Borehole geophysical logs and thermal imaging data were collected by the U.S. Geological Survey near the Hemphill Road TCE (trichloroethylene) National Priorities List Superfund site near Gastonia, North Carolina, during August 2014 through February 2015. In an effort to assist the U.S. Environmental Protection Agency in the development of a conceptual groundwater model for the assessment of current contaminant distribution and future migration of contaminants, surface geological mapping and borehole geophysical log and thermal imaging data collection, which included the delineation of more than 600 subsurface features (primarily fracture orientations), was completed in five open borehole wells and two private supply bedrock wells. In addition, areas of possible groundwater discharge within a nearby creek downgradient of the study site were determined based on temperature differences between the stream and bank seepage using thermal imagery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171017","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Region 4 Superfund Section","usgsCitation":"Antolino, D.J., and Chapman, M.J., 2017, Geophysical logging and thermal imaging near the Hemphill Road TCE National Priorities List Superfund site near Gastonia, North Carolina (ver. 1.1, March 2017): U.S. Geological Survey Open-File Report 2017–1017, 47 p., https://doi.org/10.3133/ofr20171017.","productDescription":"Report: v, 47 p.; Data Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079978","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":337458,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1017/coverthb2.jpg"},{"id":337459,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1017/ofr20171017.pdf","text":"Report","size":"19.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1017"},{"id":337460,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6NPM","text":"USGS data release ","description":"USGS data release","linkHelpText":"Geophysical logging and thermal imaging at the Hemphill Road TCE NPL Superfund site near Gastonia, North Carolina"},{"id":338827,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1017/versionHist.txt","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina","county":"Gaston County","city":"Gastonia","otherGeospatial":"Hemphill Road trichloroethylene National Priorities List Superfund site","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-81.4535,35.4201],[-81.2581,35.4132],[-81.0069,35.4038],[-80.9549,35.4006],[-80.9554,35.3925],[-80.9632,35.3901],[-80.9761,35.3828],[-80.9806,35.3823],[-80.9846,35.3822],[-80.9868,35.38],[-80.9844,35.3695],[-80.9776,35.3646],[-80.9742,35.3642],[-80.9697,35.3669],[-80.9669,35.3688],[-80.9647,35.3738],[-80.9625,35.3756],[-80.9597,35.3756],[-80.9563,35.3738],[-80.9505,35.3675],[-80.9432,35.3658],[-80.9296,35.3636],[-80.9268,35.3627],[-80.9285,35.3614],[-80.9374,35.3572],[-80.9442,35.3521],[-80.9537,35.3521],[-80.9593,35.3489],[-80.9656,35.3506],[-80.9706,35.3501],[-80.9818,35.3446],[-80.984,35.3373],[-80.9823,35.3341],[-80.9805,35.3287],[-80.9844,35.3237],[-80.9894,35.3205],[-80.9938,35.3132],[-80.9961,35.3113],[-81.0022,35.3045],[-81.0033,35.3017],[-81.0105,35.2944],[-81.0133,35.293],[-81.0143,35.2876],[-81.0152,35.2685],[-81.0139,35.2585],[-81.0082,35.2509],[-81.012,35.2349],[-81.0113,35.2309],[-81.0129,35.2231],[-81.0071,35.2109],[-81.0054,35.2055],[-81.0064,35.1973],[-81.0063,35.1923],[-81.0046,35.1864],[-81.0045,35.1814],[-81.0049,35.1728],[-81.0088,35.165],[-81.0076,35.1569],[-81.0109,35.1532],[-81.0176,35.1536],[-81.0238,35.1486],[-81.0448,35.1494],[-81.0682,35.1507],[-81.1814,35.1568],[-81.2141,35.1586],[-81.3277,35.1637],[-81.3163,35.1906],[-81.3209,35.2609],[-81.355,35.2796],[-81.3548,35.2946],[-81.3594,35.3022],[-81.3675,35.314],[-81.3659,35.3181],[-81.3565,35.3309],[-81.3986,35.3531],[-81.4535,35.4201]]]},\"properties\":{\"name\":\"Gaston\",\"state\":\"NC\"}}]}","edition":"Version 1.0: Originally posted March 27, 2017; Version 1.1: March 30, 2017","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
https://www2.usgs.gov/water/southatlantic/
Ethiopia experiences significant climate-induced drought and stress on crop and livestock productivity, contributing to widespread food insecurity. Here, we present subseasonal crop water stress analyses that indicate degrading, growing conditions along Ethiopia’s eastern highlands, including productive and populated highland regions. These seasonally shifting areas of increasing water stress stretch from the north to south across eastern Ethiopia, intersecting regions of acute food insecurity and/or high population. Crop model simulations indicate that between 1982 and 2014, parts of eastern Amhara and eastern Oromia experienced increasing water deficits during the critical sowing, flowering, and ripening periods of crop growth. These trends occurred while population in these regions increased by 143% between 2000 and 2015. These areas of enhanced crop water stress in south-central Ethiopia coincide with regions of high population growth and ongoing crop extensification. Conversely, large regions of relatively unpopulated western Ethiopia are becoming wetter. These areas may therefore be good targets for agricultural development.
The U.S. Geological Survey Central Plains Water Science Center, serving the states of Kansas and Nebraska, has collected and interpreted hydrologic information for more than a century. Data collected include streamflow and gage height, reservoir content, water quality and water quantity, suspended sediment, and groundwater levels. Interpretative hydrologic studies are completed on national, regional, statewide, and local levels and cooperatively funded through partnerships with these agencies. The U.S. Geological Survey provides impartial scientific information to describe and understand the health of our ecosystems and environment; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect our quality of life. These collected data are in the National Water Information System (Kansas: https://dashboard.waterdata.usgs.gov/app/nwd/en/ and Nebraska: https://dashboard.waterdata.usgs.gov/app/nwd/en/), and all results are documented in reports that also are online (Kansas: https://www.usgs.gov/centers/kswsc and Nebraska: https://www.usgs.gov/centers/nebraska-water-science-center/publications).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip173","usgsCitation":"U.S. Geological Survey, 2017, Central Plains Water Science Center bookmark (ver. 1.2, July 2025): U.S. Geological Survey General Information Product 173, 2 p., https://doi.org/10.3133/gip173.","productDescription":"Bookmark: 2.25 x 7.50 inches","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-085657","costCenters":[{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":492407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0173/coverthb4.jpg"},{"id":492363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0173/gip173.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 173, ver. 1.2"},{"id":492422,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/gip/0173/versionHist.txt","text":"Version History","size":"1KB txt"}],"edition":"Version 1.0: March 27, 2017; Version 1.1: September 11, 2018; Version 1.2: July 17, 2025","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Dr
Lawrence, KS 66049
Freshwater mussels, one of the most imperiled groups of animals in the world, are generally underrepresented in toxicity databases used for the development of ambient water quality criteria and other environmental guidance values. Acute 96-h toxicity tests were conducted to evaluate the sensitivity of 5 species of juvenile mussels from 2 families and 4 tribes to 10 chemicals (ammonia, metals, major ions, and organic compounds) and to screen 10 additional chemicals (mainly organic compounds) with a commonly tested mussel species, fatmucket (Lampsilis siliquoidea). In the multi-species study, median effect concentrations (EC50s) among the 5 species differed by a factor of ≤2 for chloride, potassium, sulfate, and zinc; a factor of ≤5 for ammonia, chromium, copper, and nickel; and factors of 6 and 12 for metolachlor and alachlor, respectively, indicating that mussels representing different families or tribes had similar sensitivity to most of the tested chemicals, regardless of modes of action. There was a strong linear relationship between EC50s for fatmucket and the other 4 mussel species across the 10 chemicals (r2 = 0.97, slope close to 1.0), indicating that fatmucket was similar to other mussel species; thus, this commonly tested species can be a good surrogate for protecting other mussels in acute exposures. The sensitivity of juvenile fatmucket among different populations or cultured from larvae of wild adults and captive-cultured adults was also similar in acute exposures to copper or chloride, indicating captive-cultured adult mussels can reliably be used to reproduce juveniles for toxicity testing. In compiled databases for all freshwater species, 1 or more mussel species were among the 4 most sensitive species for alachlor, ammonia, chloride, potassium, sulfate, copper, nickel, and zinc; therefore, the development of water quality criteria and other environmental guidance values for these chemicals should reflect the sensitivity of mussels. In contrast, the EC50s of fatmucket tested in the single-species study were in the high percentiles (>75th) of species sensitivity distributions for 6 of 7 organic chemicals, indicating mussels might be relatively insensitive to organic chemicals in acute exposures.
","language":"English","publisher":"SETAC Press","doi":"10.1002/etc.3642","usgsCitation":"Wang, N., Ivey, C.D., Ingersoll, C.G., Brumbaugh, W.G., Alvarez, D., Hammer, E.J., Bauer, C.R., Augspurger, T., Raimondo, S., and Barnhart, M., 2017, Acute sensitivity of a broad range of freshwater mussels to chemicals with different modes of toxic action: Environmental Toxicology and Chemistry, v. 36, no. 3, p. 786-796, https://doi.org/10.1002/etc.3642.","productDescription":"11 p.","startPage":"786","endPage":"796","ipdsId":"IP-077267","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":469990,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8220997","text":"External Repository"},{"id":338421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"58da2517e4b0543bf7fda7ec","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":150499,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hammer, Edward J.","contributorId":150723,"corporation":false,"usgs":false,"family":"Hammer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":686407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bauer, Candice R.","contributorId":150724,"corporation":false,"usgs":false,"family":"Bauer","given":"Candice","email":"","middleInitial":"R.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":686408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Augspurger, Tom","contributorId":189894,"corporation":false,"usgs":false,"family":"Augspurger","given":"Tom","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":686409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Raimondo, Sandy","contributorId":150748,"corporation":false,"usgs":false,"family":"Raimondo","given":"Sandy","email":"","affiliations":[{"id":18090,"text":"U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL","active":true,"usgs":false}],"preferred":false,"id":686410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Barnhart, M.Christopher","contributorId":189895,"corporation":false,"usgs":false,"family":"Barnhart","given":"M.Christopher","affiliations":[],"preferred":false,"id":686411,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70181998,"text":"ds1034 - 2017 - Bathymetry data collected in October 2014 from Fire Island, New York—The wilderness breach, shoreface, and bay","interactions":[],"lastModifiedDate":"2017-03-27T09:54:31","indexId":"ds1034","displayToPublicDate":"2017-03-24T17:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1034","title":"Bathymetry data collected in October 2014 from Fire Island, New York—The wilderness breach, shoreface, and bay","docAbstract":"Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, using single-beam echo sounders and global positioning systems mounted to personal watercraft, along the Fire Island shoreface and within the wilderness breach, Fire Island Inlet, Narrow Bay, and Great South Bay east of Nicoll Bay. Additional bathymetry and elevation data were collected using backpack and wheel-mounted global positioning systems along the subaerial beach (foreshore and backshore), flood shoals, and shallow channels within the wilderness breach and adjacent shoreface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1034","usgsCitation":"Nelson, T.R., Miselis, J.L., Hapke, C.J., Brenner, O.T., Henderson, R.E., Reynolds, B.J., and Wilson, K.E., 2017, Bathymetry data collected in October 2014 from Fire Island, New York—The wilderness breach, shoreface, and bay: U.S. Geological Survey Data Series 1034, https://doi.org/10.3133/ds1034.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071668","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":337454,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1034/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1034"},{"id":337453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1034/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3172607421875,\n 40.60821853973967\n ],\n [\n -72.77412414550781,\n 40.60821853973967\n ],\n [\n -72.77412414550781,\n 40.77586181063573\n ],\n [\n -73.3172607421875,\n 40.77586181063573\n ],\n [\n -73.3172607421875,\n 40.60821853973967\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
https://coastal.er.usgs.gov/
County-level estimates of nitrogen and phosphorus inputs from animal manure for the conterminous United States were calculated from animal population inventories in the 2007 and 2012 Census of Agriculture, using previously published methods. These estimates of non-point nitrogen and phosphorus inputs from animal manure were compiled in support of the U.S. Geological Survey’s National Water-Quality Assessment Project of the National Water Quality Program and are needed to support national-scale investigations of stream and groundwater water quality. The estimates published in this report are comparable with older estimates which can be compared to show changes in nitrogen and phosphorus inputs from manure over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171021","issn":"2331-1258","usgsCitation":"Gronberg, J.M., and Arnold, T.L., 2017, County-level estimates of nitrogen and phosphorus from animal manure for the conterminous United States, 2007 and 2012: U.S. Geological Survey Open-File Report 2017–1021, 6 p., https://doi.org/10.3133/ofr20171021.","productDescription":"iii, 6 p.","numberOfPages":"14","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438408,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X34VMZ","text":"USGS data release","linkHelpText":"County-level estimates of nitrogen and phosphorus from animal manure (2007 and 2012) and 30-meter-resolution grid of counties (2010) for the conterminous United States"},{"id":338286,"rank":3,"type":{"id":30,"text":"Data 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\"}}]}\n","contact":"To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2755","usgsCitation":"Reese, G.C., and Skagen, S., 2017, Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change: Ecology and Evolution, v. 7, no. 5, p. 1497-1513, https://doi.org/10.1002/ece3.2755.","productDescription":"17 p.","startPage":"1497","endPage":"1513","ipdsId":"IP-073714","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2755","text":"Publisher Index Page"},{"id":338301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Plains Landscape Conservation Cooperative","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.01806640624999,\n 29.649868677972304\n ],\n [\n -95.47119140625,\n 29.649868677972304\n ],\n [\n -95.47119140625,\n 43.43696596521823\n ],\n [\n -106.01806640624999,\n 43.43696596521823\n ],\n [\n -106.01806640624999,\n 29.649868677972304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-07","publicationStatus":"PW","scienceBaseUri":"58d63031e4b05ec7991310cb","chorus":{"doi":"10.1002/ece3.2755","url":"http://dx.doi.org/10.1002/ece3.2755","publisher":"Wiley-Blackwell","authors":"Reese Gordon C., Skagen Susan K.","journalName":"Ecology and Evolution","publicationDate":"2/7/2017","publiclyAccessibleDate":"2/7/2017"},"contributors":{"authors":[{"text":"Reese, Gordon C. 0000-0002-5191-7770 greese@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-7770","contributorId":189809,"corporation":false,"usgs":true,"family":"Reese","given":"Gordon","email":"greese@usgs.gov","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":686087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":167829,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan K.","email":"skagens@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":686088,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185562,"text":"70185562 - 2017 - Effects of impervious area and BMP implementation and design on storm runoff and water quality in eight small watersheds","interactions":[],"lastModifiedDate":"2017-04-10T08:41:30","indexId":"70185562","displayToPublicDate":"2017-03-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Effects of impervious area and BMP implementation and design on storm runoff and water quality in eight small watersheds","docAbstract":"The effects of increases in effective impervious area (EIA) and the implementation of water quality protection designed detention pond best management practices (BMPs) on storm runoff and stormwater quality were assessed in Gwinnett County, Georgia, for the period 2001-2008. Trends among eight small watersheds were compared, using a time trend study design. Significant trends were detected in three storm hydrologic metrics and in five water quality constituents that were adjusted for variability in storm characteristics and climate. Trends in EIA ranged from 0.10 to 1.35, and changes in EIA treated by BMPs ranged from 0.19 to 1.32; both expressed in units of percentage of drainage area per year. Trend relations indicated that for every 1% increase in watershed EIA, about 2.6, 1.1, and 1.5% increases in EIA treated by BMPs would be required to counteract the effects of EIA added to the watersheds on peak streamflow, stormwater yield, and storm streamflow runoff, respectively. Relations between trends in EIA, BMP implementation, and water quality were counterintuitive. This may be the result of (1) changes in constituent inputs in the watersheds, especially downstream of areas treated by BMPs; (2) BMPs may have increased the duration of stormflow that results in downstream channel erosion; and/or (3) spurious relationships between increases in EIA, BMP implementation, and constituent inputs with development rates.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12501","usgsCitation":"Aulenbach, B.T., Landers, M.N., Musser, J.W., and Painter, J.A., 2017, Effects of impervious area and BMP implementation and design on storm runoff and water quality in eight small watersheds: Journal of the American Water Resources Association, v. 53, no. 2, p. 382-399, https://doi.org/10.1111/1752-1688.12501.","productDescription":"18 p.","startPage":"382","endPage":"399","ipdsId":"IP-066225","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":338266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-30","publicationStatus":"PW","scienceBaseUri":"58d63034e4b05ec7991310d3","contributors":{"authors":[{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":685966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landers, Mark N. 0000-0002-3014-0480 landers@usgs.gov","orcid":"https://orcid.org/0000-0002-3014-0480","contributorId":1103,"corporation":false,"usgs":true,"family":"Landers","given":"Mark","email":"landers@usgs.gov","middleInitial":"N.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":685967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":685968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":685969,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184191,"text":"sir20175002 - 2017 - Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations","interactions":[],"lastModifiedDate":"2017-03-23T11:48:40","indexId":"sir20175002","displayToPublicDate":"2017-03-23T00:00:00","publicationYear":"2017","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":"2017-5002","title":"Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations","docAbstract":"A common statistical procedure for estimating streamflow statistics at ungaged locations is to develop a relational model between streamflow and drainage basin characteristics at gaged locations using least squares regression analysis; however, least squares regression methods are parametric and make constraining assumptions about the data distribution. The random forest regression method provides an alternative nonparametric method for estimating streamflow characteristics at ungaged sites and requires that the data meet fewer statistical conditions than least squares regression methods.
Random forest regression analysis was used to develop predictive models for 89 streamflow characteristics using Precipitation-Runoff Modeling System simulated streamflow data and drainage basin characteristics at 179 sites in central and eastern Montana. The predictive models were developed from streamflow data simulated for current (baseline, water years 1982–99) conditions and three future periods (water years 2021–38, 2046–63, and 2071–88) under three different climate-change scenarios. These predictive models were then used to predict streamflow characteristics for baseline conditions and three future periods at 1,707 fish sampling sites in central and eastern Montana. The average root mean square error for all predictive models was about 50 percent. When streamflow predictions at 23 fish sampling sites were compared to nearby locations with simulated data, the mean relative percent difference was about 43 percent. When predictions were compared to streamflow data recorded at 21 U.S. Geological Survey streamflow-gaging stations outside of the calibration basins, the average mean absolute percent error was about 73 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175002","collaboration":"Prepared in cooperation with the Plains and Prairie Potholes Landscape Conservation Cooperative and the Bureau of Land Management","usgsCitation":"Sando, Roy, and Chase, K.J., 2017, Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations: U.S. Geological Survey Scientific Investigations Report 2017–5002, 23 p., https://doi.org/10.3133/sir20175002.","productDescription":"Report: vi, 26 p.; Appendixes 1-1 to 1-18","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069581","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":338115,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5002/sir20175002.pdf","text":"Report","size":"14.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5002"},{"id":338114,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5002/coverthb.jpg"},{"id":338116,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5002/sir20175002_appendixtables.xlsx","text":"Appendix Tables 1–1 to 1–18","size":"11.9 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5002 Appendix Tables 1–1 to 1–18"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.291015625,\n 43.99281450048989\n ],\n [\n -102.23876953125,\n 43.99281450048989\n ],\n [\n -102.23876953125,\n 49.59647007089266\n ],\n [\n -113.291015625,\n 49.59647007089266\n ],\n [\n -113.291015625,\n 43.99281450048989\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
High variability in precipitation and streamflow in the semiarid northern Great Plains causes large uncertainty in water availability. This uncertainty is compounded by potential effects of future climate change. We examined historical variability in annual and growing season precipitation, temperature, and streamflow within the Little Missouri River Basin and identified differences in the runoff response to precipitation for the period 1976-2012 compared to 1939-1975 (n = 37 years in both cases). Computed mean values for the second half of the record showed little change (<5%) in annual or growing season precipitation, but average annual runoff at the basin outlet decreased by 22%, with 66% of the reduction in flow occurring during the growing season. Our results show a statistically significant (p < 0.10) 27% decrease in the annual runoff response to precipitation (runoff ratio). Surface-water withdrawals for various uses appear to account for <12% of the reduction in average annual flow volume, and we found no published or reported evidence of substantial flow reduction caused by groundwater pumping in this basin. Results of our analysis suggest that increases in monthly average maximum and minimum temperatures, including >1°C increases in January through March, are the dominant driver of the observed decrease in runoff response to precipitation in the Little Missouri River Basin.
","language":"English","publisher":"American Water Resources Association","publisherLocation":"Herndon, VA","doi":"10.1111/1752-1688.12517","usgsCitation":"Griffin, E.R., and Friedman, J.M., 2017, Decreased runoff response to precipitation, Little Missouri River Basin, northern Great Plains, USA: Journal of the American Water Resources Association, v. 53, no. 3, p. 576-592, https://doi.org/10.1111/1752-1688.12517.","productDescription":"17 p.","startPage":"576","endPage":"592","ipdsId":"IP-073357","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":338166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota, Wyoming","otherGeospatial":"Little Missouri River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.435791015625,\n 44.449467536006935\n ],\n [\n -102.095947265625,\n 44.449467536006935\n ],\n [\n -102.095947265625,\n 47.88688085106901\n ],\n [\n -105.435791015625,\n 47.88688085106901\n ],\n [\n -105.435791015625,\n 44.449467536006935\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-17","publicationStatus":"PW","scienceBaseUri":"58d4deffe4b05ec79911d19a","contributors":{"authors":[{"text":"Griffin, Eleanor R. 0000-0001-6724-9853 egriffin@usgs.gov","orcid":"https://orcid.org/0000-0001-6724-9853","contributorId":1775,"corporation":false,"usgs":true,"family":"Griffin","given":"Eleanor","email":"egriffin@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":685812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":685813,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70184393,"text":"ds1042 - 2017 - Bull trout (Salvelinus confluentus) telemetry and associated habitat data collected in a geodatabase from the upper Boise River, southwestern Idaho","interactions":[],"lastModifiedDate":"2017-12-06T09:53:43","indexId":"ds1042","displayToPublicDate":"2017-03-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1042","title":"Bull trout (Salvelinus confluentus) telemetry and associated habitat data collected in a geodatabase from the upper Boise River, southwestern Idaho","docAbstract":"Bull trout (Salvelinus confluentus), listed as threatened under the Endangered Species Act, are among the more thermally sensitive of coldwater species in North America. The Boise River upstream of Arrowrock Dam in southwestern Idaho (including Arrowrock Reservoir) provides habitat for one of the southernmost populations of bull trout. The presence of the species in Arrowrock Reservoir poses implications for dam and reservoir operations. From 2011 to 2014, the Bureau of Reclamation and the U.S. Geological Survey collected fish telemetry data to improve understanding of bull trout distribution and movement in Arrowrock Reservoir and in the upper Boise River tributaries. The U.S. Geological Survey compiled the telemetry (fish location) data, along with reservoir elevation, river discharge, precipitation, and water-quality data in a geodatabase. The geodatabase includes metadata compliant with Federal Geographic Data Committee content standards. The Bureau of Reclamation plans to incorporate the data in a decision‑support tool for reservoir management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1042","collaboration":"Prepared in cooperation with Bureau of Reclamation","usgsCitation":"MacCoy, D.E., Shephard, Z.M., Benjamin, J.R., Vidergar, D.T., and Prisciandaro, A.F., 2017, Bull trout (Salvelinus confluentus) telemetry and associated habitat data collected in a geodatabase from the upper Boise River, southwestern Idaho: U.S. Geological Survey Data Series 1042, 14 p., https://doi.org/10.3133/ds1042.","productDescription":"Report: v, 14 p.; Data release","onlineOnly":"Y","ipdsId":"IP-074981","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":338145,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1042/ds1042.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1042"},{"id":338143,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MG7MQJ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geodatabase Containing Bull Trout (Salvelinus confluentus) Information from the Upper Boise River, Southwestern Idaho"},{"id":338144,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1042/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Upper Boise River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.133333,\n 43.222222\n ],\n [\n -114.7,\n 43.222222\n ],\n [\n -114.7,\n 44.083333\n ],\n [\n -116.133333,\n 44.083333\n ],\n [\n -116.133333,\n 43.222222\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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The Upper Mississippi River System (UMRS), the navigable part of the Upper Mississippi and Illinois Rivers, is a diverse ecosystem that contains river channels, tributaries, shallow-water wetlands, backwater lakes, and flood-plain forests. Approximately 10,000 years of geologic and hydrographic history exist within the UMRS. Because it maintains crucial wildlife and fish habitats, the dynamic ecosystems of the Upper Mississippi River Basin and its tributaries are contingent on the adjacent flood plains and water-level fluctuations of the Mississippi River. Separate data for flood-plain elevation (lidar) and riverbed elevation (bathymetry) were collected on the UMRS by the U.S. Army Corps of Engineers’ (USACE) Upper Mississippi River Restoration (UMRR) Program. Using the two elevation datasets, the U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) developed a systemic topobathy dataset.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163097","collaboration":"Prepared in cooperation with Upper Mississippi River Restoration","usgsCitation":"Stone, J.M., Hanson, J.L., and Sattler, S.R., 2017, The Upper Mississippi River System—Topobathy: U.S. Geological Survey Fact Sheet 2016–3097, 4 p., https://doi.org/10.3133/fs20163097.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-077869","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3097/coverthb.jpg"},{"id":338163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3097/fs20163097.pdf","text":"Fact Sheet","size":"3.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3097"}],"country":"United States","state":"Illinois, Iowa, 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U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
The U.S. Geological Survey (USGS), in cooperation with the Colorado River Basin Salinity Control Forum, studied trends in dissolved-solids loads at selected sites in and near the Uinta Basin, Utah. The Uinta Basin study area includes the Duchesne River Basin and the Middle Green River Basin in Utah from below Flaming Gorge Reservoir to the town of Green River.
Annual dissolved-solids loads for water years (WY) 1989 through 2013 were estimated for 16 gaging stations in the study area using streamflow and water-quality data from the USGS National Water Information System database. Eight gaging stations that monitored catchments with limited or no agricultural land use (natural subbasins) were used to assess loads from natural sources. Four gaging stations that monitored catchments with agricultural land in the Duchesne River Basin were used to assess loads from agricultural sources. Four other gaging stations were included in the dissolved-solids load and trend analysis to help assess the effects of agricultural areas that drain to the Green River in the Uinta Basin, but outside of the Duchesne River Basin.
Estimated mean annual dissolved-solids loads for WY 1989–2013 ranged from 1,520 tons at Lake Fork River above Moon Lake, near Mountain Home, Utah (UT), to 1,760,000 tons at Green River near Green River, UT. The flow-normalized loads at gaging stations upstream of agricultural activities showed no trend or a relatively small change. The largest net change in modeled flow-normalized load was -352,000 tons (a 17.8-percent decrease) at Green River near Green River, UT.
Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively.
Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively.
The flow-normalized dissolved-solids loads estimated at Duchesne River near Randlett, UT, and White River near Watson, UT, decreased by 68,000 and 55,300 tons, or 27.8 and 20.8 percent respectively, when comparing 1989 to 2013. The drainage basins for both rivers have undergone salinity-control projects since the early 1980s to reduce the dissolved-solids load entering the Colorado River. Approximately 19 percent of the net change in flow-normalized load at Green River at Green River, UT, is from changes in load modeled at Duchesne River near Randlett, UT, and 16 percent from changes in load modeled at White River near Watson, UT. The net change in flow-normalized load estimated at Green River near Greendale, UT, for WY 1989–2013 accounts for about 45 percent of the net change estimated at Green River at Green River, UT.
Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites in the Duchesne River Basin show that 75,400 tons or 44 percent of the load at the Duchesne River near Randlett, UT, gaging station was not accounted for at any of the upstream gages. Most of this unmonitored load is derived from tributary inflow, groundwater discharge, unconsumed irrigation water, and irrigation tail water.
A mass balance of WY 1989–2013 flow-normalized loads estimated at sites in the Duchesne River Basin indicates that the flow-normalized load of unmonitored inflow to the Duchesne River between the Myton and Randlett gaging stations decreased by 38 percent. The total net decrease in flow-normalized load calculated for unmonitored inflow in the drainage basin accounts for 94 percent of the decrease in WY 1989–2013 flow-normalized load modeled at the Duchesne River near Randlett, UT, gaging station. Irrigation improvements in the drainage basin have likely contributed to the decrease in flow-normalized load.
Reductions in dissolved-solids load estimated by the Natural Resources Conservation Service (NRCS) and the Bureau of Reclamation (Reclamation) from on- and off-farm improvements in the Uinta Basin totaled about 135,000 tons in 2013 (81,900 tons from on-farm improvements and 53,300 tons from off-farm improvements). The reduction in dissolved-solids load resulting from on- and off-farm improvements facilitated by the NRCS and Reclamation in the Price River Basin from 1989 to 2013 was estimated to be 64,800 tons.
The amount of sprinkler-irrigated land mapped in the drainage area or subbasin area for a gaging station was used to estimate the reduction in load resulting from the conversion from flood to sprinkler irrigation. Sprinkler-irrigated land mapped in the Uinta Basin totaled 109,630 acres in 2012. Assuming conversion to wheel-line sprinklers, a reduction in dissolved-solids load in the Uinta Basin of 95,800 tons in 2012 was calculated using the sprinkler-irrigation acreage and a pre-salinity-control project dissolved-solids yield of 1.04 tons per acre.
A reduction of 72,800 tons in dissolved-solids load from irrigation improvements was determined from sprinkler-irrigated lands in the Ashley Valley and Jensen, Pelican Lake, and Pleasant Valley areas (mapped in 2012); and in the Price River Basin (mapped in 2011). This decrease in dissolved-solids load is 8,800 tons more than the decrease in unmonitored flow-normalized dissolved-solids load (-64,000 tons) determined for the Green River between the Jensen and Green River gaging stations.
The net WY 1989–2013 change in flow-normalized dissolved-solids load at the Duchesne River near Randlett, UT, and the Green River between the Jensen and Green River, UT, gaging stations determined from mass-balance calculations was compared to reported reductions in dissolved-solids load from on- and off-farm improvements and estimated reductions in load determined from mapped sprinkler-irrigated areas in the Duchesne River Basin and the area draining to the Green River between the Jensen and Green River gaging stations. The combined NRCS and Reclamation estimates of reduction in dissolved-solids load from on- and off-farm improvements in the study area (200,000 tons) is more than the reduction in load estimated using the acreage with sprinkler improvements (136,000 tons) or the mass-balance of flow-normalized load (132,000 tons).
Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, UT 84119-2047
(801) 908-5000
http://ut.water.usgs.gov/
A vast array of chemical compounds are in wide commercial use in the United States, and the potential ecological and human-health effect of exposure to chemical mixtures has been identified as a high priority in environment health science. Awareness of the potential effects of low-level chemical exposures is rising. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, conducted a study in which samples were collected from 38 streams in 25 States to provide an overview of contaminants found in stream water across the Nation. Additionally, biological screening assays were used to help determine any potential ecological and human-health effects of these chemical mixtures and to prioritize target chemicals for future toxicological studies. This report describes the site locations and the sampling and analytical methods and quality-assurance procedures used in the study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171011","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Romanok, K.M., Reilly, T.J., Barber, Larry, Boone, Scott, Buxton, H.T., Foreman, W.T., Furlong, E.T., Hladik, Michelle, Iwanowicz, L.R., Journey, Celeste, Kolpin, D.W., Kuivila, Kathryn, Loftin, K.A., Mills, M.A., Meyer, M.T., Orlando, J.L., Smalling, K.L., Villeneuve, D.L., and Bradley, P.M., 2017, Methods used to characterize the chemical composition and biological activity of environmental waters throughout the United States, 2012–14: U.S. Geological Survey Open-File Report 2017–1011, 105 p., https://doi.org/10.3133/ofr20171011.","productDescription":"Report: x, 105 p.; 1 Table; Data release","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080395","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
https:www.usgs.gov/water/southatlantic/
Restrictive angling regulations in tailwater trout fisheries may be unsuccessful if food availability limits energy for fish to grow. We examined spatial and temporal variation in energy intake and growth in populations of Brown Trout Salmo trutta and Rainbow Trout Oncorhynchus mykiss within three catch-and-release (C-R) areas in Arkansas tailwaters to evaluate food availability compared with consumption. Based on bioenergetic simulations, Rainbow Trout fed at submaintenance levels in both size-classes (≤400 mm TL, >400 mm TL) throughout most seasons. A particular bottleneck in food availability occurred in the winter for Rainbow Trout when the daily ration was substantially below the minimum required for maintenance, despite reduced metabolic costs associated with lower water temperatures. Rainbow Trout growth rates followed a similar pattern to consumption with negative growth rates during the winter periods. All three size-classes (<250 mm TL, 250–400 mm TL, >400 mm TL) of Brown Trout experienced high growth rates and limited temporal bottlenecks in food availability. We observed higher mean densities for Rainbow Trout (47–342 fish/ha) than for Brown Trout (3–84 fish/ha) in all C-R areas. Lower densities of Brown Trout coupled with an ontogenetic shift towards piscivory may have allowed for higher growth rates and sufficient consumption rates to meet energetic demands. Brown Trout at current densities were more effective in maintaining adequate growth rates and larger sizes in C-R areas than were Rainbow Trout. Bioenergetic simulations suggest that reducing stocking levels of Rainbow Trout in the tailwaters may be necessary in order to achieve increased catch rates of larger trout in the C-R areas.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2017.1281169","usgsCitation":"Flinders, J.M., and Magoulick, D.D., 2017, Spatial and temporal consumption dynamics of trout in catch-and-release areas in Arkansas tailwaters: Transactions of the American Fisheries Society, v. 146, no. 3, p. 432-449, https://doi.org/10.1080/00028487.2017.1281169.","productDescription":"18 p.","startPage":"432","endPage":"449","ipdsId":"IP-082134","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","county":"Baxter County, Marion County","otherGeospatial":"Ozark Highlands, White River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.15126037597656,\n 35.94187983750328\n ],\n [\n -92.05924987792969,\n 35.94187983750328\n ],\n [\n -92.05924987792969,\n 36.01467140204727\n ],\n [\n -92.15126037597656,\n 36.01467140204727\n ],\n [\n -92.15126037597656,\n 35.94187983750328\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.57835388183594,\n 36.34776181462616\n ],\n [\n -92.56221771240233,\n 36.34776181462616\n ],\n [\n -92.56221771240233,\n 36.35965143826626\n ],\n [\n -92.57835388183594,\n 36.35965143826626\n ],\n [\n -92.57835388183594,\n 36.34776181462616\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.23846435546875,\n 36.22765795501122\n ],\n [\n -92.22232818603516,\n 36.22765795501122\n ],\n [\n -92.22232818603516,\n 36.23984280222428\n ],\n [\n -92.23846435546875,\n 36.23984280222428\n ],\n [\n -92.23846435546875,\n 36.22765795501122\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"146","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"5a0425bbe4b0dc0b45b453ad","contributors":{"authors":[{"text":"Flinders, John M.","contributorId":200040,"corporation":false,"usgs":false,"family":"Flinders","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720513,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185270,"text":"70185270 - 2017 - Body mass, wing length, and condition of wintering ducks relative to hematozoa infection","interactions":[],"lastModifiedDate":"2018-07-15T18:32:43","indexId":"70185270","displayToPublicDate":"2017-03-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Body mass, wing length, and condition of wintering ducks relative to hematozoa infection","docAbstract":"Waterfowl managers lack information regarding factors that may be reducing the positive response of waterfowl body condition to habitat improvements. Protozoan blood parasites (i.e., hematozoa) are commonly found in birds and have been related to reduced body mass, wing length, and body condition. We studied relationships between 12 measures of hematozoa infection and body mass, wing length, and body mass divided by wing length (i.e., body condition index [BCI]) of the five most common duck species (northern pintail [Anas acuta], mallard [A. platyrhynchos], green-winged teal [A. crecca], American wigeon [A. Americana], northern shoveler [A. clypeata]) wintering in the Central Valley of California during October 2006-January 2007. After accounting for variation due to species, age-sex cohort, Central Valley region, and month; wing length, body mass, and BCI were found to be negatively related to infection by Leucocytozoon and by \"any hematozoa\" but not related to infection by only Plasmodium or Haemoproteus, or coinfections of greater than one genera or parasite haplotype (albeit, few ducks had Plasmodium or Haemoproteus infection or coinfections). Evidence of a negative relationship with infection was stronger for body mass and BCI than for wing length and indicated that the relationships varied among species, age-sex cohorts, regions, and months. Compared to uninfected ducks, hematozoa-infected duck body mass, wing length, and BCI was -1.63% (85% CI = -2.79%- -0.47%), -0.12% (-0.41%- +0.17%), and -1.38% (-2.49%- -0.26%), respectively. Although, seemingly small, the -1.63% difference in body mass represents a large percentage (e.g., 38% for northern pintail) of the observed increase in wintering duck body mass associated with Central Valley habitat improvements. Because infection prevalence and relationship to body condition might change over time due to climate or other factors, tracking hematozoa infection prevalence might be important to inform and accurately assess the effect of conservation programs designed to improve waterfowl body condition.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","doi":"10.3996/082016-JFWM-063","usgsCitation":"Fleskes, J.P., Ramey, A.M., Reeves, A.B., and Yee, J.L., 2017, Body mass, wing length, and condition of wintering ducks relative to hematozoa infection: Journal of Fish and Wildlife Management, v. 8, no. 1, p. 89-100, https://doi.org/10.3996/082016-JFWM-063.","productDescription":"12 p.","startPage":"89","endPage":"100","ipdsId":"IP-079106","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470001,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/082016-jfwm-063","text":"Publisher Index Page"},{"id":337834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.84912109375,\n 34.75966612466248\n ],\n [\n -118.01513671875,\n 34.75966612466248\n ],\n [\n -118.01513671875,\n 40.613952441166596\n ],\n [\n -122.84912109375,\n 40.613952441166596\n ],\n [\n -122.84912109375,\n 34.75966612466248\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"58d0ea1ae4b0236b68f67367","contributors":{"authors":[{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":177154,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":684961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":684963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":684964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":684962,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185288,"text":"70185288 - 2017 - Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication","interactions":[],"lastModifiedDate":"2017-03-20T08:25:20","indexId":"70185288","displayToPublicDate":"2017-03-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication","docAbstract":"We used monitoring data from Lake Lugano (Switzerland and Italy) to assess key ecosystem responses to three decades of nutrient management (1983–2014). We investigated whether reductions in external phosphorus loadings (Lext) caused declines in lake phosphorus concentrations (P) and phytoplankton biomass (Chl a), as assumed by the predictive models that underpinned the management plan. Additionally, we examined the hypothesis that deep lakes respond quickly to Lext reductions. During the study period, nutrient management reduced Lext by approximately a half. However, the effects of such reduction on P and Chl a were complex. Far from the scenarios predicted by classic nutrient-management approaches, the responses of P and Chl a did not only reflect changes in Lext, but also variation in internal P loadings (Lint) and food-web structure. In turn, Lint varied depending on basin morphometry and climatic effects, whereas food-web structure varied due to apparently stochastic events of colonization and near-extinction of key species. Our results highlight the complexity of the trajectory of deep-lake ecosystems undergoing nutrient management. From an applied standpoint, they also suggest that [i] the recovery of warm monomictic lakes may be slower than expected due to the development of Lint, and that [ii] classic P and Chl a models based on Lext may be useful in nutrient management programs only if their predictions are used as starting points within adaptive frameworks.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Ann Arbor","doi":"10.1016/j.jglr.2017.01.008","usgsCitation":"Lepori, F., and Roberts, J., 2017, Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication: Journal of Great Lakes Research, v. 43, no. 2, p. 255-264, https://doi.org/10.1016/j.jglr.2017.01.008.","productDescription":"10 p.","startPage":"255","endPage":"264","ipdsId":"IP-076985","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":337833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy, Switzerland","otherGeospatial":"Lake Lugano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 8.828201293945312,\n 45.8876184503559\n ],\n [\n 9.142684936523436,\n 45.8876184503559\n ],\n [\n 9.142684936523436,\n 46.056079276178885\n ],\n [\n 8.828201293945312,\n 46.056079276178885\n ],\n [\n 8.828201293945312,\n 45.8876184503559\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58d0ea1ae4b0236b68f67365","contributors":{"authors":[{"text":"Lepori, Fabio","contributorId":166767,"corporation":false,"usgs":false,"family":"Lepori","given":"Fabio","email":"","affiliations":[{"id":24502,"text":"Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland","active":true,"usgs":false}],"preferred":false,"id":685030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":685029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209109,"text":"70209109 - 2017 - Wind River Subbasin Restoration, annual report of U.S. Geological Survey activities: Parr monitoring and instream passive integrated transponder detection, January 1, 2015 – December 31, 2015","interactions":[],"lastModifiedDate":"2020-03-18T07:31:50","indexId":"70209109","displayToPublicDate":"2017-03-17T07:35:04","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Wind River Subbasin Restoration, Annual Report of U.S. Geological Survey Activities: Parr Monitoring and Instream Passive Integrated Transponder Detection, January 1, 2015 – December 31, 2015","title":"Wind River Subbasin Restoration, annual report of U.S. Geological Survey activities: Parr monitoring and instream passive integrated transponder detection, January 1, 2015 – December 31, 2015","docAbstract":"We used Passive Integrated Transponder (PIT)-tagging and a series of instream PIT-tag\ninterrogation systems (PTIS) to investigate life-histories, populations, and efficacy of habitat\nrestoration actions for steelhead Oncorhynchus mykiss in the Wind River subbasin, WA. Our\ntagging focused on parr in headwater areas of the subbasin and our PTISs provide information on movement of these parr, which is primarily, but not exclusively downstream. The PTISs also\nprovide data on life-history aspects of other steelhead life-stages. The Wind River subbasin in\nsouthwest Washington State provides habitat for a population of wild Lower Columbia River\nsteelhead and is an excellent watershed for long-term studies of population dynamics and\nresponses to restoration of this wild population. Much data on steelhead population metrics have\nbeen gathered from the Wind River providing information on habitat restoration actions and\nongoing research into steelhead life histories. Additionally, the Wind River is an excellent\ncontrol watershed of an exclusivly wild steelhead population to which basins with hatchery\nprograms can compare. No hatchery steelhead have been planted in the Wind River subbasin\nsince 1994, and hatchery adults are estimated to be less than one percent of adults in any year\n(pers comm. Thomas Buehrens, Washington Department of Fish and Wildlife). Numerous\nrestoration actions have been implemented in the subbasin, including the removal of Hemlock\nDam on Trout Creek in 2009. Data from our study, and companion work by Washington\nDepartment of Fish and Wildlife (WDFW), will contribute to Bonneville Power Administration’s\n(BPA) Research Monitoring and Evaluation (RM&E) Program Strategy of Fish Population\nStatus Monitoring (www.cbfish.org/ProgramStrategy.mvc/ViewProgramStrategySummary/1),\nspecifically the sub-strategies of: 1) Assessing the Status and Trends of Diversity of Natural\nOrigin Fish Populations and to uncertainties research regarding differing life histories of a wild\nsteelhead population, 2) Assessing the Status and Trend of Adult Natural Origin Fish\nPopulations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions\nRelative to Environmental, Physical, or Biological Performance Objectives.\n\nDuring summer 2015, we sampled and PIT-tagged age-0 and age-1 steelhead parr in\nheadwater areas of the Wind River subbasin to characterize population traits and investigate\nvariable life-histories, including growth and parr movement downstream prior to smolting.\nThroughout the year, we maintained a series of instream PTISs to monitor movement of tagged\nsteelhead parr, smolts, and adults. Detections at the instream PTISs showed trends of parr\n8\nemigration during summer and fall, in addition to the expected movement of parr and smolts in\nspring. These data are increasing our understanding of varied life histories of juvenile steelhead;\npaired with other steelhead population work in the subbasin we hope to better understand the\nfactors influencing parr movements. Monitoring of PIT-tagged fish over multiple years is\nproviding information on contribution of various life-history strategies to smolt production and\nadult returns, as well as identifying factors influencing parr movement.\n\nMovements of PIT-tagged adult steelhead were also monitored with our instream PTISs.\nThese data have provided information on timing of adult movements to various parts of the\nwatershed, which allows us to assess adult returns to tributary watersheds within the Wind River\nsubbasin. Determination of adult use of tributary watersheds is providing data to contribute to\nevaluation of the efficacy of the removal of Hemlock Dam on Trout Creek. Hemlock Dam,\nlocated at rkm 2.0 of Trout Creek was removed in summer 2009 and had contributed to\nhydrologic impairment of Trout Creek.\n\nEvaluating restoration efforts is of interest to many managers and agencies so that\nfunding and time are allocated for best results. The evaluation of various life-his","language":"English","publisher":"Bonneville Power Administration","collaboration":"Bonneville Power Administration","usgsCitation":"Jezorek, I., and Connolly, P., 2017, Wind River Subbasin Restoration, annual report of U.S. Geological Survey activities: Parr monitoring and instream passive integrated transponder detection, January 1, 2015 – December 31, 2015, 66 p.","productDescription":"66 p.","ipdsId":"IP-081196","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":373306,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/Viewer/P151177"},{"id":373333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River subbasin ","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.963568,45.751448 ], [ -121.963568,45.969903 ], [ -121.787086,45.969903 ], [ -121.787086,45.751448 ], [ -121.963568,45.751448 ] ] ] } } ] }","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jezorek, Ian 0000-0002-3842-3485","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":217811,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, Patrick 0000-0003-3795-7490 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0003-3795-7490","contributorId":223402,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784959,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185258,"text":"70185258 - 2017 - Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production","interactions":[],"lastModifiedDate":"2017-03-17T11:58:47","indexId":"70185258","displayToPublicDate":"2017-03-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production","docAbstract":"There remains much debate regarding the perceived tradeoffs of using freshwater and sediment diversions for coastal restoration in terms of balancing the need for wetland restoration versus preserving eastern oyster (Crassostrea virginica) production. Further complicating the issue, climate change-induced sea-level rise (SLR) and land subsidence are also expected to affect estuarine water quality. In this study, we developed a process-based numerical modeling system that couples hydrodynamic, water quality, and oyster population dynamics. We selected Breton Sound Estuary (BSE) (∼2740 km2) in the eastern Mississippi River Deltaic Plain since it is home to several of the largest public oyster seed grounds and private leases for the Gulf coast. The coupled oyster population model was calibrated and validated against field observed oyster growth data. We predicted the responses of oyster population in BSE to small- (142 m3 s−1) and large-scale (7080 m3 s−1) river diversions at the Caernarvon Freshwater Diversion structure planned in the 2012 Coastal Master Plan (Louisiana) under low (0.38 m) and high (1.44 m) relative sea-level rise (RSLR = eustatic SLR + subsidence) compared to a baseline condition (Year 2009). Model results showed that the large-scale diversion had a stronger negative impact on oyster population dynamics via freshening of the entire estuary, resulting in reduced oyster growth rate and production than RSLR. Under the large-scale diversion, areas with optimal oyster growth rates (>15 mg ash-free dry weight (AFDW) oyster−1 wk−1) and production (>500 g AFDW m−2 yr−1) would shift seaward to the southeastern edge of the estuary, turning the estuary into a very low oyster production system. RSLR however played a greater role than the small-scale diversion on the magnitude and spatial pattern of oyster growth rate and production. RSLR would result in an overall estuary-wide decrease in oyster growth rate and production as a consequence of decreased salinities in the middle and lower estuary because rising sea level likely causes increased stage and overbank flow downstream along the lower Mississippi River.
","language":"English","publisher":"International Society for Ecological Modelling","publisherLocation":"Amsterdam","doi":"10.1016/j.ecolmodel.2017.02.028","usgsCitation":"Wang, H., Chen, Q., La Peyre, M., Hu, K., and La Peyre, J.F., 2017, Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production: Ecological Modelling, v. 352, p. 40-53, https://doi.org/10.1016/j.ecolmodel.2017.02.028.","productDescription":"14 p.","startPage":"40","endPage":"53","ipdsId":"IP-079318","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2017.02.028","text":"Publisher Index Page"},{"id":337805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Sound Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.0384521484375,\n 29.262440796698915\n ],\n [\n -89.03594970703125,\n 29.262440796698915\n ],\n [\n -89.03594970703125,\n 29.92637417863576\n ],\n [\n -90.0384521484375,\n 29.92637417863576\n ],\n [\n -90.0384521484375,\n 29.262440796698915\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"352","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ccf59be4b0849ce97f0cda","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":684909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":684910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":684912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":684913,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70180341,"text":"fs20173002 - 2017 - The U.S. Geological Survey Monthly Water Balance Model Futures Portal","interactions":[],"lastModifiedDate":"2017-03-16T12:27:20","indexId":"fs20173002","displayToPublicDate":"2017-03-16T11:00:00","publicationYear":"2017","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":"2017-3002","title":"The U.S. Geological Survey Monthly Water Balance Model Futures Portal","docAbstract":"Simulations of future climate suggest profiles of temperature and precipitation may differ significantly from those in the past. These changes in climate will likely lead to changes in the hydrologic cycle. As such, natural resource managers are in need of tools that can provide estimates of key components of the hydrologic cycle, uncertainty associated with the estimates, and limitations associated with the climate forcing data used to estimate these components. To help address this need, the U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) provides a user friendly interface to deliver hydrologic and meteorological variables for monthly historic and potential future climatic conditions across the continental United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173002","collaboration":"Prepared in cooperation with the U.S. Department of the Interior South Central Climate Science Center and the U.S. Environmental Protection Agency","usgsCitation":"Bock, A.R., 2017, The U.S. Geological Survey Monthly Water Balance Model Futures Portal: U.S. Geological Survey Fact Sheet 2017–3002, 6 p., https://doi.org/10.3133/fs20173002.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-073900","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":336957,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3002/fs20173002.pdf","text":"Report","size":"1.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3002"},{"id":336153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3002/coverthb2.jpg"}],"contact":"Director, USGS Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225-0046
In the southwestern U.S., the meteorological phenomenon known as atmospheric rivers (ARs) has gained increasing attention due to its strong connections to floods, snowpacks, and water supplies in the West Coast states. Relatively less is known about the ecological implications of ARs, particularly in the interior Southwest, where AR storms are less common. To address this gap, we compared a chronology of AR landfalls on the west coast between 1989 and 2011 and between 25°N and 42.5°N to annual metrics of the normalized difference vegetation index (NDVI; an indicator of vegetation productivity) and daily resolution precipitation data to assess influences of AR-fed winter precipitation on vegetation productivity across the southwestern U.S. We mapped correlations between winter AR precipitation during landfalling ARs and (1) annual maximum NDVI and (2) area burned by large wildfires summarized by ecoregion during the same year as the landfalls and during the following year. Interannual variations of AR precipitation strongly influenced both NDVI and area burned by wildfire in some dryland ecoregions. The influence of ARs on dryland vegetation varied significantly depending on the latitude of landfall, with those ARs making landfall below 35°N latitude more strongly influencing these systems, and with effects observed as far as 1300 km from the landfall location. As climatologists' understanding of the synoptic patterns associated with the occurrence of ARs continues to evolve, an increased understanding of how AR landfalls, in aggregate, influence vegetation productivity and associated wildfire activity in dryland ecosystems may provide opportunities to better predict ecological responses to climate and climate change.
","language":"English","publisher":"AGU","doi":"10.1002/2016JG003608","usgsCitation":"Albano, C.M., Dettinger, M.D., and Soulard, C.E., 2017, Influence of atmospheric rivers on vegetation productivity and fire patterns in the southwestern U.S.: Journal of Geophysical Research: Biogeosciences, v. 122, no. 2, p. 308-323, https://doi.org/10.1002/2016JG003608.","productDescription":"16 p.","startPage":"308","endPage":"323","ipdsId":"IP-077664","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470005,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jg003608","text":"Publisher Index Page"},{"id":337748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, 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Center","active":true,"usgs":true}],"preferred":true,"id":684719,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70185125,"text":"70185125 - 2017 - Toxicity of chromium (VI) to two mussels and an amphipod in water-only exposures with or without a co-stressor of elevated temperature, zinc, or nitrate","interactions":[],"lastModifiedDate":"2017-03-22T14:39:31","indexId":"70185125","displayToPublicDate":"2017-03-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":887,"text":"Archives of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of chromium (VI) to two mussels and an amphipod in water-only exposures with or without a co-stressor of elevated temperature, zinc, or nitrate","docAbstract":"The objectives of the present study were to develop methods for propagating western pearlshell (Margaritifera falcata) for laboratory toxicity testing and evaluate acute and chronic toxicity of chromium VI [Cr(VI)] to the pearlshell and a commonly tested mussel (fatmucket, Lampsilis siliquoidea at 20 °C or in association with a co-stressor of elevated temperature (27 °C), zinc (50 µg Zn/L), or nitrate (35 mg NO3/L). A commonly tested invertebrate (amphipod, Hyalella azteca) also was tested in chronic exposures. Newly transformed pearlshell (~1 week old) were successfully cultured and tested in acute 96 h Cr exposures (control survival 100%). However, the grow-out of juveniles in culture for chronic toxicity testing was less successful and chronic 28-day Cr toxicity tests started with 4 month-old pearlshell failed due to low control survival (39–68%). Acute median effect concentration (EC50) for the pearlshell (919 µg Cr/L) and fatmucket (456 µg Cr/L) tested at 20 °C without a co-stressor decreased by a factor of > 2 at elevated temperature but did not decrease at elevated Zn or elevated NO3. Chronic 28-day Cr tests were completed successfully with the fatmucket and amphipod (control survival 83–98%). Chronic maximum acceptable toxicant concentration (MATC) for fatmucket at 20 °C (26 µg Cr/L) decreased by a factor of 2 at elevated temperature or NO3 but did not decrease at elevated Zn. However, chronic MATC for amphipod at 20 °C (13 µg Cr/L) did not decrease at elevated temperature, Zn, or NO3. Acute EC50s for both mussels tested with or without a co-stressor were above the final acute value used to derive United States Environmental Protection Agency acute water quality criterion (WQC) for Cr(VI); however, chronic MATCs for fatmucket at elevated temperature or NO3 and chronic MATCs for the amphipod at 20 °C with or without elevated Zn or NO3 were about equal to the chronic WQC. The results indicate that (1) the elevated temperature increased the acute Cr toxicity to both mussel species, (2) fatmucket was acutely more sensitive to Cr than the pearlshell, (3) elevated temperature or NO3 increased chronic Cr toxicity to fatmucket, and (4) acute WQC are protective of tested mussels with or without a co-stressor; however, the chronic WQC might not protect fatmucket at elevated temperature or NO3 and might not protect the amphipod at 20 °C with or without elevated Zn or NO3.
","language":"English","publisher":"Springer","doi":"10.1007/s00244-017-0377-x","usgsCitation":"Wang, N., Kunz, J.L., Ivey, C.D., Ingersoll, C.G., Barnhart, M., and Glidewell, E.A., 2017, Toxicity of chromium (VI) to two mussels and an amphipod in water-only exposures with or without a co-stressor of elevated temperature, zinc, or nitrate: Archives of Environmental Contamination and Toxicology, v. 72, no. 3, p. 449-460, https://doi.org/10.1007/s00244-017-0377-x.","productDescription":"12 p.","startPage":"449","endPage":"460","ipdsId":"IP-079222","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":337599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-25","publicationStatus":"PW","scienceBaseUri":"58ca52c8e4b0849ce97c8682","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":684437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":684438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":684439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":684440,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnhart, M. Christopher","contributorId":189301,"corporation":false,"usgs":false,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":684441,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glidewell, Elizabeth A.","contributorId":189302,"corporation":false,"usgs":false,"family":"Glidewell","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684442,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}