During the extended history of mining in the upper Clark Fork Basin in Montana, large amounts of waste materials enriched with metallic contaminants (cadmium, copper, lead, and zinc) and the metalloid trace element arsenic were generated from mining operations near Butte and milling and smelting operations near Anaconda. Extensive deposition of mining wastes in the Silver Bow Creek and Clark Fork channels and flood plains had substantial effects on water quality. Federal Superfund remediation activities in the upper Clark Fork Basin began in 1983 and have included substantial remediation near Butte and removal of the former Milltown Dam near Missoula. To aid in evaluating the effects of remediation activities on water quality, the U.S. Geological Survey began collecting streamflow and water-quality data in the upper Clark Fork Basin in the 1980s.
Trend analysis was done on specific conductance, selected trace elements (arsenic, copper, and zinc), and suspended sediment for seven sampling sites in the Milltown Reservoir/Clark Fork River Superfund Site for water years 1996–2015. The most upstream site included in trend analysis is Silver Bow Creek at Warm Springs, Montana (sampling site 8), and the most downstream site is Clark Fork above Missoula, Montana (sampling site 22), which is just downstream from the former Milltown Dam. Water year is the 12-month period from October 1 through September 30 and is designated by the year in which it ends. Trend analysis was done by using a joint time-series model for concentration and streamflow. To provide temporal resolution of changes in water quality, trend analysis was conducted for four sequential 5-year periods: period 1 (water years 1996–2000), period 2 (water years 2001–5), period 3 (water years 2006–10), and period 4 (water years 2011–15). Because of the substantial effect of the intentional breach of Milltown Dam on March 28, 2008, period 3 was subdivided into period 3A (October 1, 2005–March 27, 2008) and period 3B (March 28, 2008–September 30, 2010) for the Clark Fork above Missoula (sampling site 22). Trend results were considered statistically significant when the statistical probability level was less than 0.01.
In conjunction with the trend analysis, estimated normalized constituent loads (hereinafter referred to as “loads”) were calculated and presented within the framework of a constituent-transport analysis to assess the temporal trends in flow-adjusted concentrations (FACs) in the context of sources and transport. The transport analysis allows assessment of temporal changes in relative contributions from upstream source areas to loads transported past each reach outflow.
Trend results indicate that FACs of unfiltered-recoverable copper decreased at the sampling sites from the start of period 1 through the end of period 4; the decreases ranged from large for one sampling site (Silver Bow Creek at Warm Springs [sampling site 8]) to moderate for two sampling sites (Clark Fork near Galen, Montana [sampling site 11] and Clark Fork above Missoula [sampling site 22]) to small for four sampling sites (Clark Fork at Deer Lodge, Montana [sampling site 14], Clark Fork at Goldcreek, Montana [sampling site 16], Clark Fork near Drummond, Montana [sampling site 18], and Clark Fork at Turah Bridge near Bonner, Montana [sampling site 20]). For period 4 (water years 2011–15), the most notable changes indicated for the Milltown Reservoir/Clark Fork River Superfund Site were statistically significant decreases in FACs and loads of unfiltered-recoverable copper for sampling sites 8 and 22. The period 4 changes in FACs of unfiltered-recoverable copper for all other sampling sites were not statistically significant.
Trend results indicate that FACs of unfiltered-recoverable arsenic decreased at the sampling sites from period 1 through period 4 (water years 1996–2015); the decreases ranged from minor (sampling sites 8–20) to small (sampling site 22). For period 4 (water years 2011–15), the most notable changes indicated for the Milltown Reservoir/Clark Fork River Superfund Site were statistically significant decreases in FACs and loads of unfiltered-recoverable arsenic for sampling site 8 and near statistically significant decreases for sampling site 22. The period 4 changes in FACs of unfiltered-recoverable arsenic for all other sampling sites were not statistically significant.
Trend results indicate that FACs of suspended sediment decreased at the sampling sites from period 1 through period 4 (water years 1996–2015); the decreases ranged from moderate (sampling site 8) to small (sampling sites 11–22). For period 4 (water years 2011–15), the changes in FACs of suspended sediment were not statistically significant for any sampling sites.
The reach of the Clark Fork from Galen to Deer Lodge is a large source of metallic contaminants and suspended sediment, which strongly affects downstream transport of those constituents. Mobilization of copper and suspended sediment from flood-plain tailings and the streambed of the Clark Fork and its tributaries within the reach results in a contribution of those constituents that is proportionally much larger than the contribution of streamflow from within the reach. Within the reach from Galen to Deer Lodge, unfiltered-recoverable copper loads increased by a factor of about 4 and suspended-sediment loads increased by a factor of about 5, whereas streamflow increased by a factor of slightly less than 2. For period 4 (water years 2011–15), unfiltered-recoverable copper and suspended-sediment loads sourced from within the reach accounted for about 41 and 14 percent, respectively, of the loads at Clark Fork above Missoula (sampling site 22), whereas streamflow sourced from within the reach accounted for about 4 percent of the streamflow at sampling site 22. During water years 1996–2015, decreases in FACs and loads of unfiltered-recoverable copper and suspended sediment for the reach generally were proportionally smaller than for most other reaches.
Unfiltered-recoverable copper loads sourced within the reaches of the Clark Fork between Deer Lodge and Turah Bridge near Bonner (just upstream from the former Milltown Dam) were proportionally smaller than contributions of streamflow sourced from within the reaches; these reaches contributed proportionally much less to copper loading in the Clark Fork than the reach between Galen and Deer Lodge. Although substantial decreases in FACs and loads of unfiltered-recoverable copper and suspended sediment were indicated for Silver Bow Creek at Warm Springs (sampling site 8), those substantial decreases were not translated to downstream reaches between Deer Lodge and Turah Bridge near Bonner. The effect of the reach of the Clark Fork from Galen to Deer Lodge as a large source of copper and suspended sediment, in combination with little temporal change in those constituents for the reach, contributes to this pattern.
With the removal of the former Milltown Dam in 2008, substantial amounts of contaminated sediments that remained in the Clark Fork channel and flood plain in reach 9 (downstream from Turah Bridge near Bonner) became more available for mobilization and transport than before the dam removal. After the removal of the former Milltown Dam, the Clark Fork above Missoula (sampling site 22) had statistically significant decreases in FACs of unfiltered-recoverable copper in period 3B (March 28, 2008, through water year 2010) that continued in period 4 (water years 2011–15). Also, decreases in FACs of unfiltered-recoverable arsenic and suspended sediment were indicated for period 4 at this site. The decrease in FACs of unfiltered-recoverable copper for sampling site 22 during period 4 was proportionally much larger than the decrease for the Clark Fork at Turah Bridge near Bonner (sampling site 20). Net mobilization of unfiltered-recoverable copper and arsenic from sources within reach 9 are smaller for period 4 than for period 1 when the former Milltown Dam was in place, providing evidence that contaminant source materials have been substantially reduced in reach 9.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165100","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Sando, S.K., and Vecchia, A.V., 2016, Water-quality trends and constituent-transport analysis for selected sampling sites in the Milltown Reservoir/Clark Fork River Superfund Site in the upper Clark Fork Basin, Montana, water years 1996–2015: U.S. Geological Survey Scientific Investigations Report 2016–5100, 82 p., https://dx.doi.org/10.3133/sir20165100.","productDescription":"viii, 82 p.","numberOfPages":"94","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1996-10-01","ipdsId":"IP-074218","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":325351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5100/coverthb.jpg"},{"id":325352,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5100/sir20165100.pdf","text":"Report","size":"3.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5100"}],"country":"United States","state":"Montana","otherGeospatial":"Upper Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 45.706179285330855\n ],\n [\n -114.027099609375,\n 47.517200697839414\n ],\n [\n -112.225341796875,\n 47.517200697839414\n ],\n [\n -112.225341796875,\n 45.706179285330855\n ],\n [\n -114.027099609375,\n 45.706179285330855\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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Estuarine habitat occupied by Alligator mississippiensis, a primarily freshwater species, is spatially and temporally heterogeneous largely due to a salinity gradient that fluctuates. Using long-term night light survey data, we examined seasonal patterns in alligators’ habitat use by size classes in midstream and downstream estuary zones of Shark River, Everglades National Park, in southern Florida. We observed predominantly large-sized alligators (total length ≥ 1.75 m); observations of alligators in the small size classes (0.5 m ≤ total length < 1.25 m) were rare especially in the higher-salinity downstream zone. The density of alligators in the downstream zone was lower than that of the midstream zone during the dry season when salinity increases due to reduced precipitation. Conversely, the density of the large size alligators was higher in the downstream zone than in the midstream zone during the wet season, likely because of reduced salinity. We also found a significant declining trend over time in the number of alligators in the dry season, which coincides with the reported decline in alligator relative density in southern Florida freshwater wetlands. Our results indicated high adaptability of alligators to the fluctuating habitat conditions. Use of estuaries by alligators is likely driven in part by physiology and possibly by reproductive cycle, and our results supported their opportunistic use of estuary habitat and ontogenetic niche shifts.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-016-0084-2","usgsCitation":"Fujisaki, I., Hart, K.M., Cherkiss, M.S., Mazzotti, F., Beauchamp, J.S., Jeffery, B.M., and Brandt, L., 2016, Spatial and temporal variability in estuary habitat use by American alligators: Estuaries and Coasts, v. 39, no. 5, p. 1561-1569, https://doi.org/10.1007/s12237-016-0084-2.","productDescription":"9 p.","startPage":"1561","endPage":"1569","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060689","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":325444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park, Shark River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n 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With advances in telemetry capabilities, animal movement models are becoming increasingly sophisticated. Despite a need for population-level inference, animal movement models are still predominantly developed for individual-level inference. Most efforts to upscale the inference to the population level are either post hoc or complicated enough that only the developer can implement the model. Hierarchical Bayesian models provide an ideal platform for the development of population-level animal movement models but can be challenging to fit due to computational limitations or extensive tuning required. We propose a two-stage procedure for fitting hierarchical animal movement models to telemetry data. The two-stage approach is statistically rigorous and allows one to fit individual-level movement models separately, then resample them using a secondary MCMC algorithm. The primary advantages of the two-stage approach are that the first stage is easily parallelizable and the second stage is completely unsupervised, allowing for an automated fitting procedure in many cases. We demonstrate the two-stage procedure with two applications of animal movement models. The first application involves a spatial point process approach to modeling telemetry data, and the second involves a more complicated continuous-time discrete-space animal movement model. We fit these models to simulated data and real telemetry data arising from a population of monitored Canada lynx in Colorado, USA.
","language":"English","publisher":"Wiley-Blackwell ","doi":"10.1002/env.2402","usgsCitation":"Hooten, M., Buderman, F.E., Brost, B.M., Hanks, E., and Ivans, J.S., 2016, Hierarchical animal movement models for population-level inference: Environmetrics , v. 27, no. 6, p. 322-333, https://doi.org/10.1002/env.2402.","productDescription":"12 p.","startPage":"322","endPage":"333","ipdsId":"IP-076019","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470741,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1606.09585","text":"External Repository"},{"id":331665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-19","publicationStatus":"PW","scienceBaseUri":"58492df2e4b06d80b7b093a4","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":655144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":655198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":655199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanks, Ephraim M.","contributorId":104630,"corporation":false,"usgs":true,"family":"Hanks","given":"Ephraim M.","affiliations":[],"preferred":false,"id":655200,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ivans, Jacob S.","contributorId":177286,"corporation":false,"usgs":false,"family":"Ivans","given":"Jacob","email":"","middleInitial":"S.","affiliations":[{"id":16861,"text":"Colorado Parks and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":655201,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176135,"text":"70176135 - 2016 - Island characteristics within wetlands influence waterbird nest success and abundance","interactions":[],"lastModifiedDate":"2017-10-30T09:44:20","indexId":"70176135","displayToPublicDate":"2016-07-18T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Island characteristics within wetlands influence waterbird nest success and abundance","docAbstract":"Coastal waterbird populations are threatened by habitat loss and degradation from urban and agricultural development and forecasted sea level rise associated with climate change. Remaining wetlands often must be managed to ensure that waterbird habitat needs, and other ecosystem functions, are met. For many waterbirds, the availability of island nesting habitat is important for conserving breeding populations. We used linear mixed models to investigate the influence of pond and island landscape characteristics on nest abundance and nest success of American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), and Forster's terns (Sterna forsteri) in San Francisco Bay, California, USA, based on a 9-year dataset that included >9,000 nests. Nest abundance and nest success were greatest within ponds and on individual islands located either <1 km or >4 km from San Francisco Bay. Further, nest abundance was greater within ponds with relatively few islands, and on linear-shaped, highly elongated islands compared to more rounded islands. Nest success was greater on islands located away from the nearest surrounding pond levee. Compared to more rounded islands, linear islands contained more near-water habitat preferred by many nesting waterbirds. Islands located away from pond levees may provide greater protection from terrestrial egg and chick predators. Our results indicate that creating and maintaining a few, relatively small, highly elongated and narrow islands away from mainland levees, in as many wetland ponds as possible would be effective at providing waterbirds with preferred nesting habitat.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21120","usgsCitation":"Hartman, C.A., Ackerman, J., and Herzog, M.P., 2016, Island characteristics within wetlands influence waterbird nest success and abundance: Journal of Wildlife Management, v. 80, no. 7, p. 1177-1188, https://doi.org/10.1002/jwmg.21120.","productDescription":"11 p.","startPage":"1177","endPage":"1188","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075274","costCenters":[{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":328034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.22290039062499,\n 38.07187927827001\n ],\n [\n -122.30804443359375,\n 38.151837403006766\n ],\n [\n -122.39593505859376,\n 38.16911413556086\n ],\n [\n -122.53051757812499,\n 38.10646650598286\n ],\n [\n -122.57171630859375,\n 38.01131226070673\n ],\n [\n -122.64038085937499,\n 37.896530447543\n ],\n [\n -122.62664794921874,\n 37.78156937014928\n ],\n [\n -122.58270263671876,\n 37.65773212628274\n ],\n [\n -122.53601074218751,\n 37.61423141542417\n ],\n [\n -122.5250244140625,\n 37.43343148473673\n ],\n [\n -122.44262695312501,\n 37.34832607355296\n ],\n [\n -122.08282470703124,\n 37.36797435878155\n ],\n [\n -121.88232421875,\n 37.39416407012379\n ],\n [\n -121.80816650390625,\n 37.446516047833484\n ],\n [\n -121.77520751953125,\n 37.62075814551956\n ],\n [\n -121.728515625,\n 37.75551557687061\n ],\n [\n -121.7120361328125,\n 37.85316995894978\n ],\n [\n -121.91253662109376,\n 37.98317483351337\n ],\n [\n -121.9921875,\n 38.02862223458794\n ],\n [\n -122.22290039062499,\n 38.07187927827001\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"57c6b091e4b0f2f0cebe5e77","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":647418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":647417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":647419,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174157,"text":"70174157 - 2016 - Evaluating habitat associations of a fish assemblage at multiple spatial scales in a minimally disturbed stream using low‐cost remote sensing","interactions":[],"lastModifiedDate":"2021-03-18T13:12:27.644533","indexId":"70174157","displayToPublicDate":"2016-07-18T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating habitat associations of a fish assemblage at multiple spatial scales in a minimally disturbed stream using low‐cost remote sensing","docAbstract":"Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and ice sheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992–2015 show time-varying trends with respect to displacement over time in California’s San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm/yr with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm/yr. Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm/yr and cumulative subsidence as much as 155 cm.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep28160","usgsCitation":"Hwang, C., Yang, Y., Kao, R., Han, J., Shum, C., Galloway, D.L., Sneed, M., Hung, W., Cheng, Y., and Li, F., 2016, Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China: Scientific Reports, v. 6, p. 1-12, https://doi.org/10.1038/srep28160.","productDescription":"Article 28160; 12 p.","startPage":"1","endPage":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066742","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":470742,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep28160","text":"Publisher Index Page"},{"id":325357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Taiwan, United States","state":"California","volume":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"578defa4e4b0f1bea0e03bd5","contributors":{"authors":[{"text":"Hwang, Cheinway 0000-0002-3322-353X","orcid":"https://orcid.org/0000-0002-3322-353X","contributorId":172932,"corporation":false,"usgs":false,"family":"Hwang","given":"Cheinway","email":"","affiliations":[{"id":27120,"text":"Department of Civil Engineering, National Chiao Tung University, Taiwan","active":true,"usgs":false}],"preferred":false,"id":642676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Yuande","contributorId":172933,"corporation":false,"usgs":false,"family":"Yang","given":"Yuande","email":"","affiliations":[{"id":27121,"text":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, China","active":true,"usgs":false}],"preferred":false,"id":642677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kao, Ricky","contributorId":172934,"corporation":false,"usgs":false,"family":"Kao","given":"Ricky","email":"","affiliations":[{"id":27120,"text":"Department of Civil Engineering, National Chiao Tung University, Taiwan","active":true,"usgs":false}],"preferred":false,"id":642678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Han, Jiancheng","contributorId":172935,"corporation":false,"usgs":false,"family":"Han","given":"Jiancheng","email":"","affiliations":[{"id":27120,"text":"Department of Civil Engineering, National Chiao Tung University, Taiwan","active":true,"usgs":false}],"preferred":false,"id":642679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shum, C.K.","contributorId":172936,"corporation":false,"usgs":false,"family":"Shum","given":"C.K.","email":"","affiliations":[{"id":27122,"text":"Division of Geodetic Science, School of Earth Science, the Ohio State University","active":true,"usgs":false}],"preferred":false,"id":642680,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":642675,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642681,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hung, Wei-Chia","contributorId":172937,"corporation":false,"usgs":false,"family":"Hung","given":"Wei-Chia","email":"","affiliations":[{"id":27123,"text":"Green Environmental Engineering Consultant Co. LTD, Hsinchu, Taiwan","active":true,"usgs":false}],"preferred":false,"id":642682,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cheng, Yung-Sheng","contributorId":172938,"corporation":false,"usgs":false,"family":"Cheng","given":"Yung-Sheng","email":"","affiliations":[{"id":27120,"text":"Department of Civil Engineering, National Chiao Tung University, Taiwan","active":true,"usgs":false}],"preferred":false,"id":642683,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Li, Fei","contributorId":172939,"corporation":false,"usgs":false,"family":"Li","given":"Fei","email":"","affiliations":[{"id":27121,"text":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, China","active":true,"usgs":false}],"preferred":false,"id":642684,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70174832,"text":"70174832 - 2016 - Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010","interactions":[],"lastModifiedDate":"2017-04-07T13:54:11","indexId":"70174832","displayToPublicDate":"2016-07-18T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1183,"text":"Carbon Balance and Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010","docAbstract":"Background: Human activities have diverse and profound impacts on ecosystem carbon cycles. The Piedmont ecoregion in the eastern United States has undergone significant land use and land cover change in the past few decades. The purpose of this study was to use newly available land use and land cover change data to quantify carbon changes within the ecoregion. Land use and land cover change data (60-m spatial resolution) derived from sequential remotely sensed Landsat imagery were used to generate 960-m resolution land cover change maps for the Piedmont ecoregion. These maps were used in the Integrated Biosphere Simulator (IBIS) to simulate ecosystem carbon stock and flux changes from 1971 to 2010. Results: Results show that land use change, especially urbanization and forest harvest had significant impacts on carbon sources and sinks. From 1971 to 2010, forest ecosystems sequestered 0.25 Mg C ha−1 yr−1, while agricultural ecosystems sequestered 0.03 Mg C ha−1 yr−1. The total ecosystem C stock increased from 2271 Tg C in 1971 to 2402 Tg C in 2010, with an annual average increase of 3.3 Tg C yr−1. Conclusions: Terrestrial lands in the Piedmont ecoregion were estimated to be weak net carbon sink during the study period. The major factors contributing to the carbon sink were forest growth and afforestation; the major factors contributing to terrestrial emissions were human induced land cover change, especially urbanization and forest harvest. An additional amount of carbon continues to be stored in harvested wood products. If this pool were included the carbon sink would be stronger. Keywords: Land-use change, Carbon change, Piedmont ecoregion, IBIS model
","language":"English","publisher":"Springer","doi":"10.1186/s13021-016-0052-y","usgsCitation":"Liu, J., Sleeter, B.M., Zhu, Z., Heath, L., Tan, Z., Wilson, T., Sherba, J.T., and Zhou, D., 2016, Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010: Carbon Balance and Management, v. 11, no. 10, p. 1-13, https://doi.org/10.1186/s13021-016-0052-y.","productDescription":"13 p.","startPage":"1","endPage":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075244","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470744,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13021-016-0052-y","text":"Publisher Index Page"},{"id":325355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-13","publicationStatus":"PW","scienceBaseUri":"578defa3e4b0f1bea0e03bc9","chorus":{"doi":"10.1186/s13021-016-0052-y","url":"http://dx.doi.org/10.1186/s13021-016-0052-y","publisher":"Springer Nature","authors":"Liu Jinxun, Sleeter Benjamin M., Zhu Zhiliang, Heath Linda S., Tan Zhengxi, Wilson Tamara S., Sherba Jason, Zhou Decheng","journalName":"Carbon Balance and Management","publicationDate":"6/13/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"6/13/2016"},"contributors":{"authors":[{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":642686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":642687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":642688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heath, Linda S.","contributorId":84207,"corporation":false,"usgs":true,"family":"Heath","given":"Linda S.","affiliations":[],"preferred":false,"id":642692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tan, Zhengxi 0000-0002-4136-0921 ztan@usgs.gov","orcid":"https://orcid.org/0000-0002-4136-0921","contributorId":2945,"corporation":false,"usgs":true,"family":"Tan","given":"Zhengxi","email":"ztan@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":642689,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Tamara 0000-0001-7399-7532 tswilson@usgs.gov","orcid":"https://orcid.org/0000-0001-7399-7532","contributorId":2975,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"tswilson@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":642690,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sherba, Jason T. jsherba@usgs.gov","contributorId":5972,"corporation":false,"usgs":true,"family":"Sherba","given":"Jason","email":"jsherba@usgs.gov","middleInitial":"T.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":642691,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhou, Decheng","contributorId":172941,"corporation":false,"usgs":false,"family":"Zhou","given":"Decheng","email":"","affiliations":[{"id":27124,"text":"Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China","active":true,"usgs":false}],"preferred":false,"id":642693,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174021,"text":"ofr20161108 - 2016 - Pacific walrus coastal haulout database, 1852-2016— Background report","interactions":[],"lastModifiedDate":"2018-06-16T17:47:52","indexId":"ofr20161108","displayToPublicDate":"2016-07-18T12:00:00","publicationYear":"2016","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":"2016-1108","title":"Pacific walrus coastal haulout database, 1852-2016— Background report","docAbstract":"Walruses are large benthic predators that rest out of water between foraging bouts. Coastal “haulouts” (places where walruses rest) are formed by adult males in summer and sometimes by females and young when sea ice is absent, and are often used repeatedly across seasons and years. Understanding the geography and historical use of haulouts provides a context for conservation efforts. We summarize information on Pacific walrus haulouts from available reports (n =151), interviews with coastal residents and aviators, and personal observations of the authors. We provide this in the form of a georeferenced database that can be queried and displayed with standard geographic information system and database management software. The database contains 150 records of Pacific walrus haulouts, with a summary of basic characteristics on maximum haulout aggregation size, age-sex composition, season of use, and decade of most recent use. Citations to reports are provided in the appendix and as a bibliographic database. Haulouts were distributed across the coasts of the Pacific walrus range; however, the largest (maximum >10,000 walruses) of the haulouts reported in the recent 4 decades (n=19) were concentrated on the Russian shores in regions near the Bering Strait and northward into the western Chukchi Sea (n=17). Haulouts of adult female and young walruses primarily occurred in the Bering Strait region and areas northward, with others occurring in the central Bering Sea, Gulf of Anadyr, and Saint Lawrence Island regions. The Gulf of Anadyr was the only region to contain female and young walrus haulouts, which formed after the northward spring migration and prior to autumn ice formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161108","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and Chukot-TINRO and Institute of Biological Problems of the North Far East Branch of Russian Academy of Sciences","usgsCitation":"Fischbach, A.S., Kochnev, A.A., Garlich-Miller, J.L., and Jay, C.V., 2016, Pacific walrus coastal haulout database, 1852-2016— Background report: U.S. Geological Survey Open-File Report 2016-1108, Report: iv, 27 p.; Data Release, https://doi.org/10.3133/ofr20161108.","productDescription":"Report: iv, 27 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076335","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":325339,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7RX994P","text":"USGS data release","description":"USGS data release","linkHelpText":"Pacific Walrus Coastal Haulout Database, 1852-2016"},{"id":438584,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VD6WK5","text":"USGS data release","linkHelpText":"ArcGIS Mapping Service for Pacific Walrus Coastal Haulouts"},{"id":438583,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RX994P","text":"USGS data release","linkHelpText":"Pacific Walrus Coastal Haulout Database 1852-2016"},{"id":325338,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1108/ofr20161108.pdf","text":"Report","size":"1.3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1108 Report PDF"},{"id":325337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1108/coverthb.jpg"}],"country":"Russia, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -203.642578125,\n 50.12057809796008\n ],\n [\n -203.642578125,\n 72.18180355624855\n ],\n [\n -149.765625,\n 72.18180355624855\n ],\n [\n -149.765625,\n 50.12057809796008\n ],\n [\n -203.642578125,\n 50.12057809796008\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr
Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
The Equus Beds aquifer in south-central Kansas is aprimary water source for the city of Wichita. The Equus Beds aquifer storage and recovery (ASR) project was developed to help the city of Wichita meet increasing current (2016) and future water demands. The Equus Beds ASR project pumps water out of the Little Arkansas River during above-base flow conditions, treats it using drinking-water quality standards as a guideline, and recharges it into the Equus Beds aquifer for later use. Phase II of the Equus Beds ASR project currently (2016) includes a river intake facility and a surface-water treatment facility with a 30 million gallon per day capacity. Water diverted from the Little Arkansas River is delivered to an adjacent presedimentation basin for solids removal. Subsequently, waste from the surface-water treatment facility and the presedimentation basin is returned to the Little Arkansas River through a residuals return line. The U.S. Geological Survey, in cooperation with the city of Wichita, developed and implemented a hydrobiological monitoring program as part of the ASR project to characterize and quantify the effects of aquifer storage and recovery activities on the Little Arkansas River and Equus Beds aquifer water quality.
Data were collected from 2 surface-water sites (one upstream and one downstream from the residuals return line), 1 residuals return line site, and 2 groundwater well sites (each having a shallow and deep part): the Little Arkansas River upstream from the ASR facility near Sedgwick, Kansas (upstream surface-water site 375350097262800), about 0.03 mile (mi) upstream from the residuals return line site; the Little Arkansas River near Sedgwick, Kans. (downstream surface-water site 07144100), about 1.68 mi downstream from the residuals return line site; discharge from the Little Arkansas River ASR facility near Sedgwick, Kansas (residuals return line site 375348097262800); 25S 01 W 07BCCC01 SMW–S11 near CW36 (MW–7 shallow groundwater well site 375327097285401); 25S01 W 07BCCC02 DMW–S10 near CW36 (MW–7 deep groundwater well site 375327097285402); 25S 01W 07BCCA01 SMW–S13 near CW36 (MW–8 shallow groundwater well site 375332097284801); and 25S 01W 07BCCA02 DMW–S14 near CW36 (MW–8 deep groundwater well site 375332097284802). The U.S. Geological Survey, in cooperation with the city of Wichita, assessed the effects of the ASR Phase II facility residuals return line discharges on stream quality of the Little Arkansas River by measuring continuous physicochemical properties and collecting discrete water-quality and sediment samples for about 2 years pre- (January 2011 through April 2013) and post-ASR (May 2013 through December 2014) Phase II facility operation upstream and downstream from the ASR Phase II facility. Additionally, habitat variables were quantified and macroinvertebrate and fish communities were sampled upstream and downstream from the ASR Phase II facility during the study period. To assess the effects of aquifer recharge on Equus Beds groundwater quality, continuous physicochemical properties were measured and discrete water-quality samples were collected before and during the onset of Phase II aquifer recharge in two (shallow and deep) groundwater wells.
Little Arkansas River streamflow was about 10 times larger after the facility began operating because of greater rainfall. Residuals return line release volumes were a very minimal proportion (0.06 percent) of downstream streamflow volume during the months the ASR facility was operating. Upstream and downstream continuously measured water temperature and dissolved oxygen median differences were smaller post-ASR than pre-ASR. Turbidity generally was smaller at the downstream site throughout the study period and decreased at both sites after the ASR Phase II facility began discharging despite a median residuals return line turbidity that was about an order of magnitude larger than the median turbidity at the downstream site. Upstream and downstream continuously measured turbidity median differences were larger post-ASR than pre-ASR. Median post-ASR continuously measured nitrite plus nitrate and continuously computed total suspended solids and suspended-sediment concentrations were smaller than pre-ASR likely because of higher streamflows and dilution; whereas, median continuously computed dissolved and total organic carbon concentrations were larger likely because of higher streamflows and runoff conditions.
None of the discretely measured water-quality constituents (dissolved and suspended solids, primary ions, suspended sediment, nutrients, carbon, trace elements, viral and bacterial indicators, and pesticides) in surface water were significantly different between the upstream and downstream sites after the ASR Phase II facility began discharging; however, pre-ASR calcium, sodium, hardness, manganese, and arsenate concentrations were significantly larger at the upstream site, which indicates that some water-quality conditions at the upstream and downstream sites were more similar post-ASR. Most of the primary constituents that make up dissolved solids decreased at both sites after the ASR Phase II facility began operation. Discretely collected total suspended solids concentrations were similar between the upstream and downstream sites before the facility began operating but were about 27 percent smaller at the downstream site after the facility began operating, despite the total suspended solids concentrations in the residuals return line being 15 times larger than the downstream site.
Overall habitat scores were indicative of suboptimal conditions upstream and downstream from the ASR Phase II facility throughout the study period. Substrate fouling and sediment deposition mean scores indicated marginal conditions at the upstream and downstream sites during the study period, demonstrating that sediment deposition was evident pre- and post-ASR and no substantial changes in these habitat characteristics were noted after the ASR Phase II facility began discharging. Macroinvertebrate community composition (evaluated using functional feeding, behavioral, and tolerance metrics) generally was similar between sites during the study period. Fewer macroinvertebrate metrics were significant between the upstream and downstream sites post-ASR (6) than pre-ASR (14), which suggests that macroinvertebate communities were more similar after the ASR facility began discharging. Upstream-downstream comparisons in macroinvertebrate aquatic-life-support metrics had no significant differences for the post-ASR time period and neither site was fully supporting for any of the Kansas Department of Health and Environment aquatic-life-support metrics (Macroinvertebrate Biotic Index; Kansas Biotic Index with tolerances for nutrients and oxygen-demanding substances; Ephemeroptera, Plecoptera, and Trichoptera [EPT] richness; and percentage of EPT species). Overall, using macroinvertebrate aquatic life-support criteria from the Kansas Department of Health and Environment, upstream and downstream sites were classified as partially supporting before and after the onset of ASR facility operations. Fish community trophic status and tolerance groups generally were similar among sites during the study period. Fish community Little Arkansas River Basin Index of Biotic Integrity scores at the upstream and downstream sites were indicative of fair-to-good conditions before the facility began operating and decreased to fair conditions after the facility began operating.
Groundwater physicochemical changes concurrent with the beginning of recharge operations at the Sedgwick basin were more pronounced in shallow groundwater. No constituent concentrations in the pre-recharge period in comparison to the post-recharge period increased to concentrations exceeding drinking water regulations; however, nitrate decreased significantly from a pre-recharge exceedance of the U.S. Environmental Protection Agency maximum contaminant level to a post recharge nonexceedance. Shallow groundwater chemical concentrations or rates of detection increased after artificial recharge began for the ions potassium, chloride, and fluoride; phosphorus and organic carbon species; trace elements barium, manganese, nickel, arsenate, arsenic, and boron; agricultural pesticides atrazine, metolachlor, metribuzin, and simazine; organic disinfection byproducts bromodichloromethane and trichloromethane; and gross beta levels. Additionally, water temperature, and pH were larger after recharge began; and total solids and slime-forming bacteria concentrations and densities were smaller. Total solids, nitrate, and selenium significantly decreased; and potassium, chloride, nickel, arsenic, fluoride, phosphorus and carbon species, and gross beta levels significantly increased in shallow groundwater after artificial recharge. Results of biological activity reaction tests indicated that water quality microbiology was different before and after artificial recharge began; at times, these differences may lead to changes in dominant bacterial populations that, in turn, may lead to formation and expansion in populations that may cause bioplugging and other unwanted effects. Calcite, iron (II) hydroxide, hydroxyapatite, and similar minerals, had shifts in saturation indices that generally were from undersaturation toward equilibrium and, in some cases, toward oversaturation. These shifts toward neutral saturation indices might suggest reduced weathering of the minerals present in the Equus Beds aquifer. Chemical weathering in the shallow parts of the aquifer may be accelerated because of the increased water temperatures and the system is more vulnerable to clogged pores and mineral dissolution as the equilibrium state is affected by recharge and withdrawal. When oversaturation is indicated for iron minerals, plugging of aquifer materials may happen.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165042","collaboration":"Prepared in cooperation with the City of Wichita, Kansas","usgsCitation":"Stone, M.L., Garrett, J.D., Poulton, B.C., and Ziegler, A.C., 2016, Effects of aquifer storage and recovery activities on water quality in the Little Arkansas River and Equus Beds aquifer, south-central Kansas, 2011–14: U.S. Geological Survey Scientific Investigations Report 2016–5024, 88 p., https://dx.doi.org/10.3133/sir20165042.","productDescription":"Report: xii, 88 p.; Appendix Files","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068666","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":325362,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5042/sir20165042.pdf","text":"Report","size":"5.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5024"},{"id":325361,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5042/coverthb.jpg"},{"id":325363,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5042/sir20165042_appendixtables.xlsx","text":"Appendix Files","size":"199 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5024 Appendix Files"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.70416259765625,\n 38.10106333042556\n ],\n [\n -97.57232666015625,\n 38.09998264736481\n ],\n [\n -97.57781982421875,\n 38.08160859009049\n ],\n [\n -97.55035400390625,\n 38.0545795282119\n ],\n [\n -97.525634765625,\n 38.019967758742766\n ],\n [\n -97.48580932617188,\n 38.01239425385966\n ],\n [\n -97.43499755859374,\n 37.94203148678865\n ],\n [\n -97.42813110351562,\n 37.90845010709064\n ],\n [\n -97.36221313476562,\n 37.814123701604466\n ],\n [\n -97.46520996093749,\n 37.814123701604466\n ],\n [\n -97.47894287109375,\n 37.82280243352756\n ],\n [\n -97.50640869140625,\n 37.820632846207864\n ],\n [\n -97.52838134765624,\n 37.83473402375478\n ],\n [\n -97.57095336914062,\n 37.85859141570558\n ],\n [\n -97.61764526367188,\n 37.87702138607635\n ],\n [\n -97.67120361328125,\n 37.88677656291023\n ],\n [\n -97.70278930664062,\n 37.898697801966094\n ],\n [\n -97.70416259765625,\n 38.10106333042556\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place Lawrence, KS 66049
In 2015, the U.S. Geological Survey (USGS) released an updated assessment of undiscovered, technically recoverable shale gas and shale oil resources of the Mississippian Barnett Shale in north-central Texas (Marra and others, 2015). The Barnett Shale was assessed using the standard continuous (unconventional) methodology established by the USGS for two assessment units (AUs): (1) Barnett Continuous Gas AU, and (2) Barnett Mixed Continuous Gas and Oil AU. A third assessment unit, the Western Barnett Continuous Oil AU, was also defined but was not quantitatively assessed because of limited data within the extent of the AU. The purpose of this report is to provide supplemental documentation of the quantitative input parameters applied in the Barnett Shale assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20161097","usgsCitation":"Marra, K.R., Charpentier, R.R., Schenk, C.J., Lewan, M.D., Leathers-Miller, H.M., Klett, T.R., Gaswirth, S.B., Le, P.A., Mercier, T.J., Pitman, J.K., and Tennyson, M.E., 2016, Input-form data for the U.S. Geological Survey assessment of the Mississippian Barnett Shale of the Bend Arch–Fort Worth Basin Province, 2015: U.S. Geological Survey Open-File Report 2016-1097, 31 p., https://dx.doi.org/10.3133/ofr20161097.","productDescription":"iii, 34 p.","startPage":"1","endPage":"31","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073625","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":325066,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1097/ofr20161097.pdf","text":"Report","size":"212 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1097"},{"id":325065,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1097/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Mississippian Barnett Shale","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.6297607421875,\n 33.4039312002347\n ],\n [\n -98.33862304687499,\n 32.10118973232094\n ],\n [\n -97.81677246093749,\n 31.85889704445453\n ],\n [\n -96.932373046875,\n 31.840232667909365\n ],\n [\n -96.12487792968749,\n 32.040676557717454\n ],\n [\n -95.6854248046875,\n 32.7872745269555\n ],\n [\n -95.6854248046875,\n 33.408516828002675\n ],\n [\n -95.97656249999999,\n 33.75174787568194\n ],\n [\n -96.558837890625,\n 33.61461929233378\n ],\n [\n -97.0037841796875,\n 33.578014746143985\n ],\n [\n -97.833251953125,\n 33.68321092658007\n ],\n [\n -98.250732421875,\n 34.07086232376631\n ],\n [\n -98.6187744140625,\n 33.710632271492095\n ],\n [\n -98.6297607421875,\n 33.4039312002347\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS 939
Denver Federal Center
Denver, CO 80225-0046
The Missouri River Pallid Sturgeon Effects Analysis was designed to carry out three components of an assessment of how Missouri River management has affected, and will affect, population dynamics of endangered Scaphirhynchus albus (pallid sturgeon): (1) collection of reliable scientific information, (2) critical assessment and synthesis of available data and analyses, and (3) analysis of the effects of actions on listed species and their habitats. This report is a synthesis of the three components emphasizing development of lines of evidence relating potential future management actions to pallid sturgeon population dynamics. We address 21 working management hypotheses that emerged from an expert opinion-based filtering process.
The ability to quantify linkages from abiotic changes to pallid sturgeon population dynamics is compromised by fundamental information gaps. Although a substantial foundation of pallid sturgeon science has been developed during the past 20 years, our efforts attempt to push beyond that understanding to provide predictions of how future management actions may affect pallid sturgeon responses. For some of the 21 hypotheses, lines of evidence are limited to theoretical deduction, inference from sparse empirical datasets, or expert opinion. Useful simulation models have been developed to predict the effects of management actions on survival of drifting pallid sturgeon free embryos in the Yellowstone and Upper Missouri River complex (hereafter referred to as the “upper river”), and to assess the effects of flow and channel reconfigurations on habitat availability in the Lower Missouri River, tributaries, and Mississippi River downstream of Gavins Point Dam (hereafter referred to as the “lower river”). A population model also has been developed that can be used to assess sensitivity of the population to survival of specific life stages, assess some hypotheses related to stocking decisions, and explore a limited number of management scenarios.
Consideration of lines of evidence for each of the 21 hypotheses includes a discussion of how the degree of uncertainty and risk associated with each hypothesis may guide science and implementation strategies. Implementation strategies include full implementation in the field, limited implementations as field-scale experiments, or (in the case of greatest uncertainty) implementation as learning actions, including research and opportunistic experiments or field-based gradient studies. Given the substantive uncertainties associated with pallid sturgeon population dynamics and the need to continually assimilate and assess new information, we proposed that an Effects Analysis-like process should be considered an integral part of ongoing Missouri River adaptive management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165064","collaboration":"Prepared in cooperation with the Missouri River Recovery Program","usgsCitation":"Jacobson, R.B., Annis, M.L., Colvin, M.E., James, D.A., Welker, T.L., and Parsley, M.J., 2016, Missouri River Scaphirhynchus albus (pallid sturgeon) effects analysis—Integrative report 2016: U.S. Geological Survey Scientific Investigations Report 2016–5064, 154 p., https://dx.doi.org/10.3133/sir20165064.","productDescription":"xv, 154 p.","numberOfPages":"174","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064765","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":325271,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5064/coverthb.jpg"},{"id":325272,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5064/sir20165064.pdf","text":"Report","size":"18.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5064"}],"country":"United States","state":"Missouri","otherGeospatial":"Missouri River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.80712890625,\n 48.922499263758255\n ],\n [\n -114.67529296874999,\n 47.931066347509784\n ],\n [\n -115.4443359375,\n 47.27922900257082\n ],\n [\n -114.08203125,\n 46.78501604269254\n ],\n [\n -113.5986328125,\n 46.9502622421856\n ],\n [\n -113.04931640625,\n 46.51351558059737\n ],\n [\n -112.30224609374999,\n 45.73685954736049\n ],\n [\n -109.86328125,\n 43.78695837311561\n ],\n [\n -107.90771484375,\n 42.601619944327965\n ],\n [\n -107.24853515625,\n 42.90816007196054\n ],\n [\n -106.787109375,\n 42.61779143282346\n ],\n [\n -106.98486328124999,\n 42.309815415686664\n ],\n [\n -106.89697265625,\n 41.623655390686395\n ],\n [\n -106.962890625,\n 41.244772343082104\n ],\n [\n -107.09472656249999,\n 40.830436877649255\n ],\n [\n -106.61132812499999,\n 40.41349604970198\n ],\n [\n -106.34765625,\n 40.027614437486655\n ],\n [\n -105.9521484375,\n 40.16208338164619\n ],\n [\n -105.75439453125,\n 40.01078714046552\n ],\n [\n -105.99609375,\n 39.605688178320804\n ],\n [\n -105.64453124999999,\n 39.04478604850143\n ],\n [\n -102.72216796875,\n 38.59970036588819\n ],\n [\n -95.0537109375,\n 28.86391842622456\n ],\n [\n -94.24072265625,\n 29.32472016151103\n ],\n [\n -92.04345703125,\n 29.401319510041485\n ],\n [\n -89.49462890625,\n 28.844673680771795\n ],\n [\n -88.59374999999999,\n 29.32472016151103\n ],\n [\n -88.26416015625,\n 33.00866349457558\n ],\n [\n -88.11035156249999,\n 35.11990857099681\n ],\n [\n -88.92333984375,\n 37.03763967977139\n ],\n [\n -90.04394531249999,\n 38.30718056188316\n ],\n [\n -89.9560546875,\n 38.976492485539424\n ],\n [\n -90.87890625,\n 39.63953756436671\n ],\n [\n -91.23046875,\n 40.195659093364654\n ],\n [\n -91.91162109375,\n 41.0130657870063\n ],\n [\n -93.8232421875,\n 41.09591205639546\n ],\n [\n -95.77880859375,\n 42.52069952914966\n ],\n [\n -97.14111328125,\n 43.59630591596548\n ],\n [\n -98.6572265625,\n 44.69989765840318\n ],\n [\n -100.74462890625,\n 47.57652571374621\n ],\n [\n -101.88720703125,\n 48.32703913063476\n ],\n [\n -104.47998046875,\n 49.009050809382046\n ],\n [\n -114.80712890625,\n 48.922499263758255\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center (CERC)
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-07-15","noUsgsAuthors":false,"publicationDate":"2016-07-15","publicationStatus":"PW","scienceBaseUri":"5789fb23e4b0c1aacab77894","contributors":{"authors":[{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":629913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Annis, Mandy L. mannis@usgs.gov","contributorId":3498,"corporation":false,"usgs":true,"family":"Annis","given":"Mandy","email":"mannis@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":629914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colvin, Michael E.","contributorId":140975,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":629915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"James, Daniel A.","contributorId":41737,"corporation":false,"usgs":true,"family":"James","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":629916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welker, Timothy L.","contributorId":140976,"corporation":false,"usgs":false,"family":"Welker","given":"Timothy","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":629917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parsley, Michael J. 0000-0003-0097-6364 mparsley@usgs.gov","orcid":"https://orcid.org/0000-0003-0097-6364","contributorId":2608,"corporation":false,"usgs":true,"family":"Parsley","given":"Michael","email":"mparsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":629918,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70173928,"text":"ofr20161101 - 2016 - Low-flow frequency and flow duration of selected South Carolina streams in the Savannah and Salkehatchie River Basins through March 2014","interactions":[],"lastModifiedDate":"2016-11-15T09:31:00","indexId":"ofr20161101","displayToPublicDate":"2016-07-14T14:00:00","publicationYear":"2016","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":"2016-1101","title":"Low-flow frequency and flow duration of selected South Carolina streams in the Savannah and Salkehatchie River Basins through March 2014","docAbstract":"
An ongoing understanding of streamflow characteristics of the rivers and streams in South Carolina is important for the protection and preservation of the State’s water resources. Information concerning the low-flow characteristics of streams is especially important during critical flow periods, such as during the historic droughts that South Carolina has experienced in the past few decades.
In 2008, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, initiated a study to update low-flow statistics at continuous-record streamgaging stations operated by the U.S. Geological Survey in South Carolina. This report presents the low-flow statistics for 28 selected streamgaging stations in the Savannah and Salkehatchie River Basins in South Carolina. The low-flow statistics include daily mean flow durations for the 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance and the annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day mean flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years, depending on the length of record available at the streamgaging station. The low-flow statistics were computed from records available through March 31, 2014.
Low-flow statistics are influenced by length of record, hydrologic regime under which the data were collected, analytical techniques used, and other factors, such as urbanization, diversions, and droughts that may have occurred in the basin. To assess changes in the low-flow statistics from the previously published values, a comparison of the low-flow statistics for the annual minimum 7-day average streamflow with a 10-year recurrence interval (7Q10) from this study was made with the most recently published values. Of the 28 streamgaging stations for which recurrence interval computations were made, 14 streamgaging stations were suitable for comparing to low-flow statistics that were previously published in U.S. Geological Survey reports. These comparisons indicated that seven of the streamgaging stations had values lower than the previous values, two streamgaging stations had values higher than the previous values, and two streamgaging stations had values that were unchanged from previous values. The remaining three stations for which previous 7Q10 values were computed, which are located on the main stem of the Savannah River, were not compared with current estimates because of differences in the way the pre-regulation and regulated flow data were analyzed.
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U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Prediction of primary production of lentic water bodies (i.e., lakes and reservoirs) is valuable to researchers and resource managers alike, but is very rarely done at the global scale. With the development of remote sensing technologies, it is now feasible to gather large amounts of data across the world, including understudied and remote regions. To determine which factors were most important in explaining the variation of chlorophyll a (Chl-a), an indicator of primary production in water bodies, at global and regional scales, we first developed a geospatial database of 227 water bodies and watersheds with corresponding Chl-a, nutrient, hydrogeomorphic, and climate data. Then we used a generalized additive modeling approach and developed model selection criteria to select models that most parsimoniously related Chl-a to predictor variables for all 227 water bodies and for 51 lakes in the Laurentian Great Lakes region in the data set. Our best global model contained two hydrogeomorphic variables (water body surface area and the ratio of watershed to water body surface area) and a climate variable (average temperature in the warmest model selection criteria to select models that most parsimoniously related Chl-a to predictor variables quarter) and explained ~ 30% of variation in Chl-a. Our regional model contained one hydrogeomorphic variable (flow accumulation) and the same climate variable, but explained substantially more variation (58%). Our results indicate that a regional approach to watershed modeling may be more informative to predicting Chl-a, and that nearly a third of global variability in Chl-a may be explained using hydrogeomorphic and climate variables.
","language":"English","publisher":"International Society of Limnology","doi":"10.1080/IW-6.3.964","usgsCitation":"Woelmer, W., Kao, Y., Bunnell, D., Deines, A.M., Bennion, D., Rogers, M.W., Brooks, C., Sayers, M.J., Banach, D.M., Grimm, A.G., and Shuchman, R.A., 2016, Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales: Inland Waters, v. 6, no. 3, p. 379-392, https://doi.org/10.1080/IW-6.3.964.","productDescription":"14 p.","startPage":"379","endPage":"392","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071310","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":325241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5788a99ae4b0d27deb3813c2","contributors":{"authors":[{"text":"Woelmer, Whitney 0000-0001-5147-3877 wwoelmer@usgs.gov","orcid":"https://orcid.org/0000-0001-5147-3877","contributorId":150485,"corporation":false,"usgs":true,"family":"Woelmer","given":"Whitney","email":"wwoelmer@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kao, Yu-Chun","contributorId":35626,"corporation":false,"usgs":false,"family":"Kao","given":"Yu-Chun","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":642454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":169859,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":642452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deines, Andrew M.","contributorId":166920,"corporation":false,"usgs":false,"family":"Deines","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":642455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bennion, David 0000-0003-4927-4195 dbennion@usgs.gov","orcid":"https://orcid.org/0000-0003-4927-4195","contributorId":149533,"corporation":false,"usgs":true,"family":"Bennion","given":"David","email":"dbennion@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":642457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooks, Colin N.","contributorId":103961,"corporation":false,"usgs":true,"family":"Brooks","given":"Colin N.","affiliations":[],"preferred":false,"id":642458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sayers, Michael J.","contributorId":172893,"corporation":false,"usgs":false,"family":"Sayers","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":27113,"text":"Michigan Tech University","active":true,"usgs":false}],"preferred":false,"id":642459,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Banach, David M.","contributorId":172894,"corporation":false,"usgs":false,"family":"Banach","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":27113,"text":"Michigan Tech University","active":true,"usgs":false}],"preferred":false,"id":642460,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grimm, Amanda G.","contributorId":150482,"corporation":false,"usgs":false,"family":"Grimm","given":"Amanda","email":"","middleInitial":"G.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":642461,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shuchman, Robert A.","contributorId":150483,"corporation":false,"usgs":false,"family":"Shuchman","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":642462,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70174673,"text":"70174673 - 2016 - Long-term decreases in phosphorus and suspended solids, but not nitrogen, in six upper Mississippi River tributaries, 1991–2014","interactions":[],"lastModifiedDate":"2016-07-14T09:46:33","indexId":"70174673","displayToPublicDate":"2016-07-14T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Long-term decreases in phosphorus and suspended solids, but not nitrogen, in six upper Mississippi River tributaries, 1991–2014","docAbstract":"Long-term trends in tributaries provide valuable information about temporal changes in inputs of nutrients and sediments to large rivers. Data collected from 1991 to 2014 were used to investigate trends in total nitrogen (TN), total phosphorus (TP), nitrate (NO3–N), soluble-reactive P (SRP), and total suspended solids (TSS) in the following six tributaries of the upper Mississippi River: Cannon (CaR; Minnesota (MN)), Maquoketa (MR; Iowa (IA)), Wapsipinicon (WR; IA), Cuivre (CuR; Missouri (MO)), Chippewa (ChR; Wisconsin (WI)), and Black (BR; WI) rivers. Weighted regression on time discharge and season was used to statistically remove effects of random variation in discharge from estimated trends in flow-normalized concentrations and flux. Concentration and flux of TSS declined in all six rivers. Concentration of P declined in four of the rivers, and P flux declined in five rivers. Concentration and flux of N exhibited small changes relative to TP. TN concentration and flux did not change substantially in four of the rivers and decreased in two (ChR, CuR). Nitrate concentration and flux increased in three rivers (ChR, BR, CaR) and remained relatively constant in the other three rivers. General declines in P and TSS suggest that improvements in agricultural land management, such as the adoption of conservation tillage and enrollment of vulnerable acreage into the Conservation Reserve Program, may have reduced surface runoff; similar reductions in N were not observed.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-016-5464-3","usgsCitation":"Kreiling, R., and Houser, J.N., 2016, Long-term decreases in phosphorus and suspended solids, but not nitrogen, in six upper Mississippi River tributaries, 1991–2014: Environmental Monitoring and Assessment, v. 188, Article 454; 19 p., https://doi.org/10.1007/s10661-016-5464-3.","productDescription":"Article 454; 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072837","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":325238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.94335937499999,\n 36.98500309285596\n ],\n [\n -96.94335937499999,\n 47.60616304386874\n ],\n [\n -87.4072265625,\n 47.60616304386874\n ],\n [\n -87.4072265625,\n 36.98500309285596\n ],\n [\n -96.94335937499999,\n 36.98500309285596\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"188","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-08","publicationStatus":"PW","scienceBaseUri":"5788a99ce4b0d27deb3813c8","contributors":{"authors":[{"text":"Kreiling, Rebecca 0000-0002-9295-4156 rkreiling@usgs.gov","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":147679,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","email":"rkreiling@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":642463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":642464,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148408,"text":"70148408 - 2016 - Operational thermal remote sensing and lava flow monitoring at the Hawaiian Volcano Observatory","interactions":[],"lastModifiedDate":"2017-05-15T11:33:18","indexId":"70148408","displayToPublicDate":"2016-07-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5011,"text":"Geological Society of London Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Operational thermal remote sensing and lava flow monitoring at the Hawaiian Volcano Observatory","docAbstract":"Hawaiian volcanoes are highly accessible and well monitored by ground instruments. Nevertheless, observational gaps remain and thermal satellite imagery has proven useful in Hawai‘i for providing synoptic views of activity during intervals between field visits. Here we describe the beginning of a thermal remote sensing programme at the US Geological Survey Hawaiian Volcano Observatory (HVO). Whereas expensive receiving stations have been traditionally required to achieve rapid downloading of satellite data, we exploit free, low-latency data sources on the internet for timely access to GOES, MODIS, ASTER and EO-1 ALI imagery. Automated scripts at the observatory download these data and provide a basic display of the images. Satellite data have been extremely useful for monitoring the ongoing lava flow activity on Kīlauea's East Rift Zone at Pu‘u ‘Ō‘ō over the past few years. A recent lava flow, named Kahauale‘a 2, was upslope from residential subdivisions for over a year. Satellite data helped track the slow advance of the flow and contributed to hazard assessments. Ongoing improvement to thermal remote sensing at HVO incorporates automated hotspot detection, effusion rate estimation and lava flow forecasting, as has been done in Italy. These improvements should be useful for monitoring future activity on Mauna Loa.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP426.17","usgsCitation":"Patrick, M.R., Kauahikaua, J.P., Orr, T., Davies, A., and Ramsey, M.S., 2016, Operational thermal remote sensing and lava flow monitoring at the Hawaiian Volcano Observatory: Geological Society of London Special Publications, v. 426, no. 1, p. 489-503, https://doi.org/10.1144/SP426.17.","productDescription":"15 p.","startPage":"489","endPage":"503","ipdsId":"IP-058010","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":341307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"426","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-06","publicationStatus":"PW","scienceBaseUri":"591abe35e4b0a7fdb43c8bf3","contributors":{"authors":[{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":548039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauahikaua, James P. 0000-0003-3777-503X jimk@usgs.gov","orcid":"https://orcid.org/0000-0003-3777-503X","contributorId":2146,"corporation":false,"usgs":true,"family":"Kauahikaua","given":"James","email":"jimk@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":548040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orr, Tim R. torr@usgs.gov","contributorId":140376,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","email":"torr@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":548041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davies, Ashley G.","contributorId":36827,"corporation":false,"usgs":true,"family":"Davies","given":"Ashley G.","affiliations":[],"preferred":false,"id":548042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramsey, Michael S.","contributorId":58514,"corporation":false,"usgs":true,"family":"Ramsey","given":"Michael","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":548043,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174570,"text":"70174570 - 2016 - Can you hear me now? Range-testing a submerged passive acoustic receiver array in a Caribbean coral reef habitat","interactions":[],"lastModifiedDate":"2016-07-28T10:26:07","indexId":"70174570","displayToPublicDate":"2016-07-13T17:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Can you hear me now? Range-testing a submerged passive acoustic receiver array in a Caribbean coral reef habitat","docAbstract":"Submerged passive acoustic technology allows researchers to investigate spatial and temporal movement patterns of many marine and freshwater species. The technology uses receivers to detect and record acoustic transmissions emitted from tags attached to an individual. Acoustic signal strength naturally attenuates over distance, but numerous environmental variables also affect the probability a tag is detected. Knowledge of receiver range is crucial for designing acoustic arrays and analyzing telemetry data. Here, we present a method for testing a relatively large-scale receiver array in a dynamic Caribbean coastal environment intended for long-term monitoring of multiple species. The U.S. Geological Survey and several academic institutions in collaboration with resource management at Buck Island Reef National Monument (BIRNM), off the coast of St. Croix, recently deployed a 52 passive acoustic receiver array. We targeted 19 array-representative receivers for range-testing by submersing fixed delay interval range-testing tags at various distance intervals in each cardinal direction from a receiver for a minimum of an hour. Using a generalized linear mixed model (GLMM), we estimated the probability of detection across the array and assessed the effect of water depth, habitat, wind, temperature, and time of day on the probability of detection. The predicted probability of detection across the entire array at 100 m distance from a receiver was 58.2% (95% CI: 44.0–73.0%) and dropped to 26.0% (95% CI: 11.4–39.3%) 200 m from a receiver indicating a somewhat constrained effective detection range. Detection probability varied across habitat classes with the greatest effective detection range occurring in homogenous sand substrate and the smallest in high rugosity reef. Predicted probability of detection across BIRNM highlights potential gaps in coverage using the current array as well as limitations of passive acoustic technology within a complex coral reef environment.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2228","usgsCitation":"Selby, T.H., Hart, K.M., Fujisaki, I., Smith, B.J., Pollock, C.J., Hillis-Star, Z.M., Lundgren, I., and Oli, M.K., 2016, Can you hear me now? Range-testing a submerged passive acoustic receiver array in a Caribbean coral reef habitat: Ecology and Evolution, v. 6, no. 14, p. 4823-4835, https://doi.org/10.1002/ece3.2228.","productDescription":"13 p.","startPage":"4823","endPage":"4835","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070624","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2228","text":"Publisher Index Page"},{"id":325231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Buck Island Reef National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.65763092041016,\n 17.771573896194067\n ],\n [\n -64.65763092041016,\n 17.833027985030018\n ],\n [\n -64.57592010498047,\n 17.833027985030018\n ],\n [\n -64.57592010498047,\n 17.771573896194067\n ],\n [\n -64.65763092041016,\n 17.771573896194067\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"14","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-17","publicationStatus":"PW","scienceBaseUri":"57875827e4b0d27deb364f54","contributors":{"authors":[{"text":"Selby, Thomas H. 0000-0003-2116-0807 tselby@usgs.gov","orcid":"https://orcid.org/0000-0003-2116-0807","contributorId":5685,"corporation":false,"usgs":true,"family":"Selby","given":"Thomas","email":"tselby@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":642332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":642331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":642333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Brian J. 0000-0002-0531-0492 bjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":899,"corporation":false,"usgs":true,"family":"Smith","given":"Brian","email":"bjsmith@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":642334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pollock, Clayton J","contributorId":172870,"corporation":false,"usgs":false,"family":"Pollock","given":"Clayton","email":"","middleInitial":"J","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":642335,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hillis-Star, Zandy M","contributorId":106418,"corporation":false,"usgs":true,"family":"Hillis-Star","given":"Zandy","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":642336,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lundgren, Ian","contributorId":29727,"corporation":false,"usgs":true,"family":"Lundgren","given":"Ian","affiliations":[],"preferred":false,"id":642337,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oli, Madan K.","contributorId":86089,"corporation":false,"usgs":true,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":642338,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174573,"text":"sir20105090Z - 2016 - Spatial database for a global assessment of undiscovered copper resources: Chapter Z in Global mineral resource assessment","interactions":[{"subject":{"id":70174573,"text":"sir20105090Z - 2016 - Spatial database for a global assessment of undiscovered copper resources: Chapter Z in Global mineral resource assessment","indexId":"sir20105090Z","publicationYear":"2016","noYear":false,"chapter":"Z","title":"Spatial database for a global assessment of undiscovered copper resources: Chapter Z in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2018-10-29T08:57:57","indexId":"sir20105090Z","displayToPublicDate":"2016-07-13T13:00:00","publicationYear":"2016","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":"2010-5090","chapter":"Z","title":"Spatial database for a global assessment of undiscovered copper resources: Chapter Z in Global mineral resource assessment","docAbstract":"As part of the first-ever U.S. Geological Survey global assessment of undiscovered copper resources, data common to several regional spatial databases published by the U.S. Geological Survey, including one report from Finland and one from Greenland, were standardized, updated, and compiled into a global copper resource database. This integrated collection of spatial databases provides location, geologic and mineral resource data, and source references for deposits, significant prospects, and areas permissive for undiscovered deposits of both porphyry copper and sediment-hosted copper. The copper resource database allows for efficient modeling on a global scale in a geographic information system (GIS) and is provided in an Esri ArcGIS file geodatabase format.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090Z","usgsCitation":"Dicken, C.L., Dunlap, Pamela, Parks, H.L., Hammarstrom, J.M., and Zientek, M.L., 2016, Spatial database for a global assessment of undiscovered copper resources: U.S. Geological Survey Scientific Investigations Report 2010–5090–Z, 29 p., and GIS data, available at https://dx.doi.org/10.3133/sir20105090Z.","productDescription":"Report: v, 29 p.; GIS Data","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066779","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":325183,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/z/sir20105090z.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090-Z Report PDF"},{"id":325184,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/z/sir20105090z_gis.zip","text":"GIS Data","size":"66 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2010-5090-Z GIS Data"},{"id":325182,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5090/z/coverthb.jpg"}],"contact":"Contact Information, Mineral Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
http://minerals.usgs.gov/
In 2015, as part of an on-going screening program for contaminants of emerging concern (CECs) in conjunction with the Environmental Protection Agency (EPA) Region 8, surface waters at 18 locations in or near seven national park units within the Northern Colorado Plateau Network (NCPN) were sampled for pesticides and pesticide degradation products, pharmaceuticals and personal care products, hormones, organic-wastewater-indictor chemicals, and nutrients. Most sites were sampled in spring (May or June) and fall (September).
\nThe Colorado River at the Potash boat ramp site, just upstream of Canyonlands National Park, continued to show chronic contamination by caffeine, the pesticide 2,4-D, and prescription drugs (gabapentin, lamotrigine, metformin, and sulfamethoxazole). Samples at the Moab wastewater treatment plant effluent outflow pipe showed a high number and concentration of contaminants entering the river about 14 miles upstream of the long-term sampling location and are the nearest point source for contaminants of emerging concern. Samples from 400 m downstream of the effluent pipe in the Colorado River had decreased numbers and concentrations of contaminants, indicating relatively quick dilution by the river. However, some contaminants persisted at the long-term sampling site downstream.
\nPatterns of detections at other sampling locations will be explored in future reports. This is an interim report. Limited sampling will continue in 2016 at selected sites in coordination with the USGS. A final report is expected upon completion of the USGS project in 2017.
","language":"English","publisher":"US National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Weissinger, R., Battaglin, W.A., and Bradley, P.M., 2016, Screening for contaminants of emerging concern in Northern Colorado Plateau Network waters: 2015 surface-water data: Natural Resource Report 2016-1239, xi, 41 p.","productDescription":"xi, 41 p.","numberOfPages":"58","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-076062","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":325169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324700,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/DownloadFile/551578"}],"country":"United States","state":"Arizona, Colorado, Idaho, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.3349609375,\n 36.50963615733049\n ],\n [\n -114.356689453125,\n 39.74943369178247\n ],\n [\n -113.851318359375,\n 40.75557964275591\n ],\n [\n -112.950439453125,\n 42.032974332441405\n ],\n [\n -111.95068359374999,\n 42.779275360241904\n ],\n [\n -111.07177734375,\n 42.67435857693384\n ],\n [\n -109.4073486328125,\n 43.15710884095329\n ],\n [\n -105.09521484375,\n 38.013476231041935\n ],\n [\n -109.061279296875,\n 36.98500309285596\n ],\n [\n -110.55541992187499,\n 38.12159327165922\n ],\n [\n -113.3349609375,\n 36.50963615733049\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57875828e4b0d27deb364f60","contributors":{"authors":[{"text":"Weissinger, R","contributorId":172623,"corporation":false,"usgs":false,"family":"Weissinger","given":"R","email":"","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":641453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641452,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174953,"text":"70174953 - 2016 - The PRISM4 (mid-Piacenzian) paleoenvironmental reconstruction","interactions":[],"lastModifiedDate":"2016-07-22T16:26:06","indexId":"70174953","displayToPublicDate":"2016-07-13T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"The PRISM4 (mid-Piacenzian) paleoenvironmental reconstruction","docAbstract":"The mid-Piacenzian is known as a period of relative warmth when compared to the present day. A comprehensive understanding of conditions during the Piacenzian serves as both a conceptual model and a source for boundary conditions as well as means of verification of global climate model experiments. In this paper we present the PRISM4 reconstruction, a paleoenvironmental reconstruction of the mid-Piacenzian ( ∼ 3 Ma) containing data for paleogeography, land and sea ice, sea-surface temperature, vegetation, soils, and lakes. Our retrodicted paleogeography takes into account glacial isostatic adjustments and changes in dynamic topography. Soils and lakes, both significant as land surface features, are introduced to the PRISM reconstruction for the first time. Sea-surface temperature and vegetation reconstructions are unchanged but now have confidence assessments. The PRISM4 reconstruction is being used as boundary condition data for the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) experiments.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/cp-12-1519-2016","usgsCitation":"Dowsett, H.J., Dolan, A.M., Rowley, D., Moucha, R., Forte, A., Mitrovica, J.X., Pound, M., Salzmann, U., Robinson, M.M., Chandler, M., Foley, K.M., and Haywood, A.M., 2016, The PRISM4 (mid-Piacenzian) paleoenvironmental reconstruction: Climate of the Past, v. 12, no. 7, p. 1519-1538, https://doi.org/10.5194/cp-12-1519-2016.","productDescription":"20 p.","startPage":"1519","endPage":"1538","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074298","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470753,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-12-1519-2016","text":"Publisher Index Page"},{"id":438588,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NF43WW","text":"USGS data release","linkHelpText":"PRISM4 (mid-Piacenzian) Paleoenvironmental Reconstruction Data"},{"id":325569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-13","publicationStatus":"PW","scienceBaseUri":"5793444de4b0eb1ce79e8c1b","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":643308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dolan, Aisling M.","contributorId":30117,"corporation":false,"usgs":true,"family":"Dolan","given":"Aisling","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rowley, David","contributorId":173099,"corporation":false,"usgs":false,"family":"Rowley","given":"David","email":"","affiliations":[{"id":12621,"text":"University of Chicago and University of South Florida","active":true,"usgs":false}],"preferred":false,"id":643310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moucha, Robert","contributorId":173102,"corporation":false,"usgs":false,"family":"Moucha","given":"Robert","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":643317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forte, Alessandro","contributorId":173103,"corporation":false,"usgs":false,"family":"Forte","given":"Alessandro","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":643318,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mitrovica, Jerry X.","contributorId":86200,"corporation":false,"usgs":true,"family":"Mitrovica","given":"Jerry","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":643319,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pound, Matthew","contributorId":173100,"corporation":false,"usgs":false,"family":"Pound","given":"Matthew","email":"","affiliations":[{"id":18103,"text":"Northumbria University, Newcastle Upon Tyne, UK","active":true,"usgs":false}],"preferred":false,"id":643311,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Salzmann, Ulrich","contributorId":173101,"corporation":false,"usgs":false,"family":"Salzmann","given":"Ulrich","email":"","affiliations":[{"id":18103,"text":"Northumbria University, Newcastle Upon Tyne, UK","active":true,"usgs":false}],"preferred":false,"id":643312,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":2082,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643313,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chandler, Mark","contributorId":17320,"corporation":false,"usgs":true,"family":"Chandler","given":"Mark","affiliations":[],"preferred":false,"id":643314,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643315,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Haywood, Alan M.","contributorId":86663,"corporation":false,"usgs":true,"family":"Haywood","given":"Alan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643316,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70188890,"text":"70188890 - 2016 - Aeromagnetic map of northwest Utah and adjacent parts of Nevada and Idaho","interactions":[],"lastModifiedDate":"2025-02-25T15:22:21.086949","indexId":"70188890","displayToPublicDate":"2016-07-13T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5437,"text":"Utah Geological Survey Miscellaneous Publication","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"16-4","title":"Aeromagnetic map of northwest Utah and adjacent parts of Nevada and Idaho","docAbstract":"Two aeromagnetic surveys were flown to promote further understanding of the geology and structure in northwest Utah and adjacent parts of Nevada and Idaho by serving as a basis for geophysical interpretations and by supporting geological mapping, water and mineral resource investigations, and other topical studies. Although this area is in general sparsely populated, (except for cities and towns along the Wasatch Front such as Ogden and Brigham City), it encompasses metamorphic core complexes in the Grouse Creek and Raft River Mountains (figure 1) of interest to earth scientists studying Cenozoic extension. The region was shaken in 1909 and 1934 by M6+ earthquakes east of the Hansel Mountains (Doser, 1989; Arabasz and others, 1994); damage from the 1934 earthquake occurred as far east as Logan, Utah (http:// www.seis.utah.edu/lqthreat/nehrp_htm/1934hans/n1934ha1. shtml#urbse). The presence of Quaternary shield volcanoes and bimodal Pleistocene volcanism in Curlew Valley (Miller and others, 1995; Felger and others, 2016) as well as relatively high temperature gradients encountered in the Indian Cove drillhole in the north arm of Great Salt Lake (Blackett and others, 2014) may indicate some potential for geothermal energy development in the area (Miller and others, 1995). The area also hosts four significant mining districts, in the northern Pilot Range, the Goose Creek Mountains in the northwest corner of the map, the southern end of the Promontory Mountains, and the southwest part of the Raft River Mountains, although production notably waned after World War II (Doelling, 1980). Other prospects of interest include those in the southern Grouse Creek Mountains, Silver Island, and the northern Newfoundland Mountains.
Large areas of northwest Utah are covered by young, surficial deposits or by Great Salt Lake or are down-dropped into deep Cenozoic basins, making extrapolation of bedrock geology from widely spaced exposures difficult or tenuous (figure 1). Local spatial variations in the Earth's magnetic field (evident as anomalies on aeromagnetic maps) reflect the distribution of magnetic minerals, primarily magnetite, in the underlying rocks. In many cases the volume content of magnetic minerals can be related to rock type, and abrupt spatial changes in the amount of magnetic minerals commonly mark lithologic or structural boundaries. Magnetic data reflect magnetization variations within the crust and are well suited for mapping the distribution of mafic igneous rocks, although felsic igneous rocks, some mineralized zones, and other rock types also can produce measurable magnetic anomalies. For these reasons, the U.S. Geological Survey (USGS) and Utah Geological Survey (UGS) contracted for the collection of aeromagnetic data in this area.
","language":"English","publisher":"Utah Geological Survey","publisherLocation":"Salt Lake City, UT","doi":"10.34191/MP-16-4","isbn":"978-1-55791-931-1","collaboration":"Prepared in cooperation with U.S. Department of the Interior, U.S. Geological Survey","usgsCitation":"Langenheim, V., 2016, Aeromagnetic map of northwest Utah and adjacent parts of Nevada and Idaho: Utah Geological Survey Miscellaneous Publication 16-4, 13 p., https://doi.org/10.34191/MP-16-4.","productDescription":"13 p.","ipdsId":"IP-073411","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":342956,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.141667,\n 42.041667\n ],\n [\n -111.916667,\n 42.041667\n ],\n [\n -111.916667,\n 40.858333\n ],\n [\n -114.141667,\n 40.858333\n ],\n [\n -114.141667,\n 42.041667\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536ea7e4b062508e3c7a75","contributors":{"authors":[{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700845,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188883,"text":"70188883 - 2016 - GIS methodology for geothermal play fairway analysis: Example from the Snake River Plain volcanic province","interactions":[],"lastModifiedDate":"2017-06-27T13:33:24","indexId":"70188883","displayToPublicDate":"2016-07-13T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"GIS methodology for geothermal play fairway analysis: Example from the Snake River Plain volcanic province","docAbstract":"Play fairway analysis in geothermal exploration derives from a systematic methodology originally developed within the petroleum industry and is based on a geologic and hydrologic framework of identified geothermal systems. We are tailoring this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region. This project has contributed to the success of this approach by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building automated tools to process results. ArcGIS was used to compile a range of different data types, which we refer to as ‘elements’ (e.g., faults, vents, heatflow…), with distinct characteristics and confidence values.
Raw data for each element were transformed into data layers with a common format. Because different data types have different uncertainties, each evidence layer had an accompanying confidence layer, which reflects spatial variations in these uncertainties. Risk maps represent the product of evidence and confidence layers, and are the basic building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map for analysis that reveals favorable areas for geothermal exploration.
Python scripts were developed to automate data processing and to enhance the flexibility of the data analysis. Python scripting provided the structure that makes a custom workflow possible. Nearly every tool available in the ArcGIS ArcToolbox can be executed using commands in the Python programming language. This enabled the construction of a group of tools that could automate most of the processing for the project. Currently, our tools are repeatable, scalable, modifiable, and transferrable, allowing us to automate the task of data analysis and the production of CRS and CCRS maps. Our ultimate goal is to produce a toolkit that can be imported into ArcGIS and applied to any geothermal play type, with fully tunable parameters that will allow for the production of multiple versions of the CRS and CCRS maps in order to better test for sensitivity and to validate results.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, 41st Workshop on Geothermal Reservoir Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"41st Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 22-24, 2016","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","publisherLocation":"Stanford, CA","usgsCitation":"DeAngelo, J., Shervais, J.W., Glen, J.M., Nielson, D.L., Garg, S., Dobson, P., Gasperikova, E., Sonnenthal, E., Visser, C., Liberty, L.M., Siler, D., Evans, J.P., and Santellanes, S., 2016, GIS methodology for geothermal play fairway analysis: Example from the Snake River Plain volcanic province, in Proceedings, 41st Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 22-24, 2016, 10 p.","productDescription":"10 p.","ipdsId":"IP-070241","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science 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W.","contributorId":57753,"corporation":false,"usgs":true,"family":"Shervais","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":700814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glen, Jonathan M. jglen@usgs.gov","contributorId":193556,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":700813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nielson, Dennis L.","contributorId":38220,"corporation":false,"usgs":true,"family":"Nielson","given":"Dennis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":700821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garg, Sabodh","contributorId":193564,"corporation":false,"usgs":false,"family":"Garg","given":"Sabodh","email":"","affiliations":[],"preferred":false,"id":700822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dobson, Patrick","contributorId":193558,"corporation":false,"usgs":false,"family":"Dobson","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":700815,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gasperikova, Erika","contributorId":193561,"corporation":false,"usgs":false,"family":"Gasperikova","given":"Erika","affiliations":[],"preferred":false,"id":700818,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sonnenthal, Eric","contributorId":146807,"corporation":false,"usgs":false,"family":"Sonnenthal","given":"Eric","affiliations":[],"preferred":false,"id":700819,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Visser, Charles","contributorId":193562,"corporation":false,"usgs":false,"family":"Visser","given":"Charles","email":"","affiliations":[],"preferred":false,"id":700820,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Liberty, Lee M.","contributorId":89631,"corporation":false,"usgs":true,"family":"Liberty","given":"Lee","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":700817,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Siler, Drew","contributorId":193559,"corporation":false,"usgs":false,"family":"Siler","given":"Drew","affiliations":[],"preferred":false,"id":700816,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Evans, James P.","contributorId":53760,"corporation":false,"usgs":true,"family":"Evans","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":700823,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Santellanes, Sean","contributorId":193566,"corporation":false,"usgs":false,"family":"Santellanes","given":"Sean","email":"","affiliations":[],"preferred":false,"id":700824,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70171098,"text":"ds1001 - 2016 - Phosphorus in sediment in the Kent Park Lake watershed, Johnson County, Iowa, 2014–15","interactions":[],"lastModifiedDate":"2016-07-12T12:51:05","indexId":"ds1001","displayToPublicDate":"2016-07-12T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1001","title":"Phosphorus in sediment in the Kent Park Lake watershed, Johnson County, Iowa, 2014–15","docAbstract":"Phosphorus data were collected from the Kent Park Lake watershed in Johnson County, Iowa, in 2014 and 2015 to obtain information to assist in the management of the water quality in the lake. Phosphorus concentrations were measured for sediment from several ponds in the watershed and sediment deposited in the lake. The first set of samples was collected in 2014 to understand phosphorus in several potential sources to the lake and the spatial variability in lake sediments. Phosphorus concentrations ranged from 68 to 380 milligrams per kilogram in lake sediment and from 57 to 220 milligrams per kilogram in sedimentation and dredge spoil ponds. Additional samples were collected in 2015 to determine how phosphorus concentrations vary with depth in the lake sediment. Phosphorus concentrations generally decreased with increasing depth within the lake sediment. In 2015, total phosphorus concentrations in lake sediment ranged from 50 to 340 milligrams per kilogram.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1001","collaboration":"Prepared in cooperation with the Johnson County Conservation Board","usgsCitation":"Kalkhoff, S.J., 2016, Phosphorus in sediment in the Kent Park Lake watershed, Johnson County, Iowa, 2014–15: U.S. Geological Survey Data Series 1001, 18 p., https://dx.doi.org/10.3133/ds1001.","productDescription":"vi, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-01-01","ipdsId":"IP-071552","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":325076,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1001/coverthb.jpg"},{"id":325077,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1001/ds1001.pdf","text":"Report","size":"2.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Data Series 1001"}],"country":"United States","state":"Iowa","county":"Johnson County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-91.3677,41.8603],[-91.3673,41.7745],[-91.3675,41.6855],[-91.3671,41.5987],[-91.3679,41.5107],[-91.3687,41.4235],[-91.4839,41.4222],[-91.4843,41.4286],[-91.492,41.4405],[-91.5033,41.4493],[-91.5026,41.452],[-91.4989,41.4538],[-91.4988,41.4592],[-91.5145,41.4676],[-91.5156,41.4704],[-91.5136,41.4767],[-91.5038,41.4779],[-91.5029,41.4874],[-91.5039,41.4933],[-91.5076,41.4939],[-91.5107,41.4944],[-91.5112,41.4971],[-91.508,41.5016],[-91.5098,41.5034],[-91.5117,41.5016],[-91.5148,41.4985],[-91.5197,41.4981],[-91.5196,41.5027],[-91.5281,41.5078],[-91.528,41.511],[-91.5991,41.5107],[-91.7138,41.511],[-91.8291,41.5116],[-91.827,41.6001],[-91.8337,41.6006],[-91.8335,41.6865],[-91.8327,41.775],[-91.8318,41.8617],[-91.716,41.862],[-91.5989,41.8612],[-91.4836,41.8608],[-91.3677,41.8603]]]},\"properties\":{\"name\":\"Johnson\",\"state\":\"IA\"}}]}","contact":"Director, Iowa Water Science Center
U.S. Geological Survey
P.O. Box 1230
Iowa City, IA 52244
The Hells Canyon Complex (HCC) is a hydroelectric project built and operated by the Idaho Power Company (IPC) that consists of three dams on the Snake River along the Oregon and Idaho border (fig. 1). The dams have resulted in the creation of Brownlee, Oxbow, and Hells Canyon Reservoirs, which have a combined storage capacity of more than 1.5 million acre-feet and span about 90 miles of the Snake River. The Snake River upstream of and through the HCC historically has been impaired by water-quality issues related to excessive contributions of nutrients, algae, sediment, and other pollutants. In addition, historical data collected since the 1960s from the Snake River and tributaries near the HCC have documented high concentrations of mercury in fish tissue and sediment (Harris and Beals, 2013). Data collected from more recent investigations within the HCC continue to indicate elevated concentrations of mercury and methylmercury in the water column, bottom sediments, and biota (Clark and Maret, 1998; Essig, 2010; Fosness and others, 2013). As a result, Brownlee and Hells Canyon Reservoirs are listed as impaired for mercury by the State of Idaho, and the Snake River from the Oregon and Idaho border through the HCC downstream to the Oregon and Washington border is listed as impaired for mercury by the State of Oregon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163051","usgsCitation":"Clark, G.M., Naymik, Jesse, Krabbenhoft, D.P., Eagles-Smith, C.A., Aiken, G.R., Marvin-DiPasquale, M.C., Harris, R.C., and Myers, Ralph, 2016, Mercury cycling in the Hells Canyon Complex of the Snake River, Idaho and Oregon: U.S. Geological Survey Fact Sheet 2016-3051, 6 p., https://dx.doi.org/10.3133/fs20163051.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072163","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":325057,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3051/fs20163051.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3051 Fact Sheet PDF"},{"id":325056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3051/coverthb.jpg"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Brownlee Dam, Hells Canyon Dam, Oxbow Dam, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 43.5\n ],\n [\n -118,\n 46.4\n ],\n [\n -116,\n 46.4\n ],\n [\n -116,\n 43.5\n ],\n [\n -118,\n 43.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center,
U.S. Geological Survey
230 Collins Road, Boise, Idaho 83702
http://id.water.usgs.gov/
Suspended-sediment characteristics can be computed using acoustic indices derived from acoustic Doppler velocity meter (ADVM) backscatter data. The sediment acoustic index method applied in these types of studies can be used to more accurately and cost-effectively provide time-series estimates of suspended-sediment concentration and load, which is essential for informed solutions to many sediment-related environmental, engineering, and agricultural concerns. Advantages of this approach over other sediment surrogate methods include: (1) better representation of cross-sectional conditions from large measurement volumes, compared to other surrogate instruments that measure data at a single point; (2) high temporal resolution of collected data; (3) data integrity when biofouling is present; and (4) less rating curve hysteresis compared to streamflow as a surrogate. An additional advantage of this technique is the potential expansion of monitoring suspended-sediment concentrations at sites with existing ADVMs used in streamflow velocity monitoring. This report provides much-needed standard techniques for sediment acoustic index methods to help ensure accurate and comparable documented results.
\nA sediment acoustic index gage is used to collect continuous acoustic backscatter data, using an ADVM deployed in a fixed location, which are related to results from discrete suspended-sediment samples. The raw ADVM backscatter data are adjusted for variables affecting backscatter other than the sediment concentration to compute the sediment-corrected backscatter (SCB) and sediment attenuation coefficient (SAC). The sediment acoustic index rating (rating) is then developed by relating the sediment characteristics from the periodic samples to the SCB and (or) SAC and other explanatory variables in a site-specific, instrument-specific, simple or multiple linear regression model. The rating is reviewed and checked to ensure the technique has been applied appropriately. This review includes an assessment of the theoretical soundness, the adequacy of the model calibration dataset, and the quality of the regression model and regression diagnostics. The rating can then be applied to the acoustic surrogates and other explanatory variables to obtain continuous records of computed suspended-sediment concentration. The estimates of suspended-sediment concentration can then be paired with streamflow data, if available, to compute continuous records of suspended-sediment load.
\nOnce developed, sediment acoustic index ratings must be validated with additional suspended-sediment samples, beyond the period of record used in the rating development, to verify that the regression model continues to adequately represent sediment conditions within the stream. Changes in ADVM configuration or installation, or replacement with another ADVM, may require development of a new rating. The best practices described in this report can be used to develop continuous estimates of suspended-sediment concentration and load using sediment acoustic surrogates to enable more informed and accurate responses to diverse sedimentation issues.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Sediment and erosion techniques in Book 3: Applications of Hydraulics","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm3C5","usgsCitation":"Landers, M.N., Straub, T.D., Wood, M.S., and Domanski, M.M., 2016, Sediment acoustic index method for computing continuous suspended-sediment concentrations: U.S. Geological Survey Techniques and Methods, book 3, chap. C5, 63 p., https://dx.doi.org/10.3133/tm3C5.","productDescription":"vii, 63 p.","endPage":"83","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062080","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":324847,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/03/c05/coverthb.jpg"},{"id":324848,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/03/c05/tm3c5.pdf","text":"Report","size":"9.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 3C-05"}],"publicComments":"This report is Chapter 5 of Section C: Sediment and erosion techniques in Book 3: Applications of Hydraulics.","contact":"Chief, Office of Surface Water
U.S. Geological Survey
415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
(703) 648-5301
Or visit the Office of Surface Water Web site at: http://water.usgs.gov/osw/
","tableOfContents":"Livestock fences have been hypothesized to significantly contribute to mortality of lesser prairie-chickens (Tympanuchus pallidicinctus); however, quantification of mortality due to fence collisions is lacking across their current distribution. Variation in fence density, landscape composition and configuration, and land use could influence collision risk of lesser prairie-chickens. We monitored fences within 3 km of known leks during spring and fall and surveyed for signs of collision occurrence within 20 m of fences in 6 study sites in Kansas and Colorado, USA during 2013 and 2014. We assessed mortality locations of radio-tagged birds (n = 286) for evidence of fence collisions and compared distance to fence relative to random points. Additionally, we quantified locations, propensity, and frequency of fences crossed by lesser prairie-chickens. We tested for landscape and vegetative characteristics that influenced fence-cross propensity and frequency of global positioning system (GPS)-marked birds. A minimum of 12,706 fence crossings occurred by GPS-marked lesser prairie-chickens. We found 3 carcasses and 12 additional possible instances of evidence of collision during >2,800 km of surveyed fences. We found evidence for a single suspected collision based on carcass evidence for 148 mortalities of transmittered birds. Mortality locations of transmittered birds were located at distances from fences 15% farther than expected at random. Our data suggested minimal biological significance and indicated that propensity and frequency of fence crossings were random processes. Lesser prairie-chickens do not appear to be experiencing significant mortality risk due to fence collisions in Kansas and Colorado. Focusing resources on other limiting factors (i.e., habitat quality) has greater potential for impact on population demography than fence marking and removal.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.1073","usgsCitation":"Robinson, S.G., Haukos, D.A., Plumb, R.T., Hagen, C.A., Pitman, J.C., Lautenbach, J.M., Sullins, D.S., Kraft, J.D., and Lautenbach, J.D., 2016, Lesser prairie-chicken fence collision risk across its northern distribution: Journal of Wildlife Management, v. 80, no. 5, p. 906-915, https://doi.org/10.1002/jwmg.1073.","productDescription":"10 p.","startPage":"906","endPage":"915","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071444","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":325001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, 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