sediment transport rate along Breton Island, Louisiana","interactions":[],"lastModifiedDate":"2017-11-15T14:21:55","indexId":"ofr20151055","displayToPublicDate":"2015-05-14T12:45:00","publicationYear":"2015","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":"2015-1055","title":"Effects of proposed sediment borrow pits on nearshore wave climate and longshore sediment transport rate along Breton Island, Louisiana","docAbstract":"As part of a plan to preserve bird habitat on Breton Island, the southernmost extent of the Chandeleur Islands and part of the Breton National Wildlife Refuge in Louisiana, the U.S. Fish and Wildlife Service plans to increase island elevation with sand supplied from offshore resources. Proposed sand extraction sites include areas offshore where the seafloor morphology suggests suitable quantities of sediment may be found. Two proposed locations east and south of the island, between 5.5–9 kilometers from the island in 3–6 meters of water, have been identified. Borrow pits are perturbations to shallow-water bathymetry and thus can affect the wave field in a variety of ways, including alterations in sediment transport and new erosional or accretional patterns along the beach. A scenario-based numerical modeling strategy was used to assess the effects of the proposed offshore borrow pits on the nearshore wave field. Effects were assessed over a range of wave conditions and were gaged by changes in significant wave height and wave direction inshore of the borrow sites, as well as by changes in the calculated longshore sediment transport rate. The change in magnitude of the calculated sediment transport rate with the addition of the two borrow pits was an order of magnitude less than the calculated baseline transport rate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151055","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Dalyander, P.S., Mickey, R.C., Long, J.W., and Flocks, James, 2017, Effects of proposed borrow pits on the nearshore wave climate and longshore sediment transport rate along Breton Island, Louisiana (ver. 2.0, August 2017): U.S. Geological Survey Open-File Report 2015–1055, 44 p., https://doi.org/10.3133/ofr20151055.","productDescription":"Report: vi, 44 p.; HTML Document; Downloads Directory; Data Release; Version History","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059343","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":345194,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2015/1055/VersionHist.txt","size":"1.18 KB","linkFileType":{"id":2,"text":"txt"}},{"id":300407,"rank":1,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2015/1055/pdf/ofr20151055.pdf","text":"Report","size":"3.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300406,"rank":2,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2015/1055/ofr2015-1055_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"},{"id":299991,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1055/index.html","text":"Index page"},{"id":300409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1055/coverthb2.jpg"},{"id":345198,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC81B1","text":"USGS data release","description":"USGS data release","linkHelpText":"Wave Scenario Results of Proposed Sediment Borrow Pit 3 on the Nearshore Wave Climate of Breton Island, LA"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.23301696777342,\n 29.453350219723674\n ],\n [\n -89.23301696777342,\n 29.51013490234384\n ],\n [\n -89.10873413085938,\n 29.51013490234384\n ],\n [\n -89.10873413085938,\n 29.453350219723674\n ],\n [\n -89.23301696777342,\n 29.453350219723674\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: May 2015; Version 2.0: August 2017","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Reduction of cross-sectional data using a genetic algorithm method, and the effects of data reduction on channel geometry and steady-flow profiles, were analyzed. Two reduction methods─standard and genetic algorithms─were used to reduce cross-sectional data from the Kootenai River in northern Idaho. Cross sections that are representative of meander, straight, braided, and canyon reaches were used to evalutate the reduction methods. Visual and hydraulic analyses were used to assess the methods. The genetic algorithm-reduced cross sections approximated the shape of the original cross sections better than the standard-reduced cross sections. A greater number of cross-sectional data points were needed for reduced cross sections in the straight reach, and even more in the braided reach, because a greater amount of data points are needed to adequately define cross sections that have greater topographic varability. For the genetic algorithm-reduction method, about 40 data points were needed to adequately define the shape of a reduced cross section in the braided reach compared to 10 to 20 data points in the meander and canyon reaches. The standard-reduction method needed about 70 data points for the braided reach and more than 30 points for the meander and canyon reaches. The genetic algorithm can effectively reduce data while staying within the threshold set by the maximum number of points to be included in the reduced dataset.
\nThe effects of reduced cross-sectional data points on steady-flow profiles were also determined. Thirty-five cross sections of the original steady-flow model of the Kootenai River were used. These two methods were tested for all cross sections with each cross section resolution reduced to 10, 20 and 30 data points, that is, six tests were completed for each of the thirty-five cross sections. Generally, differences from the original water-surface elevation were smaller as the number of data points in reduced cross sections increased, but this was not always the case, especially in the braided reach. Differences were smaller for reduced cross sections developed by the genetic algorithm method than the standard algorithm method.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155034","usgsCitation":"Berenbrock, C.E., 2015, Reducing cross-sectional data using a genetic algorithm method and effects on cross-section geometry and steady-flow profiles: U.S. Geological Survey Scientific Investigations Report 2015-5034, iv, 16 p., https://doi.org/10.3133/sir20155034.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040903","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":300405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155034.jpg"},{"id":300403,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5034/"},{"id":300404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5034/pdf/sir2015-5034.pdf","size":"639 KB","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5555b938e4b0a92fa7e9512e","contributors":{"authors":[{"text":"Berenbrock, Charles E. ceberenb@usgs.gov","contributorId":857,"corporation":false,"usgs":true,"family":"Berenbrock","given":"Charles","email":"ceberenb@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":543786,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148053,"text":"70148053 - 2015 - Evapotranspiration trends over the eastern United States during the 20th century","interactions":[],"lastModifiedDate":"2019-09-04T14:35:57","indexId":"70148053","displayToPublicDate":"2015-05-14T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evapotranspiration trends over the eastern United States during the 20th century","docAbstract":"Most models evaluated by the Intergovernmental Panel for Climate change estimate projected increases in temperature and precipitation with rising atmospheric CO2 levels. Researchers have suggested that increases in CO2 and associated increases in temperature and precipitation may stimulate vegetation growth and increase evapotranspiration (ET), which acts as a cooling mechanism, and on a global scale, may slow the climate-warming trend. This hypothesis has been modeled under increased CO2 conditions with models of different vegetation-climate dynamics. The significance of this vegetation negative feedback, however, has varied between models. Here we conduct a century-scale observational analysis of the Eastern US water balance to determine historical evapotranspiration trends and whether vegetation greening has affected these trends. We show that precipitation has increased significantly over the twentieth century while runoff has not. We also show that ET has increased and vegetation growth is partially responsible.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"Katlenburg-Lindau, Germany","doi":"10.3390/hydrology2020093","usgsCitation":"Kramer, R.J., Bounoua, L., Zhang, P., Wolfe, R.E., Huntington, T.G., Imhoff, M.L., Thome, K., and Noyce, G.L., 2015, Evapotranspiration trends over the eastern United States during the 20th century: Hydrology and Earth System Sciences, v. 2, no. 2, p. 93-111, https://doi.org/10.3390/hydrology2020093.","productDescription":"19 p.","startPage":"93","endPage":"111","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056810","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":472089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology2020093","text":"Publisher Index Page"},{"id":300464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-14","publicationStatus":"PW","scienceBaseUri":"555b0d43e4b0a92fa7eac61c","contributors":{"authors":[{"text":"Kramer, Ryan J.","contributorId":140788,"corporation":false,"usgs":false,"family":"Kramer","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":546977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bounoua, Lahouari","contributorId":140790,"corporation":false,"usgs":false,"family":"Bounoua","given":"Lahouari","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":546979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Ping","contributorId":140789,"corporation":false,"usgs":false,"family":"Zhang","given":"Ping","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":546978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolfe, Robert E.","contributorId":56560,"corporation":false,"usgs":true,"family":"Wolfe","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":546980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":1884,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Imhoff, Marc L.","contributorId":140791,"corporation":false,"usgs":false,"family":"Imhoff","given":"Marc","email":"","middleInitial":"L.","affiliations":[{"id":13566,"text":"Joint Global Change Research Institute, Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":546981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thome, Kurt","contributorId":140792,"corporation":false,"usgs":false,"family":"Thome","given":"Kurt","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":546982,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Noyce, Genevieve L.","contributorId":140793,"corporation":false,"usgs":false,"family":"Noyce","given":"Genevieve","email":"","middleInitial":"L.","affiliations":[{"id":13567,"text":"Goddard Space Flight Center, 100 St. George Street, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":546983,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70143879,"text":"sir20155046 - 2015 - Assessing geomorphic change along the Trinity River downstream from Lewiston Dam, California, 1980-2011","interactions":[],"lastModifiedDate":"2015-05-14T08:43:47","indexId":"sir20155046","displayToPublicDate":"2015-05-14T09:30:00","publicationYear":"2015","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":"2015-5046","title":"Assessing geomorphic change along the Trinity River downstream from Lewiston Dam, California, 1980-2011","docAbstract":"The Trinity River Restoration Program, one of the nation’s largest adaptively managed river restoration programs, requires periodic assessment to determine the effectiveness of management actions in restoring channel dynamics and habitat features. This study documents riparian and channel changes along an intensively managed 65-kilometer reach of the Trinity River in California, downstream from Lewiston Dam. The two primary periods of interest, from 1980 to 2001 and from 2001 to 2011, are separated by a shift in restoration activities mandated by the U.S. Department of the Interior December 2000 Record of Decision. The post-2001 restoration strategy increased managed-flow releases, gravel augmentation, watershed restoration, and mechanical channel rehabilitation.
\nWe assessed the nature and extent of geomorphic change and a series of ecological performance measures (channel complexity, shoreline length, and channel–floodplain connectivity) by using a series of maps digitized from available rectified orthophotography acquired during low-flow conditions in 1980, 1997, 2001, 2006, 2009, and 2011. Lateral changes in riparian and channel features were used to quantify alluvial processes, and a review of existing streamflow, sediment, and restoration records was used to assess causal mechanisms. During the study period, natural bank erosion and mechanical rehabilitation of channel margins converted riparian features to channel features and expanded the active-channel area. The primary period of bank erosion and expansion of the active channel was from 1980 to 1997. Subsequent bar accretion from 1997 to 2001, followed by slightly greater bar scour from 2001 to 2006, took place primarily in the central and lower reaches of the study area, downstream of Indian Creek. In comparison, post‑2006 bank and bar changes were spatially limited to reaches that had sufficient local transport capacity or sediment supply supported by gravel augmentation, mechanical channel rehabilitation, and tributary contributions.
\nThe highest rates of change in the areal extents of channel and riparian features were observed during the pre‑2001 period, which was longer and relatively wetter than the post-2001 period. A series of tributary floods in 1997, 1998, and 2006 increased channel complexity and floodplain connectivity. During the post-2006 period, managed-flow releases, in the absence of tributary flooding, combined with gravel augmentation and mechanical restoration, caused localized increases in sediment supply and transport capacity that led to smaller, but measurable, increases in channel complexity and floodplain connectivity in the upper river near Lewiston Dam. Extensive pre-2001 channel widening and the muted geomorphic response of channel rehabilitation sites to post-2001 managed flows highlight the need for continued monitoring and assessment of the magnitude, duration, and timing of prescriptive flows and associated geomorphic responses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155046","collaboration":"Prepared in cooperation with the Trinity River Restoration Program","usgsCitation":"Curtis, J.A., Wright, S., Minear, J.T., and Flint, L.E., 2015, Assessing geomorphic change along the Trinity River downstream from Lewiston Dam, California, 1980-2011: U.S. Geological Survey Scientific Investigations Report 2015-5046, viii, 69 p., https://doi.org/10.3133/sir20155046.","productDescription":"viii, 69 p.","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1980-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-033655","costCenters":[{"id":154,"text":"California Water Science 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Washington, based on an airborne lidar survey of October 2007","interactions":[],"lastModifiedDate":"2015-05-14T09:38:52","indexId":"ds936","displayToPublicDate":"2015-05-14T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"936","title":"High-resolution digital elevation model of lower Cowlitz and Toutle Rivers, adjacent to Mount St. Helens, Washington, based on an airborne lidar survey of October 2007","docAbstract":"The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the Toutle River basin, which drains the northern and western flanks of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and lower Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, continues to monitor and mitigate excess sediment in North and South Fork Toutle River basins to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From October 22–27, 2007, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 273 square kilometers (105 square miles) of lower Cowlitz and Toutle River tributaries from the Columbia River at Kelso, Washington, to upper North Fork Toutle River (below the volcano's edifice), including lower South Fork Toutle River. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at Castle and Coldwater Lakes. Final results averaged about two laser last-return points per square meter. As reported by Watershed Sciences, Inc., vertical accuracy is 10 centimeters (cm) at the 95-percent confidence interval on bare road surfaces; however, over natural terrain, USGS found vertical accuracy to be 10–50 cm. This USGS data series contains the bare-earth lidar data as 1- and 10-meter (m) resolution Esri grid files. Digital-elevation data can be downloaded (1m_DEM.zip and 10m_DEM.zip), as well as a 1-m resolution hillshade image with pyramids (1m_hillshade.zip). These geospatial data files require geographic information system (GIS) software for viewing.
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2015 - Geomorphic mapping to support river restoration on the Trinity River downstream from Lewiston Dam, California, 1980-2011","interactions":[],"lastModifiedDate":"2015-05-14T08:36:04","indexId":"ofr20151047","displayToPublicDate":"2015-05-14T08:15:00","publicationYear":"2015","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":"2015-1047","title":"Geomorphic mapping to support river restoration on the Trinity River downstream from Lewiston Dam, California, 1980-2011","docAbstract":"Historic land use, dam construction, water storage, and flow diversions in the Trinity River watershed have resulted in downstream geomorphic change, loss of salmonid habitat, and declines in salmonid populations. 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During the Medieval Climate Anomaly (~ A.D. 900–1300) the four basins collectively experienced 13 large floods compared to nine large floods in the previous 800 years, including the largest floods of the last 2000 years for two of the four basins. This high concentration of extreme floods is likely caused by one or more of the following: 1) instability of air masses caused by stronger than normal westerlies; 2) larger or more frequent hurricanes in the Gulf of Mexico and Atlantic Ocean; and/or 3) reduced land covering vegetation or increased forest fires caused by persistent regional drought.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2014.10.002","usgsCitation":"Harden, T., O'Connor, J., and Driscoll, D.G., 2015, Late Holocene flood probabilities in the Black Hills, South Dakota with emphasis on the Medieval Climate Anomaly: Catena, v. 130, p. 62-68, https://doi.org/10.1016/j.catena.2014.10.002.","productDescription":"7 p.","startPage":"62","endPage":"68","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055115","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":300376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Black Hills","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.55318069458008,\n 44.078706730986426\n ],\n [\n -103.55781555175781,\n 44.08388589964452\n ],\n [\n -103.53378295898438,\n 44.31009208868226\n ],\n [\n -103.42889785766602,\n 44.2867486691176\n ],\n [\n -103.22959899902344,\n 43.97848702497319\n ],\n [\n -103.33946228027344,\n 43.9814516139716\n ],\n [\n -103.55318069458008,\n 44.078706730986426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"130","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555467a5e4b0a92fa7e94f11","contributors":{"authors":[{"text":"Harden, Tessa M. 0000-0001-9854-1347","orcid":"https://orcid.org/0000-0001-9854-1347","contributorId":85690,"corporation":false,"usgs":false,"family":"Harden","given":"Tessa M.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":546900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, James E. oconnor@usgs.gov","contributorId":138998,"corporation":false,"usgs":true,"family":"O'Connor","given":"James E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":546901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, Daniel G. dgdrisco@usgs.gov","contributorId":1558,"corporation":false,"usgs":true,"family":"Driscoll","given":"Daniel","email":"dgdrisco@usgs.gov","middleInitial":"G.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546902,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148032,"text":"70148032 - 2015 - Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata","interactions":[],"lastModifiedDate":"2015-08-03T10:20:43","indexId":"70148032","displayToPublicDate":"2015-05-13T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata","docAbstract":"The perennial shrub Larrea tridentata is widely successful in North American warm deserts but is also susceptible to climatic perturbations. Understanding its response to rainfall variability requires consideration of multiple timescales. We examine intra-annual to multi-year relationships using model simulations of soil moisture and vegetation growth over 50 years in the Mojave National Preserve in southeastern California (USA). Ecohydrological model parameters are conditioned on field and remote sensing data using an ensemble Kalman filter. Although no specific periodicities were detected in the rainfall record, simulated leaf-area-index exhibits multi-year dynamics that are driven by multi-year (∼3-years) rains, but with up to a 1-year delay in peak response. Within a multi-year period, Larrea tridentata is more sensitive to winter rains than summer. In the most active part of the root zone (above ∼80 cm), >1-year average soil moisture drives vegetation growth, but monthly average soil moisture is controlled by root uptake. Moisture inputs reach the lower part of the root zone (below ∼80 cm) infrequently, but once there they can persist over a year to help sustain plant growth. Parameter estimates highlight efficient plant physiological properties facilitating persistent growth and high soil hydraulic conductivity allowing deep soil moisture stores. We show that soil moisture as an ecological indicator is complicated by bidirectional interactions with vegetation that depend on timescale and depth. Under changing climate, Larrea tridentata will likely be relatively resilient to shorter-term moisture variability but will exhibit higher sensitivity to shifts in seasonal to multi-year moisture inputs.
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Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Using biotic ligand models to predict metal toxicity in mineralized systems","docAbstract":"The biotic ligand model (BLM) is a numerical approach that couples chemical speciation calculations with toxicological information to predict the toxicity of aquatic metals. This approach was proposed as an alternative to expensive toxicological testing, and the U.S. Environmental Protection Agency incorporated the BLM into the 2007 revised aquatic life ambient freshwater quality criteria for Cu. Research BLMs for Ag, Ni, Pb, and Zn are also available, and many other BLMs are under development. Current BLMs are limited to ‘one metal, one organism’ considerations. Although the BLM generally is an improvement over previous approaches to determining water quality criteria, there are several challenges in implementing the BLM, particularly at mined and mineralized sites. These challenges include: (1) historically incomplete datasets for BLM input parameters, especially dissolved organic carbon (DOC), (2) several concerns about DOC, such as DOC fractionation in Fe- and Al-rich systems and differences in DOC quality that result in variations in metal-binding affinities, (3) water-quality parameters and resulting metal-toxicity predictions that are temporally and spatially dependent, (4) additional influences on metal bioavailability, such as multiple metal toxicity, dietary metal toxicity, and competition among organisms or metals, (5) potential importance of metal interactions with solid or gas phases and/or kinetically controlled reactions, and (6) tolerance to metal toxicity observed for aquatic organisms living in areas with elevated metal concentrations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.07.005","usgsCitation":"Smith, K.S., Balistrieri, L.S., and Todd, A.S., 2015, Using biotic ligand models to predict metal toxicity in mineralized systems: Applied Geochemistry, v. 57, p. 55-72, https://doi.org/10.1016/j.apgeochem.2014.07.005.","productDescription":"18 p.","startPage":"55","endPage":"72","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057252","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":472092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2014.07.005","text":"Publisher Index Page"},{"id":300370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555467aae4b0a92fa7e94f1b","contributors":{"authors":[{"text":"Smith, Kathleen S. 0000-0001-8547-9804 ksmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8547-9804","contributorId":182,"corporation":false,"usgs":true,"family":"Smith","given":"Kathleen","email":"ksmith@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":546874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, Andrew S. atodd@usgs.gov","contributorId":1022,"corporation":false,"usgs":true,"family":"Todd","given":"Andrew","email":"atodd@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":546876,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148025,"text":"70148025 - 2015 - The fate of cyanide in leach wastes at gold mines: an environmental perspective","interactions":[],"lastModifiedDate":"2015-05-13T11:22:28","indexId":"70148025","displayToPublicDate":"2015-05-13T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"The fate of cyanide in leach wastes at gold mines: an environmental perspective","docAbstract":"This paper reviews the basic chemistry of cyanide, methods by which cyanide can be analyzed, and aspects of cyanide behavior that are most relevant to environmental considerations at mineral processing operations associated with gold mines. The emphasis is on research results reported since 1999 and on data gathered for a series of U.S. Geological Survey studies that began in the late 1990s. Cyanide is added to process solutions as the CN− anion, but ore leaching produces numerous other cyanide-containing and cyanide-related species in addition to the desired cyanocomplex of gold. These can include hydrogen cyanide (HCN); cyanometallic complexes of iron, copper, zinc, nickel, and many other metals; cyanate (CNO−); and thiocyanate (SCN−). The fate of these species in solid wastes and residual process solutions that remain once gold recovery activities are terminated and in any water that moves beyond the ore processing facility dictates the degree to which cyanide poses a risk to aquatic organisms and aquatic-dependent organisms in the local environment.
\nCyanide-containing and cyanide-related species are subject to attenuation mechanisms that lead to dispersal to the atmosphere, chemical transformation to other carbon and nitrogen species, or sequestration as cyanometallic precipitates or adsorbed species on mineral surfaces. Dispersal to the atmosphere and chemical transformation amount to permanent elimination of cyanide, whereas sequestration amounts to storage of cyanide in locations from which it can potentially be remobilized by infiltrating waters if conditions change. From an environmental perspective, the most significant cyanide releases from gold leach operations involve catastrophic spills of process solutions or leakage of effluent to the unsaturated or saturated zones. These release pathways are unfavorable for two important cyanide attenuation mechanisms that tend to occur naturally: dispersal of free cyanide to the atmosphere and sunlight-catalyzed dissociation of strong cyanometallic complexes, which produces free cyanide that can then disperse to the atmosphere. The widest margins of environmental safety will be achieved where mineral processing operations are designed so that time for offgassing, aeration, and sunlight exposure are maximized in the event that cyanide-bearing solutions are released inadvertently.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.05.023","usgsCitation":"Johnson, C.A., 2015, The fate of cyanide in leach wastes at gold mines: an environmental perspective: Applied Geochemistry, v. 57, p. 194-205, https://doi.org/10.1016/j.apgeochem.2014.05.023.","productDescription":"12 p.","startPage":"194","endPage":"205","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056745","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":300365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555467a6e4b0a92fa7e94f15","contributors":{"authors":[{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":546853,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148019,"text":"70148019 - 2015 - Characteristics and environmental aspects of slag: a review","interactions":[],"lastModifiedDate":"2018-09-25T10:52:00","indexId":"70148019","displayToPublicDate":"2015-05-13T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Characteristics and environmental aspects of slag: a review","docAbstract":"Slag is a waste product from the pyrometallurgical processing of various ores. Based on over 150 published studies, this paper provides an overview of mineralogical and geochemical characteristics of different types of slag and their environmental consequences, particularly from the release of potentially toxic elements to water. This chapter reviews the characteristics of both ferrous (steel and blast furnace Fe) and non-ferrous (Ag, Cu, Ni, Pb, Sn, Zn) slag. Interest in slag has been increasing steadily as large volumes, on the order of hundreds of millions of tonnes, are produced annually worldwide. Research on slag generally focuses on potential environmental issues related to the weathering of slag dumps or on its utility as a construction material or reprocessing for secondary metal recovery. The chemistry and mineralogy of slag depend on the metallurgical processes that create the material and will influence its fate as waste or as a reusable product.
\nThe composition of ferrous slag is dominated by Ca and Si. Steel slag may contain significant Fe, whereas Mg and Al may be significant in Fe slag. Calcium-rich olivine-group silicates, melilite-group silicates that contain Al or Mg, Ca-rich glass, and oxides are the most commonly reported major phases in ferrous slag. Calcite and trace amounts of a variety of sulfides, intermetallic compounds, and pure metals are typically also present. The composition of non-ferrous slag, most commonly from base-metal production, is dominated by Fe and Si with significant but lesser amounts of Al and Ca. Silicates in the olivine, pyroxene, and melilite groups, as well as glass, spinels, and SiO2 (i.e., quartz and other polymorphs) are commonly found in non-ferrous slag. Sulfides and intermetallic compounds are less abundant than the silicates and oxides. The concentrations of some elements exceed generic USEPA soil screening levels for human contact based on multiple exposure pathways; these elements include Al, Cr, Cu, Fe, Mn, Pb, and Zn based on bulk chemical composition. Each slag type usually contains a specific suite of elements that may be of environmental concern. In general, non-ferrous slag may have a higher potential to negatively impact the environment compared to ferrous slag, and is thus a less attractive material for reuse, based on trace element chemistry, principally for base metals. However, the amount of elements released into the environment is not always consistent with bulk chemical composition. Many types of leaching tests have been used to help predict slag’s long-term environmental behavior. Overall, ferrous slags produce an alkaline leachate due to the dissolution of Ca oxides and silicates derived from compounds originally added as fluxing agents, such as lime. Ferrous slag leachate is commonly less metal-rich than leachate from non-ferrous slag generated during base metal extraction; the latter leachate may even be acidic due to the oxidation of sulfides. Because of its characteristics, ferrous slag is commonly used for construction and environmental applications, whereas both non-ferrous and ferrous slag may be reprocessed for secondary metal recovery. Both types of slag have been a source of some environmental contamination. Research into the environmental aspects of slag will continue to be an important topic whether the goal is its reuse, recycling, or remediation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.04.009","usgsCitation":"Piatak, N.M., Parsons, M.B., and Seal, R., 2015, Characteristics and environmental aspects of slag: a review: Applied Geochemistry, v. 57, p. 236-266, https://doi.org/10.1016/j.apgeochem.2014.04.009.","productDescription":"31 p.","startPage":"236","endPage":"266","numberOfPages":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025316","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":300358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555467a3e4b0a92fa7e94f0b","contributors":{"authors":[{"text":"Piatak, Nadine M. 0000-0002-1973-8537 npiatak@usgs.gov","orcid":"https://orcid.org/0000-0002-1973-8537","contributorId":2324,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine","email":"npiatak@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":546838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Michael B.","contributorId":140759,"corporation":false,"usgs":false,"family":"Parsons","given":"Michael","email":"","middleInitial":"B.","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":546839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":546840,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70145247,"text":"ofr20151057 - 2015 - Field observations of artificial sand and oil agglomerates","interactions":[],"lastModifiedDate":"2015-05-12T11:41:56","indexId":"ofr20151057","displayToPublicDate":"2015-05-12T12:30:00","publicationYear":"2015","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":"2015-1057","title":"Field observations of artificial sand and oil agglomerates","docAbstract":"Oil that comes into the surf zone following spills, such as occurred during the 2010 Deepwater Horizon (DWH) blowout, can mix with local sediment to form heavier-than-water sand and oil agglomerates (SOAs), at times in the form of mats a few centimeters thick and tens of meters long. Smaller agglomerates that form in situ or pieces that break off of larger mats, sometimes referred to as surface residual balls (SRBs), range in size from sand-sized grains to patty-shaped pieces several centimeters (cm) in diameter. These mobile SOAs can cause beach oiling for extended periods following the spill, on the scale of years as in the case of DWH. Limited research, including a prior effort by the U.S. Geological Survey (USGS) investigating SOA mobility, alongshore transport, and seafloor interaction using numerical model output, focused on the physical dynamics of SOAs. To address this data gap, we constructed artificial sand and oil agglomerates (aSOAs) with sand and paraffin wax to mimic the size and density of genuine SOAs. These aSOAs were deployed in the nearshore off the coast of St. Petersburg, Florida, during a field experiment to investigate their movement and seafloor interaction. This report presents the methodology for constructing aSOAs and describes the field experiment. Data acquired during the field campaign, including videos and images of aSOA movement in the nearshore (1.5-meter and 0.5-meter water depth) and in the swash zone, are also presented in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151057","usgsCitation":"Dalyander, P., Long, J.W., Plant, N.G., McLaughlin, M.R., and Mickey, R., 2015, Field observations of artificial sand and oil agglomerates: U.S. Geological Survey Open-File Report 2015-1057, HTML Document, https://doi.org/10.3133/ofr20151057.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059854","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":300347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151057.jpg"},{"id":300346,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1057/ofr2015-1057_title-page.html","linkFileType":{"id":5,"text":"html"}},{"id":299400,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1057/"}],"country":"United States","state":"Florida","county":"Pinellas County","city":"St. Petersberg","otherGeospatial":"Fort De Soto Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.75074005126953,\n 27.604910228553223\n ],\n [\n -82.75074005126953,\n 27.633048834227715\n ],\n [\n -82.72069931030273,\n 27.633048834227715\n ],\n [\n -82.72069931030273,\n 27.604910228553223\n ],\n [\n -82.75074005126953,\n 27.604910228553223\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55531620e4b0a92fa7e94c43","contributors":{"authors":[{"text":"Dalyander, Patricia (Soupy) 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":5318,"corporation":false,"usgs":true,"family":"Dalyander","given":"Patricia (Soupy)","email":"sdalyander@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":544125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":544127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McLaughlin, Molly R. 0000-0001-6962-6392 mmclaughlin@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-6392","contributorId":4089,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Molly","email":"mmclaughlin@usgs.gov","middleInitial":"R.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544128,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mickey, Rangley C. rmickey@usgs.gov","contributorId":5741,"corporation":false,"usgs":true,"family":"Mickey","given":"Rangley C.","email":"rmickey@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":544129,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147789,"text":"sir20155006 - 2015 - Summary of urban stormwater quality in Albuquerque, New Mexico, 2003-12","interactions":[],"lastModifiedDate":"2015-05-12T11:28:25","indexId":"sir20155006","displayToPublicDate":"2015-05-12T11:45:00","publicationYear":"2015","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":"2015-5006","title":"Summary of urban stormwater quality in Albuquerque, New Mexico, 2003-12","docAbstract":"Urban stormwater in the Albuquerque metropolitan area was sampled by the U.S. Geological Survey in cooperation with the City of Albuquerque, the Albuquerque Metropolitan Arroyo Flood Control Authority, the New Mexico Department of Transportation, and the University of New Mexico. Stormwater was sampled from a network of monitoring stations from 2003 to 2012 by following regulatory requirements for the National Pollutant Discharge Elimination System stormwater permit. During this period, stormwater was sampled in the Albuquerque metropolitan area at outfalls from nine drainage basins with residential, industrial, commercial, agricultural, and undeveloped land uses. Stormwater samples were analyzed for selected physical and chemical characteristics, nutrients, major ions, metals, organic compounds, and bacteria.
\nGeneral quality of stormwater samples, as measured by dissolved solids, nutrient (with the exception of phosphorus), major ion, and dissolved metal concentrations, was similar to that in samples from the Rio Grande.
\nOf the nearly 200 organic compounds that were analyzed for this study, less than one-third (58 constituents) were positively identified at or above the analytical detection limit in stormwater. Concentrations for volatile organic compounds, semivolatile organic compounds, polychlorinated biphenyls, and pesticides were generally low in the stormwater samples. Fifteen of the 16 polycyclic aromatic hydrocarbons listed on the U.S. Environmental Protection Agency Priority Chemicals list were detected in at least one stormwater sample from each outfall. Maximum concentrations for some polycyclic aromatic hydrocarbons in stormwater did exceed a water-quality criterion.
\nMedian concentrations for Escherichia coli (E. coli) bacteria in the stormwater samples, including those from the background location (Embudo Arroyo), were above the New Mexico water-quality standard. Concentrations for E. coli in stormwater often exceeded the water-quality criterion.
\nThe stormwater quality in Albuquerque was compared with that of six other Western U.S. cities (Phoenix, Arizona; Tucson, Arizona; Las Vegas, Nevada; Denver, Colorado; Salt Lake City, Utah; and Boise, Idaho) for selected constituents. In general, water-quality data for stormwater samples from these six other Western U.S. cities were similar to water-quality data for the stormwater samples from the Albuquerque outfalls. Median concentrations for suspended solids, total phosphorus, and bacteria (E. coli and fecal coliform) in stormwater samples from the Albuquerque outfalls, as a whole, were higher than those in samples from the other Western U.S. cities except for Las Vegas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155006","collaboration":"Prepared in cooperation with the City of Albuquerque, the Albuquerque Metropolitan Arroyo Flood Control Authority, the New Mexico Department of Transportation, and the University of New Mexico","usgsCitation":"Storms, E.F., Oelsner, G.P., Locke, E.A., Stevens, M.R., and Romero, O.C., 2015, Summary of urban stormwater quality in Albuquerque, New Mexico, 2003-12: U.S. Geological Survey Scientific Investigations Report 2015-5006, ix, 48 p.; 3 Appendices, https://doi.org/10.3133/sir20155006.","productDescription":"ix, 48 p.; 3 Appendices","numberOfPages":"61","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2003-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-053307","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":300334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155006.jpg"},{"id":300330,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5006/pdf/sir2015-5006.pdf","text":"Report","size":"1.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300331,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5006/downloads/sir2015-5006_appendix1","text":"Appendix 1","description":"Appendix 1"},{"id":300332,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5006/downloads/sir2015-5006_appendix2","text":"Appendix 2","description":"Appendix 2"},{"id":300333,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5006/downloads/sir2015-5006_appendix3.xlsx","text":"Appendix 3","size":"238 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 3"},{"id":300127,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5006/"}],"country":"United States","state":"New Mexico","city":"Albuquerque","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.81869506835938,\n 35.0120020431607\n ],\n [\n -106.81869506835938,\n 35.2355245419696\n ],\n [\n -106.46026611328125,\n 35.2355245419696\n ],\n [\n -106.46026611328125,\n 35.0120020431607\n ],\n [\n -106.81869506835938,\n 35.0120020431607\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55531622e4b0a92fa7e94c4b","contributors":{"authors":[{"text":"Storms, Erik F. estorms@usgs.gov","contributorId":5582,"corporation":false,"usgs":true,"family":"Storms","given":"Erik","email":"estorms@usgs.gov","middleInitial":"F.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oelsner, Gretchen P. 0000-0001-9329-7357 goelsner@usgs.gov","orcid":"https://orcid.org/0000-0001-9329-7357","contributorId":4440,"corporation":false,"usgs":true,"family":"Oelsner","given":"Gretchen","email":"goelsner@usgs.gov","middleInitial":"P.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":546291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Locke, Evan A. elocke@usgs.gov","contributorId":5583,"corporation":false,"usgs":true,"family":"Locke","given":"Evan","email":"elocke@usgs.gov","middleInitial":"A.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stevens, Michael R. 0000-0002-9476-6335 mrsteven@usgs.gov","orcid":"https://orcid.org/0000-0002-9476-6335","contributorId":769,"corporation":false,"usgs":true,"family":"Stevens","given":"Michael","email":"mrsteven@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546293,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romero, Orlando C. 0000-0003-0162-0239 ocromero@usgs.gov","orcid":"https://orcid.org/0000-0003-0162-0239","contributorId":5077,"corporation":false,"usgs":true,"family":"Romero","given":"Orlando","email":"ocromero@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546294,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145564,"text":"sir20155048 - 2015 - Bathymetric and velocimetric surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, June 2014","interactions":[],"lastModifiedDate":"2015-05-12T10:31:47","indexId":"sir20155048","displayToPublicDate":"2015-05-12T11:30:00","publicationYear":"2015","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":"2015-5048","title":"Bathymetric and velocimetric surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, June 2014","docAbstract":"Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, in the vicinity of 8 bridges at 7 highway crossings of the Missouri and Mississippi Rivers on the periphery of Missouri from June 3 to 11, 2014. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches ranging from 1,525 to 1,640 feet longitudinally, and extending laterally across the active channel from bank to bank during low- to moderate-flow conditions. These bathymetric surveys indicate the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low- to moderate-flow comparison to help assess the bridges for stability and integrity issues with respect to bridge scour during floods.
\nBathymetric data were collected around every pier that was in water, except those at the edge of water or in very shallow water (less than about 6 feet). Scour holes were observed at most piers for which bathymetry could be obtained, except at piers on channel banks, on exposed bedrock outcrops, or surrounded by riprap. Scour holes observed at the surveyed bridges were examined with respect to depth and shape, and the effects of riprap blankets or other rock near the piers. The presence of riprap blankets, depth of fluvial material on top of a riprap blanket, and alignment to flow had a substantial effect on the size of the scour hole observed for a given pier. Piers that were surrounded by riprap blankets had scour holes that were substantially smaller (to non-existent) compared to piers at which no rock or riprap was present. Although exposure of parts of foundational support elements was observed at several piers, at most sites the exposure likely can be considered minimal compared to the overall substructure that remains buried in channel-bed material; however, there were several notable exceptions where the bed material thickness between the bottom of the scour hole and bedrock was less than 6 feet. Such substantial exposure of usually buried substructural elements may warrant special observation in future flood events, even when designed to be exposed.
\nPrevious bathymetric surveys had been done at both of the sites on the Missouri River and one of the sites on the Mississippi River examined in this study. Comparisons between bathymetric surfaces from the previous surveys during the 2011 flood and those of this study generally indicate that there was an increase in the elevation of the channel bed at these sites that likely was caused by a substantial decrease in discharge and water-surface elevation compared to the 2011 surveys. However, the scour holes observed at these sites were either the same size or larger in 2014 compared to the 2011 surveys, indicating that the flow condition is not the sole variable in the determination of the size of scour holes, and that local velocity and depth also are critical variables, as indicated by predictive pier scour equations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155048","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2015, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, June 2014: U.S. Geological Survey Scientific Investigations Report 2015-5048, ix, 81 p., https://doi.org/10.3133/sir20155048.","productDescription":"ix, 81 p.","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-06-01","temporalEnd":"2014-06-30","ipdsId":"IP-062935","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":300329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155048.jpg"},{"id":300328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5048/pdf/sir2015-5048.pdf","size":"17.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":300327,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5048/"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","otherGeospatial":"Mississippi River, Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.7952880859375,\n 40.60978237983301\n ],\n [\n -95.73486328124999,\n 40.588928169693745\n ],\n [\n -95.69641113281249,\n 40.53050177574321\n ],\n [\n 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Here we use a hydrological model and risk assessment framework to understand the influence of temperature on the water year (WY) 2014 drought in California and examine the probability that this drought would have been less severe if temperatures resembled the historical climatology. Our results indicate that temperature played an important role in exacerbating the WY 2014 drought severity. We found that if WY 2014 temperatures resembled the 1916–2012 climatology, there would have been at least an 86% chance that winter snow water equivalent and spring-summer soil moisture and runoff deficits would have been less severe than the observed conditions. We also report that the temperature forecast skill in California for the important seasons of winter and spring is negligible, beyond a lead-time of one month, which we postulate might hinder skillful drought prediction in California.
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University","active":true,"usgs":false}],"preferred":false,"id":546724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":546720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145954,"text":"sir20155053 - 2015 - Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling","interactions":[],"lastModifiedDate":"2015-05-12T09:30:22","indexId":"sir20155053","displayToPublicDate":"2015-05-12T10:30:00","publicationYear":"2015","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":"2015-5053","title":"Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling","docAbstract":"The Lake Michigan Diversion Accounting (LMDA) system has been developed by the U.S. Army Corps of Engineers, Chicago District (USACE-Chicago) and the State of Illinois as a part of the interstate Great Lakes water regulatory program. The diverted Lake Michigan watershed is a 673-square-mile watershed that is comprised of the Chicago River and Calumet River watersheds. They originally drained into Lake Michigan, but now flow to the Mississippi River watershed via three canals constructed in the Chicago area in the early twentieth century. Approximately 393 square miles of the diverted watershed is ungaged, and the runoff from the ungaged portion of the diverted watershed has been estimated by the USACE-Chicago using the Hydrological Simulation Program-FORTRAN (HSPF) program. The accuracy of simulated runoff depends on the accuracy of the parameter set used in the HSPF program. Nine parameter sets comprised of the North Branch, Little Calumet, Des Plaines, Hickory Creek, CSSC, NIPC, 1999, CTE, and 2008 have been developed at different time periods and used by the USACE-Chicago. In this study, the U.S. Geological Survey and the USACE-Chicago collaboratively analyzed the parameter sets using nine gaged watersheds in or adjacent to the diverted watershed to assess the predictive accuracies of selected parameter sets. Six of the parameter sets, comprising North Branch, Hickory Creek, NIPC, 1999, CTE, and 2008, were applied to the nine gaged watersheds for evaluating their simulation accuracy from water years 1996 to 2011. The nine gaged watersheds were modeled by using the three LMDA land-cover types (grass, forest, and hydraulically connected imperviousness) based on the 2006 National Land Cover Database, and the latest meteorological and precipitation data consistent with the current (2014) LMDA modeling framework.
\nResults indicate that the North Branch and Hickory Creek parameter sets, which belong to the original calibration group, attained an overall “satisfactory” rating on monthly runoff volumes based on the three performance statistics selected, but the annual and over-the-period runoff volumes were generally underestimated. Parameter sets CTE and 2008 attained a similar satisfactory rating on monthly runoff volumes but the annual and over-the-period runoff volumes were overestimated in general. Although the percent bias was improved, the CTE and 2008 parameter sets also had increased residuals in monthly runoff volumes and decreased quality of the model fit to the measured streamflows relative to the North Branch and Hickory Creek parameter sets. The NIPC and 1999 parameter sets, on the other hand, had larger percent bias and residuals in monthly runoff volumes, and underestimated the annual and over-the-period runoff volumes.
\nRecalibration of the HSPF parameters to the updated inputs and land covers was completed on two representative watershed models selected from the nine by using a manual method (HSPEXP) and an automatic method (PEST). The objective of the recalibration was to develop a regional parameter set that improves the accuracy in runoff volume prediction for the nine study watersheds. Knowledge about flow and watershed characteristics plays a vital role for validating the calibration in both manual and automatic methods. The best performing parameter set was determined by the automatic calibration method on a two-watershed model. Applying this newly determined parameter set to the nine watersheds for runoff volume simulation resulted in “very good” ratings in five watersheds, an improvement as compared to “very good” ratings achieved for three watersheds by the North Branch parameter set.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155053","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Soong, D.T., and Over, T.M., 2015, Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling: U.S. Geological Survey Scientific Investigations Report 2015-5053, vii, 55 p., https://doi.org/10.3133/sir20155053.","productDescription":"vii, 55 p.","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044193","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":300319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155053.jpg"},{"id":300317,"rank":1,"type":{"id":15,"text":"Index 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New Mexico, FY 2015","docAbstract":"The U.S. Geological Survey (USGS) has collected hydrologic information in New Mexico since 1889, beginning with the first USGS streamflow-gaging station in the Nation, located on the Rio Grande near Embudo, New Mexico. Water-resources information provided by the USGS is used by many government agencies for issuing flood warnings to protect lives and reduce property damage,managing water rights and interstate water use, protecting water quality and regulating pollution discharges, designing highways and bridges, planning, designing, and operating reservoirs and watersupply facilities, monitoring the availability of groundwater resources and forecasting aquifer response to human and environmental stressors, and prioritizing areas where emergency erosion mitigation or other protective measures may be necessary after a wildfire. For more than 100 years, the Cooperative Water Program has been a highly successful cost-sharing partnership between the USGS and water-resources agencies at the State, local, and tribal levels. It would be difficult to effectively accomplish the mission of the USGS without the contributions of the Cooperative Water Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153039","usgsCitation":"Mau, D.P., 2015, U.S. Geological Survey water-resources programs in New Mexico, FY 2015: U.S. Geological Survey Fact Sheet 2015-3039, 2 p., https://doi.org/10.3133/fs20153039.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065455","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":300283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153039.jpg"},{"id":300282,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3039/pdf/fs2015-3039.pdf","text":"Report","size":"439 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300281,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3039/"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.072265625,\n 31.31610138349565\n ],\n [\n -108.226318359375,\n 31.3348710339506\n ],\n [\n -108.21533203125,\n 31.77487761850741\n ],\n [\n -106.490478515625,\n 31.77487761850741\n ],\n [\n -106.622314453125,\n 31.98012335736804\n ],\n [\n -103.07373046875,\n 31.99875937194732\n ],\n [\n -102.996826171875,\n 37.00255267215955\n ],\n [\n -109.072265625,\n 37.01132594307015\n ],\n [\n -109.072265625,\n 31.31610138349565\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5551c4abe4b0a92fa7e93b98","contributors":{"authors":[{"text":"Mau, David P. dpmau@usgs.gov","contributorId":457,"corporation":false,"usgs":true,"family":"Mau","given":"David","email":"dpmau@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":546408,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144853,"text":"ofr20151065 - 2015 - Results from laboratory and field testing of nitrate measuring spectrophotometers","interactions":[],"lastModifiedDate":"2015-05-12T13:25:42","indexId":"ofr20151065","displayToPublicDate":"2015-05-11T11:45:00","publicationYear":"2015","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":"2015-1065","title":"Results from laboratory and field testing of nitrate measuring spectrophotometers","docAbstract":"Five ultraviolet (UV) spectrophotometer nitrate analyzers were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) during a two-phase evaluation. In Phase I, the TriOS ProPs (10-millimeter (mm) path length), Hach NITRATAX plus sc (5-mm path length), Satlantic Submersible UV Nitrate Analyzer (SUNA, 10-mm path length), and S::CAN Spectro::lyser (5-mm path length) were evaluated in the HIF Water-Quality Servicing Laboratory to determine the validity of the manufacturer's technical specifications for accuracy, limit of linearity (LOL), drift, and range of operating temperature. Accuracy specifications were met in the TriOS, Hach, and SUNA. The stock calibration of the S::CAN required two offset adjustments before the analyzer met the manufacturer's accuracy specification. Instrument drift was observed only in the S::CAN and was the result of leaching from the optical path insert seals. All tested models, except for the Hach, met their specified LOL in the laboratory testing. The Hach's range was found to be approximately 18 milligrams nitrogen per liter (mg-N/L) and not the manufacturer-specified 25 mg-N/L. Measurements by all of the tested analyzers showed signs of hysteresis in the operating temperature tests. Only the SUNA measurements demonstrated excessive noise and instability in temperatures above 20 degrees Celsius (°C). The SUNA analyzer was returned to the manufacturer at the completion of the Phase II field deployment evaluation for repair and recalibration, and the performance of the sensor improved significantly.
\nIn Phase II, the analyzers were deployed in field conditions at three diferent USGS sites. The measured nitrate concentrations were compared to discrete (reference) samples analyzed by the Direct UV method on a Shimadzu UV1800 bench top spectrophotometer, and by the National Environmental Methods Index (NEMI) method I-2548-11 at the USGS National Water Quality Laboratory. The first deployment at USGS site 0249620 on the East Pearl River in Hancock County, Mississippi, tested the ability of the TriOs ProPs (10-mm path length), Hach NITRATAX (5 mm), Satlantic SUNA (10 mm), and the S::CAN Spectro::lyser (5 mm) to accurately measure low-level (less than 2 mg-N/L) nitrate concentrations while observing the effect turbidity and colored dissolved organic matter (CDOM) would have on the analyzers' measurements. The second deployment at USGS site 01389005 Passaic River below Pompton River at Two Bridges, New Jersey, tested the analyzer's accuracy in mid-level (2-8 mg-N/L) nitrate concentrations. This site provided the means to test the analyzers' performance in two distinct matrices—the Passaic and the Pompton Rivers. In this deployment, three instruments tested in Phase I (TriOS, Hach, and SUNA) were deployed with the S::CAN Spectro::lyser (35 mm) already placed by the New Jersey Water Science Center (WSC). The third deployment at USGS site 05579610 Kickapoo Creek at 2100E Road near Bloomington, Illinois, tested the ability of the analyzers to measure high nitrate concentrations (greater than 8 mg-N/L) in turbid waters. For Kickapoo Creek, the HIF provided the TriOS (10 mm) and S::CAN (5 mm) from Phase I, and a SUNA V2 (5 mm) to be deployed adjacent to the Illinois WSC-owned Hach (2 mm). A total of 40 discrete samples were collected from the three deployment sites and analyzed. The nitrate concentration of the samples ranged from 0.3–22.2 mg-N/L. The average absolute difference between the TriOS measurements and discrete samples was 0.46 mg-N/L. For the combined data from the Hach 5-mm and 2-mm analyzers, the average absolute difference between the Hach samples and the discrete samples was 0.13 mg-N/L. For the SUNA and SUNA V2 combined data, the average absolute difference between the SUNA samples and the discrete samples was 0.66 mg-N/L. The average absolute difference between the S::CAN samples and the discrete samples was 0.63 mg-N/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151065","usgsCitation":"Snazelle, T., 2015, Results from laboratory and field testing of nitrate measuring spectrophotometers: U.S. Geological Survey Open-File Report 2015-1065, v, 15 p., https://doi.org/10.3133/ofr20151065.","productDescription":"v, 15 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057525","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":300295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151065.jpg"},{"id":300294,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1065/pdf/ofr2015-1065.pdf","text":"Report","size":"2.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300293,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1065/"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5551c4aae4b0a92fa7e93b94","contributors":{"authors":[{"text":"Snazelle, Teri T. tsnazelle@usgs.gov","contributorId":5663,"corporation":false,"usgs":true,"family":"Snazelle","given":"Teri T.","email":"tsnazelle@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":543804,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144854,"text":"ofr20151063 - 2015 - Evaluation of Xylem EXO water-quality sondes and sensors","interactions":[],"lastModifiedDate":"2015-05-11T11:41:57","indexId":"ofr20151063","displayToPublicDate":"2015-05-11T11:30:00","publicationYear":"2015","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":"2015-1063","title":"Evaluation of Xylem EXO water-quality sondes and sensors","docAbstract":"Two models of multiparameter sondes manufactured by Xylem, parent company of Yellow Springs Incorporated (YSI)—EXO1 and EXO2—equipped with EXO conductivity/temperature (C/T), pH, dissolved oxygen (DO), and turbidity sensors, were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility. The sondes and sensors were evaluated in two phases for compliance with the manufacturer’s specifications and the USGS acceptance criteria for continuous water-quality monitors. Phase one tested the accuracy of the water-quality sondes equipped: (a) with a C/T, pH, DO, and turbidity sensor by comparing the EXO sensors’ measured values to those of an equivalently configured YSI 6920 V2-2 sensor, and (b) with multiple sensors of the same parameter type (such as three pH sensors and a C/T sensor) on a single sonde at room temperature and at an extended temperature range. In addition to accuracy, the communication protocols and the manufacturing specifications for range of detection and operating temperature were also tested during this phase. Phase two evaluated the sondes’ performance in a surface-water environment by deploying an EXO1 and an EXO2 equipped with pH, C/T, DO, and turbidity sensors at USGS site 02492620 located at East Pearl River near Bay Saint Louis, Mississippi. The EXO sondes’ temperature deviations from a certified YSI 4600 digital thermometer were within the ±0.2 degree Celsius (°C) USGS criteria, but were greater than the ±0.01 °C manufacturing specification. The conductivity sensors met the ±3 percent USGS criteria for specific conductance greater than 100 microsiemens per centimeter. The sensors met the more stringent ±0.5 percent manufacturing specification only at room temperature in the 250 microsiemens per centimeter (µS/cm) standard. The manufacturing and USGS criteria (±0.2 pH unit) were met in pH standards 4, 9.2, 10, and 12.45, but were not met in pH 1.68 standard. The DO sensors met both the ±0.3 milligram per liter (mg/L) USGS criteria and the ±1 percent manufacturing specification. The ±5 percent USGS criteria for turbidity in waters not exceeding 2,000 formazin nephelometric units (FNU) were met by the five turbidity sensors tested; however, all five sensors failed to meet these requirements at turbidities exceeding 2,000 FNU. The more stringent ±2 percent manufacturing turbidity specification for water with less than 1,000 FNU was met by only one of the five sensors tested. The results from the field deployment indicated acceptable agreement in temperature, specific conductance, pH, and DO between the EXO sondes, the site sonde, and the reference sonde. The EXO1 and EXO2 turbidity measurements differed from the site sonde by approximately 23 and 25 percent, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151063","usgsCitation":"Snazelle, T., 2015, Evaluation of Xylem EXO water-quality sondes and sensors: U.S. Geological Survey Open-File Report 2015-1063, vi, 14 p., https://doi.org/10.3133/ofr20151063.","productDescription":"vi, 14 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057551","costCenters":[{"id":339,"text":"Hydrologic Instrumentation Facility","active":false,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":300291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1063/pdf/ofr2015-1063.pdf","text":"Report","size":"2.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300290,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1063/"},{"id":300292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151063.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5551c4a8e4b0a92fa7e93b90","contributors":{"authors":[{"text":"Snazelle, Teri T. tsnazelle@usgs.gov","contributorId":5663,"corporation":false,"usgs":true,"family":"Snazelle","given":"Teri T.","email":"tsnazelle@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":543805,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70147964,"text":"sir20155027 - 2015 - The source, discharge, and chemical characteristics of selected springs, and the abundance and health of associated endemic anuran species in the Mojave network parks","interactions":[],"lastModifiedDate":"2025-05-14T14:51:12.751726","indexId":"sir20155027","displayToPublicDate":"2015-05-11T08:15:00","publicationYear":"2015","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":"2015-5027","title":"The source, discharge, and chemical characteristics of selected springs, and the abundance and health of associated endemic anuran species in the Mojave network parks","docAbstract":"Hydrological and biological investigations were done during 2005 and 2006 in cooperation with the U.S. National Park Service to investigate the source, discharge, and chemical characteristics of selected springs and the abundance and health of endemic anuran (frog and toad) species at Darwin Falls in Death Valley National Park, Piute Spring in Mojave National Preserve, and Fortynine Palms Oasis in Joshua Tree National Park. Discharge from the springs at these sites sustains isolated riparian habitats in the normally dry Mojave Desert. Data were collected on water quantity (discharge) and quality, air and water temperature, and abundance and health of endemic anuran species. In addition, a single survey of the abundance and health of endemic anuran species was completed at Rattlesnake Canyon in Joshua Tree National Park. Results from this study were compared to limited historical data, where they exist, and can provide a baseline for future hydrological and biological investigations to evaluate the health and sustainability of the resource and its response to changing climate and increasing human use.
\nRadiocarbon dating of the water yielded estimated ages of about 7,000 years at Piute Spring and about 3,000 years at Darwin Spring, and tritium-helium-3 dating indicated an age of less than 2 years at Fortynine Palms Oasis. Stable hydrogen-isotope ratios were used to interpret an average altitude of recharge of 2,348 meters for Darwin Spring (about 1,415 meters higher than the altitude of Darwin Spring), 1,668 meters for Piute Spring (about 766 meters higher than the altitude of Piute Spring), and 1,400 meters for the Upper Pool at Fortynine Palms Oasis (about 543 meters higher than the altitude of the Upper Pool). Water-quality data collected for this study did not appear to be sensitive to trends in precipitation or seasonality in the Darwin Falls and Piute Spring study areas; however, it was sensitive to trends in Fortynine Palms Oasis where salinity increased by more than 10 percent during the 2 years of this study. Such a rapid response is consistent with the comparatively short travel time of less than 2 years from recharge to discharge at Fortynine Palms Oasis. Of the 14 trace elements analyzed, only concentrations of uranium at Fortynine Palms Oasis and arsenic at Darwin Spring were above drinking water standards; both constituents are derived from natural sources in the drainage basin and, therefore, are likely to have accumulated as a result of natural processes.
\nEndemic anuran species were surveyed at Darwin Falls for the western toad (Anaxyrus boreas) and the red-spotted toad (Anaxyrus punctatus), at Piute Spring for the red-spotted toad, and at Fortynine Palms Oasis for the red-spotted toad and California treefrog (Pseudacris cadaverina). Historically, red-spotted toads were at the edge of their range at Darwin Falls, but they were not detected during this study and have not been detected since the early 1980s. The 2006 western toad population at Darwin Falls was estimated at 381 adults (95-percent confidence interval [CI] of 314–482). The population of red-spotted toads at Piute Spring was estimated at 1,153 adults (95-percent CI of 935–1,503). However, an elevated rate of abnormalities (approximately 5 percent) was recorded in red-spotted toads as well as the presence of the chytrid fungus,Bactrochochytrium dendrobatidis, at Piute Spring. In Joshua Tree National Park, the California treefrog now occupies only three of the seven historically occupied drainages. Populations of California treefrogs at Fortynine Palms Oasis have declined more than 50 percent from 288 in 1969–71 to 109 in 2006. A similar decline was observed in the populations of red-spotted toads at Fortynine Palms Oasis from 300 adults in 1969–71 to 155 adults (95-percent CI of 90–139) in 2006. The red-spotted toads at Fortynine Palms Oasis also exhibited the presence of Bactrochochytrium dendrobatidis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155027","collaboration":"Prepared in cooperation with the U.S. National Park Service","usgsCitation":"Schroeder, R.A., Smith, G.A., Martin, P., Flint, A.L., Gallegos, E., and Fisher, R.N., 2015, The source, discharge, and chemical characteristics of selected springs, and the abundance and health of associated endemic anuran species in the Mojave network parks: U.S. Geological Survey Scientific Investigations Report 2015-5027, xviii, 128 p., https://doi.org/10.3133/sir20155027.","productDescription":"xviii, 128 p.","numberOfPages":"150","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-002272","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":300258,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5027/pdf/sir2015-5027.pdf","text":"Report","size":"54.8 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rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":546513,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70186235,"text":"70186235 - 2015 - Monitoring Greater Yellowstone Ecosystem wetlands: Can long-term monitoring help us understand their future?","interactions":[],"lastModifiedDate":"2017-04-03T12:04:34","indexId":"70186235","displayToPublicDate":"2015-05-11T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3802,"text":"Yellowstone Science","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring Greater Yellowstone Ecosystem wetlands: Can long-term monitoring help us understand their future?","docAbstract":"In the Greater Yellowstone Ecosystem (GYE), changes in the drying cycles of wetlands have been documented. Wetlands are areas where the water table is at or near the land surface and standing shallow water is present for much or all of the growing season. We discuss how monitoring data can be used to document variation in annual flooding and drying patterns of wetlands monitored across Yellowstone and Grand Teton national parks, investigate how these patterns are related to a changing climate, and explore how drying of wetlands may impact amphibians. The documented declines of some amphibian species are of growing concern to scientists and land managers alike, in part because disappearances have occurred in some of the most protected places. These disappearances are a recognized component of what is being described as Earth’s sixth mass extinction.
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