The U.S. Geological Survey, working with the Montana Department of Environmental Quality and the British Columbia Ministry of the Environment and Climate Change Strategy, has developed a conceptual modeling framework that can be used to provide structured and scientifically based input to the Lake Koocanusa Monitoring and Research Working Group as they consider potential site-specific selenium criteria for Lake Koocanusa, a transboundary reservoir located in Montana and British Columbia. This report describes that modeling framework, provides an example of how it can be applied, and outlines possible next steps for implementing the framework.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171130","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality","usgsCitation":"Jenni, K.E., Naftz, D.L., and Presser, T.S., 2017, Conceptual modeling framework to support development of site-specific selenium criteria for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada: U.S. Geological Survey Open-File Report 2017–1130, 14 p., https://doi.org/10.3133/ofr20171130.","productDescription":"Report: iv, 14 p.; Data Release","numberOfPages":"22","onlineOnly":"N","ipdsId":"IP-091389","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":346538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1130/coverthb.jpg"},{"id":346541,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F7ZP44C9","text":"USGS Data Release – ","description":"USGS Data Release","linkHelpText":"USGS Measurements of Dissolved and Suspended Particulate Material Selenium in Lake Koocanusa in the Vicinity of Libby Dam (MT), 2015–2016"},{"id":346539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1130/ofr20171130.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1130"}],"country":"Canada, United States","state":"British Columbia, Montana","otherGeospatial":" Lake Koocanusa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.98266601562499,\n 48.356249029540734\n ],\n [\n -114.8565673828125,\n 48.356249029540734\n ],\n [\n -114.8565673828125,\n 50.42601852427907\n ],\n [\n -115.98266601562499,\n 50.42601852427907\n ],\n [\n -115.98266601562499,\n 48.356249029540734\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency‐specific purposes, collectively these efforts constitute a massive distributed sensing array that generates an untapped wealth of data. Using the framework provided by the National Hydrography Dataset, we organized temperature records from dozens of agencies in the western U.S. to create the NorWeST database that hosts >220,000,000 temperature recordings from >22,700 stream and river sites. Spatial‐stream‐network models were fit to a subset of those data that described mean August water temperatures (AugTw) during 63,641 monitoring site‐years to develop accurate temperature models (r2 = 0.91; RMSPE = 1.10°C; MAPE = 0.72°C), assess covariate effects, and make predictions at 1 km intervals to create summer climate scenarios. AugTw averaged 14.2°C (SD = 4.0°C) during the baseline period of 1993–2011 in 343,000 km of western perennial streams but trend reconstructions also indicated warming had occurred at the rate of 0.17°C/decade (SD = 0.067°C/decade) during the 40 year period of 1976–2015. Future scenarios suggest continued warming, although variation will occur within and among river networks due to differences in local climate forcing and stream responsiveness. NorWeST scenarios and data are available online in user‐friendly digital formats and are widely used to coordinate monitoring efforts among agencies, for new research, and for conservation planning.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR020969","usgsCitation":"Isaak, D.J., Wenger, S.J., Peterson, E.E., Ver Hoef, J.M., Nagel, D., Luce, C.H., Hostetler, S.W., Dunham, J.B., Roper, B.B., Wollrab, S., Chandler, G.L., Horan, D., and Parkes-Payne, S., 2017, The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams: Water Resources Research, v. 53, no. 11, p. 9181-9205, https://doi.org/10.1002/2017WR020969.","productDescription":"25 p.","startPage":"9181","endPage":"9205","ipdsId":"IP-090157","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020969","text":"Publisher Index Page"},{"id":365806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-104.053249,41.001406],[-102.124972,41.002338],[-102.051292,40.749591],[-102.04192,37.035083],[-102.979613,36.998549],[-103.002247,36.911587],[-103.064423,32.000518],[-106.565142,32.000736],[-106.577244,31.810406],[-106.750547,31.783706],[-108.208394,31.783599],[-108.208573,31.333395],[-111.000643,31.332177],[-114.813613,32.494277],[-114.722746,32.713071],[-117.118868,32.534706],[-117.50565,33.334063],[-118.088896,33.729817],[-118.428407,33.774715],[-118.519514,34.027509],[-119.159554,34.119653],[-119.616862,34.420995],[-120.441975,34.451512],[-120.608355,34.556656],[-120.644311,35.139616],[-120.873046,35.225688],[-120.884757,35.430196],[-121.851967,36.277831],[-121.932508,36.559935],[-121.788278,36.803994],[-121.880167,36.950151],[-122.140578,36.97495],[-122.419113,37.24147],[-122.511983,37.77113],[-122.425942,37.810979],[-122.168449,37.504143],[-122.144396,37.581866],[-122.385908,37.908136],[-122.301804,38.105142],[-122.484411,38.11496],[-122.492474,37.82484],[-122.972378,38.020247],[-123.103706,38.415541],[-123.725367,38.917438],[-123.851714,39.832041],[-124.373599,40.392923],[-124.063076,41.439579],[-124.536073,42.814175],[-124.150267,43.91085],[-123.962887,45.280218],[-123.996766,46.20399],[-123.548194,46.248245],[-124.029924,46.308312],[-124.06842,46.601397],[-123.97083,46.47537],[-123.84621,46.716795],[-124.022413,46.708973],[-124.108078,46.836388],[-123.86018,46.948556],[-124.138035,46.970959],[-124.425195,47.738434],[-124.672427,47.964414],[-124.727022,48.371101],[-123.981032,48.164761],[-122.748911,48.117026],[-122.637425,47.889945],[-123.15598,47.355745],[-122.527593,47.905882],[-122.578211,47.254804],[-122.725738,47.33047],[-122.691771,47.141958],[-122.796646,47.341654],[-122.863732,47.270221],[-122.67813,47.103866],[-122.364168,47.335953],[-122.429841,47.658919],[-122.230046,47.970917],[-122.425572,48.232887],[-122.358375,48.056133],[-122.512031,48.133931],[-122.424102,48.334346],[-122.689121,48.476849],[-122.425271,48.599522],[-122.796887,48.975026],[-104.048736,48.999877],[-104.053249,41.001406]]],[[[-119.789798,34.05726],[-119.5667,34.053452],[-119.795938,33.962929],[-119.916216,34.058351],[-119.789798,34.05726]]],[[[-118.524531,32.895488],[-118.573522,32.969183],[-118.369984,32.839273],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.32446,33.348782],[-118.593969,33.467198],[-118.500212,33.449592]]],[[[-122.519535,48.288314],[-122.66921,48.240614],[-122.400628,48.036563],[-122.419274,47.912125],[-122.744612,48.20965],[-122.664928,48.374823],[-122.519535,48.288314]]],[[[-122.800217,48.60169],[-122.883759,48.418793],[-123.173061,48.579086],[-122.949116,48.693398],[-122.743049,48.661991],[-122.800217,48.60169]]]]},\"properties\":{\"name\":\"Arizona\",\"nation\":\"USA \"}}]}","volume":"53","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Isaak, Daniel J.","contributorId":177835,"corporation":false,"usgs":false,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":766575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wenger, Seth J.","contributorId":64786,"corporation":false,"usgs":true,"family":"Wenger","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":766576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Erin E.","contributorId":177839,"corporation":false,"usgs":false,"family":"Peterson","given":"Erin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":766577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ver Hoef, Jay M","contributorId":217318,"corporation":false,"usgs":false,"family":"Ver Hoef","given":"Jay","email":"","middleInitial":"M","affiliations":[{"id":39604,"text":"NOAA-NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":766578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagel, David E","contributorId":217319,"corporation":false,"usgs":false,"family":"Nagel","given":"David E","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luce, Charlie H.","contributorId":173471,"corporation":false,"usgs":false,"family":"Luce","given":"Charlie","email":"","middleInitial":"H.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":766580,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":766581,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":766574,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roper, Brett B.","contributorId":120701,"corporation":false,"usgs":false,"family":"Roper","given":"Brett","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":766582,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wollrab, Sherry P","contributorId":217320,"corporation":false,"usgs":false,"family":"Wollrab","given":"Sherry P","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766583,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Chandler, Gwynne L","contributorId":217321,"corporation":false,"usgs":false,"family":"Chandler","given":"Gwynne","email":"","middleInitial":"L","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766584,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Horan, Dona L","contributorId":217322,"corporation":false,"usgs":false,"family":"Horan","given":"Dona L","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766585,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Parkes-Payne, Sharon","contributorId":217323,"corporation":false,"usgs":false,"family":"Parkes-Payne","given":"Sharon","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766586,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70191492,"text":"70191492 - 2017 - Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest","interactions":[],"lastModifiedDate":"2022-11-02T13:53:22.124712","indexId":"70191492","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest","title":"Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest","docAbstract":"Although floodplains are thought to serve as important buffers against nitrogen (N) transport to aquatic systems, frequent flooding and high levels of nutrient availability also make these systems prone to invasion by exotic plant species. Invasive plants could modify the cycling and availability of nutrients within floodplains, with effects that could feedback to promote the persistence of the invasive species and impact N export to riverine and coastal areas. We examined the effect of flooding on soil properties and N cycling at a floodplain site in Pool 8 of the Upper Mississippi River with 2 plant communities: mature native forest (Acer saccharinum) and patches of an invasive grass (Phalaris arundinacea). Plots were established within each vegetation type along an elevation gradient and sampled throughout the summers of 2013 and 2014. Spatial trends in flooding resulted in higher soil organic matter, porosity, and total nitrogen and carbon in low elevations. Nutrient processes and NH4+ and NO3− availability, however, were best explained by vegetation type and time after flooding. Phalaris plots maintained higher rates of nitrification and higher concentrations of available NH4+ and NO3−. These results suggest that invasion by Phalarismay make nitrogen more readily available and could help to reinforce this species' persistence in floodplain wetlands. They also raise the possibility that Phalaris may decrease floodplain N storage capacity and influence downstream transport of N to coastal zones.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1877","usgsCitation":"Swanson, W., De Jager, N.R., Strauss, E.A., and Thomsen, M., 2017, Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest: Ecohydrology, v. 10, no. 7, e1877; 12 p., https://doi.org/10.1002/eco.1877.","productDescription":"e1877; 12 p.","ipdsId":"IP-076663","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.2547981144141,\n 43.78463269677704\n ],\n [\n -91.2547981144141,\n 43.674577852975204\n ],\n [\n -91.18842801676165,\n 43.674577852975204\n ],\n [\n -91.18842801676165,\n 43.78463269677704\n ],\n [\n -91.2547981144141,\n 43.78463269677704\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"7","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-05","publicationStatus":"PW","scienceBaseUri":"59e5c51ae4b05fe04cd1c9c8","contributors":{"authors":[{"text":"Swanson, Whitney","contributorId":194558,"corporation":false,"usgs":false,"family":"Swanson","given":"Whitney","affiliations":[],"preferred":false,"id":712432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strauss, Eric A.","contributorId":190148,"corporation":false,"usgs":false,"family":"Strauss","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomsen, Meredith","contributorId":197064,"corporation":false,"usgs":false,"family":"Thomsen","given":"Meredith","affiliations":[],"preferred":false,"id":712434,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191491,"text":"70191491 - 2017 - Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River","interactions":[],"lastModifiedDate":"2017-10-16T10:09:52","indexId":"70191491","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River","docAbstract":"Dams are a conservation threat because they function as barriers to native fish movement; however, they may prevent the spread of invasive species. Invasive bigheaded carps (Hypophthalmichthys spp.) threaten the Great Lakes ecosystem and are advancing towards Lake Michigan via the Illinois River. Navigation dams on the Illinois River may deter bigheaded carps' upstream movement. We investigated the permeability of the Starved Rock Lock and Dam (SRLD), the most downstream gated Illinois River dam, to bigheaded carps' migration by examining the timing of individuals approaching and passing through SRLD in relation to gate openness, tailwater elevation, and water temperature. Using acoustic telemetry of (N = ~104 per year) tagged fish, 13 upstream passages of bigheaded carps occurred through SRLD between 2013 and 2016. Eleven passages occurred through the dam gates and 2 through the lock chamber, indicating deterrents (e.g., CO2) placed in SRLD lock chamber may only limit passage of a small proportion of all fish passing through the lock-and-dam structure. Passages were documented only in 2013 and 2015. Most of the dam gate passages occurred during high water when gates were completely out of the water. Timing of bigheaded carps approaching SRLD was positively correlated with rising water temperature and high tailwater elevation, and all fish approached during late March through mid-September. Movement through dams is rare; modifying gate operations to reduce gate openness during late spring and summer could further reduce the permeability of gated dams such as SRLD to bigheaded carps, slowing their upstream advance.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3180","usgsCitation":"Lubejko, M., Whitledge, G., Coulter, A.A., Brey, M.K., Oliver, D., and Garvey, J.E., 2017, Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River: River Research and Applications, v. 33, no. 8, p. 1268-1278, https://doi.org/10.1002/rra.3180.","productDescription":"11 p.","startPage":"1268","endPage":"1278","ipdsId":"IP-084443","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River, Starved Rock Lock and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.04041290283203,\n 41.308502890261764\n ],\n [\n -88.94634246826172,\n 41.308502890261764\n ],\n [\n -88.94634246826172,\n 41.333513657873205\n ],\n [\n -89.04041290283203,\n 41.333513657873205\n ],\n [\n -89.04041290283203,\n 41.308502890261764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"8","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-21","publicationStatus":"PW","scienceBaseUri":"59e5c51ae4b05fe04cd1c9ca","contributors":{"authors":[{"text":"Lubejko, Matthew","contributorId":195897,"corporation":false,"usgs":false,"family":"Lubejko","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":712426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitledge, Greg","contributorId":195898,"corporation":false,"usgs":false,"family":"Whitledge","given":"Greg","affiliations":[],"preferred":false,"id":712427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coulter, Alison A.","contributorId":187652,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oliver, Devon","contributorId":195899,"corporation":false,"usgs":false,"family":"Oliver","given":"Devon","affiliations":[],"preferred":false,"id":712429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garvey, James E.","contributorId":178007,"corporation":false,"usgs":false,"family":"Garvey","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":712430,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192246,"text":"70192246 - 2017 - Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment","interactions":[],"lastModifiedDate":"2017-10-25T10:54:04","indexId":"70192246","displayToPublicDate":"2017-10-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment","docAbstract":"Hydrologic recovery after wildfire is critical for restoring the ecosystem services of protecting of human lives and infrastructure from hazards and delivering water supply of sufficient quality and quantity. Recovery of soil-hydraulic properties, such as field-saturated hydraulic conductivity (Kfs), is a key factor for assessing the duration of watershed-scale flash flood and debris flow risks after wildfire. Despite the crucial role of Kfs in parameterizing numerical hydrologic models to predict the magnitude of postwildfire run-off and erosion, existing quantitative relations to predict Kfsrecovery with time since wildfire are lacking. Here, we conduct meta-analyses of 5 datasets from the literature that measure or estimate Kfs with time since wildfire for longer than 3-year duration. The meta-analyses focus on fitting 2 quantitative relations (linear and non-linear logistic) to explain trends in Kfs temporal recovery. The 2 relations adequately described temporal recovery except for 1 site where macropore flow dominated infiltration and Kfs recovery. This work also suggests that Kfs can have low hydrologic resistance (large postfire changes), and moderate to high hydrologic stability (recovery time relative to disturbance recurrence interval) and resilience (recovery of hydrologic function and provision of ecosystem services). Future Kfs relations could more explicitly incorporate processes such as soil-water repellency, ground cover and soil structure regeneration, macropore recovery, and vegetation regrowth.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11288","usgsCitation":"Ebel, B.A., and Martin, D.A., 2017, Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment: Hydrological Processes, v. 31, no. 21, p. 3682-3696, https://doi.org/10.1002/hyp.11288.","productDescription":"15 p.","startPage":"3682","endPage":"3696","ipdsId":"IP-084869","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":347327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"21","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-30","publicationStatus":"PW","scienceBaseUri":"59f1a2a4e4b0220bbd9d9f34","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":714985,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193775,"text":"70193775 - 2017 - Sex difference in PCB concentrations of a catostomid fish","interactions":[],"lastModifiedDate":"2025-05-21T14:43:00.473932","indexId":"70193775","displayToPublicDate":"2017-10-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5543,"text":"Journal of Environmental & Analytical Toxicology","onlineIssn":"2161-0525","active":true,"publicationSubtype":{"id":10}},"title":"Sex difference in PCB concentrations of a catostomid fish","docAbstract":"Unraveling the complexities associated with the relative differences in contaminant concentrations between the sexes of mature fish may provide insights into important behavioral and physiological differences between the sexes of not just fish but higher vertebrates as well. Whole-fish polychlorinated biphenyl (PCB) concentrations were determined in 25 mature female white suckers (Catostomus commersoni) and 26 mature male white suckers caught during their spawning run in the Kewaunee River, a tributary to Lake Michigan. Total length and weight were measured for each fish, and age of each fish was estimated from thin-sectioned otoliths. PCB concentration significantly increased with increasing total length, weight, and age. Consequently, three analysis of covariance (ANCOVA) models were fitted to the data to assess the effect of sex on white sucker PCB concentration. Based on model averaging, estimates of mean PCB concentrations in female and male white suckers were 185 and 219 ng/g, respectively. Thus, males were 18% greater in PCB concentration than females. We conclude that this difference between the sexes was most likely mainly driven by a higher rate of energy expenditure in males compared with females. Greater energy expenditure, owing to greater swimming activity and a higher resting metabolic rate, resulted in a higher rate of food consumption, which in turn led to a greater rate of PCB accumulation. Higher whole-fish PCB concentration in males compared with females has now been shown in nine different fish species. Our study represented the first documentation of this type of sex difference in a catostomid fish.
","language":"English","publisher":"OMICS International","doi":"10.4172/2161-0525.1000515","usgsCitation":"Madenjian, C.P., Stevens, A.L., Stapanian, M.A., Batterman, S.A., Chernyak, S.M., Menczer, J.E., and McIntyre, P.B., 2017, Sex difference in PCB concentrations of a catostomid fish: Journal of Environmental & Analytical Toxicology, v. 7, no. 6, 1000515, 6 p., https://doi.org/10.4172/2161-0525.1000515.","productDescription":"1000515, 6 p.","ipdsId":"IP-090486","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":348466,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":469441,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4172/2161-0525.1000515","text":"Publisher Index Page"}],"country":"United States","otherGeospatial":"Kewaunee River, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.55987644195555,\n 44.454981738717876\n ],\n [\n -87.53923416137695,\n 44.454981738717876\n ],\n [\n -87.53923416137695,\n 44.46380338011975\n ],\n [\n -87.55987644195555,\n 44.46380338011975\n ],\n [\n -87.55987644195555,\n 44.454981738717876\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425b3e4b0dc0b45b4531a","contributors":{"authors":[{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":720379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Andrew L.","contributorId":199914,"corporation":false,"usgs":false,"family":"Stevens","given":"Andrew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":720380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":720385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batterman, Stuart A.","contributorId":199915,"corporation":false,"usgs":false,"family":"Batterman","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chernyak, Sergei M.","contributorId":199916,"corporation":false,"usgs":false,"family":"Chernyak","given":"Sergei","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":720382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Menczer, Jordan E.","contributorId":199917,"corporation":false,"usgs":false,"family":"Menczer","given":"Jordan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":720383,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McIntyre, Peter B.","contributorId":166828,"corporation":false,"usgs":false,"family":"McIntyre","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":24540,"text":"Center for Limnology, University of Wisconsin, Madison, Wisconsin, 53706, USA.","active":true,"usgs":false}],"preferred":false,"id":720384,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204370,"text":"70204370 - 2017 - Viability analysis for multiple populations","interactions":[],"lastModifiedDate":"2019-07-22T13:39:20","indexId":"70204370","displayToPublicDate":"2017-10-13T13:35:43","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Viability analysis for multiple populations","docAbstract":"Many species of conservation interest exist solely or largely in isolated populations. Ideally, prioritization of management actions among such populations would be guided by quantitative estimates of extinction risk, but conventional methods of demographic population viability analysis (PVA) model each population separately and require temporally extensive datasets that are rarely available in practice. We introduce a general class of statistical PVA that can be applied to many populations at once, which we term multiple population viability analysis or MPVA. The approach combines models of abundance at multiple spatial locations with temporal models of population dynamics, effectively borrowing information from more data-rich populations to inform inferences for data-poor populations. Covariates are used to explain population variability in space and time. Using Bayesian analysis, we illustrate the method with a dataset of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) observations that previously had been analyzed with conventional PVA. We find that MPVA predictions are similar in bias and higher in precision than predictions from simple PVA models that treat each population individually; moreover, the use of covariates in MPVA allows for predictions in minimally-sampled and unsampled populations. The basic MPVA model can be extended in multiple ways, such as by linking to a sampling and observation model to provide a full accounting of uncertainty. We conclude that the approach has great potential to expand the use of PVA for species that exist in multiple, isolated populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2017.10.006","usgsCitation":"Wenger, S.J., Leasure, D.R., Dauwalter, D.C., Peacock, M.M., Dunham, J.B., Chelgren, N., and Neville, H.M., 2017, Viability analysis for multiple populations: Biological Conservation, v. 216, p. 69-77, https://doi.org/10.1016/j.biocon.2017.10.006.","productDescription":"9 p.","startPage":"69","endPage":"77","ipdsId":"IP-090218","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":365804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"216","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wenger, Seth J.","contributorId":64786,"corporation":false,"usgs":true,"family":"Wenger","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":766568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leasure, Douglas R.","contributorId":145643,"corporation":false,"usgs":false,"family":"Leasure","given":"Douglas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":766569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dauwalter, Daniel C.","contributorId":214339,"corporation":false,"usgs":false,"family":"Dauwalter","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":766570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peacock, Mary M.","contributorId":167605,"corporation":false,"usgs":false,"family":"Peacock","given":"Mary","email":"","middleInitial":"M.","affiliations":[{"id":24774,"text":"Department of Natural Resources, College of Agriculture and Life","active":true,"usgs":false}],"preferred":false,"id":766571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":766567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":766573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neville, Helen M.","contributorId":214338,"corporation":false,"usgs":false,"family":"Neville","given":"Helen","email":"","middleInitial":"M.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":766572,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190439,"text":"sir20175085 - 2017 - Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Barbour Pointe, Chatham County, Georgia","interactions":[],"lastModifiedDate":"2017-10-26T15:49:51","indexId":"sir20175085","displayToPublicDate":"2017-10-13T03:00:00","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":"2017-5085","title":"Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Barbour Pointe, Chatham County, Georgia","docAbstract":"Steady-state simulations using a revised regional groundwater-flow model based on MODFLOW were run to assess the potential long-term effects on the Upper Floridan aquifer (UFA) of pumping the Lower Floridan aquifer (LFA) at well 36Q398, located at Barbour Pointe in coastal Georgia near Savannah. Simulated pumping of well 36Q398 at a rate of 750 gallons per minute (gal/min; or 1.08 million gallons per day [Mgal/d]) indicated a maximum drawdown of about 2.19 feet (ft) in the UFA directly above the pumped well and at least 1 ft of drawdown within a nearly 190-square-mile area (scenario A). Induced vertical leakage from the UFA provided about 98 percent of the water to the pumped well. Simulated pumping of well 36Q398 caused increased downward leakage in all layers above the LFA, decreased upward leakage in all layers above the LFA, increased inflow to and decreased outflow from lateral specified-head boundaries in the UFA and LFA, and an increase in the volume of induced inflow from the general-head boundary representing outcrop units. Water budgets for scenario A indicated that changes in inflows and outflows through general-head boundaries would compose about 45 percent of the simulated pumpage from well 36Q398, with the remaining 55 percent of the pumped water derived from flow across lateral specified-head boundaries.
Additional steady-state simulations were run to evaluate a pumping rate in the UFA of 240 gal/min (0.346 Mgal/d), which would produce an equivalent maximum drawdown in the UFA as pumping from well 36Q398 in the LFA at a rate of 750 gal/min (called the “drawdown offset”; scenario B). Simulated pumping in the UFA for the drawdown offset produced about 2.18 ft of drawdown, comparable to 2.19 ft of drawdown in the UFA simulated in scenario A. Water budgets for scenario B also provided favorable comparisons with scenario A, indicating that 42 percent of the drawdown-offset pumpage (0.346 Mgal/d) in the UFA originates as increased inflow and decreased outflow across general-head boundaries from overlying units in the surficial and Brunswick aquifer systems and that the remaining simulated pumpage originates as flow across general- and specified-head boundaries within the UFA and LFA.
The revised model was evaluated for sensitivity by first altering horizontal and vertical hydraulic conductivity in the Lower Floridan semiconfining unit and then adjusting horizontal and vertical hydraulic conductivity in the LFA to match the 35.6 ft of drawdown at pumping well 36Q398. These adjustments also affected the maximum simulated drawdown in the UFA and the equivalent offset pumping in the UFA that would produce the same amount of drawdown. The maximum drawdown in the UFA ranged from 1.82 to 2.57 ft and the equivalent offset pumping in the UFA ranged from 199 to 278 gal/min.
The revised model reasonably depicts changes in groundwater levels resulting from pumping the LFA at Barbour Pointe at a rate of 750 gal/min. Results are limited, however, by the same model assumptions and design as the original model, and placement of boundaries and type of boundary used exert the greatest control on overall groundwater flow and interaquifer leakage in the system. Simulation results have improved regional characterization of the Floridan aquifer system, which could be used by State officials in evaluating requests for groundwater withdrawal from the LFA.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175085","collaboration":"Prepared in cooperation with Consolidated Utilities LLC","usgsCitation":"Cherry, G.S., and Clarke, J.S., 2017, Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Barbour Pointe, Chatham County, Georgia: U.S. Geological Survey Scientific Investigations Report 2017–5085, 34 p., https://doi.org/10.3133/sir20175085.","productDescription":"Report: vi, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-045187","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":346501,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5085/sir20175085.pdf","text":"Report","description":"SIR 2017-5085"},{"id":346500,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5085/coverthb.jpg"},{"id":346502,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VH5KZ1","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW grid for simulations used to evaluate the potential effect of Lower Floridan aquifer groundwater pumpage on the Upper Floridan aquifer at Barbour Pointe community in Chatham County, Georgia"}],"country":"United States","state":"Georgia","county":"Chatham County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.3922119140625,\n 32.09595459833164\n ],\n [\n -81.13883972167969,\n 31.717654042594468\n ],\n [\n -80.82847595214842,\n 32.02146689475617\n ],\n [\n -81.17729187011719,\n 32.24823229303316\n ],\n [\n -81.3922119140625,\n 32.09595459833164\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Recent efforts to advance river connectivity for the Millstone River watershed in New Jersey have led to the evaluation of a low-flow gauging weir that spans the full width of the river. The methods and results of a desktop modelling exercise were used to evaluate the potential ability of three anadromous fish species (Alosa sapidissima [American shad], Alosa pseudoharengus [alewife], and Alosa aestivalis [blueback herring]) to pass upstream over the U.S. Geological Survey Blackwells Mills streamgage (01402000) and weir on the Millstone River, New Jersey, at various streamflows, and to estimate the probability that the weir will be passable during the spring migratory season.
Based on data from daily fishway counts downstream from the Blackwells Mills streamgage and weir between 1996 and 2014, the general migratory period was defined as April 14 to May 28. Recorded water levels and flow data were used to theoretically estimate water depths and velocities over the weir, as well as flow exceedances occurring during the migratory period.
Results indicate that the weir is a potential depth barrier to fish passage when streamflows are below 200 cubic feet per second using a 1-body-depth criterion for American shad (the largest fish among the target species). Streamflows in that range occur on average 35 percent of the time during the migratory period. An increase of the depth criterion to 2 body depths causes the weir to become a possible barrier to passage when flows are below 400 cubic feet per second. Streamflows in that range occur on average 73 percent of the time during the migration season. Average cross-sectional velocities at several points along the weir do not seem to be limiting to the fish migration, but maximum theoretical velocities estimated without friction loss over the face of the weir could be potentially limiting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175103","usgsCitation":"Haro, Alex, Mulligan, Kevin, Suro, T.P., Noreika, John, and McHugh, Amy, 2017, Hydraulic and biological analysis of the passability of select fish species at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017–5103, 15 p., https://doi.org/10.3133/sir20175103.","productDescription":"viii, 15 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-082637","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":346487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5103/coverthb.jpg"},{"id":346491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5103/sir20175103.pdf","text":"Report","size":"3.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5103"}],"country":"United States","state":"New Jersey","otherGeospatial":"Millstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.66995239257812,\n 40.45060475430765\n ],\n [\n -74.48867797851562,\n 40.45060475430765\n ],\n [\n -74.48867797851562,\n 40.567545853080496\n ],\n [\n -74.66995239257812,\n 40.567545853080496\n ],\n [\n -74.66995239257812,\n 40.45060475430765\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Email: gs_nea_lsc_publications@usgs.gov
The shortgrass steppe (SGS) occupies the southwestern part of the Great Plains. Half of the land is cultivated, but significant areas remain under natural vegetation. Despite previous studies of the SGS carbon cycle, not all aspects have been completely addressed, including gross productivity, ecosystem respiration, and ecophysiological parameters. Our analysis of 1998 − 2007 flux tower measurements at five Bowen ratio–energy balance (BREB) and three eddy covariance (EC) sites characterized seasonal and interannual variability of gross photosynthesis and ecosystem respiration. Identification of the nonrectangular hyperbolic equation for the diurnal CO2 exchange, with vapor pressure deficit (VPD) limitation and exponential temperature response, quantified quantum yield α, photosynthetic capacity Amax, and respiration rate rd with variation ranges (19 \\< α \\< 51 mmol mol− 1, 0.48 \\< Amax \\< 2.1 mg CO2 m− 2 s− 1, 0.15 \\< rd \\< 0.49 mg CO2 m− 2 s− 1). Gross photosynthesis varied from 1 100 to 2 700 g CO2 m− 2 yr− 1, respiration from 900 to 3,000 g CO2 m− 2 yr− 1, and net ecosystem production from − 900 to + 700 g CO2 m− 2 yr− 1, indicating that SGS may switch from a sink to a source depending on weather. Comparison of the 2004 − 2006 measurements at two BREB and two parallel EC flux towers located at comparable SGS sites showed moderately higher photosynthesis, lower respiration, and higher net production at the BREB than EC sites. However, the difference was not related only to methodologies, as the normalized difference vegetation index at the BREB sites was higher than at the EC sites. Overall magnitudes and seasonal patterns at the BREB and the EC sites during the 3-yr period were similar, with trajectories within the ± 1.5 standard deviation around the mean of the four sites and mostly reflecting the effects of meteorology.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2017.06.007","usgsCitation":"Gilmanov, T.G., Morgan, J.A., Hanan, N., Wylie, B.K., Rajan, N., Smith, D.P., and Howard, D., 2017, Productivity and CO2 exchange of Great Plains ecoregions. I. Shortgrass steppe: Flux tower estimates: Rangeland Ecology and Management, v. 70, no. 6, p. 700-717, https://doi.org/10.1016/j.rama.2017.06.007.","productDescription":"18 p.","startPage":"700","endPage":"717","ipdsId":"IP-063726","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":461387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2017.06.007","text":"Publisher Index Page"},{"id":346604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105,\n 40.6667\n ],\n [\n -104.1667,\n 40.6667\n ],\n [\n -104.1667,\n 41.1667\n ],\n [\n -105,\n 41.1667\n ],\n [\n -105,\n 40.6667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"70","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e1d095e4b05fe04cd11798","contributors":{"authors":[{"text":"Gilmanov, Tagir G.","contributorId":82162,"corporation":false,"usgs":true,"family":"Gilmanov","given":"Tagir","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":712415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Jack A.","contributorId":66982,"corporation":false,"usgs":true,"family":"Morgan","given":"Jack","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanan, Niall P.","contributorId":86667,"corporation":false,"usgs":true,"family":"Hanan","given":"Niall P.","affiliations":[],"preferred":false,"id":712417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":712414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rajan, Nithya","contributorId":197061,"corporation":false,"usgs":false,"family":"Rajan","given":"Nithya","email":"","affiliations":[],"preferred":false,"id":712418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, David P.","contributorId":197062,"corporation":false,"usgs":false,"family":"Smith","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":712419,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Howard, Daniel M. 0000-0002-7563-7538 dhoward@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":4431,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel M.","email":"dhoward@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":712420,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70191459,"text":"70191459 - 2017 - Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise","interactions":[],"lastModifiedDate":"2017-10-13T10:57:57","indexId":"70191459","displayToPublicDate":"2017-10-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise","title":"Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise","docAbstract":"Global sea level rise (SLR) will significantly alter\ncoastal landscapes through inundation and erosion of lowlying\nareas. Animals that display area fidelity and rely on\nfringing coastal habitats during multiple life stages, such as\ndiamondback terrapins (Malaclemys terrapin Schoepff 1793),\nare likely to be particularly vulnerable to SLR-induced changes.\nWe used a combination of empirical nest survey data and\nresults from a regional SLR model to explore the long-term\navailability of known nesting locations and the modeled availability\nof fringing coastal habitats under multiple SLR scenarios\nfor diamondback terrapin in the MD portion of\nChesapeake Bay and the MD coastal bays. All SLR scenarios\nprojected the rapid inundation of historically used nesting locations\nof diamondback terrapins with 25%–55% loss within\nthe next 10 years and over 80% loss by the end of the century.\nModel trajectories of habitat losses or gains depended on habitat\ntype and location. A key foraging habitat, brackish marsh,\nwas projected to decline 6%–94%, with projections varying\nspatially and among scenarios. Despite predicted losses of\nextant beach habitats, future gains in beach habitat due to\nerosion and overwash were projected to reach 40%–600%.\nThese results demonstrate the potential vulnerability of diamondback terrapins to SLR in Chesapeake Bay and underscore\nthe possibility of compounding negative effects of SLR\non animals whose habitat requirements differ among life\nstages. More broadly, this study highlights the vulnerability\nof species dependent on fringing coastal habitats and emphasizes\nthe need for a long-term perspective for coastal development\nin the face of SLR.","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0209-2","usgsCitation":"Woodland, R.J., Rowe, C.L., and Henry, P.F., 2017, Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise: Estuaries and Coasts, v. 40, no. 5, p. 1502-1515, https://doi.org/10.1007/s12237-017-0209-2.","productDescription":"14 p.","startPage":"1502","endPage":"1515","ipdsId":"IP-077271","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":346567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.62139892578125,\n 37.88569271818349\n ],\n [\n -75.60516357421874,\n 37.88569271818349\n ],\n [\n -75.60516357421874,\n 39.612036199336956\n ],\n [\n -76.62139892578125,\n 39.612036199336956\n ],\n [\n -76.62139892578125,\n 37.88569271818349\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-11","publicationStatus":"PW","scienceBaseUri":"59e1d097e4b05fe04cd117a3","contributors":{"authors":[{"text":"Woodland, Ryan J.","contributorId":197043,"corporation":false,"usgs":false,"family":"Woodland","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowe, Christopher L.","contributorId":197044,"corporation":false,"usgs":false,"family":"Rowe","given":"Christopher","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":712366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Paula F. P. 0000-0002-7601-5546 phenry@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-5546","contributorId":4485,"corporation":false,"usgs":true,"family":"Henry","given":"Paula","email":"phenry@usgs.gov","middleInitial":"F. P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":712351,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189709,"text":"sir20175074 - 2017 - Estimation of the groundwater resources of the bedrock aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin","interactions":[],"lastModifiedDate":"2017-10-12T11:27:22","indexId":"sir20175074","displayToPublicDate":"2017-10-12T11:00:00","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":"2017-5074","title":"Estimation of the groundwater resources of the bedrock aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin","docAbstract":"Groundwater resources information was needed to understand regional aquifer systems and water available to wells and springs for rearing important Lake Michigan fish species at the Kettle Moraine Springs State Fish Hatchery in Sheboygan County, Wisconsin. As a basis for estimating the groundwater resources available, an existing groundwater-flow model was refined, and new groundwater-flow models were developed for the Kettle Moraine Springs State Fish Hatchery area using the U.S. Geological Survey (USGS) finite-difference code MODFLOW. This report describes the origin and construction of these groundwater-flow models and their use in testing conceptual models and simulating the hydrogeologic system.
The study area is in the Eastern Ridges and Lowlands geographical province of Wisconsin, and the hatchery property is situated on the southeastern edge of the Kettle Moraine, a north-south trending topographic high of glacial origin. The bedrock units underlying the study area consist of Cambrian, Ordovician, and Silurian units of carbonate and siliciclastic lithology. In the Sheboygan County area, the sedimentary bedrock sequence reaches a thickness of as much as about 1,600 feet (ft).
Two aquifer systems are present at the Kettle Moraine Springs State Fish Hatchery. A shallow system is made up of Silurian bedrock, consisting chiefly of dolomite, overlain by unconsolidated Quaternary-age glacial deposits. The glacial deposits of this aquifer system are the typical source of water to local springs, including the springs that have historically supplied the hatchery. The shallow aquifer system, therefore, consists of the unconsolidated glacial aquifer and the underlying bedrock Silurian aquifer. Most residential wells in the area draw from the Silurian aquifer. A deeper confined aquifer system is made up of Cambrian- and Ordovician-age bedrock units including sandstone formations. Because of its depth, very few wells are completed in the Cambrian-Ordovician aquifer system (COAS) near the Kettle Moraine Springs State Fish Hatchery.
Three groundwater-flow models were used to estimate the water resources available to the hatchery from bedrock aquifers under selected scenarios of well placement and seasonal water requirements and subject to constraints on the effects of pumping on neighboring wells, local springs, and creeks. Model input data (recharge, water withdrawal, and boundary conditions) for these models were compiled from a number of data and information sources.
The first model, named the “KMS model,” (KMS stands for Kettle Moraine Springs) is an inset model derived from a published USGS regional Lake Michigan Basin model and was constructed to simulate groundwater pumping from the semiconfined Silurian aquifer. The second model, named the “Pumping Test model,” was constructed to evaluate an aquifer pumping test conducted in the COAS as part of this project. The Pumping Test model was also used to simulate the local effects of 20 years of groundwater pumping from this deep bedrock aquifer for future hatchery operations. The third model, named the “LMB modified model,” is a version of the published Lake Michigan Basin (LMB) model that was modified with aquifer parameters refined in an area around the hatchery (approximately a 5-mile radius circle, corresponding to the area stressed by the aquifer pumping test). This LMB modified model was applied to evaluate regional effects of pumping from the confined COAS.
The available Silurian aquifer groundwater resource was estimated using the KMS model with three scenarios—named “AllConstraints,” “Constraints2,” and “Constraints3”—that specified local water-level and flow constraints such as drawdown at nearby household wells, water levels inside pumping well boreholes, and flow in local streams and springs. Each scenario utilized the MODFLOW Groundwater Management Process (GWM) to select three locations from six candidate locations that provided the greatest combined flow while satisfying the constraints. The three constraint scenarios provided estimates of 430 gallons per minute (gal/min), 480 gal/min, and 520 gal/min pumping from three wells—AllConstraints, Constraints2, and Constraints3, respectively. The same three wells were selected for the scenarios that estimated 480 gal/min and 520 gal/min; the scenario that estimated 430 gal/min shared two of these same wells, but the third selected well was different.
The available COAS groundwater resource was estimated by two scenarios with each conducted over a period of 20 years with the Pumping Test model and the LMB modified model. The Pumping Test model was used to simulate local effects of pumping, and the LMB modified model was used to simulate regional effects of pumping. The scenarios simulate a range of total and seasonal pumping rates potentially linked to site activities. Scenario 1 simulates two wells completed in the Cambrian-Ordovician aquifer system, each pumping for 8 months at 300 gal/min, followed by pumping for 4 months at 600 gal/min. The average yearly pumping rate of Scenario 1 is 800 gal/min. Scenario 2 simulates three wells completed in the Cambrian-Ordovician aquifer system pumping for 8 months at 200 gal/min, followed by pumping for 4 months at 500 gal/min. The average yearly pumping rate of Scenario 2 is 900 gal/min. The Pumping Test model simulations confirmed that drawdown in the boreholes of the pumping wells at the selected 2-well or 3-well rates will meet the desired condition that the pumping water level remains at least 100 ft above the highest Cambrian-Ordovician unit open to the well.
The LMB modified model was used to evaluate the regional drawdown of the pumping from the confined COAS under the same 2-well and 3-well scenarios. At the nearest known existing COAS well, Campbellsport production well #4, the simulated drawdown for Scenario 1 after 20 years of cyclical pumping with two pumping wells averaging a total of 800 gal/min is 16.9 ft, whereas the simulated drawdown for Scenario 2 after 20 years of pumping with three pumping wells averaging a total of 900 gal/min is 19.0 ft. The total deep aquifer thickness at the Campbellsport location is on the order of 620 ft, meaning that the simulated drawdown for either scenario is about 3 percent of the confined aquifer thickness.
The models developed as part of this project are archived in the project data release. The archive includes the model input and output files as well as MODFLOW source code and executables. (Haserodt and others, 2017).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175074","collaboration":"Prepared in cooperation with the Fisheries Management Program of the Wisconsin Department of Natural Resources","usgsCitation":"Dunning, C.P., Feinstein, D.T., Buchwald, C.A., Hunt, R.J., and Haserodt, M.J., 2017, Estimation of the groundwater resources of the bedrock aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2017–5074, 104 p., https://doi.org/10.3133/sir20175074.","productDescription":"Report: ix, 104 p.; Data Release","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-079387","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":346498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5074/sir20175074.pdf","text":"Report","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5074"},{"id":346497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5074/coverthb.jpg"},{"id":346499,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77S7KW2","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"GWM-2005, MODFLOW-2005, MODFLOW-NWT, and SEAWAT-2000 groundwater flow models of the Bedrock Aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin"}],"country":"United States","state":"Wisconsin","county":"Sheboygan County","otherGeospatial":"Kettle Moraine Springs State Fish Hatchery","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.0778,\n 43.5944\n ],\n [\n -88.0889,\n 43.5944\n ],\n [\n -88.0889,\n 43.6167\n ],\n [\n -88.0778,\n 43.6167\n ],\n [\n -88.0778,\n 43.5944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
This paper details how the United States Geological Survey (USGS) Community for Data Integration (CDI) Data Management Working Group developed a Science Data Lifecycle Model, and the role the Model plays in shaping agency-wide policies. Starting with an extensive literature review of existing data Lifecycle models, representatives from various backgrounds in USGS attended a two-day meeting where the basic elements for the Science Data Lifecycle Model were determined. Refinements and reviews spanned two years, leading to finalization of the model and documentation in a formal agency publication .
The Model serves as a critical framework for data management policy, instructional resources, and tools. The Model helps the USGS address both the Office of Science and Technology Policy (OSTP) for increased public access to federally funded research, and the Office of Management and Budget (OMB) 2013 Open Data directives, as the foundation for a series of agency policies related to data management planning, metadata development, data release procedures, and the long-term preservation of data. Additionally, the agency website devoted to data management instruction and best practices (www2.usgs.gov/datamanagement) is designed around the Model’s structure and concepts. This paper also illustrates how the Model is being used to develop tools for supporting USGS research and data management processes.
","language":"English","publisher":"University of Massachusetts","doi":"10.7191/jeslib.2017.1117","usgsCitation":"Faundeen, J., and Hutchison, V.B., 2017, The evolution, approval and implementation of the U.S. Geological Survey Science Data Lifecycle Model: Journal of eScience Librarianship, v. 6, no. 2, p. 1-10, https://doi.org/10.7191/jeslib.2017.1117.","productDescription":"e1117; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-076346","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469446,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7191/jeslib.2017.1117","text":"Publisher Index Page"},{"id":346546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-12","publicationStatus":"PW","scienceBaseUri":"59e07f2ee4b05fe04ccfcd02","contributors":{"authors":[{"text":"Faundeen, John 0000-0003-0287-2921 faundeen@usgs.gov","orcid":"https://orcid.org/0000-0003-0287-2921","contributorId":3097,"corporation":false,"usgs":true,"family":"Faundeen","given":"John","email":"faundeen@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":712269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 vhutchison@usgs.gov","orcid":"https://orcid.org/0000-0001-5301-3698","contributorId":173674,"corporation":false,"usgs":true,"family":"Hutchison","given":"Vivian","email":"vhutchison@usgs.gov","middleInitial":"B.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":712270,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191436,"text":"70191436 - 2017 - Source spectral properties of small-to-moderate earthquakes in southern Kansas","interactions":[],"lastModifiedDate":"2017-11-29T16:27:20","indexId":"70191436","displayToPublicDate":"2017-10-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Source spectral properties of small-to-moderate earthquakes in southern Kansas","docAbstract":"The source spectral properties of injection-induced earthquakes give insight into their nucleation, rupture processes, and influence on ground motion. Here we apply a spectral decomposition approach to analyze P-wave spectra and estimate Brune-type stress drop for more than 2000 ML1.5–5.2 earthquakes occurring in southern Kansas from 2014 to 2016. We find that these earthquakes are characterized by low stress drop values (median ∼0.4MPa) compared to natural seismicity in California. We observe a significant increase in stress drop as a function of depth, but the shallow depth distribution of these events is not by itself sufficient to explain their lower stress drop. Stress drop increases with magnitude from M1.5–M3.5, but this scaling trend may weaken above M4 and also depends on the assumed source model. Although we observe a nonstationary, sequence-specific temporal evolution in stress drop, we find no clear systematic relation with the activity of nearby injection wells.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014649","usgsCitation":"Trugman, D.T., Dougherty, S.L., Cochran, E.S., and Shearer, P.M., 2017, Source spectral properties of small-to-moderate earthquakes in southern Kansas: Journal of Geophysical Research B: Solid Earth, v. 122, no. 10, p. 8021-8034, https://doi.org/10.1002/2017JB014649.","productDescription":"14 p.","startPage":"8021","endPage":"8034","ipdsId":"IP-088045","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":346537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.1683349609375,\n 36.99816565700228\n ],\n [\n -97.46246337890625,\n 36.99816565700228\n ],\n [\n -97.46246337890625,\n 37.47485808497102\n ],\n [\n -98.1683349609375,\n 37.47485808497102\n ],\n [\n -98.1683349609375,\n 36.99816565700228\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-17","publicationStatus":"PW","scienceBaseUri":"59defbb2e4b05fe04ccd3d3b","contributors":{"authors":[{"text":"Trugman, Daniel T.","contributorId":197011,"corporation":false,"usgs":false,"family":"Trugman","given":"Daniel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":712247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dougherty, Sara L. 0000-0002-5327-3286 sdougherty@usgs.gov","orcid":"https://orcid.org/0000-0002-5327-3286","contributorId":191210,"corporation":false,"usgs":true,"family":"Dougherty","given":"Sara","email":"sdougherty@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shearer, Peter M.","contributorId":197012,"corporation":false,"usgs":false,"family":"Shearer","given":"Peter","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":712249,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191374,"text":"70191374 - 2017 - Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions","interactions":[],"lastModifiedDate":"2017-10-10T16:00:45","indexId":"70191374","displayToPublicDate":"2017-10-10T00:00:00","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":"Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions","docAbstract":"Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12562","usgsCitation":"Austin, S.H., and Nelms, D.L., 2017, Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions: Journal of the American Water Resources Association, v. 53, no. 5, p. 1133-1146, https://doi.org/10.1111/1752-1688.12562.","productDescription":"14 p.","startPage":"1133","endPage":"1146","ipdsId":"IP-069502","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":469450,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12562","text":"Publisher Index Page"},{"id":438190,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6H8H","text":"USGS data release","linkHelpText":"Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in 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States\"}}]}","volume":"53","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-28","publicationStatus":"PW","scienceBaseUri":"59dddc09e4b05fe04ccd05c6","contributors":{"authors":[{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":712131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelms, David L. 0000-0001-5747-642X dlnelms@usgs.gov","orcid":"https://orcid.org/0000-0001-5747-642X","contributorId":1892,"corporation":false,"usgs":true,"family":"Nelms","given":"David","email":"dlnelms@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712132,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191359,"text":"70191359 - 2017 - Smartphone technologies and Bayesian networks to assess shorebird habitat selection","interactions":[],"lastModifiedDate":"2018-01-05T14:28:23","indexId":"70191359","displayToPublicDate":"2017-10-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Smartphone technologies and Bayesian networks to assess shorebird habitat selection","docAbstract":"Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, >30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection from many locations and sources, which can be used in management and decision-making applications.
Crustal pathways connecting deep sources of melt and the active volcanoes they supply are poorly understood. Beneath Mounts St. Helens, Adams, and Rainier these pathways connect subduction-induced ascending melts to shallow magma reservoirs. Petrogenetic modeling predicts that when these melts are emplaced as a succession of sills into the lower crust they generate deep crustal hot zones. While these zones are increasingly recognized as a primary site for silicic differentiation at a range of volcanic settings globally, imaging them remains challenging. Near Mount Rainier, ascending melt has previously been imaged ~28 km northwest of the volcano, while to the south, the volcano lies on the margin of a broad conductive region in the deep crust. Using 3D full-waveform tomography, we reveal an expansive low-velocity zone, which we interpret as a possible hot zone, linking ascending melts and shallow reservoirs. This hot zone may supply evolved magmas to Mounts St. Helens and Adams, and possibly Rainier, and could contain approximately twice the melt volume as the total eruptive products of all three volcanoes combined. Hot zones like this may be the primary reservoirs for arc volcanism, influencing compositional variations and spatial-segmentation along the entire 1100 km-long Cascades Arc.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-017-07123-w","usgsCitation":"Flinders, A.F., and Shen, Y., 2017, Seismic evidence for a possible deep crustal hot zone beneath Southwest Washington: Scientific Reports, v. 7, Article 7400; 10 p., https://doi.org/10.1038/s41598-017-07123-w.","productDescription":"Article 7400; 10 p.","ipdsId":"IP-077970","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469452,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-07123-w","text":"Publisher Index Page"},{"id":346465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 46\n ],\n [\n -121,\n 46\n ],\n [\n -121,\n 47.4\n ],\n [\n -123,\n 47.4\n ],\n [\n -123,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-07","publicationStatus":"PW","scienceBaseUri":"59defbb3e4b05fe04ccd3d41","contributors":{"authors":[{"text":"Flinders, Ashton F. 0000-0003-2483-4635 aflinders@usgs.gov","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":196960,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"aflinders@usgs.gov","middleInitial":"F.","affiliations":[{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":712091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shen, Yang","contributorId":196961,"corporation":false,"usgs":false,"family":"Shen","given":"Yang","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":712092,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206814,"text":"70206814 - 2017 - Estimating daily lake evaporation from biweekly energy‐budget data","interactions":[],"lastModifiedDate":"2019-11-22T13:26:24","indexId":"70206814","displayToPublicDate":"2017-10-06T13:22:26","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Estimating daily lake evaporation from biweekly energy‐budget data","docAbstract":"Estimates of daily lake evaporation based on energy‐budget data are poor because of large\nerrors associated with quantifying change in lake heat storage over periods of less than about\n10 days. Energy‐budget evaporation was determined during approximately biweekly periods at\na northern Minnesota, USA, lake for 5 years. Various combinations of shortwave radiation, air\ntemperature, wind speed, lake‐surface temperature, and vapour‐pressure difference were\nrelated to energy‐budget evaporation using linear‐regression models in an effort to determine\ndaily evaporation without requiring the heat‐storage term. The model that combined the product\nof shortwave radiation and air temperature with the product of vapour‐pressure difference\nand wind speed provided the second best fit based on statistics but provided the best daily\ndata based on comparisons with evaporation determined with the eddy‐covariance method.\nBest‐model daily values ranged from −0.6 to 7.1 mm/day over a 5‐year period. Daily averages\nof best‐model evaporation and eddy‐covariance evaporation were nearly identical for all\n28 days of comparisons with a standard deviation of the differences between the two\nmethods of 0.68 mm/day. Best‐model daily evaporation also was compared with two other\nevaporation models, Jensen–Haise and a mass‐transfer model. Best‐model daily values were\nsubstantially improved relative to Jensen–Haise and mass‐transfer values when daily values\nwere summed over biweekly energy‐budget periods for comparison with energy‐budget\nresults.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11375","usgsCitation":"Andreasen, M., Rosenberry, D.O., and Stannard, D., 2017, Estimating daily lake evaporation from biweekly energy‐budget data: Hydrological Processes, v. 31, no. 25, p. 4530-4539, https://doi.org/10.1002/hyp.11375.","productDescription":"10 p.","startPage":"4530","endPage":"4539","ipdsId":"IP-051452","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":369472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.78955078125,\n 46.89023157359399\n ],\n [\n -92.21923828124999,\n 46.437856895024204\n ],\n [\n -89.3408203125,\n 48.03401915864286\n ],\n [\n -92.46093749999999,\n 48.63290858589535\n ],\n [\n -94.39453125,\n 48.80686346108517\n ],\n [\n -94.85595703125,\n 49.48240137826932\n ],\n [\n -95.33935546875,\n 49.48240137826932\n ],\n [\n -95.3173828125,\n 49.023461463214126\n ],\n [\n -97.3388671875,\n 49.081062364320736\n ],\n [\n -96.78955078125,\n 46.89023157359399\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"25","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Andreasen, Mie 0000-0002-5661-1359","orcid":"https://orcid.org/0000-0002-5661-1359","contributorId":220835,"corporation":false,"usgs":false,"family":"Andreasen","given":"Mie","email":"","affiliations":[{"id":40283,"text":"University of Copenhagen, Denmark","active":true,"usgs":false}],"preferred":false,"id":775879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","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":775878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stannard, David distanna@usgs.gov","contributorId":220836,"corporation":false,"usgs":true,"family":"Stannard","given":"David","email":"distanna@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":775880,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188270,"text":"tm6B8 - 2017 - Documentation of the dynamic parameter, water-use, stream and lake flow routing, and two summary output modules and updates to surface-depression storage simulation and initial conditions specification options with the Precipitation-Runoff Modeling System (PRMS)","interactions":[],"lastModifiedDate":"2017-10-05T11:31:16","indexId":"tm6B8","displayToPublicDate":"2017-10-05T09:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-B8","title":"Documentation of the dynamic parameter, water-use, stream and lake flow routing, and two summary output modules and updates to surface-depression storage simulation and initial conditions specification options with the Precipitation-Runoff Modeling System (PRMS)","docAbstract":"This report documents seven enhancements to the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS) hydrologic simulation code: two time-series input options, two new output options, and three updates of existing capabilities. The enhancements are (1) new dynamic parameter module, (2) new water-use module, (3) new Hydrologic Response Unit (HRU) summary output module, (4) new basin variables summary output module, (5) new stream and lake flow routing module, (6) update to surface-depression storage and flow simulation, and (7) update to the initial-conditions specification. This report relies heavily upon U.S. Geological Survey Techniques and Methods, book 6, chapter B7, which documents PRMS version 4 (PRMS-IV). A brief description of PRMS is included in this report.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Surface water in Book 6: Modeling techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B8","collaboration":"National Water Census, Water Availability and Use Science Program","usgsCitation":"Regan, R.S., and LaFontaine, J.H., 2017, Documentation of the dynamic parameter, water-use, stream and lake flow routing, and two summary output modules and updates to surface-depression storage simulation and initial conditions specification options with the Precipitation-Runoff Modeling System (PRMS): U.S. Geological Survey Techniques and Methods, book 6, chap. B8, 60 p., https://doi.org/10.3133/tm6B8.","productDescription":"Report: ix, 60 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075744","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":346255,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XG9PCF","text":"USGS data release","description":"USGS data release","linkHelpText":"Model Input and Output for Hydrologic Simulations of the Upper Chattahoochee River Basin that Demonstrate Enhancements to the Precipitation Runoff Modeling System"},{"id":346254,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/b8/tm6b8.pdf","text":"Report","size":"3.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-B8"},{"id":346253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/b8/coverthb.jpg"}],"publicComments":"This report is Chapter 8 of Section B: Surface water in Book 6: Modeling techniques","contact":"Director
U.S. Geological Survey, South Atlantic Water Science Center
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
(803) 750-6100
https://www.usgs.gov/centers/sa-water
Historically, thermoelectric water withdrawal has been estimated by the Energy Information Administration (EIA) and the U.S. Geological Survey's (USGS) water-use compilations. Recently, the USGS developed models for estimating withdrawal at thermoelectric plants to provide estimates independent from plant operator-reported withdrawal data. This article compares three federal datasets of thermoelectric withdrawals for the United States in 2010: one based on the USGS water-use compilation, another based on EIA data, and the third based on USGS model-estimated data. The withdrawal data varied widely. Many plants had three different withdrawal values, and for approximately 54% of the plants the largest withdrawal value was twice the smallest, or larger. The causes of discrepancies among withdrawal estimates included definitional differences, definitional noise, and various nondefinitional causes. The uncertainty in national totals can be characterized by the range among the three datasets, from 5,640 m3/s (129 billion gallons per day [bgd]) to 6,954 m3/s (158 bgd), or by the aggregate difference between the smallest and largest values at each plant, from 4,014 m3/s (92 bgd) to 8,590 m3/s (196 bgd). When used to assess the accuracy of reported values, the USGS model estimates identify plants that need to be reviewed.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12551","usgsCitation":"Harris, M.A., and Diehl, T.H., 2017, A comparison of three federal datasets for thermoelectric water withdrawals in the United States for 2010: Journal of the American Water Resources Association, v. 53, no. 5, p. 1062-1080, https://doi.org/10.1111/1752-1688.12551.","productDescription":"19 p.","startPage":"1062","endPage":"1080","ipdsId":"IP-072613","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":469458,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12551","text":"Publisher Index Page"},{"id":438193,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HX19VW","text":"USGS data release","linkHelpText":"Thermoelectric power plant water withdrawals and associated attributes for three Federal datasets in the United States, 2010"},{"id":346380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-09","publicationStatus":"PW","scienceBaseUri":"59d5f344e4b05fe04cc652c1","contributors":{"authors":[{"text":"Harris, Melissa A. 0000-0003-2659-9763 mharris@usgs.gov","orcid":"https://orcid.org/0000-0003-2659-9763","contributorId":1903,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","email":"mharris@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711925,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191326,"text":"70191326 - 2017 - Short-term and long-term evapotranspiration rates at ecological restoration sites along a large river receiving rare flow events","interactions":[],"lastModifiedDate":"2017-11-29T16:28:13","indexId":"70191326","displayToPublicDate":"2017-10-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Short-term and long-term evapotranspiration rates at ecological restoration sites along a large river receiving rare flow events","docAbstract":"Many large rivers around the world no longer flow to their deltas, due to ever greater water withdrawals and diversions for human needs. However, the importance of riparian ecosystems is drawing increasing recognition, leading to the allocation of environmental flows to restore river processes. Accurate estimates of riparian plant evapotranspiration (ET) are needed to understand how the riverine system responds to these rare events and achieve the goals of environmental flows. In 2014, historic environmental flows were released into the Lower Colorado River at Morelos Dam (Mexico); this once perennial but now dry reach is the final stretch to the mighty Colorado River Delta. One of the primary goals was to supply native vegetation restoration sites along the reach with water to help seedlings establish and boost groundwater levels to foster the planted saplings. Patterns in ET before, during, and after the flows are useful for evaluating whether this goal was met and understanding the role that ET plays in this now ephemeral river system. Here, diurnal fluctuations in groundwater levels and MODIS data were used to compare estimates of ET specifically at three native vegetation restoration sites during 2014 planned flow events, while MODIS data was used to evaluate long-term (2002 – 2016) ET responses to restoration efforts at these sites. Overall, ET was generally 0 - 10 mm d-1 across sites and although daily ET values from groundwater data were highly variable, weekly averaged estimates were highly correlated with MODIS-derived estimates at most sites. The influence of the 2014 flow events was not immediately apparent in the results, although the process of clearing vegetation and planting native vegetation at the restoration sites was clearly visible in the results.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11359","usgsCitation":"Shanafield, M., Jurado, H.G., Burgueno, J.E., Hernandez, J.R., Jarchow, C., and Nagler, P.L., 2017, Short-term and long-term evapotranspiration rates at ecological restoration sites along a large river receiving rare flow events: Hydrological Processes, v. 31, no. 24, p. 4328-4337, https://doi.org/10.1002/hyp.11359.","productDescription":"10 p.","startPage":"4328","endPage":"4337","ipdsId":"IP-068603","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11359","text":"Publisher Index Page"},{"id":346385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.08453369140625,\n 32.217448573031014\n ],\n [\n -114.63821411132812,\n 32.217448573031014\n ],\n [\n -114.63821411132812,\n 32.751477587458865\n ],\n [\n -115.08453369140625,\n 32.751477587458865\n ],\n [\n -115.08453369140625,\n 32.217448573031014\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"24","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-17","publicationStatus":"PW","scienceBaseUri":"59d5f342e4b05fe04cc652b8","contributors":{"authors":[{"text":"Shanafield, Margaret","contributorId":196916,"corporation":false,"usgs":false,"family":"Shanafield","given":"Margaret","email":"","affiliations":[],"preferred":false,"id":711930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurado, Hugo Gutierrez","contributorId":196917,"corporation":false,"usgs":false,"family":"Jurado","given":"Hugo","email":"","middleInitial":"Gutierrez","affiliations":[],"preferred":false,"id":711931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burgueno, Jesus Eliana Rodriguez","contributorId":196918,"corporation":false,"usgs":false,"family":"Burgueno","given":"Jesus","email":"","middleInitial":"Eliana Rodriguez","affiliations":[],"preferred":false,"id":711932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hernandez, Jorge Ramirez","contributorId":196919,"corporation":false,"usgs":false,"family":"Hernandez","given":"Jorge","email":"","middleInitial":"Ramirez","affiliations":[],"preferred":false,"id":711933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":711928,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":711927,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191322,"text":"70191322 - 2017 - Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.","interactions":[],"lastModifiedDate":"2017-12-11T13:37:05","indexId":"70191322","displayToPublicDate":"2017-10-04T00:00:00","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":"Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.","docAbstract":"We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater-level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness-of-fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month-to-month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low-threshold events. We identified challenges in deriving probabilistic-forecasting models and possible approaches for addressing those challenges.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12582","usgsCitation":"Dudley, R.W., Hodgkins, G.A., and Dickinson, J.E., 2017, Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.: Journal of the American Water Resources Association, v. 53, no. 6, p. 1424-1436, https://doi.org/10.1111/1752-1688.12582.","productDescription":"13 p.","startPage":"1424","endPage":"1436","ipdsId":"IP-071588","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":346381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-21","publicationStatus":"PW","scienceBaseUri":"59d5f344e4b05fe04cc652c7","contributors":{"authors":[{"text":"Dudley, Robert W. 0000-0002-0934-0568 rwdudley@usgs.gov","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":2223,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","email":"rwdudley@usgs.gov","middleInitial":"W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191273,"text":"70191273 - 2017 - Projected atoll shoreline and run-up changes in response to sea-level rise and varying large wave conditions at Wake and Midway Atolls, Northwestern Hawaiian Islands","interactions":[],"lastModifiedDate":"2017-10-03T09:57:18","indexId":"70191273","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Projected atoll shoreline and run-up changes in response to sea-level rise and varying large wave conditions at Wake and Midway Atolls, Northwestern Hawaiian Islands","docAbstract":"Atoll islands are dynamic features that respond to seasonal alterations in wave conditions and sea level. It is unclear how shoreline wave run-up and erosion patterns along these low elevation islands will respond to projected sea-level rise (SLR) and changes in wave climate over the next century, hindering communities' preparation for the future. To elucidate how these processes may respond to climate change, extreme boreal winter and summer wave conditions under future sea-level rise (SLR) and wave climate scenarios were simulated at two atolls, Wake and Midway, using a shallow-water hydrodynamic model. Nearshore wave conditions were used to compute the potential longshore sediment flux along island shorelines via the CERC empirical formula and wave-driven erosion was calculated as the divergence of the longshore drift; run-up and the locations where the run-up exceed the berm elevation were also determined. SLR is projected to predominantly drive future island morphological change and flooding. Seaward shorelines (i.e., ocean fronted shorelines directly facing incident wave energy) were projected to experience greater erosion and flooding with SLR and in hypothetical scenarios where changes to deep water wave directions were altered, as informed by previous climate change forced Pacific wave modeling efforts. These changes caused nearshore waves to become more shore-normal, increasing wave attack along previously protected shorelines. With SLR, leeward shorelines (i.e., an ocean facing shoreline but sheltered from incident wave energy) became more accretive on windward islands and marginally more erosive along leeward islands. These shorelines became more accretionary and subject to more flooding with nearshore waves becoming more shore-normal. Lagoon shorelines demonstrated the greatest SLR-driven increase in erosion and run-up. They exhibited the greatest relative change with increasing wave heights where both erosion and run-up magnitudes increased. Wider reef flat-fronted seaward shorelines became more accretive as all oceanographic forcing parameters increased in magnitude and exhibited large run-up increases following increasing wave heights. Island end shorelines became subject to increased flooding, erosion at Wake, and accretion at Midway with SLR. Under future conditions, windward and leeward islands are projected to become thinner as ocean facing and lagoonal shorelines erode, with leeward islands becoming more elongate. Island shorelines will change dramatically over the next century as SLR and altered wave climates drive new erosional regimes. It is vital to the sustainability of island communities that the relative magnitudes of these effects are addressed when planning for projected future climates.
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Advances in renewable energy will incur steep environmental costs to landscapes in which facilities are constructed and operated. Scientists – including those from academia, industry, and government agencies – have only recently begun to quantify trade-offs in this arena, often using ground-mounted, utility-scale solar energy facilities (USSE, ≥1 megawatt) as a model. Here, we discuss five critical ecological concepts applicable to the development of more sustainable USSE with benefits over fossil-fuel-generated energy: (1) more sustainable USSE development requires careful evaluation of trade-offs between land, energy, and ecology; (2) species responses to habitat modification by USSE vary; (3) cumulative and large-scale ecological impacts are complex and challenging to mitigate; (4) USSE development affects different types of ecosystems and requires customized design and management strategies; and (5) long-term ecological consequences associated with USSE sites must be carefully considered. These critical concepts provide a framework for reducing adverse environmental impacts, informing policy to establish and address conservation priorities, and improving energy production sustainability.
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","language":"English","publisher":"University of Hawaii at Hilo","usgsCitation":"Guillaumet, A., and Paxton, E., 2017, Program MAMO: Models for avian management optimization-user guide: Technical Report TR-HCSU-077, Report: iii, 84 p.; Code.","productDescription":"Report: iii, 84 p.; Code","ipdsId":"IP-079991","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":346356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346037,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/10790/3312"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1a4e4b05fe04cc4e0e2","contributors":{"authors":[{"text":"Guillaumet, Alban","contributorId":150397,"corporation":false,"usgs":false,"family":"Guillaumet","given":"Alban","email":"","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":711083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":711082,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}