Although a species of conservation concern, little is known about the reproductive success of Least Terns (Sternula antillarum) throughout the southeastern USA where availability of natural beaches for nesting is limited. Daily survival rate (DSR) of nests and chicks was examined at four natural nesting sites in Cape Romain National Wildlife Refuge, South Carolina, 2009–2010. Measures of nest success (n = 257 nests) ranged from 0–93% among colony sites. The DSR of nests was primarily related to colony site, but year and estimates of predation risk also were related to DSR. Predation was the principal cause of identifiable nest loss, accounting for 47% of nest failures when the two years of data were pooled. The probability (± SE) of a chick surviving from hatching to fledging = 0.449 ± 0.01 (n = 92 chicks). DSR of chicks was negatively related to tide height and rainfall. Therefore, productivity of Least Terns is being lost during both the nesting and chick stage through a combination of biotic and abiotic factors that may prove difficult to fully mitigate or manage. Although natural nesting sites within Cape Romain National Wildlife Refuge intermittently produce successful nests, the consistency of productivity over the long term is still unknown. Given that the long term availability of anthropogenic nest sites (e.g., rooftops, dredge-spoil islands) for Least Terns is questionable, further research is required both locally and throughout the region to assess the extent to which natural sites act as population sources or sinks.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.036.0101","usgsCitation":"Brooks, G.L., Sanders, F.J., Gerard, P., and Jodice, P.G., 2013, Daily survival rate for nests and chicks of Least Terns (Sternula antillarum) at natural nest sites in South Carolina: Waterbirds, v. 36, no. 1, p. 1-10, https://doi.org/10.1675/063.036.0101.","productDescription":"10 p.","startPage":"1","endPage":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-035360","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":305899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Cape Romain National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.52796936035156,\n 33.00636021320537\n ],\n [\n -79.52796936035156,\n 33.09643121740349\n ],\n [\n -79.3267822265625,\n 33.09643121740349\n ],\n [\n -79.3267822265625,\n 33.00636021320537\n ],\n [\n -79.52796936035156,\n 33.00636021320537\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b0beaae4b09a3b01b53086","contributors":{"authors":[{"text":"Brooks, Gillian L.","contributorId":31033,"corporation":false,"usgs":true,"family":"Brooks","given":"Gillian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":565335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanders, Felicia J.","contributorId":56574,"corporation":false,"usgs":false,"family":"Sanders","given":"Felicia","email":"","middleInitial":"J.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":565336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerard, Patrick D.","contributorId":140181,"corporation":false,"usgs":false,"family":"Gerard","given":"Patrick D.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":565337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":1119,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564468,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156344,"text":"70156344 - 2013 - Tidally influenced alongshore circulation at an inlet-adjacent shoreline","interactions":[],"lastModifiedDate":"2015-08-20T13:09:15","indexId":"70156344","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Tidally influenced alongshore circulation at an inlet-adjacent shoreline","docAbstract":"The contribution of tidal forcing to alongshore circulation inside the surfzone is investigated at a 7 km long sandy beach adjacent to a large tidal inlet. Ocean Beach in San Francisco, CA (USA) is onshore of a ∼150 km2 ebb-tidal delta and directly south of the Golden Gate, the sole entrance to San Francisco Bay. Using a coupled flow-wave numerical model, we find that the tides modulate, and in some cases can reverse the direction of, surfzone alongshore flows through two separate mechanisms. First, tidal flow through the inlet results in a barotropic tidal pressure gradient that, when integrated across the surfzone, represents an important contribution to the surfzone alongshore force balance. Even during energetic wave conditions, the tidal pressure gradient can account for more than 30% of the total alongshore pressure gradient (wave and tidal components) and up to 55% during small waves. The wave driven component of the alongshore pressure gradient results from alongshore wave height and corresponding setup gradients induced by refraction over the ebb-tidal delta. Second, wave refraction patterns over the inner shelf are tidally modulated as a result of both tidal water depth changes and strong tidal flows (∼1 m/s), with the effect from currents being larger. These tidally induced changes in wave refraction result in corresponding variability of the alongshore radiation stress and pressure gradients within the surfzone. Our results indicate that tidal contributions to the surfzone force balance can be significant and important in determining the direction and magnitude of alongshore flow.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2013.01.017","usgsCitation":"Hansen, J., Elias, E.P., List, J.H., Erikson, L., and Barnard, P.L., 2013, Tidally influenced alongshore circulation at an inlet-adjacent shoreline: Continental Shelf Research, v. 56, p. 26-38, https://doi.org/10.1016/j.csr.2013.01.017.","productDescription":"13 p.","startPage":"26","endPage":"38","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032119","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438793,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DN4330","text":"USGS data release","linkHelpText":"San Francisco Bay Basic Tide Model"},{"id":307028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"San Francisco","otherGeospatial":"Ocean Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.51953124999999,\n 37.729724141962045\n ],\n [\n -122.51953124999999,\n 37.78781006166099\n ],\n [\n -122.5037384033203,\n 37.78781006166099\n ],\n [\n -122.5037384033203,\n 37.729724141962045\n ],\n [\n -122.51953124999999,\n 37.729724141962045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d6fa38e4b0518e3546bc5c","contributors":{"authors":[{"text":"Hansen, Jeff E.","contributorId":60339,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeff E.","affiliations":[],"preferred":false,"id":568791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elias, Edwin P.L.","contributorId":47295,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","email":"","middleInitial":"P.L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"List, Jeffrey H. jlist@usgs.gov","contributorId":140039,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. lerikson@usgs.gov","contributorId":145944,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":568794,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70044195,"text":"fs20133011 - 2013 - Concentrations of chloride and sodium in groundwater in New Hampshire from 1960 through 2011","interactions":[],"lastModifiedDate":"2016-08-10T15:32:19","indexId":"fs20133011","displayToPublicDate":"2013-02-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3011","title":"Concentrations of chloride and sodium in groundwater in New Hampshire from 1960 through 2011","docAbstract":"Several studies from the 1970s and more recently (for example, Hall (1975), Daley and others (2009) and Mullaney (2009)) have found that concentrations of chloride and sodium in groundwater in New Hampshire have increased during the past 50 years. Increases likely are related to road salt and other anthropogenic sources, such as septic systems, wastewater, and contamination from landfills and salt-storage areas. According to water-quality data reported to the New Hampshire Department of Environmental Services (NHDES), about 100 public water systems (5 percent) in 2010 had at least one groundwater sample with chloride concentrations that were equal to or exceeded the U.S. Environmental Protection Agency (USEPA) secondary maximum contaminant level (SMCL) of 250 mg/L before the water was treated for public consumption. The SMCL for chloride is a measurement of potential cosmetic or aesthetic effects of chloride in water. High concentrations of chloride and sodium in drinking-water sources can be costly to remove.
\nA new cooperative study between the U.S. Geological Survey (USGS) and the NHDES (Medalie, 2012) assessed chloride and sodium levels in groundwater in New Hampshire from the 1960s through 2011. The purpose of the study was to integrate all data on concentrations of chloride and sodium from groundwater in New Hampshire available from various Federal and State sources, including from the NHDES, the New Hamsphire Department of Health and Human Services, the USGS, and the U.S. Environmental Protection SurveyAgency (USEPA), for public and private (domestic) wells and to organize the data into a database. Medalie (2012) explained the many assumptions and limitations of disparate data that were collected to meet wide-ranging objectives. This fact sheet summarizes the most important findings of the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133011","collaboration":"Prepared in cooperation with the New Hampshire Department of Environmental Services","usgsCitation":"Medalie, L., 2013, Concentrations of chloride and sodium in groundwater in New Hampshire from 1960 through 2011: U.S. Geological Survey Fact Sheet 2013-3011, 2 p., https://doi.org/10.3133/fs20133011.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1960-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":268539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2013_3011.gif"},{"id":268537,"type":{"id":15,"text":"Index 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Hampshire\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51307c5fe4b04c194073ad93","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475083,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70043581,"text":"70043581 - 2013 - Prolactin regulates transcription of the ion uptake Na+/Cl- cotransporter (ncc) gene in zebrafish gill","interactions":[],"lastModifiedDate":"2013-03-11T21:21:18","indexId":"70043581","displayToPublicDate":"2013-02-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2782,"text":"Molecular and Cellular Endocrinology","active":true,"publicationSubtype":{"id":10}},"title":"Prolactin regulates transcription of the ion uptake Na+/Cl- cotransporter (ncc) gene in zebrafish gill","docAbstract":"Prolactin (PRL) is a well-known regulator of ion and water transport within osmoregulatory tissues across vertebrate species, yet how PRL acts on some of its target tissues remains poorly understood. Using zebrafish as a model, we show that ionocytes in the gill directly respond to systemic PRL to regulate mechanisms of ion uptake. Ion-poor conditions led to increases in the expression of PRL receptor (prlra), Na+/Cl− cotransporter (ncc; slc12a10.2), Na+/H+ exchanger (nhe3b; slc9a3.2), and epithelial Ca2+ channel (ecac; trpv6) transcripts within the gill. Intraperitoneal injection of ovine PRL (oPRL) increased ncc and prlra transcripts, but did not affect nhe3b or ecac. Consistent with direct PRL action in the gill, addition of oPRL to cultured gill filaments stimulated ncc in a concentration-dependent manner, an effect blocked by a pure human PRL receptor antagonist (Δ1-9-G129R-hPRL). These results suggest that PRL signaling through PRL receptors in the gill regulates the expression of ncc, thereby linking this pituitary hormone with an effector of Cl− uptake in zebrafish for the first time.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Molecular and Cellular Endocrinology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.mce.2013.01.021","usgsCitation":"Breves, J.P., Serizier, S.B., Goffin, V., McCormick, S., and Karlstrom, R.O., 2013, Prolactin regulates transcription of the ion uptake Na+/Cl- cotransporter (ncc) gene in zebrafish gill: Molecular and Cellular Endocrinology, In Press, Corrected Proof, https://doi.org/10.1016/j.mce.2013.01.021.","productDescription":"In Press, Corrected Proof","ipdsId":"IP-042950","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":473940,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3664226","text":"External Repository"},{"id":269099,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.mce.2013.01.021"},{"id":269100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"513efcf9e4b0dcc7339693bf","contributors":{"authors":[{"text":"Breves, Jason P.","contributorId":6349,"corporation":false,"usgs":false,"family":"Breves","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":473887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Serizier, Sandy B.","contributorId":26597,"corporation":false,"usgs":true,"family":"Serizier","given":"Sandy","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":473889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goffin, Vincent","contributorId":25056,"corporation":false,"usgs":true,"family":"Goffin","given":"Vincent","email":"","affiliations":[],"preferred":false,"id":473888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":39666,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen D.","email":"smccormick@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":473890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karlstrom, Rolf O.","contributorId":42502,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Rolf","email":"","middleInitial":"O.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":473891,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70044294,"text":"sir20135016 - 2013 - Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon","interactions":[],"lastModifiedDate":"2013-03-01T14:08:40","indexId":"sir20135016","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5016","title":"Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon","docAbstract":"A hydrodynamic, water temperature, and water-quality model of the Link River to Keno Dam reach of the upper Klamath River was updated to account for macrophytes and enhanced pH buffering from dissolved organic matter, ammonia, and orthophosphorus. Macrophytes had been observed in this reach by field personnel, so macrophyte field data were collected in summer and fall (June-October) 2011 to provide a dataset to guide the inclusion of macrophytes in the model. Three types of macrophytes were most common: pondweed (Potamogeton species), coontail (Ceratophyllum demersum), and common waterweed (Elodea canadensis). Pondweed was found throughout the Link River to Keno Dam reach in early summer with densities declining by mid-summer and fall. Coontail and common waterweed were more common in the lower reach near Keno Dam and were at highest density in summer. All species were most dense in shallow water (less than 2 meters deep) near shore. The highest estimated dry weight biomass for any sample during the study was 202 grams per square meter for coontail in August. Guided by field results, three macrophyte groups were incorporated into the CE-QUAL-W2 model for calendar years 2006-09. The CE-QUAL-W2 model code was adjusted to allow the user to initialize macrophyte populations spatially across the model grid. The default CE-QUAL-W2 model includes pH buffering by carbonates, but does not include pH buffering by organic matter, ammonia, or orthophosphorus. These three constituents, especially dissolved organic matter, are present in the upper Klamath River at concentrations that provide substantial pH buffering capacity. In this study, CE-QUAL-W2 was updated to include this enhanced buffering capacity in the simulation of pH. Acid dissociation constants for ammonium and phosphoric acid were taken from the literature. For dissolved organic matter, the number of organic acid groups and each group's acid dissociation constant (Ka) and site density (moles of sites per mole of carbon) were derived by fitting a theoretical buffering response to measured upper Klamath River alkalinity titration curves. The organic matter buffering in the Klamath River was modeled with two monoprotic organic acids: carboxylic acids with a mean pKa of 5.584 and site density of 0.1925, and phenolic organic acids with a mean pKa of 9.594 and site density of 0.6466. Total inorganic carbon concentrations in the model boundary inputs were recalculated based on the new buffering equations. CE-QUAL-W2 was also adjusted to allow the simulation of nonconservative alkalinity caused by nitrification, denitrification, photosynthesis, and respiration. The Klamath River model was recalibrated after the macrophyte and pH buffering updates producing improved predictions for pH, dissolved oxygen, and particulate carbon.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135016","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., Rounds, S.A., Asbill-Case, J.R., and Deas, M., 2013, Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon: U.S. Geological Survey Scientific Investigations Report 2013-5016, viii, 54 p., https://doi.org/10.3133/sir20135016.","productDescription":"viii, 54 p.","numberOfPages":"64","onlineOnly":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":268629,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5016/pdf/sir20135016.pdf"},{"id":268628,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5016/index.html"},{"id":268630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2013_5016.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 122,42.03 ], [ 122,42.33 ], [ 121.75,42.33 ], [ 121.75,42.03 ], [ 122,42.03 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5131dc02e4b0140546f53bf9","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":475250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asbill-Case, Jessica R.","contributorId":32058,"corporation":false,"usgs":true,"family":"Asbill-Case","given":"Jessica","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":475249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deas, Michael L.","contributorId":98830,"corporation":false,"usgs":true,"family":"Deas","given":"Michael L.","affiliations":[],"preferred":false,"id":475251,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044172,"text":"ofr20131043 - 2013 - Monitoring storm tide and flooding from Hurricane Sandy along the Atlantic coast of the United States, October 2012","interactions":[],"lastModifiedDate":"2017-02-03T12:20:59","indexId":"ofr20131043","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1043","title":"Monitoring storm tide and flooding from Hurricane Sandy along the Atlantic coast of the United States, October 2012","docAbstract":"The U.S. Geological Survey (USGS) deployed a temporary monitoring network of water-level and barometric pressure sensors at 224 locations along the Atlantic coast from Virginia to Maine to continuously record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Sandy. These records were greatly supplemented by an extensive post-flood high-water mark (HWM) flagging and surveying campaign from November to December 2012 involving more than 950 HWMs. Both efforts were undertaken as part of a coordinated federal emergency response as outlined by the Stafford Act under a directed mission assignment by the Federal Emergency Management Agency (FEMA).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131043","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"McCallum, B.E., Wicklein, S., Reiser, R.G., Busciolano, R., Morrison, J., Verdi, R.J., Painter, J.A., Frantz, E.R., and Gotvald, A.J., 2013, Monitoring storm tide and flooding from Hurricane Sandy along the Atlantic coast of the United States, October 2012: U.S. Geological Survey Open-File Report 2013-1043, 42 p.; Tables 2-6, https://doi.org/10.3133/ofr20131043.","productDescription":"42 p.; 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low-organic content methane seep sediments","docAbstract":"Sulfate-dependent anaerobic oxidation of methane (AOM) is the key sedimentary microbial process limiting methane emissions from marine sediments and methane seeps. In this study, we investigate how the presence of low-organic content sediment influences the capacity and efficiency of AOM at Bullseye vent, a gas hydrate-bearing cold seep offshore of Vancouver Island, Canada. The upper 8 m of sediment contains < 0.4 wt% total organic carbon (OC) and primarily consists of glacially-derived material that was deposited 14,900 to 15,900 yrs BP during the retreat of the late Quaternary Cordilleran Ice Sheet. We hypothesize this aged and exceptionally low-OC content sedimentary OM is biologically refractory, thereby limiting degradation of non-methane OM by sulfate reduction and maximizing methane consumption by sulfate-dependent AOM. A radiocarbon-based dissolved inorganic carbon (DIC) isotope mass balance model demonstrates that respired DIC in sediment pore fluids is derived from a fossil carbon source that is devoid of 14C. A fossil origin for the DIC precludes remineralization of non-fossil OM present within the sulfate zone as a significant contributor to pore water DIC, suggesting that nearly all sulfate is available for anaerobic oxidation of fossil seep methane. Methane flux from the SMT to the sediment water interface in a diffusion-dominated flux region of Bullseye vent was, on average, 96% less than at an OM-rich seep in the Gulf of Mexico with a similar methane flux regime. Evidence for enhanced methane oxidation capacity within OM-poor sediments has implications for assessing how climate-sensitive reservoirs of sedimentary methane (e.g., gas hydrate) will respond to ocean warming, particularly along glacially-influenced mid and high latitude continental margins.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.gca.2013.01.022","usgsCitation":"Pohlman, J., Riedel, M., Bauer, J., Canuel, E.A., Paull, C.K., Lapham, L., Grabowski, K.S., Coffin, R., and Spence, G.D., 2013, Anaerobic methane oxidation in low-organic content methane seep sediments: Geochimica et Cosmochimica Acta, v. 108, p. 184-201, https://doi.org/10.1016/j.gca.2013.01.022.","productDescription":"18 p.","startPage":"184","endPage":"201","ipdsId":"IP-042835","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473944,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5947","text":"External Repository"},{"id":268294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268292,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.gca.2013.01.022"}],"volume":"108","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515ea0e5e4b088aa22580949","contributors":{"authors":[{"text":"Pohlman, John W.","contributorId":95288,"corporation":false,"usgs":true,"family":"Pohlman","given":"John W.","affiliations":[],"preferred":false,"id":474669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":474664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bauer, James E.","contributorId":100262,"corporation":false,"usgs":true,"family":"Bauer","given":"James E.","affiliations":[],"preferred":false,"id":474671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Canuel, Elizabeth A.","contributorId":98604,"corporation":false,"usgs":true,"family":"Canuel","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474670,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":474667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lapham, Laura","contributorId":100263,"corporation":false,"usgs":true,"family":"Lapham","given":"Laura","affiliations":[],"preferred":false,"id":474672,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grabowski, Kenneth S.","contributorId":79374,"corporation":false,"usgs":true,"family":"Grabowski","given":"Kenneth","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":474668,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coffin, Richard B.","contributorId":36027,"corporation":false,"usgs":true,"family":"Coffin","given":"Richard B.","affiliations":[],"preferred":false,"id":474665,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spence, George D.","contributorId":54066,"corporation":false,"usgs":true,"family":"Spence","given":"George","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":474666,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70043595,"text":"70043595 - 2013 - A data-based conservation planning tool for Florida panthers","interactions":[],"lastModifiedDate":"2013-03-04T21:06:08","indexId":"70043595","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1550,"text":"Environmental Modeling & Assessment","onlineIssn":" 1573-296","printIssn":"1420-2026","active":true,"publicationSubtype":{"id":10}},"title":"A data-based conservation planning tool for Florida panthers","docAbstract":"Habitat loss and fragmentation are the greatest threats to the endangered Florida panther (Puma concolor coryi). We developed a data-based habitat model and user-friendly interface so that land managers can objectively evaluate Florida panther habitat. We used a geographic information system (GIS) and the Mahalanobis distance statistic (D2) to develop a model based on broad-scale landscape characteristics associated with panther home ranges. Variables in our model were Euclidean distance to natural land cover, road density, distance to major roads, human density, amount of natural land cover, amount of semi-natural land cover, amount of permanent or semi-permanent flooded area–open water, and a cost–distance variable. We then developed a Florida Panther Habitat Estimator tool, which automates and replicates the GIS processes used to apply the statistical habitat model. The estimator can be used by persons with moderate GIS skills to quantify effects of land-use changes on panther habitat at local and landscape scales. 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In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water-balance method was combined with a climate and land-cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971-2000 across the U.S. to obtain long-term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land-cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land-cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land-cover data can also improve those predictions. Using the climate and land-cover data at an 800-m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land-cover data are plentiful.
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\"}}]}","volume":"49","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-26","publicationStatus":"PW","scienceBaseUri":"53cd581fe4b0b290850f7e42","contributors":{"authors":[{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":474744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selnick, David L.","contributorId":13480,"corporation":false,"usgs":true,"family":"Selnick","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":474745,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70057429,"text":"ofr20131202B - 2013 - Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials","interactions":[],"lastModifiedDate":"2014-03-10T10:09:31","indexId":"ofr20131202B","displayToPublicDate":"2013-02-25T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1202","chapter":"B","title":"Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials","docAbstract":"This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan.
\nFlown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines.
\nThe reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131202B","collaboration":"Prepared in cooperation with the U.S. Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations","usgsCitation":"King, T., Hoefen, T.M., Kokaly, R., Livo, K.E., Johnson, M., and Giles, S.A., 2013, Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials: U.S. Geological Survey Open-File Report 2013-1202, 37 x 23 inches, https://doi.org/10.3133/ofr20131202B.","productDescription":"37 x 23 inches","onlineOnly":"Y","ipdsId":"IP-050472","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":282356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131202b.jpg"},{"id":283578,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1202/B/"},{"id":283579,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1202/B/pdf/ofr2013-1202b.pdf"}],"scale":"250000","projection":"Universal Transverse Mercator","datum":"WGS 1984","country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 62.0,35.0 ], [ 62.0,36.0 ], [ 64.0,36.0 ], [ 64.0,35.0 ], [ 62.0,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd61dae4b0b290850fdc9e","contributors":{"authors":[{"text":"King, Trude","contributorId":29831,"corporation":false,"usgs":true,"family":"King","given":"Trude","email":"","affiliations":[],"preferred":false,"id":486684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"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":486680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":81442,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","affiliations":[],"preferred":false,"id":486685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livo, Keith E. 0000-0001-7331-8130 elivo@usgs.gov","orcid":"https://orcid.org/0000-0001-7331-8130","contributorId":1750,"corporation":false,"usgs":true,"family":"Livo","given":"Keith","email":"elivo@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":486683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giles, Stuart A. 0000-0002-8696-5078 sgiles@usgs.gov","orcid":"https://orcid.org/0000-0002-8696-5078","contributorId":1233,"corporation":false,"usgs":true,"family":"Giles","given":"Stuart","email":"sgiles@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":486682,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70146651,"text":"70146651 - 2013 - Fens as whole-ecosystem gauges of groundwater recharge under climate change","interactions":[],"lastModifiedDate":"2015-04-20T09:17:35","indexId":"70146651","displayToPublicDate":"2013-02-25T10:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Fens as whole-ecosystem gauges of groundwater recharge under climate change","docAbstract":"Currently, little is known about the impact of climate change on groundwater recharge in the Sierra Nevada and southern Cascade Range of California or other mountainous regions of the world. The purpose of this study was to determine whether small alpine peat lands called fens can be used as whole-ecosystem gauges of groundwater recharge through time. Fens are sustained by groundwater discharge and are highly sensitive to changes in groundwater flow due to hydrologic disturbance including climate change. Seven fens in the Sierra Nevada and southern Cascade Range were studied over a 50-80 year period using historic aerial photography. In each aerial photograph, fen areas were identified as open lawn and partially treed areas that exhibited (1) dark brownish-green coloring or various shades of gray and black in black and white imagery and (2) mottling of colors and clustering of vegetation, which signified a distinct moss canopy with overlying clumped sedge vegetation. In addition to the aerial photography study, a climate analysis for the study sites was carried out using both measured data (U.S. Department of Agriculture Natural Resources Conservation Service SNOwpack TELemetry system) and modeled data (a downscaled version of the Parameter-elevation Regressions on Independent Slopes Model) for the period from 1951 to 2010. Over the study period, the five fens in the Sierra Nevada were found to be decreasing between 10% and 16% in delineated area. The climate analysis revealed significant increases through time in annual mean minimum temperature (Tmin) between 1951-1980 and 1981-2010. In addition, April 1 snow water equivalent and snowpack longevity also decreased between 1951-1980 and 1981-2010. For the fens in the Cascade Range, there were no discernible changes in delineated area. At these sites, increases in Tmin occurred only within the past 20-25 years and decreases in snowpack longevity were more subtle. A conceptual model is presented, which illustrates that basic differences in hydrogeology of the Sierra Nevada vs. the Cascade Range may control the threshold at which changes in delineated fen areas are discernible. Overall, the results from this study show that fens in the Sierra Nevada have strong potential as whole ecosystem gauges for determining long-term changes in groundwater recharge under climate change. Due to either more moderate climate change and/or hydrogeological differences, fens in the southern Cascade Range currently do not appear to have the same utility. A greater sample size of fens in the Sierra Nevada is needed to confirm the general applicability of this method. In addition, future work needs to focus on integrating fen monitoring with geochemical and/or isotopic process-level studies in order to quantify changes in groundwater recharge identified using this new approach.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"New York, NY","doi":"10.1016/j.jhydrol.2012.11.056","usgsCitation":"Drexler, J., Knifong, D.L., Tuil, J., Flint, L.E., and Flint, A.L., 2013, Fens as whole-ecosystem gauges of groundwater recharge under climate change: Journal of Hydrology, v. 481, p. 22-34, https://doi.org/10.1016/j.jhydrol.2012.11.056.","productDescription":"13 p.","startPage":"22","endPage":"34","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040704","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":299768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"481","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5536233ae4b0b22a15807a94","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":1659,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","email":"jdrexler@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knifong, Donna L. dknifong@usgs.gov","contributorId":1517,"corporation":false,"usgs":true,"family":"Knifong","given":"Donna","email":"dknifong@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":545227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tuil, JayLee","contributorId":140341,"corporation":false,"usgs":false,"family":"Tuil","given":"JayLee","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":545230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":545226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70044020,"text":"ofr20131034 - 2013 - Water quality in the Anacostia River, Maryland and Rock Creek, Washington, D.C.: Continuous and discrete monitoring with simulations to estimate concentrations and yields of nutrients, suspended sediment, and bacteria","interactions":[],"lastModifiedDate":"2023-03-09T20:14:16.958533","indexId":"ofr20131034","displayToPublicDate":"2013-02-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1034","title":"Water quality in the Anacostia River, Maryland and Rock Creek, Washington, D.C.: Continuous and discrete monitoring with simulations to estimate concentrations and yields of nutrients, suspended sediment, and bacteria","docAbstract":"Concentrations and loading estimates for nutrients, suspended sediment, and E. coli bacteria were summarized for three water-quality monitoring stations on the Anacostia River in Maryland and one station on Rock Creek in Washington, D.C. Both streams are tributaries to the Potomac River in the Washington, D.C. metropolitan area and contribute to the Chesapeake Bay estuary. Two stations on the Anacostia River, Northeast Branch at Riverdale, Maryland and Northwest Branch near Hyattsville, Maryland, have been monitored for water quality during the study period from 2003 to 2011 and are located near the shift from nontidal to tidal conditions near Bladensburg, Maryland. A station on Paint Branch is nested above the station on the Northeast Branch Anacostia River, and has slightly less developed land cover than the Northeast and Northwest Branch stations. The Rock Creek station is located in Rock Creek Park, but the land cover in the watershed surrounding the park is urbanized. Stepwise log-linear regression models were developed to estimate the concentrations of suspended sediment, total nitrogen, total phosphorus, and E. coli bacteria from continuous field monitors. Turbidity was the strongest predictor variable for all water-quality parameters. For bacteria, water temperature improved the models enough to be included as a second predictor variable due to the strong dependence of stream metabolism on temperature. Coefficients of determination (R2) for the models were highest for log concentrations of suspended sediment (0.9) and total phosphorus (0.8 to 0.9), followed by E. coli bacteria (0.75 to 0.8), and total nitrogen (0.6). Water-quality data provided baselines for conditions prior to accelerated implementation of multiple stormwater controls in the watersheds. Counties are currently in the process of enhancing stormwater controls in both watersheds. Annual yields were estimated for suspended sediment, total nitrogen, total phosphorus, and E. coli bacteria using the U.S. Geological Survey model LOADEST with hourly time steps of turbidity, flow, and time. Yields of all four parameters were within ranges found in other urbanized watersheds in Chesapeake Bay. Annual yields for all four watersheds over the period of study were estimated for suspended sediment (65,500 – 166,000 kilograms per year per square kilometer; kg/yr/km2), total nitrogen (465 - 911 kg/yr/km2), total phosphorus (36 - 113 kg/yr/km2), and E. coli bacteria (6.0 – 38 x 1012 colony forming units/yr/km2). The length of record was not sufficient to determine trends for any of the water-quality parameters; within confidence intervals of the models, results were similar to loads determined by previous studies for the Northeast and Northwest Branch stations of the Anacostia River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131034","collaboration":"Prepared in cooperation with Montgomery County, Maryland","usgsCitation":"Miller, C.V., Chanat, J.G., and Bell, J.M., 2013, Water quality in the Anacostia River, Maryland and Rock Creek, Washington, D.C.: Continuous and discrete monitoring with simulations to estimate concentrations and yields of nutrients, suspended sediment, and bacteria: U.S. Geological Survey Open-File Report 2013-1034, vi, 37 p., https://doi.org/10.3133/ofr20131034.","productDescription":"vi, 37 p.","startPage":"i","endPage":"37","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":268259,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1034.gif"},{"id":268257,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1034/"},{"id":268258,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1034/pdf/ofr2013-1034.pdf"}],"country":"United States","state":"Maryl","city":"Washington;D.C.","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.49,37.89 ], [ -79.49,39.72 ], [ -75.05,39.72 ], [ -75.05,37.89 ], [ -79.49,37.89 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512c87eae4b0855fde669734","contributors":{"authors":[{"text":"Miller, Cherie V. 0000-0001-7765-5919 cvmiller@usgs.gov","orcid":"https://orcid.org/0000-0001-7765-5919","contributorId":863,"corporation":false,"usgs":true,"family":"Miller","given":"Cherie","email":"cvmiller@usgs.gov","middleInitial":"V.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":474638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chanat, Jeffrey G. 0000-0002-3629-7307 jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Joseph M. 0000-0002-2536-2070 jmbell@usgs.gov","orcid":"https://orcid.org/0000-0002-2536-2070","contributorId":5063,"corporation":false,"usgs":true,"family":"Bell","given":"Joseph","email":"jmbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474640,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044000,"text":"70044000 - 2013 - Nitrate in watersheds: straight from soils to streams?","interactions":[],"lastModifiedDate":"2013-04-20T19:35:59","indexId":"70044000","displayToPublicDate":"2013-02-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Nitrate in watersheds: straight from soils to streams?","docAbstract":"Human activities are rapidly increasing the global supply of reactive N and substantially altering the structure and hydrologic connectivity of managed ecosystems. There is long-standing recognition that N must be removed along hydrologic flowpaths from uplands to streams, yet it has proven difficult to assess the generality of this removal across ecosystem types, and whether these patterns are influenced by land-use change. To assess how well upland nitrate (NO3-) loss is reflected in stream export, we gathered information from >50 watershed biogeochemical studies that reported nitrate concentrations ([NO3-]) for stream water and for either upslope soil solution or groundwater NO3- to examine whether stream export of NO3- accurately reflects upland NO3- losses. In this dataset, soil solution and streamwater [NO3-] were correlated across 40 undisturbed forest watersheds, with streamwater [NO3-] typically half (median = 50%) soil solution [NO3-]. A similar relationship was seen in 10 disturbed forest watersheds. However, for 12 watersheds with significant agricultural or urban development, the intercept and slope were both significantly higher than the relationship seen in forest watersheds. Differences in concentration between soil solution or groundwater and stream water may be attributed to biological uptake, microbial processes including denitrification, and/or preferential flow routing. The results of this synthesis are consistent with the hypotheses that undisturbed watersheds have a significant capacity to remove nitrate after it passes below the rooting zone and that land use changes tend to alter the efficiency or the length of watershed flowpaths, leading to reductions in nitrate removal and increased stream nitrate concentrations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research G: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","publisherLocation":"Washington, D.C.","doi":"10.1002/jgrg.20030","usgsCitation":"Sudduth, E.B., Perakis, S., and Bernhardt, E., 2013, Nitrate in watersheds: straight from soils to streams?: Journal of Geophysical Research G: Biogeosciences, v. 118, no. G1, p. 291-302, https://doi.org/10.1002/jgrg.20030.","productDescription":"45 p.","startPage":"291","endPage":"302","ipdsId":"IP-018046","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268256,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrg.20030"}],"volume":"118","issue":"G1","noUsgsAuthors":false,"publicationDate":"2013-03-21","publicationStatus":"PW","scienceBaseUri":"512c87e9e4b0855fde669730","contributors":{"authors":[{"text":"Sudduth, Elizabeth B.","contributorId":8747,"corporation":false,"usgs":true,"family":"Sudduth","given":"Elizabeth","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":474588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perakis, Steven S. 0000-0003-0703-9314","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":16797,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven S.","affiliations":[],"preferred":false,"id":474589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":474590,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70043953,"text":"70043953 - 2013 - An ecohydraulic model to identify and monitor moapa dace habitat","interactions":[],"lastModifiedDate":"2013-02-25T10:27:58","indexId":"70043953","displayToPublicDate":"2013-02-25T00:00:00","publicationYear":"2013","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":"An ecohydraulic model to identify and monitor moapa dace habitat","docAbstract":"Moapa dace (Moapa coriacea) is a critically endangered thermophilic minnow native to the Muddy River ecosystem in southeastern Nevada, USA. Restricted to temperatures between 26.0 and 32.0°C, these fish are constrained to the upper two km of the Muddy River and several small tributaries fed by warm springs. Habitat alterations, nonnative species invasion, and water withdrawals during the 20th century resulted in a drastic decline in the dace population and in 1979 the Moapa Valley National Wildlife Refuge (Refuge) was created to protect them. The goal of our study was to determine the potential effects of reduced surface flows that might result from groundwater pumping or water diversions on Moapa dace habitat inside the Refuge. We accomplished our goal in several steps. First, we conducted snorkel surveys to determine the locations of Moapa dace on three warm-spring tributaries of the Muddy River. Second, we conducted hydraulic simulations over a range of flows with a two-dimensional hydrodynamic model. Third, we developed a set of Moapa dace habitat models with logistic regression and a geographic information system. Fourth, we estimated Moapa dace habitat over a range of flows (plus or minus 30% of base flow). Our spatially explicit habitat models achieved classification accuracies between 85% and 91%, depending on the snorkel survey and creek. Water depth was the most significant covariate in our models, followed by substrate, Froude number, velocity, and water temperature. Hydraulic simulations showed 2-11% gains in dace habitat when flows were increased by 30%, and 8-32% losses when flows were reduced by 30%. To ensure the health and survival of Moapa dace and the Muddy River ecosystem, groundwater and surface-water withdrawals and diversions need to be carefully monitored, while fully implementing a proactive conservation strategy.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0055551","usgsCitation":"Hatten, J.R., Batt, T.R., Scoppettone, G.G., and Dixon, C.J., 2013, An ecohydraulic model to identify and monitor moapa dace habitat: PLoS ONE, v. 8, no. 2, 12 p., https://doi.org/10.1371/journal.pone.0055551.","productDescription":"12 p.","numberOfPages":"12","ipdsId":"IP-040200","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":473945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0055551","text":"Publisher Index Page"},{"id":268203,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0055551"},{"id":268204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.720236063,36.7088462532 ], [ -114.720236063,36.7149528124 ], [ -114.7083055973,36.7149528124 ], [ -114.7083055973,36.7088462532 ], [ -114.720236063,36.7088462532 ] ] ] } } ] }","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-07","publicationStatus":"PW","scienceBaseUri":"512c87e7e4b0855fde66972c","contributors":{"authors":[{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batt, Thomas R. tbatt@usgs.gov","contributorId":3432,"corporation":false,"usgs":true,"family":"Batt","given":"Thomas","email":"tbatt@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scoppettone, Gayton G. gary_scoppettone@usgs.gov","contributorId":2848,"corporation":false,"usgs":true,"family":"Scoppettone","given":"Gayton","email":"gary_scoppettone@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dixon, Christopher J.","contributorId":42110,"corporation":false,"usgs":true,"family":"Dixon","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":474540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70043954,"text":"70043954 - 2013 - Potential effects of changes in temperature and food resources on life history trajectories of juvenile Oncorhynchus mykiss","interactions":[],"lastModifiedDate":"2016-05-04T14:33:36","indexId":"70043954","displayToPublicDate":"2013-02-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Potential effects of changes in temperature and food resources on life history trajectories of juvenile Oncorhynchus mykiss","docAbstract":"Increasing temperatures and changes in food resources owing to climate change may alter the growth and migratory behavior of organisms. This is particularly important for salmonid species like Oncorhynchus mykiss, where some individuals remain in freshwater to mature (nonanadromous Rainbow Trout) and others migrate to sea (anadromous Steelhead). Whether one strategy is adopted over the other may depend on the individual's growth and size. In this study, we explored (1) how water temperature in Beaver Creek, a tributary to the Methow River, Washington, may increase under four climate scenarios, (2) how these thermal changes may alter the life history trajectory followed by O. mykiss (i.e., when and if to smolt), and (3) how changes in food quality or quantity might interact with increasing temperatures. We combined bioenergetic and state-dependent life history models parameterized for O. mykiss in Beaver Creek to mimic baseline life history trajectories. Based on our simulations, when mean water temperature was increased by 0.6°C there was a reduction in life history diversity and a 57% increase in the number of individuals becoming smolts. When mean temperature was increased by 2.7°C, it resulted in 87% fewer smolts than in the baseline and fewer life history trajectories expressed. A reduction in food resources led to slower growth, more life history trajectories, and a greater proportion of smolts. In contrast, when food resources were increased, fish grew faster, which reduced the proportion of smolts and life history diversity. Our modeling suggests that warmer water temperatures associated with climate change could decrease the life history diversity of O. mykiss in the central portion of their range and thereby reduce resiliency to other disturbances. In addition, changes in food resources could mediate or exacerbate the effect of water temperature on the life history trajectories of O. mykiss.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2012.728162","usgsCitation":"Benjamin, J.R., Connolly, P., Romine, J.G., and Perry, R.W., 2013, Potential effects of changes in temperature and food resources on life history trajectories of juvenile Oncorhynchus mykiss: Transactions of the American Fisheries Society, v. 142, no. 1, p. 208-220, https://doi.org/10.1080/00028487.2012.728162.","productDescription":"13 p.","startPage":"208","endPage":"220","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-034810","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":268206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"142","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-21","publicationStatus":"PW","scienceBaseUri":"512c961be4b0855fde6697f6","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":474544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, Patrick J. 0000-0001-7365-7618 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0001-7365-7618","contributorId":2920,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick J.","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474542,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474541,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70043711,"text":"70043711 - 2013 - Comparison of filters for concentrating microbial indicators and pathogens in lake-water samples","interactions":[],"lastModifiedDate":"2017-02-17T15:10:19","indexId":"70043711","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of filters for concentrating microbial indicators and pathogens in lake-water samples","docAbstract":"Bacterial indicators are used to indicate increased health risk from pathogens and to make beach closure and advisory decisions; however, beaches are seldom monitored for the pathogens themselves. Studies of sources and types of pathogens at beaches are needed to improve estimates of swimming-associated health risks. It would be advantageous and cost-effective, especially for studies conducted on a regional scale, to use a method that can simultaneously filter and concentrate all classes of pathogens from the large volumes of water needed to detect pathogens. In seven recovery experiments, stock cultures of viruses and protozoa were seeded into 10-liter lake water samples, and concentrations of naturally occurring bacterial indicators were used to determine recoveries. For the five filtration methods tested, the highest median recoveries were as follows: glass wool for adenovirus (4.7%); NanoCeram for enterovirus (14.5%) and MS2 coliphage (84%); continuous-flow centrifugation (CFC) plus Virocap (CFC+ViroCap) for Escherichia coli (68.3%) and Cryptosporidium (54%); automatic ultrafiltration (UF) for norovirus GII (2.4%); and dead-end UF for Enterococcus faecalis (80.5%), avian influenza virus (0.02%), and Giardia (57%). In evaluating filter performance in terms of both recovery and variability, the automatic UF resulted in the highest recovery while maintaining low variability for all nine microorganisms. The automatic UF was used to demonstrate that filtration can be scaled up to field deployment and the collection of 200-liter lake water samples.
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G.","contributorId":29774,"corporation":false,"usgs":true,"family":"Brady","given":"Amie M. G.","affiliations":[],"preferred":false,"id":474146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huitger, Carrie","contributorId":86242,"corporation":false,"usgs":true,"family":"Huitger","given":"Carrie","affiliations":[],"preferred":false,"id":474150,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bushon, Rebecca N. rnbushon@usgs.gov","contributorId":2304,"corporation":false,"usgs":true,"family":"Bushon","given":"Rebecca","email":"rnbushon@usgs.gov","middleInitial":"N.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474144,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":474141,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ware, Michael W.","contributorId":65357,"corporation":false,"usgs":true,"family":"Ware","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":474149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Villegas, Eric N.","contributorId":56947,"corporation":false,"usgs":true,"family":"Villegas","given":"Eric","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":474148,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gallardo, Vincent","contributorId":7585,"corporation":false,"usgs":true,"family":"Gallardo","given":"Vincent","email":"","affiliations":[],"preferred":false,"id":474145,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lindquist, H.D. Alan","contributorId":48666,"corporation":false,"usgs":true,"family":"Lindquist","given":"H.D.","email":"","middleInitial":"Alan","affiliations":[],"preferred":false,"id":474147,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70043710,"text":"70043710 - 2013 - Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection","interactions":[],"lastModifiedDate":"2018-09-13T10:20:27","indexId":"70043710","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection","title":"Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection","docAbstract":"Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for Escherichia coli and to understand the links between E. coli concentrations, predictive variables, and pathogens. Based upon results from 21 beach sites, models were developed for 13 sites, and the most predictive variables were rainfall, wind direction and speed, turbidity, and water temperature. Models were not developed at sites where the E. coli standard was seldom exceeded. Models were validated at nine sites during an independent year. At three sites, the model resulted in increased correct responses, sensitivities, and specificities compared to use of the previous day's E. coli concentration (the current method). Drought conditions during the validation year precluded being able to adequately assess model performance at most of the other sites. Cryptosporidium, adenovirus, eaeA (E. coli), ipaH (Shigella), and spvC (Salmonella) were found in at least 20% of samples collected for pathogens at five sites. The presence or absence of the three bacterial genes was related to some of the model variables but was not consistently related to E. coli concentrations. Predictive models were not effective at all inland lake sites; however, their use at two lakes with high swimmer densities will provide better estimates of public health risk than current methods and will be a valuable resource for beach managers and the public.","language":"English","publisher":"American Society for Microbiology","publisherLocation":"Washington, D.C.","doi":"10.1128/AEM.02995-12","usgsCitation":"Francy, D.S., Stelzer, E.A., Duris, J.W., Brady, A., Harrison, J.H., Johnson, H., and Ware, M.W., 2013, Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection: Applied and Environmental Microbiology, v. 79, no. 5, p. 1676-1688, https://doi.org/10.1128/AEM.02995-12.","productDescription":"13 p.","startPage":"1676","endPage":"1688","ipdsId":"IP-032379","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":473950,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/aem.02995-12","text":"External Repository"},{"id":267893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267892,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1128/AEM.02995-12"}],"country":"United States","state":"Ohio","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.8203,38.4034 ], [ -84.8203,41.9773 ], [ -80.5182,41.9773 ], [ -80.5182,38.4034 ], [ -84.8203,38.4034 ] ] ] } } ] }","volume":"79","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51274202e4b07fa41a6044de","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":1981,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":474136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brady, Amie M. G.","contributorId":29774,"corporation":false,"usgs":true,"family":"Brady","given":"Amie M. G.","affiliations":[],"preferred":false,"id":474138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrison, John H.","contributorId":34011,"corporation":false,"usgs":true,"family":"Harrison","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":474139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Heather E.","contributorId":207837,"corporation":false,"usgs":false,"family":"Johnson","given":"Heather E.","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":744844,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ware, Michael W.","contributorId":65357,"corporation":false,"usgs":true,"family":"Ware","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":474140,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70043832,"text":"ofr20131032 - 2013 - Development of flood profiles and flood-inundation maps for the Village of Killbuck, Ohio","interactions":[],"lastModifiedDate":"2013-02-20T16:25:51","indexId":"ofr20131032","displayToPublicDate":"2013-02-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1032","title":"Development of flood profiles and flood-inundation maps for the Village of Killbuck, Ohio","docAbstract":"Digital flood-inundation maps for a reach of Killbuck Creek near the Village of Killbuck, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with Holmes County, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the USGS streamgage Killbuck Creek near Killbuck (03139000) and were completed as part of an update to Federal Emergency Management Agency Flood-Insurance Study. The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. The digital maps also have been submitted for inclusion in the data libraries of the USGS interactive Flood Inundation Mapper. Data from the streamgage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating a steady-state step-backwater model to an established streamgage rating curve. The step-backwater model then was used to determine water-surface-elevation profiles for 10 flood stages at the streamgage with corresponding streamflows ranging from approximately the 50- to 0.2-percent annual exceedance probabilities. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131032","collaboration":"Prepared in cooperation with Holmes County, Ohio","usgsCitation":"Ostheimer, C.J., 2013, Development of flood profiles and flood-inundation maps for the Village of Killbuck, Ohio: U.S. Geological Survey Open-File Report 2013-1032, iv, 8 p.; Downloads Directory, https://doi.org/10.3133/ofr20131032.","productDescription":"iv, 8 p.; Downloads Directory","startPage":"i","endPage":"8","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":267855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1032.gif"},{"id":267854,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1032/GIS_data_downloads"},{"id":267852,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1032/"},{"id":267853,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1032/pdf/OFR2013-1032.pdf"}],"country":"United States","state":"Ohio","city":"Killbuck","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.987175,40.487845 ], [ -81.987175,40.506004 ], [ -81.975585,40.506004 ], [ -81.975585,40.487845 ], [ -81.987175,40.487845 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5125f084e4b09d00759cd050","contributors":{"authors":[{"text":"Ostheimer, Chad J. ostheime@usgs.gov","contributorId":2160,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad","email":"ostheime@usgs.gov","middleInitial":"J.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":474286,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70043831,"text":"sir20125275 - 2013 - Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona","interactions":[],"lastModifiedDate":"2013-02-20T16:12:11","indexId":"sir20125275","displayToPublicDate":"2013-02-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5275","title":"Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona","docAbstract":"We have investigated the hydrogeology of the Hualapai Valley, Detrital Valley, and Sacramento Valley basins of Mohave County in northwestern Arizona to develop a better understanding of groundwater storage within the basin fill aquifers. In our investigation we used geologic maps, well-log data, and geophysical surveys to delineate the sedimentary textures and lithology of the basin fill. We used gravity data to construct a basin geometry model that defines smaller subbasins within the larger basins, and airborne transient-electromagnetic modeled results along with well-log lithology data to infer the subsurface distribution of basin fill within the subbasins. Hydrogeologic units (HGUs) are delineated within the subbasins on the basis of the inferred lithology of saturated basin fill. We used the extent and size of HGUs to estimate groundwater storage to depths of 400 meters (m) below land surface (bls). The basin geometry model for the Hualapai Valley basin consists of three subbasins: the Kingman, Hualapai, and southern Gregg subbasins. In the Kingman subbasin, which is estimated to be 1,200 m deep, saturated basin fill consists of a mixture of fine- to coarse-grained sedimentary deposits. The Hualapai subbasin, which is the largest of the subbasins, contains a thick halite body from about 400 m to about 4,300 m bls. Saturated basin fill overlying the salt body consists predominately of fine-grained older playa deposits. In the southern Gregg subbasin, which is estimated to be 1,400 m deep, saturated basin fill is interpreted to consist primarily of fine- to coarse-grained sedimentary deposits. Groundwater storage to 400 m bls in the Hualapai Valley basin is estimated to be 14.1 cubic kilometers (km3). The basin geometry model for the Detrital Valley basin consists of three subbasins: northern Detrital, central Detrital, and southern Detrital subbasins. The northern and central Detrital subbasins are characterized by a predominance of playa evaporite and fine-grained clastic deposits; evaporite deposits in the northern Detrital subbasin include halite. The northern Detrital subbasin is estimated to be 600 m deep and the middle Detrital subbasin is estimated to be 700 m deep. The southern Detrital subbasin, which is estimated to be 1,500 m deep, is characterized by a mixture of fine- to coarse-grained basin fill deposits. Groundwater storage to 400 m bls in the Detrital Valley basin is estimated to be 9.8 km3. The basin geometry model for the Sacramento Valley basin consists of three subbasins: the Chloride, Golden Valley, and Dutch Flat subbasins. The Chloride subbasin, which is estimated to be 900 m deep, is characterized by fine- to coarse-grained basin fill deposits. In the Golden Valley subbasin, which is elongated north-south, and is estimated to be 1,300 m deep, basin fill includes fine-grained sedimentary deposits overlain by coarse-grained sedimentary deposits in much of the subbasin. The Dutch Flat subbasin is estimated to be 2,600 m deep, and well-log lithologic data suggest that the basin fill consists of interlayers of gravel, sand, and clay. Groundwater storage to 400 m bls in the Sacramento Valley basin is estimated to be 35.1 km3.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125275","collaboration":"Prepared in cooperation with the Arizona Department of Water Resources and Mohave County, Arizona","usgsCitation":"Truini, M., Beard, L.S., Kennedy, J., and Anning, D., 2013, Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona: U.S. Geological Survey Scientific Investigations Report 2012-5275, vi, 47 p., https://doi.org/10.3133/sir20125275.","productDescription":"vi, 47 p.","startPage":"i","endPage":"47","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":267851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5275.gif"},{"id":267850,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5275/"},{"id":267849,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5275/sir2012-5275.pdf"}],"country":"United States","state":"Arizona","county":"Mohave County","otherGeospatial":"Hualapai Valley;Detrital Valley;Sacramento Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.82,31.33 ], [ -114.82,37.0 ], [ -109.0,37.0 ], [ -109.0,31.33 ], [ -114.82,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5125f086e4b09d00759cd054","contributors":{"authors":[{"text":"Truini, Margot mtruini@usgs.gov","contributorId":599,"corporation":false,"usgs":true,"family":"Truini","given":"Margot","email":"mtruini@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beard, L. Sue","contributorId":87607,"corporation":false,"usgs":true,"family":"Beard","given":"L.","email":"","middleInitial":"Sue","affiliations":[],"preferred":false,"id":474284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Jeffrey 0000-0002-3365-6589","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":101124,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","affiliations":[],"preferred":false,"id":474285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anning, Dave W.","contributorId":36025,"corporation":false,"usgs":true,"family":"Anning","given":"Dave W.","affiliations":[],"preferred":false,"id":474283,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70043737,"text":"sir20125258 - 2013 - Effects of recent climate variability on groundwater levels in eastern Arkansas","interactions":[],"lastModifiedDate":"2013-02-19T13:28:51","indexId":"sir20125258","displayToPublicDate":"2013-02-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5258","title":"Effects of recent climate variability on groundwater levels in eastern Arkansas","docAbstract":"Water-level fluctuations in wells completed in the Mississippi River Valley alluvial aquifer in eastern Arkansas were compared to variability in annual precipitation, an indicator of climate variability. The wettest year on record in Little Rock, Arkansas, occurred in 2009 with 81.79 inches of precipitation compared to an average of 47.1 inches per year. In contrast, 2005 and 2010 were the 7th and 14th driest years on record with 34.55 and 36.52 inches per year, respectively. This variability in precipitation was reflected in water-level altitude changes between 2004 and 2008 and 2006 and 2010. Generally, drier conditions between 2004 and 2008 led to an average decline in water levels of 1.62 feet, whereas wetter conditions between 2006 and 2010 led to an average rise in water levels of 1.36 feet. Drier periods likely resulted in less recharge compared to wetter periods. Groundwater use from the alluvial aquifer peaked in 2000 and has since declined, in part, because of conservation measures and substantial reduction in aquifer saturated thickness. Groundwater-flow model results showed some areas of the alluvial aquifer simulated as dry in 2010, indicating a reduced capacity of the alluvial aquifer to produce water in those areas. Additional factors affecting groundwater use include the types of crops grown in an area and the availabitiliy of crop subsidies. Real-time continuous water-level measurements in wells allow for a more accurate assessment of the effect of variability in precipitation and water use than periodic water-level measurements.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125258","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission","usgsCitation":"Czarnecki, J.B., and Schrader, T., 2013, Effects of recent climate variability on groundwater levels in eastern Arkansas: U.S. Geological Survey Scientific Investigations Report 2012-5258, iv, 17 p., https://doi.org/10.3133/sir20125258.","productDescription":"iv, 17 p.","startPage":"i","endPage":"17","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":267725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5258.gif"},{"id":267724,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5258/sir2012-5258.pdf"},{"id":267723,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5258/"}],"country":"United States","state":"Arkansas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.62,33.0 ], [ -94.62,36.5 ], [ -89.64,36.5 ], [ -89.64,33.0 ], [ -94.62,33.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51249f02e4b0b6328103b30f","contributors":{"authors":[{"text":"Czarnecki, John B. jczarnec@usgs.gov","contributorId":2555,"corporation":false,"usgs":true,"family":"Czarnecki","given":"John","email":"jczarnec@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":474187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schrader, T. P.","contributorId":56300,"corporation":false,"usgs":true,"family":"Schrader","given":"T.","middleInitial":"P.","affiliations":[],"preferred":false,"id":474188,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043741,"text":"fs20133005 - 2013 - Groundwater resources of the Wood River Valley, Idaho--A groundwater-flow model for resource management","interactions":[],"lastModifiedDate":"2026-06-04T16:33:54.814482","indexId":"fs20133005","displayToPublicDate":"2013-02-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3005","title":"Groundwater resources of the Wood River Valley, Idaho--A groundwater-flow model for resource management","docAbstract":"The U.S. Geological Survey (USGS), in collaboration with the Idaho Department of Water Resources (IDWR), will use the current understanding of the Wood River Valley aquifer system to construct a MODFLOW numerical groundwater-flow model to simulate potential anthropogenic and climatic effects on groundwater and surface-water resources. This model will serve as a tool for water rights administration and water-resource management and planning. The study will be conducted over a 3-year period from late 2012 until model and report completion in 2015.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133005","collaboration":"Prepared in cooperation with Idaho Department of Water Resources","usgsCitation":"Bartolino, J., and Vincent, S., 2013, Groundwater resources of the Wood River Valley, Idaho--A groundwater-flow model for resource management: U.S. Geological Survey Fact Sheet 2013-3005, 4 p., https://doi.org/10.3133/fs20133005.","productDescription":"4 p.","startPage":"1","endPage":"4","numberOfPages":"4","additionalOnlineFiles":"N","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":505012,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98168.htm","linkFileType":{"id":5,"text":"html"}},{"id":267727,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3005/"},{"id":267729,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2013_3005.png"},{"id":267728,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3005/pdf/fs2013-3005.pdf"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.24,42.0 ], [ -117.24,49.0 ], [ -111.0,49.0 ], [ -111.0,42.0 ], [ -117.24,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51249f04e4b0b6328103b313","contributors":{"authors":[{"text":"Bartolino, James","contributorId":46849,"corporation":false,"usgs":true,"family":"Bartolino","given":"James","email":"","affiliations":[],"preferred":false,"id":474190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vincent, Sean","contributorId":52465,"corporation":false,"usgs":true,"family":"Vincent","given":"Sean","affiliations":[],"preferred":false,"id":474191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043743,"text":"fs20123135 - 2013 - Drought and deluge: Effects of recent climate variability on groundwater levels in eastern Arkansas","interactions":[],"lastModifiedDate":"2026-06-05T13:30:44.434489","indexId":"fs20123135","displayToPublicDate":"2013-02-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3135","title":"Drought and deluge: Effects of recent climate variability on groundwater levels in eastern Arkansas","docAbstract":"Arkansas experienced wide extremes in climate variability during the period of 2005 to 2010, recording the largest annual precipitation ever recorded in the State (100.05 inches) in 2009. Many weather stations across the State reported between 80 to 90 inches of rainfall in 2009. For comparison, the average annual precipitation in Little Rock, Arkansas, for the period 1878 to 2010 was 47.1 inches. In contrast, 2005 and 2010 were the 7th and 14th driest years on record in Little Rock with 34.55 and 36.52 inches, respectively; both tied as the hottest years ever recorded in Arkansas. The wettest year on record in Little Rock (2009) was interspersed within these dry years, with a total of 81.79 inches. Fifteen weather stations within the State ranked 2009 as the wettest year on record. Extremes in annual precipitation rates may lead to greater variability in groundwater recharge rates and water use, particularly in the agricultural areas in eastern Arkansas that rely heavily on groundwater produced from the Mississippi River Valley alluvial aquifer (hereafter referred to as the alluvial aquifer). How does this variability affect the groundwater system and water use therein? Are the effects of this variability discernable in measured water levels in wells? Czarnecki and Schrader examined these questions and provided some insights, the results of which are presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123135","usgsCitation":"Czarnecki, J.B., and Schrader, T., 2013, Drought and deluge: Effects of recent climate variability on groundwater levels in eastern Arkansas: U.S. Geological Survey Fact Sheet 2012-3135, 6 p., https://doi.org/10.3133/fs20123135.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":505006,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98171.htm","linkFileType":{"id":5,"text":"html"}},{"id":267733,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3135.gif"},{"id":267731,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3135/"},{"id":267732,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3135/fs2012-3135.pdf"}],"scale":"3429000","country":"United States","state":"Arkansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.33987129096217,\n 36.467930211688355\n ],\n [\n -89.60321209121454,\n 36.467930211688355\n ],\n [\n -89.60321209121454,\n 33.06745923952951\n ],\n [\n -92.33987129096217,\n 33.06745923952951\n ],\n [\n -92.33987129096217,\n 36.467930211688355\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51249edfe4b0b6328103b30b","contributors":{"authors":[{"text":"Czarnecki, John B. jczarnec@usgs.gov","contributorId":2555,"corporation":false,"usgs":true,"family":"Czarnecki","given":"John","email":"jczarnec@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":474193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schrader, T. P.","contributorId":56300,"corporation":false,"usgs":true,"family":"Schrader","given":"T.","middleInitial":"P.","affiliations":[],"preferred":false,"id":474194,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043614,"text":"sim3242 - 2013 - Flood-inundation maps for an 8.9-mile reach of the South Fork Little River at Hopkinsville, Kentucky","interactions":[],"lastModifiedDate":"2013-02-15T10:40:05","indexId":"sim3242","displayToPublicDate":"2013-02-15T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3242","title":"Flood-inundation maps for an 8.9-mile reach of the South Fork Little River at Hopkinsville, Kentucky","docAbstract":"Digital flood-inundation maps for an 8.9-mile reach of South Fork Little River at Hopkinsville, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Hopkinsville Community Development Services. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at South Fork Little River at Highway 68 By-Pass at Hopkinsville, Kentucky (station no. 03437495). Current conditions for the USGS streamgage may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis/inventory?agency_code=USGS&site_no=03437495). In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. The forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the South Fork Little River reach by using HEC-RAS, a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (2012) stage-discharge relation at the South Fork Little River at Highway 68 By-Pass at Hopkinsville, Kentucky, streamgage and measurements collected during recent flood events. The calibrated model was then used to calculate 13 water-surface profiles for a sequence of flood stages, most at 1-foot intervals, referenced to the streamgage datum and ranging from a stage near bank full to the estimated elevation of the 1.0-percent annual exceedance probability flood at the streamgage. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a Digital Elevation Model (DEM) of the study area by using Geographic Information System (GIS) software. The DEM consisted of bare-earth elevations within the study area and was derived from a Light Detection And Ranging (LiDAR) dataset having a 3.28-foot horizontal resolution. These flood-inundation maps, along with online information regarding current stages from USGS streamgage and forecasted stages from the NWS, provide emergency management and local residents with critical information for flood response activities such as evacuations, road closures, and post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3242","collaboration":"Prepared in cooperation with the City of Hopkinsville, Kentucky, Community Development Services","usgsCitation":"Lant, J.G., 2013, Flood-inundation maps for an 8.9-mile reach of the South Fork Little River at Hopkinsville, Kentucky: U.S. Geological Survey Scientific Investigations Map 3242, Pamphlet: vi, 8 p.; 13 Sheets: 17 x 22 inches; Downloads Directory, https://doi.org/10.3133/sim3242.","productDescription":"Pamphlet: vi, 8 p.; 13 Sheets: 17 x 22 inches; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":267570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3242.gif"},{"id":267558,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet05_stage14_0_.pdf"},{"id":267559,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet06_stage15_0.pdf"},{"id":267560,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet07_stage16_0.pdf"},{"id":267561,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet08_stage17_0.pdf"},{"id":267562,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet09_stage18_0.pdf"},{"id":267563,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet10_stage19_0.pdf"},{"id":267564,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet11_stage20_0.pdf"},{"id":267565,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet12_stage21_0.pdf"},{"id":267566,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet13_stage21_5.pdf"},{"id":267567,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/sim/3242/images/jpg_mapsheets"},{"id":267568,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3242/pdf"},{"id":267569,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3242/Downloads"},{"id":267554,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet01_stage10_0.pdf"},{"id":267552,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3242/"},{"id":267553,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3242/pdf/sim3242.pdf"},{"id":267555,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet02_stage11_0.pdf"},{"id":267556,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet03_stage12_0.pdf"},{"id":267557,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3242/pdf/Sheet04_stage13_0.pdf"}],"projection":"Lambert Conformal Conic","datum":"North American Datum of 1983","country":"United States","state":"Kentucky","city":"Hopkinsville","otherGeospatial":"South Fork Little River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.5,36.816667 ], [ -87.5,36.866667 ], [ -87.425,36.866667 ], [ -87.425,36.816667 ], [ -87.5,36.816667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511f58e2e4b03b29402c5d4a","contributors":{"authors":[{"text":"Lant, Jeremiah G. 0000-0001-6688-4820 jlant@usgs.gov","orcid":"https://orcid.org/0000-0001-6688-4820","contributorId":4912,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","email":"jlant@usgs.gov","middleInitial":"G.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473971,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70043611,"text":"fs20133008 - 2013 - Tracking and forecasting the Nation’s water quality - Priorities and strategies for 2013-2023","interactions":[],"lastModifiedDate":"2016-06-24T09:05:06","indexId":"fs20133008","displayToPublicDate":"2013-02-15T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3008","title":"Tracking and forecasting the Nation’s water quality - Priorities and strategies for 2013-2023","docAbstract":"Water-quality issues facing the Nation are growing in number and complexity, and solutions are becoming more challenging and costly. Key factors that affect the quality of our drinking water supplies and ecosystem health include contaminants of human and natural origin in streams and groundwater; excess nutrients and sediment; alteration of natural streamflow; eutrophication of lakes, reservoirs, and coastal estuaries; and changes in surface and groundwater quality associated with changes in climate, land and water use, and management practices. Tracking and forecasting the Nation's water quality in the face of these and other pressing water-quality issues are important goals for 2013-2023, the third decade of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program. In consultation with stakeholders and the National Research Council, a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing assessment of the Nation's freshwater quality and aquatic ecosystems. The plan continues strategies that have been central to the NAWQA program's long-term success, but it also makes adjustments to the monitoring and modeling approaches NAWQA will use to address critical data and science information needs identified by stakeholders. This fact sheet describes surface-water and groundwater monitoring and modeling activities that will start in fiscal year 2013. It also provides examples of the types of data and information products planned for the next decade, including (1) restored monitoring for reliable and timely status and trend assessments, (2) maps and models that show the distribution of selected contaminants (such as atrazine, nitrate, and arsenic) in streams and aquifers, and (3) Web-based modeling tools that allow managers to evaluate how water quality may change in response to different scenarios of population growth, climate change, or land-use management.
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