1. The top 1 m of tidal wetland soils and estuarine sediments of North America contains 1,886 ± 1046 teragrams of carbon (Tg C). [High confidence, Very likely]
2. Soil carbon accumulation rate (i.e., sediment burial) in North American tidal wetlands is currently 9 ± 5 Tg C per year and estuarine carbon burial is 5 ± 3 Tg C per year. [High confidence, Likely]
3. The lateral flux of carbon from tidal wetlands to estuaries is 16 ± 10 Tg C per year for North America. [Low confidence, Likely]
4. In North America, tidal wetlands remove 27 ± 13 Tg C per year from the atmosphere, estuaries outgas 10 ± 10 Tg C per year to the atmosphere, and the net uptake by the combined wetland-estuary system is 17 ± 16 Tg C per year. [Low confidence, Likely]
5. Research and modeling needs are greatest for understanding responses to accelerated sea level rise, mapping tidal wetland and estuarine extent and quantification of CO2 and CH4 exchange with the atmosphere, especially in large, under-sampled, and rapidly changing regions. [High confidence, Likely]
Note: Confidence levels are provided as appropriate for quantitative, but not qualitative, Key Findings and statements.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Second state of the carbon cycle report (SOCCR2): A sustained assessment report","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","doi":"10.7930/SOCCR2.2018.Ch15","usgsCitation":"Windham-Myers, L., Cai, W.J., Alin, S., Andersson, A., Crosswell, J., Dunton, K., Hernandez-Ayon, J.M., Herrmann, M., Hinson, A.L., Charles Hopkinson, Howard, J., Xinping Hu, Knox, S.H., Kroeger, K., David Lagomasino, Megonigal, P., Najjar, R., Paulsen, M., Dorothy Peteet, Pidgeon, E., Karina Schafer, Elizabeth Watson, Wang, Z.A., and Maria Tzortziou, 2018, Tidal Wetlands and Estuaries , chap. 15 of Second state of the carbon cycle report (SOCCR2): A sustained assessment report, p. 596-648, https://doi.org/10.7930/SOCCR2.2018.Ch15.","productDescription":"53 p.","startPage":"596","endPage":"648","ipdsId":"IP-098391","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":365625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Howard, Jennifer","contributorId":149225,"corporation":false,"usgs":false,"family":"Howard","given":"Jennifer","email":"","affiliations":[{"id":17683,"text":"AAAS Science & Technology Policy Fellow/NOAA","active":true,"usgs":false}],"preferred":false,"id":766252,"contributorType":{"id":2,"text":"Editors"},"rank":18},{"text":"Pidgeon, Emily","contributorId":217016,"corporation":false,"usgs":false,"family":"Pidgeon","given":"Emily","email":"","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":766253,"contributorType":{"id":2,"text":"Editors"},"rank":19}],"authors":[{"text":"Windham-Myers, Lisamarie","contributorId":216999,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":766231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cai, Wei Jun","contributorId":217000,"corporation":false,"usgs":false,"family":"Cai","given":"Wei","email":"","middleInitial":"Jun","affiliations":[{"id":39556,"text":"U. 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Schafer","contributorId":217017,"corporation":false,"usgs":false,"family":"Karina Schafer","affiliations":[{"id":12642,"text":"National Science Foundation","active":true,"usgs":false}],"preferred":false,"id":766248,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Wang, Zhaohui Aleck","contributorId":217019,"corporation":false,"usgs":false,"family":"Wang","given":"Zhaohui","email":"","middleInitial":"Aleck","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":766250,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Maria Tzortziou","contributorId":217018,"corporation":false,"usgs":false,"family":"Maria Tzortziou","affiliations":[{"id":39562,"text":"City University of New York","active":true,"usgs":false}],"preferred":false,"id":766249,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Elizabeth 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and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water resource stress. In response to this need, we have developed GSFLOW–GRASS, a bundled set of open-source tools that develops inputs for, executes, and graphically displays the results of GSFLOW, the U.S. Geological Survey's coupled groundwater and surface-water flow model. In order to create a robust tool that can be widely implemented over diverse hydro(geo)logic settings, we built a series of GRASS GIS extensions that automatically discretizes a topological surface-water flow network that is linked with an underlying gridded groundwater domain. As inputs, GSFLOW–GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. We demonstrate the broad applicability of the toolbox by successfully testing it in environments with varying degrees of drainage integration, landscape relief, and grid resolution, as well as the presence of irregular coastal boundaries. These examples also show how GSFLOW–GRASS can be implemented to examine the role of groundwater–surface-water interactions in a diverse range of water resource and land management applications.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-11-4755-2018","usgsCitation":"Ng, G., Wickert, A.D., Somers, L.D., Saberi, L., Cronkite-Ratcliff, C., Niswonger, R.G., and McKenzie, J.M., 2018, GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems: Geoscientific Model Development, v. 11, p. 4755-4777, https://doi.org/10.5194/gmd-11-4755-2018.","productDescription":"23 p.","startPage":"4755","endPage":"4777","ipdsId":"IP-094852","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-11-4755-2018","text":"Publisher Index Page"},{"id":359917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-30","publicationStatus":"PW","scienceBaseUri":"5c07a063e4b0815414cee77f","contributors":{"authors":[{"text":"Ng, G.-H. Crystal","contributorId":197792,"corporation":false,"usgs":false,"family":"Ng","given":"G.-H. Crystal","affiliations":[],"preferred":false,"id":753014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wickert, Andrew D.","contributorId":211022,"corporation":false,"usgs":false,"family":"Wickert","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":753015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Somers, Lauren D.","contributorId":211023,"corporation":false,"usgs":false,"family":"Somers","given":"Lauren","email":"","middleInitial":"D.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":753016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saberi, Leila","contributorId":211024,"corporation":false,"usgs":false,"family":"Saberi","given":"Leila","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":753017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cronkite-Ratcliff, Collin 0000-0001-5485-3832 ccronkite-ratcliff@usgs.gov","orcid":"https://orcid.org/0000-0001-5485-3832","contributorId":203951,"corporation":false,"usgs":true,"family":"Cronkite-Ratcliff","given":"Collin","email":"ccronkite-ratcliff@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":753013,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":753019,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223328,"text":"70223328 - 2018 - Propagation of endangered moapa dace","interactions":[],"lastModifiedDate":"2021-08-24T12:11:17.560164","indexId":"70223328","displayToPublicDate":"2018-11-29T17:29:05","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Propagation of endangered moapa dace","docAbstract":"We report successful captive spawning and rearing of the highly endangered Moapa Dace, Moapa coriacea (approximately 650 individual fish in existence at time of this study). We simulated conditions under which this stream-dwelling southern Nevada cyprinid and similar species spawned and reared in the wild by varying temperature, photoperiod, flow, and substrate in 14 different spawning and rearing treatments in a propagation facility. Successful spawning occurred in artificial streams with the following characteristics: water flow directed both across the bottom gravel substrate into a cobble bed and across the upper water column; 12–14 fish/stream (0.016–0.026 fish/L depending on water level); static water temperature of 30–32°C; photoperiod of 12 h light and 12 h dark; gradual replacement of water from their natal stream with on-site well water; a combination of pelleted, frozen and live food; and minimal disturbance of fish. Nevada Department of Wildlife now uses these techniques successfully to produce fish in a culture setting. Identification of the effective combination of factors to trigger spawning in exceptionally rare fishes can be difficult and time consuming, and limiting factors can be subtle. Sufficient numbers of available test fish, close study and replication of wild spawning conditions, careful documentation, and patience to identify subtle limiting factors are often required to effectively rear and spawn fishes not previously propagated.
","language":"English","publisher":"BioOne","doi":"10.1643/OT-18-036","usgsCitation":"Ruggirello, J., Bonar, S.A., Feuerbacher, O.G., Simons, L.H., and Powers, C., 2018, Propagation of endangered moapa dace: Copeia, v. 106, no. 4, p. 652-662, https://doi.org/10.1643/OT-18-036.","productDescription":"11 p.","startPage":"652","endPage":"662","ipdsId":"IP-102179","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":388394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"southeast Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.433349609375,\n 36.19109202182454\n ],\n [\n -114.114990234375,\n 36.19109202182454\n ],\n [\n -114.114990234375,\n 37.02886944696474\n ],\n [\n -115.433349609375,\n 37.02886944696474\n ],\n [\n -115.433349609375,\n 36.19109202182454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ruggirello, Jack E.","contributorId":264620,"corporation":false,"usgs":false,"family":"Ruggirello","given":"Jack E.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feuerbacher, Olin G.","contributorId":264619,"corporation":false,"usgs":false,"family":"Feuerbacher","given":"Olin","email":"","middleInitial":"G.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simons, Lee H.","contributorId":264621,"corporation":false,"usgs":false,"family":"Simons","given":"Lee","email":"","middleInitial":"H.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":821766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powers, Chelsea","contributorId":264622,"corporation":false,"usgs":false,"family":"Powers","given":"Chelsea","email":"","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821767,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200652,"text":"sir20185144 - 2018 - Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10","interactions":[],"lastModifiedDate":"2018-11-30T13:15:16","indexId":"sir20185144","displayToPublicDate":"2018-11-29T14:00:39","publicationYear":"2018","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":"2018-5144","displayTitle":"Land Subsidence Along the California Aqueduct in West-Central San Joaquin Valley, California, 2003–10","title":"Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10","docAbstract":"Extensive groundwater withdrawal from the unconsolidated deposits in the San Joaquin Valley caused widespread aquifer-system compaction and resultant land subsidence from 1926 to 1970—locally exceeding 8.5 meters. The importation of surface water beginning in the early 1950s through the Delta-Mendota Canal and in the early 1970s through the California Aqueduct resulted in decreased groundwater pumping, recovery of water levels, and a reduced rate of compaction in some areas of the San Joaquin Valley. However, drought conditions during 1976–77, 1987–92, and drought conditions and operational reductions in surface-water deliveries during 2007–10 decreased surface-water availability, causing pumping to increase, water levels to decline, and renewed compaction. Land subsidence from this compaction has reduced freeboard and flow capacity of the California Aqueduct, Delta-Mendota Canal, and other canals that deliver irrigation water and transport floodwater.
The U.S. Geological Survey, in cooperation with the California Department of Water Resources, assessed more recent land subsidence near a 145-kilometer reach of the California Aqueduct in the west-central part of the San Joaquin Valley as part of an effort to minimize future subsidence-related damages to the California Aqueduct. The location, magnitude, and stress regime of land-surface deformation during 2003–10 were determined by using data and analyses associated with extensometers, Global Positioning System surveys, Interferometric Synthetic Aperture Radar, spirit-leveling surveys, and groundwater wells. Comparison of continuous Global Positioning System, shallow-extensometer, and groundwater-level data indicated that most of the compaction in this area took place beneath the Corcoran Clay, the primary regional confining unit. The integration of measurements strengthens confidence in individual measurement methods and provides the information at spatial and temporal scales that water managers need to design and implement groundwater sustainability plans in compliance with California’s Sustainable Groundwater Management Act.
Measurements of land-surface deformation during 2003–10 indicated that the parts of the California Aqueduct closest to the Coast Ranges in the west-central part of the San Joaquin Valley were fairly stable or minimally subsiding on an annual basis; some areas show seasonal periods of subsidence and uplift that resulted in little or no longer-term elevation loss. Many groundwater levels in these areas did not reach historical lows during 2003–10, indicating that deformation nearest the Coast Ranges was likely primarily elastic.
Land-surface deformation measurements indicated that some parts of the California Aqueduct that traverse farther from the Coast Ranges toward the valley center subsided. Some parts of the California Aqueduct subsided locally, but generally the California Aqueduct is within part of a 12,000-square-kilometer area affected by 25 millimeters or more of subsidence during 2008–10, with maxima in Madera County, south of the town of El Nido near the San Joaquin River and the Eastside Bypass (540 millimeters), and in Tulare County, west of the town of Pixley (345 millimeters). Interferometric Synthetic Aperture Radar-derived subsidence maps for various periods during 2003–10 show that the area of maximum active subsidence (that is, the largest rates of subsidence) shifted from its historical (1926–70) location southwest of the town of Mendota to these areas nearer the valley center. Calculations indicated that the subsidence rate doubled in 2008 in parts of the study area. Water levels declined during 2007–10 in many shallow and deep wells in the most rapidly subsiding areas, where water levels in many deep wells reached their historical lows, indicating that subsidence measured during this period was largely inelastic.
Continued groundwater-level and land-subsidence monitoring in the San Joaquin Valley is important because (1) operational- and drought-related reductions in surface-water deliveries since 1976 have resulted in increased groundwater pumping and associated water-level declines and land subsidence, (2) land use and associated pumping continue to change throughout the valley, and (3) subsidence management is stipulated in the Sustainable Groundwater Management Act. The availability of surface water remains uncertain; even during record-setting precipitation years, such as 2010–11, water deliveries fell short of requests and groundwater pumping was required to meet the irrigation demand. In some areas, the infrastructure is not available to supply surface water, and groundwater is the only source of water. Because of the expected continued demand for water and the limitations and uncertainty of surface-water supplies, groundwater pumping and associated land subsidence remains a concern. Spatially detailed information on land subsidence is needed to minimize future subsidence-related damages to the California Aqueduct and other infrastructure in the San Joaquin Valley, as well as alterations to natural resources such as stream gradients, water depths, and water temperatures. The integration of data on land-surface elevation, subsurface deformation, and water levels—particularly continuous measurements—enables the analysis of aquifer-system response to groundwater pumping, which in turn, enables estimation of the preconsolidation head and calculation of aquifer-system storage properties. This information can be used to improve numerical model simulations of groundwater flow and aquifer-system compaction and allow for consideration of land subsidence in the evaluation of water resource management alternatives and compliance with the Sustainable Groundwater Management Act.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185144","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Sneed, M., Brandt, J.T., and Solt, M., 2018, Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10: U.S. Geological Survey Scientific Investigations Report 2018–5144, 67 p., https://doi.org/10.3133/sir20185144. ","productDescription":"x, 67 p.","onlineOnly":"Y","ipdsId":"IP-044802","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437670,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NC9LLL","text":"USGS data release","linkHelpText":"Interferometric Synthetic Aperture Radar-Derived Subsidence Contours for the West-Central San Joaquin Valley, California, 2008-10"},{"id":359739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5144/sir20185144.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientfic Investigations Report 2018-5144"},{"id":359738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5144/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 35.75\n ],\n [\n -119.5,\n 35.75\n ],\n [\n -119.5,\n 37.5\n ],\n [\n -121.5,\n 37.5\n ],\n [\n -121.5,\n 35.75]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The U.S. Geological Survey monitors groundwater-storage change and land-surface elevation change caused by groundwater withdrawal in Tucson Basin and Avra Valley—the two most populated alluvial basins within the Tucson Active Management Area. The Tucson Active Management Area is one of five active management areas in Arizona established by the 1980 Groundwater Management Act and governed by the Arizona Department of Water Resources. Gravity and land-surface elevation change were monitored every 1 to 3 years at wells and benchmarks in Tucson Basin and Avra Valley from 2003 to 2016. Monitoring resulted in estimates of land-surface elevation change and groundwater-storage change. Interferometric synthetic aperture radar (InSAR) interferograms showing land-surface elevation change were constructed for the Tucson metropolitan area from (1) May 2003 to July 2006, (2) July 2006 to June 2008, (3) June 2008 to April 2011, (4) April 2011 to November 2014, and (5) November 2014 to March 2016. For the Tucson metropolitan area, maximum subsidence of about 2 inches occurred during May 2003 to July 2006. From July 2006 to June 2008, maximum subsidence of approximately 0.8 inches occurred in two regions in the Tucson metropolitan area. From June 2008 to April 2011, about 0.8 inches of subsidence also occurred in two regions. Additionally, for the period April 2011 to November 2014, a maximum of about 0.9 inches of subsidence occurred in the same two regions of Tucson Basin. For the entire monitoring period from May 2003 to March 2016, maximum subsidence of as much as 5.3 inches occurred in the Tucson metropolitan area south of Irvington Road between south 12th Avenue and south Park Avenue, and as much as 4 inches in central Tucson south of Broadway between Country Club Road and Craycroft Road. The InSAR data indicated that there was no significant land-surface deformation from 2003 to 2016 in Avra Valley, and no change in either basin from 2014 to 2016.
The volume of stored groundwater in the monitored part of Tucson Basin showed net zero change from spring 2003 to summer 2006. From summer 2006 to summer 2008 the volume of stored groundwater in the monitored part of Tucson Basin increased approximately 50,000 acre-feet; however, overdraft conditions resumed from summer 2008 to spring 2011, resulting in decreased storage of approximately 178,000 acre-feet. From spring 2011 to fall 2014, the volume of stored groundwater in Tucson Basin decreased about 200,000 acre-feet, following a period of lower than average rainfall in 2012 and 2013. The volume of stored groundwater in the monitored part of Tucson Basin increased approximately 167,000 acre-feet from fall 2014 to spring 2016.
Groundwater storage in Avra Valley increased during the entire monitoring period from spring 2003 to spring 2016, largely as a result of managed recharge of Central Arizona Project water in the monitored region. From 2003 to 2016, artificial recharge in Avra Valley totaled approximately 1,788,000 acre-feet, and in Tucson Basin artificial recharge for the entire period was about 636,790 acre-feet. Artificial recharge exceeded pumping in Avra Valley for each time interval. Pumping in Tucson Basin exceeded artificial recharge for every period except 2014 to 2016. Overall, long-term water-level declines have stabilized or reversed since 2000 at most areas in Tucson Basin and Avra Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185154","collaboration":"Prepared in cooperation with the Arizona Department of Water Resources, Pima County, Tucson Water, the Town of Oro Valley, the Town of Marana, and the Metropolitan Domestic Water Improvement District","usgsCitation":"Carruth, R.L., Kahler, L.M., and Conway, B.D., 2018, Groundwater-storage change and land-surface elevation change in Tucson Basin and Avra Valley, south-central Arizona—2003–2016: U.S. Geological Survey Scientific Investigations Report 2018–5154, 34 p., https://doi.org/10.3133/sir20185154.","productDescription":"vii, 34 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-019853","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":359796,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5154/coverthb.jpg"},{"id":359797,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5154/sir20185154.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5154"}],"country":"United States","state":"Arizona","otherGeospatial":"Avra Valley, Tucson Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5936279296875,\n 31.33311153820117\n ],\n [\n -110.44281005859375,\n 31.33311153820117\n ],\n [\n -110.44281005859375,\n 32.90726224488304\n ],\n [\n -111.5936279296875,\n 32.90726224488304\n ],\n [\n -111.5936279296875,\n 31.33311153820117\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Explore U.S. Geological Survey (USGS) water-use websites to learn how and where the Nation's water use has changed over time! Learn how to find and access USGS water-use data shown in maps, graphs, visualizations, and information products. Gain a better understanding of water-use terms and USGS educational resources. Learn how to find and use USGS visualizations to see how water use has changed in each State, and explore county water withdrawals during 2015 to see which areas withdrew the most or least water.
National Water-Use Science Project Team
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey, in cooperation with the Bureau of Reclamation and the Oklahoma Water Resources Board, (1) quantified the groundwater resources of the Rush Springs aquifer in western Oklahoma by developing a numerical groundwater-flow model, (2) evaluated the effects of estimated equal-proportionate-share (EPS) pumping rates on aquifer storage and streamflow for time periods of 20, 40, and 50 years into the future, (3) assessed the uncertainty in the EPS scenario results, and (4) evaluated the effects of (a) projected groundwater-use rates extended 50 years into the future and (b) sustained hypothetical drought conditions over a 10-year period on stream base flow and groundwater in storage.
The Rush Springs aquifer is an important source of water for municipal and irrigation use by many communities and agricultural users in the study area. The study area is composed of about 4,970 square miles (3,181,003 acres) of Rush Springs aquifer bedrock deposits located in 14 counties. The study area also includes the alluvium and terrace deposits of the Canadian and Washita Rivers, as well as alluvium along the Little Washita River, Deer Creek, and a number of smaller tributaries of the Washita River that overlie the bedrock.
A numerical groundwater-flow model of the Rush Springs aquifer was constructed by using MODFLOW with the Newton solver. Groundwater flow was simulated for January 1979–December 2015 by using monthly stress periods, and an initial steady-state stress period was configured to represent mean annual inflows and outflows. The model was calibrated to groundwater-level observations at selected wells, monthly base flow at nine streamgages, stream seepage as estimated for the conceptual water budget, and Fort Cobb Reservoir stage.
The EPS scenarios for the Rush Springs aquifer were run for periods of 20, 40, and 50 years. The 20-, 40-, and 50-year EPS pumping rates under normal recharge conditions were 0.82, 0.49, and 0.43 acre-foot per acre per year, respectively. Given the 2,954,545-acre aquifer area used for the EPS scenarios, the 20-year rate corresponds to an annual yield of about 2,422,727 acre-feet per year. Groundwater storage at the end of the 20-year EPS scenario was about 13,321,000 acre-feet, or about 31,516,437 acre-feet (70 percent) less than the starting EPS scenario storage. This decrease in storage was equivalent to a mean groundwater-level decline of about 152 feet. Water availability under the EPS pumping rate was primarily from the western area of the model. Saturation was sustained though the entire EPS scenario where the aquifer was sufficiently thick or a shallow hydraulic gradient was present. Fort Cobb Reservoir stage was below the dead-pool stage after about 5 years of 20-year EPS pumping.
An uncertainty analysis was conducted to assess the uncertainty in the EPS scenario results. An ensemble of 400 random sets of possible parameter values was performed for the uncertainty analysis by using a multivariate normal distribution centered on the calibrated parameter values. The parameter bounds for the uncertainty analysis were determined by using the posterior covariance matrix, which allows for the incorporation of knowledge gained during the calibration process as well as observation uncertainty and the correlation between estimated parameters. The uncertainty results indicate a 95-percent confidence interval for the 20-year EPS pumping rate between 0.73 and 0.95 acre-foot per acre per year.
Projected 50-year pumping scenarios were used to simulate the effects of selected well withdrawal rates on groundwater storage of the Rush Springs aquifer. The effects of well withdrawals were evaluated by comparing changes in groundwater storage between four 50-year scenarios using (1) no groundwater use, (2) mean groundwater use for the study period (1979–2015), (3) increasing groundwater use, and (4) groundwater use at the 2015 rate. The increasing-use scenario assumed a 38-percent increase in pumping over 50 years on the basis of 2010–60 demand projections for western Oklahoma. Simulated groundwater storage changes ranged between an increase of 6.3 percent for the scenario with no groundwater use, and 0.9 percent for the scenario with 2015 groundwater-use rates. For the Fort Cobb Reservoir surface watershed, simulated groundwater storage changes ranged between an increase of 23.6 percent for the scenario with no groundwater use and a decrease of 4.0 percent for the increasing groundwater-use scenario. Groundwater-level changes were generally greater in areas with a large concentration of groundwater wells and groundwater use such as the Fort Cobb Reservoir surface watershed.
A hypothetical 10-year drought scenario was used to simulate the effects of a prolonged period of reduced recharge on the Rush Springs aquifer groundwater storage and Fort Cobb Reservoir stage and storage. Drought effects were quantified by comparing the results of the drought scenario to those of the calibrated numerical model. To simulate the hypothetical drought, recharge in the calibrated numerical model was reduced by 50 percent during the simulated drought period (1983–1992), and upstream inflows to the Canadian and Washita Rivers and associated tributaries were reduced by 37 percent. Groundwater storage at the end of the hypothetical drought period in December 1992 was about 42,983,000 acre-feet, or about 3,525,000 acre-feet (7.6 percent) less than the groundwater storage of the calibrated numerical model. This change in groundwater storage is equivalent to a mean groundwater-level decline of 15.8 feet. Simulated mean base-flow declines at the Canadian and Washita River streamgages were between 39 and 59 percent during the drought period. The minimum stage in Fort Cobb Reservoir at the end of the hypothetical drought period was 1,311 feet, indicating a storage capacity of only 10 percent of active conservation pool storage. The Fort Cobb Reservoir storage declines mostly resulted from reduced base flows in Cobb, Lake, and Willow Creeks upstream from the reservoir.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185136","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Oklahoma Water Resources Board","usgsCitation":"Ellis, J.H., 2018, Simulation of groundwater flow and analysis of projected water use for the Rush Springs aquifer, western Oklahoma: U.S. Geological Survey Scientific Investigations Report 2018–5136, 156 p., https://doi.org/10.3133/sir20185136.","productDescription":"Report: xi, 156 p.; Data Release","numberOfPages":"172","onlineOnly":"N","ipdsId":"IP-095386","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":359756,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q52NXK","text":"USGS data release","linkHelpText":"MODFLOW model used in simulation of groundwater flow and analysis of projected water use for the Rush Springs aquifer, western Oklahoma"},{"id":359754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5136/coverthb.jpg"},{"id":359755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5136/sir20185136.pdf","text":"Report","size":"40.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5136"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Rush Springs Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.75,\n 34.5\n ],\n [\n -97.75,\n 34.5\n ],\n [\n -97.75,\n 36.5\n ],\n [\n -99.75,\n 36.5\n ],\n [\n -99.75,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma Water Science Center
U.S. Geological Survey
202 NW 66th Street, Building 7
Oklahoma City, Oklahoma 73116
The East Siberian Sea Basin, which lies beneath the continental shelf east of the New Siberian Islands, is one of the better-known basins in a series of postorogenic (successor) basins in the East Siberian-Chukchi Sea region because of a reconnaissance network of seismic-reflection profiles and outcrops on nearby islands. In spite of the seismic coverage, the basin’s petroleum potential is poorly known. It is considered a separate petroleum province for the purposes of the Circum-Arctic Resource Appraisal. The probability that the East Siberian Sea Basin contains at least one undiscovered accumulation >50 million barrels of oil equivalent (MMBOE) is considered to be ~22 percent. A single assessment unit was defined and studied, resulting in mean estimates of technically recoverable conventional undiscovered resources of ~20 million barrels of oil (MMBO) and 580 billion cubic feet of gas (BCFG), nonassociated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824Y","usgsCitation":"Bird, K.J., Houseknecht, D.W., and Pitman, J.K., 2018, Geology and assessment of undiscovered oil and gas resources of the East Siberian Sea Basin Province, 2008, chap. Y of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 11 p., https://doi.org/10.3133/pp1824Y.","productDescription":"Document: vi, 10 p.; Larger Work; Appendix","ipdsId":"IP-050994","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":359733,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/y/pp1824y.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Professional Paper 1824 Chapter Y"},{"id":359734,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/y/pp1824y_appendix1.xls","text":"Appendix 1","size":"30 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Professional Paper 1824 Chapter Y Appendix 1","linkHelpText":"- Input Data for the East Siberian Sea Basin Assessment Unit"},{"id":359732,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/y/coverthb.jpg"}],"otherGeospatial":"East Siberian Sea Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 152,\n 72\n ],\n [\n 168,\n 72\n ],\n [\n 168,\n 76\n ],\n [\n 152,\n 76\n ],\n [\n 152,\n 72\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
The northern diamondback terrapin (Malaclemys terrapin terrapin) is a saltmarsh-dependent turtle that occupies coastal habitats throughout much of the Atlantic coast of North America. We used a novel application of acoustic telemetry to quantify both mobility and occupancy of terrapins within a dredged harbor and surrounding habitats, and used these metrics to quantify relative risk to individuals posed by harbor dredging. Terrapins showed strong fidelity to brumating areas within subdrainages, but extensive movements between these zones during the active period. Activity was greatest in late spring and early summer, declining to near zero by December. Occupancy of the dredge zone was also greatest during spring and summer and declined throughout the autumn months to an annual minimum during winter. Taken together, these data indicate that risks from harbor dredging are minimized during the autumn and early winter months.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-018-0481-9","usgsCitation":"Castro-Santos, T.R., Bolus, M., and Danylchuk, A., 2018, Assessing risks from harbor dredging to the northernmost population of diamondback terrapins using acoustic telemetry: Estuaries and Coasts, v. 42, no. 2, p. 378-389, https://doi.org/10.1007/s12237-018-0481-9.","productDescription":"12 p.","startPage":"378","endPage":"389","ipdsId":"IP-082608","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":379959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Wellfleet","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.08316040039062,\n 41.90432124806034\n ],\n [\n -69.97055053710938,\n 41.90432124806034\n ],\n [\n -69.97055053710938,\n 41.98705662960288\n ],\n [\n -70.08316040039062,\n 41.98705662960288\n ],\n [\n -70.08316040039062,\n 41.90432124806034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":803375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bolus, M.","contributorId":244215,"corporation":false,"usgs":false,"family":"Bolus","given":"M.","email":"","affiliations":[],"preferred":false,"id":803528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danylchuk, A. J.","contributorId":146536,"corporation":false,"usgs":false,"family":"Danylchuk","given":"A. J.","affiliations":[{"id":16720,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA 01003-9485, USA","active":true,"usgs":false}],"preferred":false,"id":803529,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200438,"text":"ofr20181167 - 2018 - Biophysical assessment for indemnity selection of Federal Lands in Colorado","interactions":[],"lastModifiedDate":"2018-11-29T15:28:51","indexId":"ofr20181167","displayToPublicDate":"2018-11-28T17:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1167","title":"Biophysical assessment for indemnity selection of Federal Lands in Colorado","docAbstract":"Information on the biophysical features of Federal lands identified as suitable for transfer to the State of Colorado was requested by the Bureau of Land Management (BLM). This information is intended for use in conducting an Environmental Assessment prior to the transfer of ownership (conveyance) to the State. The Colorado State Land Board filed a selective application to obtain public land and mineral estate in lieu of lands to which the State of Colorado was entitled but did not receive at the time of statehood. To address this legal obligation, 339 parcels of Federal lands (organized into 89 indemnity units [IUs]), currently under management by the BLM, have been identified as suitable for transfer to the State. The IUs include 23,130 acres of surface and mineral estate and 6,150 acres of mineral estate only. The specific land parcels to be transferred to the State will be finalized after an Environmental Assessment and other evaluations are completed.
To provide the biophysical information necessary for conducting a future Environmental Assessment of the potential effects of the proposed land transfer, information on ecological communities, soil characteristics, and land use was summarized at three levels: (1) all of Colorado, (2) lands under the jurisdiction of the BLM, and (3) the 89 IUs. Information was also synthesized and summarized for 179 plant and animal species or subspecies of management concern to evaluate which species had the potential for occurrence on IUs. Datasets summarized for Colorado and for indemnity units and methodological details for all data summaries are provided in U.S. Geological Survey data releases available online at https://doi.org/10.5066/F7GT5MGV and https://doi.org/10.5066/F7C24VQ0.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181167","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Carr, N.B., Burris, L.E., and Manier, D.J., 2018, Biophysical assessment for indemnity selection of Federal lands in Colorado: U.S. Geological Survey Open-File Report 2018–1167, 51 p., https://doi.org/10.3133/ofr20181167.","productDescription":"Report: vii, 51 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-094998","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":359757,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GT5MGV","text":"USGS data release","linkHelpText":"Broad-scale assessment of biophysical features in 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\"}}]}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Tucked in a grove of thorny mesquite trees, on an ancient coral reef on the south side of the Hawaiian island of Oahu, west of Pearl Harbor, a small unmanned observatory quietly records the Earth’s time-varying magnetic field. The Honolulu Magnetic Observatory is 1 of 14 that the U.S. Geological Survey Geomagnetism Program operates at various locations across the United States and its territories.
Data from these observatories, Honolulu, and those operated by institutions in foreign countries, record a variety of magnetic signals related to a wide diversity of physical phenomena in the Earth’s interior and its surrounding outer-space environment. USGS magnetic observatory operations are an integral part of a U.S. National Space Weather Strategy for monitoring and assessing natural hazards that potentially threaten important technological systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183029","usgsCitation":"Love, J.J., and Finn, C.A., 2018, Honolulu Magnetic Observatory: U.S. Geological Survey Fact Sheet 2018–3029, 2 p.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-095628","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":359735,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3029/coverthb.jpg"},{"id":359736,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3029/fs20183029.pdf","text":"Report","size":"2.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3029"}],"country":"United States","state":"Hawaii","city":"Honolulu","otherGeospatial":"Oahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.8907012939453,\n 21.245062376508383\n ],\n [\n -157.76229858398438,\n 21.245062376508383\n ],\n [\n -157.76229858398438,\n 21.33830997478836\n ],\n [\n -157.8907012939453,\n 21.33830997478836\n ],\n [\n -157.8907012939453,\n 21.245062376508383\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046
An imaging sonar was used to assess the behavior and abundance of fish sized the same as salmonid smolt and bull trout (Salvelinus confluentus) at the entrance to the juvenile fish floating surface collector (FSC) at North Fork Reservoir, Oregon. The purpose of the FSC is to collect downriver migrating juvenile salmonids (Chinook salmon [Oncorhynchus tshawytscha], Coho salmon [Oncorhynchus kisutch], and steelhead [Oncorhynchus mykiss]) at the North Fork Dam and to safely route them around the hydroelectric projects. The objective of the imaging sonar component of this study was to assess the behaviors of both smolt and predator-size fish (smolt [60–250 millimeter] and predator 350–650 [millimeter]) observed near the FSC and to determine if the presence of predator-size fish influenced the abundance of smolt-size fish. An imaging sonar was deployed near the entrance to the FSC during the spring smolt out-migration period. The imaging sonar technology was an informative tool for assessing abundance and spatial and temporal behaviors of both smolt and predator-size fish near the entrance of the FSC. Both smolt and predator-size fish were regularly observed near the entrance, with greater abundances observed during day than during night. Behavioral differences were also observed between the two fish-size classes, with smolt-size fish traveling straighter with more directed movement, and predator-size fish generally showing more milling behavior. Additionally, the presence of predator-size fish may be effecting the abundance and direction of travel of smolt-size fish, as counts of smolt-size fish were reduced in conjunction with the presence of predator-size fish and a greater proportion of smolt-size fish were observed traveling away from the FSC when predator-size fish were present than when predator-size fish were absent. Results of modeling potential predator-prey interactions and influences indicated that both the number of juvenile fish tracks and photoperiod had the strongest effects on the number of predator fish tracks, with more predator-size fish tracks observed as the number of smolt-size fish tracks increased. Overall, the results indicate that predator-size fish are present near the entrance of the FSC, concomitant with smolt-size fish, and their abundances and behaviors indicate that they may be drawn to the entrance of the FSC because of the abundance of prey-sized fish found there.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181182","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., Plumb J.M., and Adams, N.S. 2018, Fish behavior and abundance monitoring near a floating surface collector in North Fork Reservoir, Clackamas River, Oregon, using multi-beam acoustic imaging sonar: U.S. Geological Survey Open-File Report 2018-1182, 28 p., https://doi.org/10.3133/ofr20181182.","productDescription":"vi, 28 p.","onlineOnly":"Y","ipdsId":"IP-100791","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359740,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1182/coverthb2.jpg"},{"id":359741,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1182/ofr20181182.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1182"}],"country":"United States","state":"Oregon","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73376464843749,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.0657615477031\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
We related Louisiana Waterthrush (Parkesia motacilla) demographic response and nest survival to benthic macroinvertebrate aquatic prey and to shale gas development parameters using models that accounted for both spatial and non-spatial sources of variability in a Central Appalachian USA watershed. In 2013, aquatic prey density and pollution intolerant genera (i.e., pollution tolerance value <4) decreased statistically with increased waterthrush territory length but not in 2014 when territory densities were lower. In general, most demographic responses to aquatic prey were variable and negatively related to aquatic prey in 2013 but positively related in 2014. Competing aquatic prey covariate models to explain nest survival were not statistically significant but differed annually and in general reversed from negative to positive influence on daily survival rate. Potential hydraulic fracturing runoff decreased nest survival both years and was statistically significant in 2014. The EPA Rapid Bioassessment protocol (EPA) and Habitat Suitability Index (HSI) designed for assessing suitability requirements for waterthrush were positively linked to aquatic prey where higher scores increased aquatic prey metrics, but EPA was more strongly linked than HSI and varied annually. While potential hydraulic fracturing runoff in 2013 may have increased Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness, in 2014 shale gas territory disturbance decreased EPT richness. In 2014, intolerant genera decreased at the territory and nest level with increased shale gas disturbance suggesting the potential for localized negative effects on waterthrush. Loss of food resources does not seem directly or solely responsible for demographic declines where waterthrush likely were able to meet their foraging needs. However collective evidence suggests there may be a shale gas disturbance threshold at which waterthrush respond negatively to aquatic prey community changes. Density-dependent regulation of their ability to adapt to environmental change through acquisition of additional resources may also alter demographic response.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0206077","usgsCitation":"Frantz, M.W., Wood, P.B., and Merovich, G.T., 2018, Demographic characteristics of an avian predator, Louisiana Waterthrush (Parkesia motacilla), in response to its aquatic prey in a Central Appalachian USA watershed impacted by shale gas development: PLoS ONE, v. 13, no. 11, p. 1-19, https://doi.org/10.1371/journal.pone.0206077.","productDescription":"e0206077, 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-095412","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468230,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0206077","text":"Publisher Index Page"},{"id":395279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Lewis Wetzel Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.66818714141846,\n 39.514702147872995\n ],\n [\n -80.64299583435057,\n 39.514702147872995\n ],\n [\n -80.64299583435057,\n 39.530790543485786\n ],\n [\n -80.66818714141846,\n 39.530790543485786\n ],\n [\n -80.66818714141846,\n 39.514702147872995\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2018-11-28","publicationStatus":"PW","contributors":{"editors":[{"text":"Lightfoot, David A.","contributorId":273594,"corporation":false,"usgs":false,"family":"Lightfoot","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":832745,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Frantz, Mack W.","contributorId":272515,"corporation":false,"usgs":false,"family":"Frantz","given":"Mack","email":"","middleInitial":"W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":832653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merovich, George T. Jr.","contributorId":172041,"corporation":false,"usgs":false,"family":"Merovich","given":"George","suffix":"Jr.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":832654,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227756,"text":"70227756 - 2018 - Influence of river discharge on grass carp occupancy dynamics in south-eastern Iowa rivers","interactions":[],"lastModifiedDate":"2022-01-28T14:42:30.747171","indexId":"70227756","displayToPublicDate":"2018-11-28T08:37:39","publicationYear":"2018","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":"Influence of river discharge on grass carp occupancy dynamics in south-eastern Iowa rivers","docAbstract":"Despite the longstanding presence of grass carp Ctenopharyngodon idella in the Upper Mississippi River (UMR) watershed, information regarding their populations remains largely unknown, in part because capture is difficult. Occupancy models are a popular wildlife assessment tool to account for imperfect detections but have been slow to be adopted in fisheries. Herein, we used occupancy modelling to evaluate the influence of two environmental covariates (river discharge and water temperature) on grass carp occupancy, extinction, colonization, and detection at nine sites within south-eastern Iowa rivers from April to October 2014 and 2015. Grass carp were detected at least once at all but one site. The most parsimonious model indicated that grass carp colonization probability increased from 0.15 to 0.67 with increases in river discharge. In contrast, occupancy (0.20), extinction (0.29), and detection (0.50) probabilities were temporally constant. Models indicated that water temperatures did not influence grass carp extinction or colonization probabilities relative to river discharge. Cumulative grass carp detection probability approached 1.0, whereas conditional occupancy estimates were less than 0.1 when using five or more sampling transects. The use of a robust design occupancy model allowed us to estimate site occupancy rates of grass carp corrected for imperfect detections, while demonstrating the importance of river discharge for site colonization. These results can be used to assess the distribution of a cryptic fish while helping to guide grass carp sampling and removal efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3385","usgsCitation":"Sullivan, C.J., Weber, M., Pierce, C., and Camacho, C.A., 2018, Influence of river discharge on grass carp occupancy dynamics in south-eastern Iowa rivers: River Research and Applications, v. 35, no. 1, p. 60-67, https://doi.org/10.1002/rra.3385.","productDescription":"8 p.","startPage":"60","endPage":"67","ipdsId":"IP-090729","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502456,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/296","text":"External Repository"},{"id":395045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.24072265625,\n 40.17887331434696\n ],\n [\n -90.54931640625,\n 40.17887331434696\n ],\n [\n -90.54931640625,\n 42.65012181368022\n ],\n [\n -94.24072265625,\n 42.65012181368022\n ],\n [\n -94.24072265625,\n 40.17887331434696\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-11-28","publicationStatus":"PW","contributors":{"editors":[{"text":"Weber, Michael J.","contributorId":272530,"corporation":false,"usgs":false,"family":"Weber","given":"Michael J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832053,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Sullivan, Christopher J.","contributorId":272528,"corporation":false,"usgs":false,"family":"Sullivan","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weber, Michael J.","contributorId":272530,"corporation":false,"usgs":false,"family":"Weber","given":"Michael J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Camacho, Carlos A.","contributorId":272529,"corporation":false,"usgs":false,"family":"Camacho","given":"Carlos","email":"","middleInitial":"A.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832052,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200972,"text":"tm9A1 - 2018 - Preparations for water sampling","interactions":[{"subject":{"id":4907,"text":"twri09A1 - 2005 - Preparations for water sampling","indexId":"twri09A1","publicationYear":"2005","noYear":false,"displayTitle":"Preparations for Water Sampling","title":"Preparations for water sampling"},"predicate":"SUPERSEDED_BY","object":{"id":70200972,"text":"tm9A1 - 2018 - Preparations for water sampling","indexId":"tm9A1","publicationYear":"2018","noYear":false,"title":"Preparations for water sampling"},"id":1}],"lastModifiedDate":"2019-03-26T13:22:42","indexId":"tm9A1","displayToPublicDate":"2018-11-27T14:30:00","publicationYear":"2018","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":"9-A1","displayTitle":"Chapter A1. Preparations for Water Sampling","title":"Preparations for water sampling","docAbstract":"The “National Field Manual for the Collection of Water-Quality Data” (NFM) provides guidelines and procedures for U.S. Geological Survey (USGS) personnel who collect data used to assess the quality of the Nation’s surface-water and groundwater resources. This chapter, NFM A1, provides an overview of preparations for water sampling, which includes site reconnaissance, project work plans, quality-assurance plans, basic equipment and supplies needed for fieldwork, safety precautions, and planning for data management. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A1, version 2.0, by F.D. Wilde.
Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.er.usgs.gov/. Comments, questions, and suggestions related to the NFM can be addressed to nfm-owq@usgs.gov.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: National field manual for the collection of water-quality data in Book 9: Handbooks for water-resources investigations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm9A1","usgsCitation":"U.S. Geological Survey, 2018, Preparations for water sampling: U.S. Geological Survey Techniques and Methods 9-A1, vii, 42 p., https://doi.org/10.3133/tm9A1.","productDescription":"vii, 42 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":359547,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/09/a1/tm9a1.pdf","text":"Report","size":"2.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 9-A1"},{"id":359548,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/09/a1/versionHist.txt","text":"Version History","size":"2.74 MB","linkFileType":{"id":2,"text":"txt"}},{"id":359546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/09/a1/coverthb2.jpg"}],"publicComments":"The 2018 release in the Techniques and Methods series supersedes two earlier editions in the Techniques of Water-Resources Investigations series. Version 1 was released in 1998 and version 2 was released in 2005. More details are in the version history document.","contact":"Chief, Office of Quality Assurance
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 432
Reston, VA 20192
In 2015–16, the U.S. Geological Survey, in cooperation with the Muskingum Watershed Conservancy District, led a study to assess baseline (2015–16) surface-water quality in six lake drainage basins within the Muskingum River watershed that are in the early years of shale-gas development. In 2015, 9 of the 10 most active counties in Ohio for oil and gas development were wholly or partially within the Muskingum River watershed. In addition to shale gas development, the area has a history of conventional oil and gas development and coal mining.
In all, 30 surface-water sites were sampled: 20 in tributaries flowing to the lakes, 4 in lakes themselves, and 6 downstream of the lakes. At each of the 30 sites, 6 samples were collected to characterize surface-water chemistry throughout a range of hydrologic conditions. The sampling generally occurred during low flows (periods of greater groundwater contribution) rather than during runoff events (periods of high stream stage).
Trilinear diagrams of major ion chemistry revealed three main types of water in the study area―sulfate-dominated waters, bicarbonate-dominated waters, and waters with mixed bicarbonate and chloride anions. Most sites produced samples of bicarbonate-dominated water, and 11 sites produced samples with sulfate-type waters. Mixed bicarbonate and chloride waters were found in samples from two of the six lake drainage basins studied.
The baseline (2015–16) assessment of surface-water quality in the study area indicated that few water-chemistry constituents and properties occurred at concentrations or levels that would adversely affect aquatic organisms. Chemical-specific, aquatic life use criteria were not met in only three instances: two were for total dissolved solids at sites likely impacted by coal mining in their drainage basins (hereafter referred to as “mine-impacted sites”), and one was for dissolved oxygen.
Mine drainage from historical coal mining in the region likely affected the quality of about one-third of the streams sampled. To simplify interpretation of water-chemistry results, 11 sites with sulfate-type water were identified as mine-impacted sites based on water-quality criteria established by Ohio Department of Natural Resources, Division of Mineral Resources Management, and separated out for subsequent statistical analysis. Concentrations or levels of bicarbonate, boron, calcium, carbonate, total dissolved solids, fluoride, magnesium, lithium, pH, potassium, sodium, specific conductance, strontium, sulfate, and suspended sediment in water were higher (significance level of 0.05) at mine-impacted stream sites than at non-mine-impacted stream sites.
An accidental release of oil- and gas-related brines could increase salinity (sodium and chloride), the concentration of total dissolved solids in shallow groundwater and streams, and specific conductance. For this study, chloride concentrations in the study area ranged from 2.12 to 76.1 milligrams per liter. Sources of chloride in water samples were evaluated using binary mixing curves and ratios of chloride to bromide. These ratios indicated that 13 samples from 3 sites in the drainage basin that contained the highest density of conventional oil and gas wells in the study, as well as 4 samples collected from other drainage basins, likely contained a component of brine. Concentrations or levels of barium, bromide, chloride, iron, lithium, manganese, and sodium were significantly higher (alpha = 0.05) in samples with a component of brine than in samples without a component of brine.
Benzene, toluene, ethylbenzene and xylene (BTEX), compounds that occur naturally in crude oil, made up 24 of the 45 detections (53 percent) of volatile organic compounds in the study area. The BTEX detections were not associated with sites containing a component of brine. The only volatile organic compound detected in any of the 17 samples that contained a component of brine was acetone, detected in 3 (18 percent) of these samples and in 11 percent of samples not containing a component of brine. Considering that BTEX are gasoline hydrocarbons and that most of the detections occurred during warmer months in and around the lakes, the BTEX detections likely are associated with increases in outdoor activities such as automobile and boating traffic.
Radium-226 and radium-228 were included in the list of analytes for this study because production water from shale-gas drilling can contain these naturally occurring radioactive materials. Concentrations of radium-226 exceeded background levels in only two surface-water samples. Concentrations of radium-228 exceeded background levels in one surface-water sample.
A brine signature potentially indicative of oil and gas contamination was detected in samples collected at two sites that contained active or plugged waste injection wells, or both. Results from the study indicated significant differences in the median concentrations of bromide, chloride, lithium, manganese, sodium, and total dissolved nitrogen between sites with and without injection wells in their drainage areas. Median concentrations of bromide, chloride, lithium, and sodium, which are common oil- and gas-related contaminants, were higher at sites with injection wells in their drainage areas compared to sites without injection wells.
Historical (1960s, 1970s, and 1980s) chloride concentrations and streamflow data at or near five of the six sampling sites downstream from each lake dam were compared to current (2015–16) values. An analysis of covariance was done to test the effects of streamflow, time (decade), and the combined effects (cross product) of streamflow and time on chloride concentrations. Those analyses indicated that streamflow was not significant in explaining the variation in chloride concentration, likely because streamflow in those locations is controlled by dam operations; therefore, association between runoff-generating events and streamflow is less direct than in unregulated streams. From the 1980s to the study period (2015–16), data for three of the five lakes indicated an increase in chloride concentrations. The comparison of historical and current (2015–16) study data from samples collected at another lake indicated that chloride concentrations increased from the 1960s to the 1970s, but concentrations in the 1970s and 2015–16 were similar even though 13 samples from this lake drainage basin were classified as having a component of brine. Median chloride concentrations for the fifth lake, however, seemed to decrease from the 1980s to 2015–16.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185113","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District","usgsCitation":"Covert, S.A., Jagucki, M.L., and Huitger, C., 2018, Baseline water quality of an area undergoing shale-gas development in the Muskingum River watershed, Ohio, 2015–16: U.S. Geological Survey Scientific Investigations Report 2018–5113, 129 p., https://doi.org/10.3133/sir20185113.","productDescription":"Report: ix, 129 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091174","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":359613,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0SRT","text":"USGS data release","description":"USGS data release","linkHelpText":"Data from quality-control equipment blanks, field blanks, and field replicates for baseline water quality of an area undergoing shale-gas development in the Muskingum River watershed, Ohio, 2015-16 "},{"id":359612,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5113/sir20185113.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5113"},{"id":359611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5113/coverthb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Muskingum River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.75,\n 39.75\n ],\n [\n -80.75,\n 39.75\n ],\n [\n -80.75,\n 40.6667\n ],\n [\n -81.75,\n 40.6667\n ],\n [\n -81.75,\n 39.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd
Suite 100
Columbus, OH 43229
Geochronologies derived from sediment cores in coastal locations are often used to infer event bed characteristics such as deposit thicknesses and accumulation rates. Such studies commonly use naturally occurring, short-lived radioisotopes, such as Beryllium-7 (7Be) and Thorium-234 (234Th), to study depositional and post-depositional processes. These radioisotope activities, however, are not generally represented in sediment transport models that characterize coastal flood and storm deposition with grain size patterns and deposit thicknesses. We modified the Community Sediment Transport Modeling System (CSTMS) to account for reactive tracers and used this capability to represent the behavior of these short-lived radioisotopes on the sediment bed. This paper describes the model and presents results from a set of idealized, one-dimensional (vertical) test cases. The model configuration represented fluvial deposition followed by periods of episodic storm resuspension. Sensitivity tests explored the influence on seabed radioisotope profiles by the intensities of bioturbation and wave resuspension and the thickness of fluvial deposits. The intensity of biodiffusion affected the persistence of fluvial event beds as evidenced by 7Be. Both resuspension and biodiffusion increased the modeled seabed inventory of 234Th. A thick fluvial deposit increased the seabed inventory of 7Be and 234Th but mixing over time greatly reduced the difference in inventory of 234Th in fluvial deposits of different thicknesses.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse6040144","usgsCitation":"Birchler, J.J., Harris, C.K., Sherwood, C.R., and Kniskern, T.A., 2018, Sediment transport model including short-lived radioisotopes: Model description and idealized test cases: Journal of Marine Science and Engineering, v. 6, no. 4, p. 1-17, https://doi.org/10.3390/jmse6040144.","productDescription":"144, 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-094563","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468231,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse6040144","text":"Publisher Index Page"},{"id":422975,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Birchler, Justin J. 0000-0002-0379-2192 jbirchler@usgs.gov","orcid":"https://orcid.org/0000-0002-0379-2192","contributorId":169117,"corporation":false,"usgs":true,"family":"Birchler","given":"Justin","email":"jbirchler@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Courtney K.","contributorId":19620,"corporation":false,"usgs":false,"family":"Harris","given":"Courtney","email":"","middleInitial":"K.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":888695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kniskern, Tara A","contributorId":202170,"corporation":false,"usgs":false,"family":"Kniskern","given":"Tara","email":"","middleInitial":"A","affiliations":[{"id":36356,"text":"Virginia Institute of Marine Science, College of William & Mary","active":true,"usgs":false}],"preferred":false,"id":888697,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201073,"text":"70201073 - 2018 - Tag retention and survival of juvenile bighead carp implanted with a dummy acoustic tag at three temperatures","interactions":[],"lastModifiedDate":"2019-05-29T09:42:15","indexId":"70201073","displayToPublicDate":"2018-11-27T10:11:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Tag retention and survival of juvenile bighead carp implanted with a dummy acoustic tag at three temperatures","docAbstract":"Bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix(together, the bigheaded carps) are invasive fishes in North America that have resulted in substantial negative effects on native fish communities and aquatic ecosystems. Movement and behavior of adult bigheaded carps has been studied previously using telemetry, while similar studies with juvenile bigheaded carps have yet to be attempted. Recent technological advances in telemetry transmitters has increased the availability of tags sufficiently small enough to implant in juvenile carps. However, the effects of surgical implantation of telemetry tags on juvenile bigheaded carps have not been evaluated. We determined tag retention and survival associated with surgical implantation of acoustic telemetry tags into juvenile bighead carp (range 128–152 mm total length) at three temperatures (13, 18, and 23°C). In addition, we assessed the effect of surgically implanted transmitters on the fitness, defined as changes in weight or critical swimming speed, of carp implanted with transmitters. Survival was high among tagged fish (85%) with 47% of tags retained at the conclusion of the 45‐day study. No substantial decline in fitness of the fish was observed in tagged fish compared to untagged fish.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.13841","usgsCitation":"Byrd, C.G., Chapman, D., Pherigo, E.K., and Jolley, J.C., 2018, Tag retention and survival of juvenile bighead carp implanted with a dummy acoustic tag at three temperatures: Journal of Applied Ichthyology, v. 35, no. 3, p. 763-768, https://doi.org/10.1111/jai.13841.","productDescription":"6 p.","startPage":"763","endPage":"768","ipdsId":"IP-098166","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":468232,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.13841","text":"Publisher Index Page"},{"id":437672,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T6QGRL","text":"USGS data release","linkHelpText":"Tag retention and survival of juvenile bighead carp implanted with an acoustic tag at three temperatures"},{"id":359699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-25","publicationStatus":"PW","scienceBaseUri":"5bfe65dfe4b0815414ca60f0","contributors":{"authors":[{"text":"Byrd, Curtis G. 0000-0002-5124-5652","orcid":"https://orcid.org/0000-0002-5124-5652","contributorId":210798,"corporation":false,"usgs":true,"family":"Byrd","given":"Curtis","email":"","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":752261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":752262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pherigo, Emily K.","contributorId":210799,"corporation":false,"usgs":false,"family":"Pherigo","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":752263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jolley, Jeffrey C. 0000-0002-4674-5126","orcid":"https://orcid.org/0000-0002-4674-5126","contributorId":210800,"corporation":false,"usgs":true,"family":"Jolley","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":752264,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199945,"text":"sir20185134 - 2018 - Modeling hydrodynamics, water temperature, and water quality in Klamath Straits Drain, Oregon and California, 2012–15","interactions":[],"lastModifiedDate":"2018-11-27T10:58:23","indexId":"sir20185134","displayToPublicDate":"2018-11-26T15:04:48","publicationYear":"2018","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":"2018-5134","displayTitle":"Modeling Hydrodynamics, Water Temperature, and Water Quality in Klamath Straits Drain, Oregon and California, 2012–15","title":"Modeling hydrodynamics, water temperature, and water quality in Klamath Straits Drain, Oregon and California, 2012–15","docAbstract":"Located southwest of Klamath Falls, Oregon, Klamath Straits Drain is a 10.1-mile-long canal that conveys water uphill and northward through the use of pumps before discharging to the Klamath River. Klamath Straits Drain traverses an area that historically encompassed Lower Klamath Lake. Currently, the Drain receives water from farmland and from parts of the Lower Klamath Lake National Wildlife Refuge. To support water-quality improvement in Klamath Straits Drain, a hydrodynamic and water-temperature model was constructed and calibrated for calendar years 2012–15 with the two-dimensional model CE-QUAL-W2 (version 4.0). Water quality was calibrated for a subset of that time, from April 1, 2012 to March 31, 2015. Flows in calendar year 2012 were within the normal range, while calendar years 2013–15 were dry years. Significant findings from this study include:
This newly constructed model of the Klamath Straits Drain simulates flow, water levels, water temperature, and water quality with acceptable accuracy but with certain data limitations. This model should prove useful in evaluating potential strategies for flow and water-quality management and restoration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185134","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., and Rounds, S.A., 2018, Modeling hydrodynamics, water temperature, and water quality in Klamath Straits Drain, Oregon and California, 2012–15: U.S. Geological Survey Scientific Investigations Report 2018-5134, 30 p., https://doi.org/10.3133/sir20185134.","productDescription":"vii, 30 p.","onlineOnly":"Y","ipdsId":"IP-099157","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":359688,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5134/coverthb.jpg"},{"id":359690,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://or.water.usgs.gov/proj/keno_reach/models.html","text":"Klamath Straits Models —","description":"SIR 2018-5134 Klamath Straits Model","linkHelpText":"Water-Quality Monitoring and Modeling of the Keno Reach of the Klamath River"},{"id":359689,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5134/sir20185134.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5134"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath Straits Drain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 41.8333\n ],\n [\n -121.5,\n 41.8333\n ],\n [\n -121.5,\n 42.33\n ],\n [\n -122,\n 42.33\n ],\n [\n -122,\n 41.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Terrestrial laser scanners (TLSs) provide a tool to assess and monitor forest structure across forest landscapes. We present TLS methods, suggestions, and mapped guidelines for planning TLS acquisitions at varying scales and forest densities. We examined rates of point‐density decline with distance from two TLS that acquire data at relatively high and low point density and found that the rates were nearly identical between scanners (pvalue <0.01), suggesting that our findings are applicable to a range of TLS types. Using unique, TLS‐adapted processing methods, we determined the relative accuracy of TLS‐derived plot‐scale estimates of tree height, diameter‐at‐breast‐height, height‐to‐canopy, tree counts, as well as treatment‐scale tree density and patch metrics, using both high point density and low point density TLS among thinned and nonthinned forest treatments. The high‐density TLS consistently provides more accurate estimates of plot‐level metrics (R2 = 0.46 to 0.87) than the low‐density TLS (R2 = −0.14 to 0.53). At treatment scales, tree density estimates are similar among scanners (R2 = 0.95 vs. 0.71), as are canopy cover and patch metrics. We develop and present the normalized density‐distance index (NDDI), which can account for up to 59% of the variance in estimate error and can be used to guide TLS‐data acquisition plans. This index indicates whether a given location has generally higher point density (higher NDDI) relative to the distance from the scanner and can be used as a proxy for uncertainty. Using NDDI as a guide for fair comparison between scanners, both plot‐ and treatment‐scale estimates improved.
","language":"English","publisher":"AGU Publications","doi":"10.1029/2018EA000417","usgsCitation":"Donager, J.J., Sankey, T.T., Sankey, J.B., Sanchez Meadorc, A.J., Springer, A., and Bailey, J.D., 2018, Examining forest structure with terrestrial lidar: Suggestions and novel techniques based on comparisons between scanners and forest treatments: Earth and Space Science, v. 5, no. 11, p. 753-776, https://doi.org/10.1029/2018EA000417.","productDescription":"14 p.","startPage":"753","endPage":"776","ipdsId":"IP-081018","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468233,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018ea000417","text":"Publisher Index Page"},{"id":437673,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F63VYX","text":"USGS data release","linkHelpText":"Northern Arizona Ponderosa Pine Forest Treatment Terrestrial Lidar Data"},{"id":359656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-12","publicationStatus":"PW","scienceBaseUri":"5bfd146be4b0815414ca38e6","contributors":{"authors":[{"text":"Donager, Jonathon J.","contributorId":210787,"corporation":false,"usgs":false,"family":"Donager","given":"Jonathon","email":"","middleInitial":"J.","affiliations":[{"id":38148,"text":"Northern Arizona University, School of Earth Science and Environmental Sustainability, 1295 S. Knoles Drive, PO Box 5695, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":751966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":751967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":751965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanchez Meadorc, Andrew J.","contributorId":210788,"corporation":false,"usgs":false,"family":"Sanchez Meadorc","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":38149,"text":"Northern Arizona University, School of Forestry, 200 East Pine Knoll Drive, PO Box 15018, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":751968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Springer, Abraham E.","contributorId":9558,"corporation":false,"usgs":true,"family":"Springer","given":"Abraham E.","affiliations":[],"preferred":false,"id":751969,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bailey, John D.","contributorId":42928,"corporation":false,"usgs":true,"family":"Bailey","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":751970,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199277,"text":"sir20185122 - 2018 - Flood-inundation maps for the North Fork Kentucky River at Hazard, Kentucky","interactions":[],"lastModifiedDate":"2018-11-26T15:06:08","indexId":"sir20185122","displayToPublicDate":"2018-11-26T11:30:00","publicationYear":"2018","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":"2018-5122","displayTitle":"Flood-Inundation Maps for the North Fork Kentucky River at Hazard, Kentucky","title":"Flood-inundation maps for the North Fork Kentucky River at Hazard, Kentucky","docAbstract":"Digital flood-inundation maps for a 7.1-mile reach of the North Fork Kentucky River at Hazard, Kentucky (Ky.), were created by the U.S. Geological Survey (USGS) in cooperation with the Kentucky Silver Jackets and the U.S. Army Corps of Engineers Louisville District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the North Fork Kentucky River at Hazard, Ky. (USGS station number 03277500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at https://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS AHPS site HAZK2). NWS AHPS forecast peak stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
Flood profiles were computed for the North Fork Kentucky River reach by means of a one-dimensional, step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating no. 24.0) at USGS streamgage 03277500, North Fork Kentucky River at Hazard, Ky. The calibrated hydraulic model was then used to compute 26 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (14 ft) to the highest even-foot increment stage (39 ft) of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from light detection and ranging data, to delineate the area flooded at each water level.
The availability of these maps, along with information on the internet regarding current stage from the USGS streamgage at North Fork Kentucky River at Hazard, Ky., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185122","collaboration":"Prepared in cooperation with the Kentucky Silver Jackets and the U.S. Army Corps of Engineers Louisville District","usgsCitation":"Boldt, J.A., Lant, J.G., and Kolarik, N.E., 2018, Flood-inundation maps for the North Fork Kentucky River at Hazard, Kentucky: U.S. Geological Survey Scientific Investigations Report 2018-5122, 12 p., https://doi.org/10.3133/sir20185122.","productDescription":"Report: vi, 12 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098752","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":359619,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CNAG9G","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial datasets and model for the flood-inundation study of the North Fork Kentucky River at Hazard, Kentucky"},{"id":359617,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5122/coverthb.jpg"},{"id":359618,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5122//sir20185122.pdf","text":"Report","size":"5.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5122"}],"country":"United States","state":"Kentucky","city":"Hazard","otherGeospatial":" North Fork Kentucky River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.20315361022949,\n 37.22158045838649\n ],\n [\n -83.15423011779785,\n 37.22158045838649\n ],\n [\n -83.15423011779785,\n 37.274872400526334\n ],\n [\n -83.20315361022949,\n 37.274872400526334\n ],\n [\n -83.20315361022949,\n 37.22158045838649\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
9818 Bluegrass Parkway
Louisville, KY 40299-1906
Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water (Burow and Belitz, 2014). The Mississippi embayment–Texas coastal uplands aquifer system constitutes one of the important aquifer systems being evaluated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183067","usgsCitation":"Kingsbury, J.A., 2018, Groundwater quality in the Mississippi embayment–Texas coastal uplands aquifer system, south-central United States (ver. 1.1, September 2020): U.S. Geological Survey Fact Sheet 2018–3067, 4 p., https://doi.org/10.3133/fs20183067.","productDescription":"4 p.","ipdsId":"IP-097552","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":358167,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3067/fs20183067_v1.1.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3067"},{"id":378457,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2018/3067/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":358166,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3067/coverthb.jpg"}],"country":"United States","otherGeospatial":"Mississippi Embayment–Texas Coastal Uplands Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100,\n 26\n ],\n [\n -87,\n 26\n ],\n [\n -87,\n 37.16031654673677\n ],\n [\n -100,\n 37.16031654673677\n ],\n [\n -100,\n 26\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: November 26, 2018; Version 1.1: September 16, 2020","contact":"National Water-Quality Assessment (NAWQA) Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water (Burow and Belitz, 2014). The Floridan aquifer system constitutes one of the important aquifer systems being evaluated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183066","usgsCitation":"Kingsbury, J.A., 2018, Groundwater quality in the Floridan aquifer system, Southeastern United States: U.S. Geological Survey Fact Sheet 2018–3066, 4 p., https://doi.org/10.3133/fs20183066.","productDescription":"4 p.","ipdsId":"IP-097551","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":358164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3066/coverthb.jpg"},{"id":358165,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3066/fs20183066.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3066"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","otherGeospatial":"Floridan Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.978515625,\n 25.64152637306577\n ],\n [\n -79.07958984375,\n 25.64152637306577\n ],\n [\n -79.07958984375,\n 33.33970700424026\n ],\n [\n -87.978515625,\n 33.33970700424026\n ],\n [\n -87.978515625,\n 25.64152637306577\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"National Water-Quality Assessment (NAWQA) Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
Background: The isolated population of desert bighorn sheep in the Silver Bell Mountains of southern Arizona underwent an unprecedented expansion in merely four years. We hypothesized that immigration from neighboring bighorn sheep populations could have caused the increase in numbers as detected by Arizona Game and Fish Department annual aerial counts.
Methods: We applied a multilocus genetic approach using mitochondrial DNA and nuclear microsatellite markers for genetic analyses to find evidence of immigration. We sampled the Silver Bell Mountains bighorn sheep before (2003) and during (2015) the population expansion, and a small number of available samples from the Gila Mountains (southwestern Arizona) and the Morenci Mine (Rocky Mountain bighorn) in an attempt to identify the source of putative immigrants and, more importantly, to serve as comparisons for genetic diversity metrics.
Results: We did not find evidence of substantial gene flow into the Silver Bell Mountains population. We did not detect any new mitochondrial haplotypes in the 2015 bighorn sheep samples. The microsatellite analyses detected only one new allele, in one individual from the 2015 population that was not detected in the 2003 samples. Overall, the genetic diversity of the Silver Bell Mountains population was lower than that seen in either the Gila population or the Morenci Mine population.
Discussion: Even though the results of this study did not help elucidate the precise reason for the recent population expansion, continued monitoring and genetic sampling could provide more clarity on the genetic demographics of this population.
Keywords: Bighorn sheep; Microsatellites; Migration; Mitochondrial DNA; Ovis canadensis; Population growth; Silver Bell Mountains.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.5978","usgsCitation":"Erwin, J.A., Vargasc, K., Blaisc, B.R., Bennettc, K., Muldoond, J., Findysz, S., Christiec, C., Heffelfingere, J.R., and Culver, M., 2018, Genetic assessment of a bighorn sheep population expansion in the Silver Bell Mountains, Arizona: PeerJ, v. 6, e5978, https://doi.org/10.7717/peerj.5978.","productDescription":"e5978","ipdsId":"IP-098318","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468234,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.5978","text":"Publisher Index Page"},{"id":395751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Silver Bell 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