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Bauxite-bearing rocks are present in several regions of Afghanistan; specifically, the southeast segment of the North Afghanistan Platform, the eastern parts of South Afghanistan, and within the Afghanistan-North and -South Pamir Fold Regions. Bauxite-bearing rocks occur at various stratigraphic levels, in lithologically different sequences of sedimentary rocks. The bauxites are paleosols and represent previous, rather than recent, weathering events. Bauxites and bauxite-type horizons are most common at the base of carbonate rock units, where they form the basal horizons of sedimentary rock sequences separated by erosion and stratigraphic unconformity surfaces. Less common are zones in redeposited weathering developed on igneous rocks. At present there are five known stratigraphic intervals with significant bauxite and bauxite-type deposits and occurrences: the lower Permian, the upper Permian, the Upper Triassic, the Lower Jurassic, and the base of the Upper Jurassic.

\n

This report summarizes a compilation and review of geological data for regions in Afghanistan that contain bauxite deposits and occurrences based on work conducted during 2009 to 2011 by the U.S. Geological Survey, the U.S. Department of Defense Task Force for Business and Stability Operations, and the Afghanistan Geological Survey.

\n

Permian strata contain bauxites and bauxite-like rocks that are recognizable at various stratigraphic intervals within several areas of southern Afghanistan and in the Central Afghan Massif in central Afghanistan. The main zones of known bauxite occurrences are the Haftqala bauxite zone (late Permian and Late Triassic), Shewa bauxite zone (early Permian), Qarghanaw bauxite zone (late Permian and Late Triassic), Arghandab block in Zabul Province (middle through late Permian), Arghandab block in Ghazni Province (early Permian), Surkhob bauxite zone (Early Jurassic), and Tirin block in Uruzgan, Zabul, and Kandahar Provinces (Late Jurassic).

\n

Although some bauxite occurrences were sampled in the course of reconnaissance exploration by Soviet workers in the 1960s and 1970s, the bauxite areas in Afghanistan generally are underexplored. The Obatu Sheila area is a known field of bauxite deposits of Late Jurassic age that had been studied in more detail than other known bauxite deposits and occurrences in Afghanistan. Obatu Sheila has an estimated reserve of 7.2 million tons.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141210","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations","usgsCitation":"Renaud, K., Wardlaw, B.R., and Hubbard, B.E., 2015, Assessment of bauxite, clay, and laterite deposits in Afghanistan: U.S. Geological Survey Open-File Report 2014-1210, v, 40 p., https://doi.org/10.3133/ofr20141210.","productDescription":"v, 40 p.","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-050785","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":497,"text":"Office of International 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2009","interactions":[],"lastModifiedDate":"2015-04-28T10:15:09","indexId":"ds930","displayToPublicDate":"2015-04-28T11:15:00","publicationYear":"2015","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":"930","title":"Post-Nor'Ida coastal oblique aerial photographs collected from Ocean City, Maryland, to Hatteras, North Carolina, December 4, 2009","docAbstract":"

The U.S. Geological Survey (USGS) conducts baseline and storm response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms. The remnants of Tropical Storm Ida intensified to become a nor'easter (herein referred to as Nor'Ida). On December 4, 2009, the USGS conducted an oblique aerial photographic survey from Ocean City, Maryland, to Hatteras, North Carolina, aboard a U.S. Coast Guard HH60 helicopter at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was flown to collect post-Nor'Ida data for assessing incremental changes since the last surveys, flown in 2008 and 2009, and the data can be used in the assessment of future coastal change.

\n

The images provided in this report are Joint Photographic Experts Group (JPEG) images. Exiftool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft and do not indicate the location of any feature in the images. These photographs document the configuration of the barrier islands and other coastal features at the time of the survey.

\n

Table 1 provides detailed information about the GPS location, name, date, and time each of the 2,381 photographs was taken along with links to each photograph. The photography is organized into segments, also referred to as contact sheets. Each segment represents approximately 5 minutes of flight time.

\n

In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files.

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Monthly water yields from 105,829 catchments and corresponding flows in 107,691 stream segments were estimated for water years 1951–2012 in the Great Lakes Basin in the United States. Both sets of estimates were computed by using the Analysis of Flows In Networks of CHannels (AFINCH) application within the NHDPlus geospatial data framework. AFINCH provides an environment to develop constrained regression models to integrate monthly streamflow and water-use data with monthly climatic data and fixed basin characteristics data available within NHDPlus or supplied by the user. For this study, the U.S. Great Lakes Basin was partitioned into seven study areas by grouping selected hydrologic subregions and adjoining cataloguing units. This report documents the regression models and data used to estimate monthly water yields and flows in each study area. Estimates of monthly water yields and flows are presented in a Web-based mapper application. Monthly flow time series for individual stream segments can be retrieved from the Web application and used to approximate monthly flow-duration characteristics and to identify possible trends.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145192","usgsCitation":"Luukkonen, C.L., Holtschlag, D.J., Reeves, H.W., Hoard, C.J., and Fuller, L.M., 2015, Estimation of monthly water yields and flows for 1951-2012 for the United States portion of the Great Lakes Basin with AFINCH: U.S. Geological Survey Scientific Investigations Report 2014-5192, Report: vii, 83 p.; The Great Lakes Restoration Initiative (GLRI) Mapper, https://doi.org/10.3133/sir20145192.","productDescription":"Report: vii, 83 p.; The Great Lakes Restoration Initiative (GLRI) Mapper","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1951-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-056761","costCenters":[{"id":382,"text":"Michigan Water Science 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A study to assess the potential of the Arkansas River Valley alluvial aquifer in the vicinity of Van Buren, Arkansas, as a viable source of public-supply water was conducted by the U.S. Geological Survey in cooperation with the Little Rock, District, U.S. Army Corps of Engineers. An important study component was to identify possible changes in hydrologic conditions following installation of James W. Trimble Lock and Dam 13 (December 1969) on the Arkansas River near the study area. Data were gathered for the study in regard to the lithology, hydrologic characteristics, and water quality of the aquifer. Lithologic information was obtained from drillers’ logs of wells drilled from 1957 through 1959. Water-quality samples were collected from 10 irrigation wells and analyzed for inorganic constituents and pesticides. To evaluate the potential viability of the alluvial aquifer in the Van Buren area, these data were compared to similar stratigraphic, lithologic, and groundwater-quality data from the Arkansas River Valley alluvial aquifer at Dardanelle, Ark., where the aquifer provides a proven, productive, sole-source of public-supply water.

\n

Drillers’ logs for 59 wells in the Van Buren study area revealed well depths ranging from 25 to 52 feet (ft), with a mean depth of 42 ft. The thickness of the lower sand/gravel interval serving as the water-producing zone ranged from 5 to 47 ft, with a mean thickness of 29 ft. The presence of gravel was noted in only 4 of 59 well logs available for review from the study area.

\n

Percent sand was calculated from well logs in the study area, and these sand percentages were overlain onto an orthophotograph map to examine the areal distribution of sand percentage in relation to geomorphologic features of the flood plain in the study area. The logs denoting the greatest percent sand tend to occur in areas near to the river and on the concave (point bar) side of abandoned channels, while the lower percent sand tends to occur on the convex (channel fill and backswamp deposits) side of the abandoned channels.

\n

Comparison of hydrographs from water levels collected between 1957 and 1972 to cumulative departure from mean monthly and mean annual precipitation showed overall good fit and explained the long-term decreasing water levels from the earliest period of record through October 1967, followed by a sharp rise in water levels concurrent with rises in cumulative departure from mean monthly and mean annual precipitation. Hydrographs for four wells ranging from 0.8 to 4.5 miles upstream from the dam and potentially affected by rising river stage were compared to graphs of river stage and cumulative departure from mean monthly precipitation. Water levels for these wells showed minimal discernible effect by rising river stage following dam completion. Periods of increased precipitation compared closely to increases in water level for all hydrographs, regardless of river stage, and periods of no precipitation resulted in declining water levels, although river stage continued to slowly rise during these same periods.

\n

The Arkansas River has greater salinity than local groundwater, providing a quantitative tracer for any groundwater recharge originating from the river. Comparison of predam and postdam groundwater-chloride concentrations showed no increase in chloride concentrations after dam installation, which is consistent with hydrologic data. These data suggest that the dominant source of groundwater recharge in the Arkansas River Valley alluvial aquifer is infiltration of precipitation through proximal, coarse channel deposits, with minimal influx of river water.

\n

Groundwater-quality data collected from 10 wells in the study area indicated a calcium-bicarbonate water type. No primary drinking-water standards were exceeded for any constituents, and iron and manganese were the only constituents exceeding secondary drinking-water regulations. Six of the 10 well-water samples were analyzed for the presence of pesticides, as row-crop agriculture is the dominant land use in the study area. Six herbicide compounds and one herbicide metabolite were detected at concentrations substantially below those of the Federal primary drinking-water standards and health advisories.

\n

The hydrologic and geochemical data gathered for this study provide a qualitative assessment of the potential of the Arkansas River Valley alluvial aquifer as a source of public water supply in the Van Buren area. Results indicate minimal influx of water from the Arkansas River, and recharge to the aquifer appears to be dominantly by infiltration of precipitation through overlying alluvium. If vertical wells are used as a source of public water supply, then several wells will have to be used in combination at relatively low pumping rates and placed in areas with a greater percent sand. Use of a horizontal well configuration near the river to increase production may depend on infiltration of river water to supplement water removed from storage, especially where areas of lower permeability sediments might be encountered within the surrounding alluvium. If a poor hydraulic connection exists between the river and the alluvium, as indicated by this study, then production will depend on ample precipitation and recharge throughout the year and groundwater storage sufficient to prevent declining water levels where pumping rates exceed recharge.

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Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

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The U.S. Geological Survey National Seismic Hazard Model for the conterminous United States was updated in 2014 to account for new methods, input models, and data necessary for assessing the seismic ground shaking hazard from natural (tectonic) earthquakes. The U.S. Geological Survey National Seismic Hazard Model project uses probabilistic seismic hazard analysis to quantify the rate of exceedance for earthquake ground shaking (ground motion). For the 2014 National Seismic Hazard Model assessment, the seismic hazard from potentially induced earthquakes was intentionally not considered because we had not determined how to properly treat these earthquakes for the seismic hazard analysis. The phrases “potentially induced” and “induced” are used interchangeably in this report, however it is acknowledged that this classification is based on circumstantial evidence and scientific judgment. For the 2014 National Seismic Hazard Model update, the potentially induced earthquakes were removed from the NSHM’s earthquake catalog, and the documentation states that we would consider alternative models for including induced seismicity in a future version of the National Seismic Hazard Model. As part of the process of incorporating induced seismicity into the seismic hazard model, we evaluate the sensitivity of the seismic hazard from induced seismicity to five parts of the hazard model: (1) the earthquake catalog, (2) earthquake rates, (3) earthquake locations, (4) earthquake Mmax (maximum magnitude), and (5) earthquake ground motions. We describe alternative input models for each of the five parts that represent differences in scientific opinions on induced seismicity characteristics. In this report, however, we do not weight these input models to come up with a preferred final model. Instead, we present a sensitivity study showing uniform seismic hazard maps obtained by applying the alternative input models for induced seismicity. The final model will be released after further consideration of the reliability and scientific acceptability of each alternative input model. Forecasting the seismic hazard from induced earthquakes is fundamentally different from forecasting the seismic hazard for natural, tectonic earthquakes. This is because the spatio-temporal patterns of induced earthquakes are reliant on economic forces and public policy decisions regarding extraction and injection of fluids. As such, the rates of induced earthquakes are inherently variable and nonstationary. Therefore, we only make maps based on an annual rate of exceedance rather than the 50-year rates calculated for previous U.S. Geological Survey hazard maps.

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This extended abstract is based on the U.S. Geological Survey Scientific Investigations Reports by Crow et al. (2013) and Banta and Ockerman (2014). Suspended sediment in rivers and streams can play an important role in ecological health of rivers and estuaries and consequently is an important issue for water-resource managers. The quantity and type of suspended sediment can affect the biological communities (Wood and Armitage, 1997), the concentration and movement of natural constituents and anthropogenic contaminants (Moran and others, 2012), and the amount of sediment deposition in coastal environments (Milliman and Meade, 1983). To better understand suspended-sediment characteristics in the San Antonio River Basin, the U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority and Texas Water Development Board, conducted a two-phase study to (1) collect and analyze sediment data to characterize sediment conditions in the San Antonio River downstream of San Antonio, Texas, and (2) develop and calibrate a watershed model to simulate hydrologic conditions and suspended-sediment loads for four watersheds in the San Antonio River Basin, downstream from San Antonio, Texas.

","conferenceTitle":"SedHydro 2015","conferenceDate":"19-23 April 2015","conferenceLocation":"Reno, Nevada","language":"English","publisher":"SedHydro Conference","usgsCitation":"Banta, J., Ockerman, D.J., Crow, C., and Opsahl, S.P., 2015, Characterizing and simulating sediment loads and transport in the lower part of the San Antonio River Basin, SedHydro 2015, Reno, Nevada, 19-23 April 2015, 6 p.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062689","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":310633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"San Antonio River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.82525634765625,\n 28.47110572883182\n ],\n [\n -97.12326049804688,\n 28.64359439042694\n ],\n [\n -97.8826904296875,\n 29.165353121242656\n ],\n [\n -98.06259155273438,\n 29.26124274448168\n ],\n [\n -98.2012939453125,\n 29.099376992628493\n ],\n [\n -98.19717407226562,\n 28.841064894531943\n ],\n [\n -97.70690917968749,\n 28.674925574564284\n ],\n [\n -97.10128784179688,\n 28.426429818183024\n ],\n [\n -96.84997558593749,\n 28.411936281507902\n ],\n [\n -96.82388305664062,\n 28.456618312416825\n ],\n [\n -96.84173583984374,\n 28.480762902990307\n ],\n [\n -96.82525634765625,\n 28.47110572883182\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562f4eafe4b093cee780a27e","contributors":{"authors":[{"text":"Banta, J. Ryan 0000-0002-2226-7270 jbanta@usgs.gov","orcid":"https://orcid.org/0000-0002-2226-7270","contributorId":4723,"corporation":false,"usgs":true,"family":"Banta","given":"J. Ryan","email":"jbanta@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":538881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":578349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crow, Cassi","contributorId":149426,"corporation":false,"usgs":false,"family":"Crow","given":"Cassi","affiliations":[],"preferred":false,"id":578350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Opsahl, Stephen P. 0000-0002-4774-0415 sopsahl@usgs.gov","orcid":"https://orcid.org/0000-0002-4774-0415","contributorId":4713,"corporation":false,"usgs":true,"family":"Opsahl","given":"Stephen","email":"sopsahl@usgs.gov","middleInitial":"P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":578351,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70137942,"text":"70137942 - 2015 - The upper bound of abutment scour defined by selected laboratory and field data","interactions":[],"lastModifiedDate":"2016-11-30T14:38:26","indexId":"70137942","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The upper bound of abutment scour defined by selected laboratory and field data","docAbstract":"

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted a field investigation of abutment scour in South Carolina and used that data to develop envelope curves defining the upper bound of abutment scour. To expand upon this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with abutment-scour data from other sources and evaluate the upper bound of abutment scour with the larger data set. To facilitate this analysis, a literature review was made to identify potential sources of published abutment-scour data, and selected data, consisting of 446 laboratory and 331 field measurements, were compiled for the analysis. These data encompassed a wide range of laboratory and field conditions and represent field data from 6 states within the United States. The data set was used to evaluate the South Carolina abutment-scour envelope curves. Additionally, the data were used to evaluate a dimensionless abutment-scour envelope curve developed by Melville (1992), highlighting the distinct difference in the upper bound for laboratory and field data. The envelope curves evaluated in this investigation provide simple but useful tools for assessing the potential maximum abutment-scour depth in the field setting.

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Center","active":true,"usgs":true}],"preferred":true,"id":579547,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137970,"text":"70137970 - 2015 - The upper bound of Pier Scour defined by selected laboratory and field data","interactions":[],"lastModifiedDate":"2017-04-24T13:29:58","indexId":"70137970","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The upper bound of Pier Scour defined by selected laboratory and field data","docAbstract":"

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted several field investigations of pier scour in South Carolina (Benedict and Caldwell, 2006; Benedict and Caldwell, 2009) and used that data to develop envelope curves defining the upper bound of pier scour. To expand upon this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with pier-scour data from other sources and evaluate the upper bound of pier scour with this larger data set. To facilitate this analysis, a literature review was made to identify potential sources of published pier-scour data, and selected data were compiled into a digital spreadsheet consisting of approximately 570 laboratory and 1,880 field measurements. These data encompass a wide range of laboratory and field conditions and represent field data from 24 states within the United States and six other countries. This extensive database was used to define the upper bound of pier-scour depth with respect to pier width encompassing the laboratory and field data. Pier width is a primary variable that influences pier-scour depth (Laursen and Toch, 1956; Melville and Coleman, 2000; Mueller and Wagner, 2005, Ettema et al. 2011, Arneson et al. 2012) and therefore, was used as the primary explanatory variable in developing the upper-bound envelope curve. The envelope curve provides a simple but useful tool for assessing the potential maximum pier-scour depth for pier widths of about 30 feet or less.

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Carolina\",\"nation\":\"USA \"}}]}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562b5a36e4b00162522207ee","contributors":{"authors":[{"text":"Benedict, Stephen benedict@usgs.gov","contributorId":127829,"corporation":false,"usgs":true,"family":"Benedict","given":"Stephen","email":"benedict@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":538349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":138690,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral W.","email":"acaldwel@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":538350,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155207,"text":"70155207 - 2015 - Suspended-sediment concentrations, yields, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011","interactions":[],"lastModifiedDate":"2016-12-20T13:47:07","indexId":"70155207","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Suspended-sediment concentrations, yields, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011","docAbstract":"Excessive sediment transport in rivers causes problems for flood control, soil conservation, irrigation, aquatic health, and navigation, as well as transporting harmful contaminants like organic chemicals and eutrophication-causing nutrients. In Minnesota, more than 5,800 miles of streams are identified as impaired by the Minnesota Pollution Control Agency (MPCA) due to elevated levels of suspended sediment. \n\nThe U.S. Geological Survey, in cooperation with the MPCA, established a sediment monitoring network in 2007 and began systematic sampling of suspended-sediment concentration (SSC), total suspended solids (TSS), and turbidity in rivers across Minnesota to improve the understanding of fluvial sediment transport relations. Suspended-sediment samples were collected from 14 sites from 2007 through 2011. Analyses of these data indicated that the Zumbro River at Kellogg in southeast Minnesota had the highest mean SSC of 226 milligrams per liter (mg/L) followed by the Minnesota River at Mankato with a mean SSC of 193 mg/L. The single highest SSC of 1,250 mg/L was measured at the Zumbro River during the 2011 spring runoff. The lowest mean SSC of 21 mg/L was measured at Rice Creek in the northern Minneapolis-St. Paul metropolitan area.\n\nTotal suspended solids (TSS) have been used as a measure of fluvial sediment by the MPCA since the early 1970s; however, TSS concentrations have been known to underrepresent the amount of suspended sediment. For this study, comparisons between concurrently sampled SSC and TSS indicated significant differences at every site, with SSC on average two times larger than TSS concentrations. \n\nRegression analysis indicated that 7 out of 14 sites had poor or no relation between SSC and streamflow. Only two sites, the Knife River and the Wild Rice River at Twin Valley, had strong correlations between SSC and streamflow, with coefficient of determination (R2) values of 0.82 and 0.80, respectively. In contrast, turbidity had moderate to strong relations with SSC at 10 of 14 sites and was superior to streamflow for estimating SSC at all sites. Suspended-sediment basin yields indicated that the Minnesota River had the largest mean annual sediment basin yield of 120 tons of sediment per year per square mile.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of joint federal Interagency conference 2015","conferenceTitle":"5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation","conferenceDate":" April 19 – 23, 2015","conferenceLocation":"Reno, NV","language":"English","collaboration":"Minnesota Pollution Control Agency","usgsCitation":"Ellison, C.A., Savage, B.E., and Johnson, G., 2015, Suspended-sediment concentrations, yields, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011, in Proceedings of joint federal Interagency conference 2015, Reno, NV, April 19 – 23, 2015, p. 869-880.","productDescription":"12 p. ","startPage":"869","endPage":"880","ipdsId":"IP-061247","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":332345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":305837,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/3rdJFIC/Proceedings.pdf"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585a51bfe4b01224f329b5f3","contributors":{"authors":[{"text":"Ellison, Christopher A. 0000-0002-5886-6654 cellison@usgs.gov","orcid":"https://orcid.org/0000-0002-5886-6654","contributorId":4891,"corporation":false,"usgs":true,"family":"Ellison","given":"Christopher","email":"cellison@usgs.gov","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":565075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, Brett E. besavage@usgs.gov","contributorId":5188,"corporation":false,"usgs":true,"family":"Savage","given":"Brett","email":"besavage@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Gregory D.","contributorId":14326,"corporation":false,"usgs":true,"family":"Johnson","given":"Gregory D.","affiliations":[],"preferred":false,"id":565077,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70137738,"text":"70137738 - 2015 - Surrogate analysis and index developer (SAID) tool and real-time data dissemination utilities","interactions":[],"lastModifiedDate":"2015-11-20T15:53:29","indexId":"70137738","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Surrogate analysis and index developer (SAID) tool and real-time data dissemination utilities","docAbstract":"

The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Critical to advancing the operational use of surrogates are tools to process and evaluate the data along with the subsequent development of regression models from which real-time sediment concentrations can be made available to the public. Recent developments in both areas are having an immediate impact on surrogate research, and on surrogate monitoring sites currently in operation. The Surrogate Analysis and Index Developer (SAID) standalone tool, under development by the U.S. Geological Survey (USGS), assists in the creation of regression models that relate response and explanatory variables by providing visual and quantitative diagnostics to the user. SAID also processes acoustic parameters to be used as explanatory variables for suspended-sediment concentrations. The sediment acoustic method utilizes acoustic parameters from fixed-mount stationary equipment. The background theory and method used by the tool have been described in recent publications, and the tool also serves to support sediment-acoustic-index methods being drafted by the multi-agency Sediment Acoustic Leadership Team (SALT), and other surrogate guidelines like USGS Techniques and Methods 3-C4 for turbidity and SSC. The regression models in SAID can be used in utilities that have been developed to work with the USGS National Water Information System (NWIS) and for the USGS National Real-Time Water Quality (NRTWQ) Web site. The real-time dissemination of predicted SSC and prediction intervals for each time step has substantial potential to improve understanding of sediment-related water-quality and associated engineering and ecological management decisions.

","conferenceTitle":"SEDHYD 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"10th Federal Interagency Sedimentation Conference","usgsCitation":"Domanski, M.M., Straub, T., Wood, M.S., Landers, M.N., Wall, G.R., and Brady, S.J., 2015, Surrogate analysis and index developer (SAID) tool and real-time data dissemination utilities, SEDHYD 2015, Reno, NV, April 19-23, 2015, 12 p.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061292","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":311627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56505258e4b0f162148c5d22","contributors":{"authors":[{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":538013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":538014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":538015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landers, Mark N. 0000-0002-3014-0480 landers@usgs.gov","orcid":"https://orcid.org/0000-0002-3014-0480","contributorId":1103,"corporation":false,"usgs":true,"family":"Landers","given":"Mark","email":"landers@usgs.gov","middleInitial":"N.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":538016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wall, Gary R. grwall@usgs.gov","contributorId":915,"corporation":false,"usgs":true,"family":"Wall","given":"Gary","email":"grwall@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":538017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brady, Steven J. 0000-0002-8527-5227 sbrady@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-5227","contributorId":4071,"corporation":false,"usgs":true,"family":"Brady","given":"Steven","email":"sbrady@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":538018,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70137268,"text":"70137268 - 2015 - Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery","interactions":[],"lastModifiedDate":"2015-10-26T11:27:56","indexId":"70137268","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery","docAbstract":"

Fluvial sediment, a vital surface water resource, is hazardous in excess. Suspended sediment, the most prevalent source of impairment of river systems, can adversely affect flood control, navigation, fisheries and aquatic ecosystems, recreation, and water supply (e.g., Rasmussen et al., 2009; Qu, 2014). Monitoring programs typically focus on suspended-sediment concentration (SSC) and discharge (SSQ). These time-series data are used to study changes to basin hydrology, geomorphology, and ecology caused by disturbances. The U.S. Geological Survey (USGS) has traditionally used physical sediment sample-based methods (Edwards and Glysson, 1999; Nolan et al., 2005; Gray et al., 2008) to compute SSC and SSQ from continuous streamflow data using a sediment transport-curve (e.g., Walling, 1977) or hydrologic interpretation (Porterfield, 1972). Accuracy of these data is typically constrained by the resources required to collect and analyze intermittent physical samples. Quantifying SSC using continuous instream turbidity is rapidly becoming common practice among sediment monitoring programs. Estimations of SSC and SSQ are modeled from linear regression analysis of concurrent turbidity and physical samples. Sediment-surrogate technologies such as turbidity promise near real-time information, increased accuracy, and reduced cost compared to traditional physical sample-based methods (Walling, 1977; Uhrich and Bragg, 2003; Gray and Gartner, 2009; Rasmussen et al., 2009; Landers et al., 2012; Landers and Sturm, 2013; Uhrich et al., 2014). Statistical comparisons among SSQ computation methods show that turbidity-SSC regression models can have much less uncertainty than streamflow-based sediment transport-curves or hydrologic interpretation (Walling, 1977; Lewis, 1996; Glysson et al., 2001; Lee et al., 2008). However, computation of SSC and SSQ records from continuous instream turbidity data is not without challenges; some of these include environmental fouling, calibration, and data range among sensors. Of greatest interest to many programs is a hysteresis in the relationship between turbidity and SSC, attributed to temporal variation of particle size distribution (Landers and Sturm, 2013; Uhrich et al., 2014). This phenomenon causes increased uncertainty in regression-estimated values of SSC, due to changes in nephelometric reflectance off the varying grain sizes in suspension (Uhrich et al., 2014). Here, we assess the feasibility and application of close-range remote sensing to quantify SSC and particle size distribution of a disturbed, and highly-turbid, river system. We use a consumer-grade digital camera to acquire imagery of the river surface and a depth-integrating sampler to collect concurrent suspended-sediment samples. We then develop two empirical linear regression models to relate image spectral information to concentrations of fine sediment (clay to silt) and total suspended sediment. Before presenting our regression model development, we briefly summarize each data-acquisition method.

","conferenceTitle":"SEDHYD 2015","conferenceDate":"19-23 April, 2015","conferenceLocation":"Reno, Nevada","language":"English","collaboration":"Federal Interagency Sediment Program","usgsCitation":"Mosbrucker, A.R., Spicer, K.R., Christianson, T.S., and Uhrich, M.A., 2015, Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery, SEDHYD 2015, Reno, Nevada, 19-23 April, 2015, 12 p.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060181","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":310634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562f4eb1e4b093cee780a287","contributors":{"authors":[{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christianson, Tami S. 0000-0002-6873-9229 tchristianson@usgs.gov","orcid":"https://orcid.org/0000-0002-6873-9229","contributorId":5986,"corporation":false,"usgs":true,"family":"Christianson","given":"Tami","email":"tchristianson@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Uhrich, Mark A. 0000-0002-5202-8086 mauhrich@usgs.gov","orcid":"https://orcid.org/0000-0002-5202-8086","contributorId":1149,"corporation":false,"usgs":true,"family":"Uhrich","given":"Mark","email":"mauhrich@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537626,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70137612,"text":"70137612 - 2015 - From mobile ADCP to high-resolution SSC: a cross-section calibration tool","interactions":[],"lastModifiedDate":"2016-03-09T15:15:35","indexId":"70137612","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"From mobile ADCP to high-resolution SSC: a cross-section calibration tool","docAbstract":"

Sediment is a major cause of stream impairment, and improved sediment monitoring is a crucial need. Point samples of suspended-sediment concentration (SSC) are often not enough to provide an understanding to answer critical questions in a changing environment. As technology has improved, there now exists the opportunity to obtain discrete measurements of SSC and flux while providing a spatial scale unmatched by any other device. Acoustic instruments are ubiquitous in the U.S. Geological Survey (USGS) for making streamflow measurements but when calibrated with physical sediment samples, they may be used for sediment measurements as well. The acoustic backscatter measured by an acoustic Doppler current profiler (ADCP) has long been known to correlate well with suspended sediment, but until recently, it has mainly been qualitative in nature. This new method using acoustic surrogates has great potential to leverage the routine data collection to provide calibrated, quantitative measures of SSC which hold promise to be more accurate, complete, and cost efficient than other methods. This extended abstract presents a method for the measurement of high spatial and temporal resolution SSC using a down-looking, mobile ADCP from discrete cross-sections. The high-resolution scales of sediment data are a primary advantage and a vast improvement over other discrete methods for measuring SSC. Although acoustic surrogate technology using continuous, fixed-deployment ADCPs (side-looking) is proven, the same methods cannot be used with down-looking ADCPs due to the fact that the SSC and particle-size distribution variation in the vertical profile violates theory and complicates assumptions. A software tool was developed to assist in using acoustic backscatter from a down-looking, mobile ADCP as a surrogate for SSC. This tool has a simple graphical user interface that loads the data, assists in the calibration procedure, and provides data visualization and output options. This tool is designed to improve ongoing efforts to monitor and predict resource responses to a changing environment. Because ADCPs are used routinely for streamflow measurements, using acoustic backscatter from ADCPs as a surrogate for SSC has the potential to revolutionize sediment measurements by providing rapid measurements of sediment flux and distribution at spatial and temporal scales that are far beyond the capabilities of traditional physical samplers.

","conferenceTitle":"SEDHYD 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, Nevada","language":"English","usgsCitation":"Boldt, J., 2015, From mobile ADCP to high-resolution SSC: a cross-section calibration tool, SEDHYD 2015, Reno, Nevada, April 19-23, 2015, 3 p.","productDescription":"3 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061674","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":310966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56389752e4b0d6133fe72fb3","contributors":{"authors":[{"text":"Boldt, Justin A. jboldt@usgs.gov","contributorId":4375,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin A.","email":"jboldt@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":537981,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70143970,"text":"70143970 - 2015 - Evaluation and application of regional turbidity-sediment regression models in Virginia","interactions":[],"lastModifiedDate":"2015-11-20T14:56:49","indexId":"70143970","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Evaluation and application of regional turbidity-sediment regression models in Virginia","docAbstract":"

Conventional thinking has long held that turbidity-sediment surrogate-regression equations are site specific and that regression equations developed at a single monitoring station should not be applied to another station; however, few studies have evaluated this issue in a rigorous manner. If robust regional turbidity-sediment models can be developed successfully, their applications could greatly expand the usage of these methods. Suspended sediment load estimation could occur as soon as flow and turbidity monitoring commence at a site, suspended sediment sampling frequencies for various projects potentially could be reduced, and special-project applications (sediment monitoring following dam removal, for example) could be significantly enhanced. The objective of this effort was to investigate the turbidity-suspended sediment concentration (SSC) relations at all available USGS monitoring sites within Virginia to determine whether meaningful turbidity-sediment regression models can be developed by combining the data from multiple monitoring stations into a single model, known as a “regional” model. Following the development of the regional model, additional objectives included a comparison of predicted SSCs between the regional model and commonly used site-specific models, as well as an evaluation of why specific monitoring stations did not fit the regional model.

","conferenceTitle":"10th Federal Interagency Sedimentation Conference","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","usgsCitation":"Hyer, K., Jastram, J.D., Moyer, D., Webber, J., and Chanat, J.G., 2015, Evaluation and application of regional turbidity-sediment regression models in Virginia, 10th Federal Interagency Sedimentation Conference, Reno, NV, April 19-23, 2015, 9 p.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061841","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":311618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.001708984375,\n 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jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543205,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70137273,"text":"sir20145233 - 2015 - Water quality of groundwater and stream base flow in the Marcellus Shale Gas Field of the Monongahela River Basin, West Virginia, 2011-12","interactions":[],"lastModifiedDate":"2015-06-25T13:10:28","indexId":"sir20145233","displayToPublicDate":"2015-04-21T10:00:00","publicationYear":"2015","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":"2014-5233","title":"Water quality of groundwater and stream base flow in the Marcellus Shale Gas Field of the Monongahela River Basin, West Virginia, 2011-12","docAbstract":"

The Marcellus Shale gas field underlies portions of New York, Pennsylvania, Ohio, Virginia, Maryland, Tennessee, and West Virginia. Development of hydraulic fracturing and horizontal drilling technology led to extensive development of gas from the Marcellus Shale beginning about 2007. The need to identify and monitor changes in water-quality conditions related to development of the Marcellus Shale gas field prompted the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection, Division of Water and Waste Management, to document water quality for comparison with water quality in samples collected at a future date. The identification of change in water-quality conditions over time is more difficult if baseline water-quality conditions have not been documented.

\n

U.S. Geological Survey personnel sampled groundwater and surface water in West Virginia’s Monongahela River Basin during 2011–12. A groundwater survey, in which 39 wells and 2 springs were sampled, was conducted during June through September 2011. A base-flow survey was conducted during July through October 2012; 50 stream sites were sampled under base-flow conditions in this survey.

\n

Because additives to hydraulic fracturing fluids are variable and decrease in flowback water over a relatively short time, water-quality analyses for this study focused on documenting the water-quality characteristics typical of water from shallow aquifers; water derived from contact with the Marcellus Shale (flowback from hydraulic fracturing or formation water); and water with constituents from conventional oil and gas development, sewage effluent, and coal-mine drainage. All samples were analyzed for field properties (water temperature, pH, specific conductance, dissolved oxygen, and turbidity), major ions, trace elements, naturally occurring radioactive materials, and stable isotopes.

\n

In addition to documenting baseline water-quality conditions for an area of shale-gas development, these data were examined for patterns in water quality. Groundwater and base-flow survey data were compared to historical data from the Monongahela River Basin in West Virginia. Additionally, groundwater- and base-flow survey samples were grouped by Marcellus Shale gas production in the subbasin in which that sampling site was located.

\n

The comparisons of data collected as part of this study with historical data identified few differences. No significant difference was found in a comparison of groundwater survey data and historical data. Base-flow survey samples differed significantly from historical data for pH, chloride, and strontium, all of which had higher concentrations in the base-flow survey samples. Differences in pH are likely related to changes in mining regulation beginning in 1977. Concentrations of chloride and strontium elevated above background concentrations may be related to saline groundwater; saline water is within 300 feet of the land surface in parts of the study area.

\n

In the comparison of base-flow survey samples grouped by shale-gas-production setting, significant differences were found for fluoride and barium. Concentrations of fluoride and barium were higher in stream subbasins with active Marcellus Shale production than in subbasins not near active Marcellus Shale production. Elevated fluoride and barium are associated with deep brines.

\n

Generally, naturally occurring radioactive materials were not found in elevated concentrations in either groundwater or base-flow samples. Only 3 samples, 2 from the groundwater survey and one from the base-flow survey, exceeded the U.S. Environmental Protection Agency maximum contaminant level for radium isotopes of 5.0 picocurie per liter for either a single isotope or a combined value of radium-226 and radium-228.

\n

Stable isotope composition indicates broad similarity among surface water, shallow groundwater, and precipitation in the region. Neither shallow groundwater nor surface water showed a marked similarity with the deep brines associated with shale gas. In most of the groundwater survey samples, 38 of 41 samples, dissolved gas profiles were similar to those previously found in samples from shallow, domestic wells in the region.

\n

This study provides a baseline of water-quality conditions in the Monongahela River Basin in West Virginia during the early phases of development of the Marcellus Shale gas field. Although not all inclusive, the results of this study provide a set of reliable water-quality data against which future data sets can be compared and the effects of shale-gas development may be determined.

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Landsat satellite data have been produced, archived, and distributed by the U.S. Geological Survey since 1972. Users rely on these data for historical study of land surface change and require consistent radiometric data processed to the highest science standards. In support of the guidelines established through the Global Climate Observing System, the U.S. Geological Survey has embarked on production of higher-level Landsat data products to support land surface change studies. One such product is Landsat surface reflectance.

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Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, South Dakota 57198

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Human land use will increasingly contribute to habitat loss and water shortages in California, given future population projections and associated land-use demand. Understanding how land-use change may impact future water use and where existing protected areas may be threatened by land-use conversion will be important if effective, sustainable management approaches are to be implemented. We used a state-and-transition simulation modeling (STSM) framework to simulate spatially-explicit (1 km2) historical (1992-2010) and future (2011-2060) land-use change for 52 California counties within Mediterranean California ecoregions. Historical land use and land cover (LULC) change estimates were derived from the Farmland Mapping and Monitoring Program dataset and attributed with county-level agricultural water-use data from the California Department of Water Resources. Five future alternative land-use scenarios were developed and modeled using the historical land-use change estimates and land-use projections based on the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios A2 and B1 scenarios. Spatial land-use transition outputs across scenarios were combined to reveal scenario agreement and a land conversion threat index was developed to evaluate vulnerability of existing protected areas to proximal land conversion. By 2060, highest LULC conversion threats were projected to impact nearly 10,500 km2 of land area within 10 km of a protected area boundary and over 18,000 km2 of land area within essential habitat connectivity areas. Agricultural water use declined across all scenarios perpetuating historical drought-related land use from 2008-2010 and trends of annual cropland conversion into perennial woody crops. STSM is useful in analyzing land-use related impacts on water resource use as well as potential threats to existing protected land. Exploring a range of alternative, yet plausible, LULC change impacts will help to better inform resource management and mitigation strategies.

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The recent proliferation of oil and natural gas energy development in the Greater Green River Basin of southwest Wyoming has accentuated the need to understand wildlife responses to this development. The location and extent of surface disturbance that is created by oil and natural gas well pad scars are key pieces of information used to assess the effects of energy infrastructure on wildlife populations and habitat. A digital database of oil and natural gas pad scars had previously been generated from 1-meter (m) National Agriculture Imagery Program imagery (NAIP) acquired in 2009 for a 7.7-million hectare (ha) (19,026,700 acres) region of southwest Wyoming. Scars included the pad area where wellheads, pumps, and storage facilities reside and the surrounding area that was scraped and denuded of vegetation during the establishment of the pad. Scars containing tanks, compressors, the storage of oil and gas related equipment, and produced-water ponds were also collected on occasion. This report updates the digital database for the five counties of southwest Wyoming (Carbon, Lincoln, Sublette, Sweetwater, Uinta) within the Wyoming Landscape Conservation Initiative (WLCI) study area and for a limited portion of Fremont, Natrona, and Albany Counties using 2012 1-m NAIP imagery and 2012 oil and natural gas well permit information. This report adds pad scars created since 2009, and updates attributes of all pad scars using the 2012 well permit information. These attributes include the origination year of the pad scar, the number of active and inactive wells on or near each pad scar in 2012, and the overall status of the pad scar (active or inactive). The new 2012 database contains 17,404 pad scars of which 15,532 are attributed as oil and natural gas well pads. Digital data are stored as shapefiles projected to the Universal Transverse Mercator (zones 12 and 13) coordinate system. These data are available from the U.S. Geological Survey (USGS) at http://dx.doi.org/10.3133/ds934.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds934","usgsCitation":"Garman, S.L., and McBeth, J.L., 2015, Digital representation of oil and natural gas well pad scars in southwest Wyoming: 2012 update: U.S. Geological Survey Data Series 934, 2 p., https://doi.org/10.3133/ds934.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059844","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":299802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds934.JPG"},{"id":299800,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0934/pdf/DS934_abstract.pdf","text":"Abstract","size":"31 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 934 Abstract"},{"id":299801,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0934/downloads/","text":"Downloads Directory","description":"DS 934 Downloads Directory","linkHelpText":"Contains: all related content to this data set."},{"id":299799,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0934/"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 40.99648401437787\n ],\n [\n -111.0498046875,\n 43.43696596521823\n ],\n [\n -107.314453125,\n 43.43696596521823\n ],\n [\n -107.314453125,\n 40.99648401437787\n ],\n [\n -111.0498046875,\n 40.99648401437787\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5536151ce4b0b22a15807a4d","contributors":{"authors":[{"text":"Garman, Steven L. 0000-0002-9032-9074 slgarman@usgs.gov","orcid":"https://orcid.org/0000-0002-9032-9074","contributorId":3741,"corporation":false,"usgs":true,"family":"Garman","given":"Steven","email":"slgarman@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":545347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McBeth, Jamie L. 0000-0002-7688-7985 jlmcbeth@usgs.gov","orcid":"https://orcid.org/0000-0002-7688-7985","contributorId":1254,"corporation":false,"usgs":true,"family":"McBeth","given":"Jamie","email":"jlmcbeth@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":545348,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70146633,"text":"70146633 - 2015 - Application of the FluEgg model to predict transport of Asian carp eggs in the Saint Joseph River (Great Lakes tributary)","interactions":[],"lastModifiedDate":"2015-06-02T11:28:45","indexId":"70146633","displayToPublicDate":"2015-04-17T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Application of the FluEgg model to predict transport of Asian carp eggs in the Saint Joseph River (Great Lakes tributary)","docAbstract":"

The Fluvial Egg Drift Simulator (FluEgg) is a three-dimensional Lagrangian model that simulates the movement and development of Asian carp eggs until hatching based on the physical characteristics of the flow field and the physical and biological characteristics of the eggs. This tool provides information concerning egg development and spawning habitat suitability including: egg plume location, egg vertical and travel time distribution, and egg-hatching risk. A case study of the simulation of Asian carp eggs in the Lower Saint Joseph River, a tributary of Lake Michigan, is presented. The river hydrodynamic input for FluEgg was generated in two ways — using hydroacoustic data and using HEC-RAS model data. The HEC-RAS model hydrodynamic input data were used to simulate 52 scenarios covering a broad range of flows and water temperatures with the eggs at risk of hatching ranging from 0 to 93% depending on river conditions. FluEgg simulations depict the highest percentage of eggs at risk of hatching occurs at the lowest discharge and at peak water temperatures. Analysis of these scenarios illustrates how the interactive relation among river length, hydrodynamics, and water temperature influence egg transport and hatching risk. An improved version of FluEgg, which more realistically simulates dispersion and egg development, is presented. Also presented is a graphical user interface that facilitates the use of FluEgg and provides a set of post-processing analysis tools to support management decision-making regarding the prevention and control of Asian carp reproduction in rivers with or without Asian carp populations.

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Ryan, Garcia Marcelo H.","journalName":"Journal of Great Lakes Research","publicationDate":"6/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Garcia, Tatiana 0000-0002-1979-7246 tgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-1979-7246","contributorId":140327,"corporation":false,"usgs":true,"family":"Garcia","given":"Tatiana","email":"tgarcia@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Elizabeth A. emurphy@usgs.gov","contributorId":3250,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","email":"emurphy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. 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The U.S. Geological Survey Kansas Water Science Center, in cooperation with Federal, State, and local agencies, maintains a long-term network of hydrologic monitoring gages in the State of Kansas. These include 206 real-time streamgages, 12 real-time reservoir-level monitoring stations, and 32 groundwater monitoring wells. These data and associated analyses, accumulated over time, provide a unique overview of hydrologic conditions and help improve our understanding of Kansas’s water resources. Yearly hydrologic conditions are determined by comparing statistical analyses of current and historical water year data for the period of record. These data are used in protecting life and property, and managing water resources for agricultural, industrial, public supply, ecological, and recreational purposes.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153027","usgsCitation":"Robison, A.L., 2015, Summary of hydrologic conditions in Kansas, water year 2014: U.S. Geological Survey Fact Sheet 2015-3027, 4 p., https://doi.org/10.3133/fs20153027.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2013-10-01","temporalEnd":"2014-09-30","ipdsId":"IP-062877","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":299750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153027.jpg"},{"id":299749,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3027/pdf/fs2015-3027.pdf","size":"3.03 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":299748,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3027/"}],"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 -102.041015625,\n 36.99377838872517\n ],\n [\n -102.073974609375,\n 40.01920130768676\n ],\n [\n -95.3173828125,\n 40.01920130768676\n ],\n [\n -95.20751953125,\n 39.926588421909436\n ],\n [\n -95.06469726562499,\n 39.85915479295669\n ],\n [\n -94.95483398437499,\n 39.918162846609455\n ],\n [\n -94.888916015625,\n 39.78321267821705\n ],\n [\n -94.95483398437499,\n 39.63953756436671\n ],\n [\n -95.0537109375,\n 39.50404070558415\n ],\n [\n -94.89990234375,\n 39.42770738465604\n ],\n [\n -94.82299804687499,\n 39.342794408952386\n ],\n [\n -94.71313476562499,\n 39.223742741391305\n ],\n [\n -94.603271484375,\n 39.08743603215884\n ],\n [\n -94.6142578125,\n 36.98500309285596\n ],\n [\n -102.041015625,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"553220a0e4b0b22a158063b7","contributors":{"authors":[{"text":"Robison, Andrew L. arobison@usgs.gov","contributorId":139840,"corporation":false,"usgs":true,"family":"Robison","given":"Andrew","email":"arobison@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":545154,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146890,"text":"70146890 - 2015 - 11.12 – Tools and techniques: gravitational method","interactions":[],"lastModifiedDate":"2015-12-08T16:43:39","indexId":"70146890","displayToPublicDate":"2015-04-17T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"11.12 – Tools and techniques: gravitational method","docAbstract":"

The gravitational method is used to investigate density variations within the subsurface at depths of several meters to tens of meters, as in depth-to-bedrock investigations, or at depths of several kilometers, as in sedimentary basin thickness investigations. This chapter covers fundamental relations, densities of Earth materials, instruments, field procedures, data reduction, filtering, forward modeling, inversion, and field examples. The focus is on near-surface investigations as distinct from the solid Earth studies found elsewhere in this treatise. The gravitational method is often used in conjunction with other geophysical methods, such as the magnetic method or the seismic method, which target similar physical properties at similar depths.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Treatise on Geophysics","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-444-53802-4.00197-4","usgsCitation":"Phillips, J., 2015, 11.12 – Tools and techniques: gravitational method, chap. of Treatise on Geophysics, v. 11, p. 393-418, https://doi.org/10.1016/B978-0-444-53802-4.00197-4.","productDescription":"26 p.","startPage":"393","endPage":"418","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044810","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":312048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","edition":"2nd","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56680d3fe4b06a3ea36c8e1e","contributors":{"authors":[{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":545488,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137525,"text":"ofr20141236 - 2015 - Accuracy testing of electric groundwater-level measurement tapes","interactions":[],"lastModifiedDate":"2015-04-16T16:14:45","indexId":"ofr20141236","displayToPublicDate":"2015-04-16T16:30:00","publicationYear":"2015","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":"2014-1236","title":"Accuracy testing of electric groundwater-level measurement tapes","docAbstract":"

Electric tapes are used to measure groundwater levels and to verify the accuracy of pressure transducers installed in wells. Electric tapes are generally assumed to be accurate to ±0.01 foot (ft), but little information is available from the manufacturers and no accuracy studies have been conducted to confirm this value. This study measured the accuracy of six popular models of electric groundwater tapes.

\n

The tapes tested include models from Durham Geo, Geotech, Heron, In-Situ, Solinst, and Waterline that are commonly used by the U.S.Geological Survey (USGS). The accuracy tests compared the length of each electric tape to a calibrated-steel reference tape and measured each probe’s activation accuracy and displacement volume. The tape-length accuracy combined with the probe-activation accuracy gave the overall measurement accuracy of the tape.

\n

The accuracy tests demonstrated that none of the electric-tape models tested consistently met the suggested USGS accuracy of ±0.01 ft. The test data show that the tape models in the study should give a water-level measurement that is accurate to roughly ±0.05 ft per 100 ft without additional calibration. To meet USGS accuracy guidelines, the electric-tape models tested will need to be individually calibrated. Specific conductance also plays a part in tape accuracy. The probes will not work in water with specific conductance values near zero, and the accuracy of one probe was unreliable in very high conductivity water (10,000 microsiemens per centimeter).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141236","usgsCitation":"Jelinski, J., Clayton, C.S., and Fulford, J.M., 2015, Accuracy testing of electric groundwater-level measurement tapes: U.S. Geological Survey Open-File Report 2014-1236, vi, 27 p., https://doi.org/10.3133/ofr20141236.","productDescription":"vi, 27 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052287","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":299747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141236.jpg"},{"id":299745,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1236/"},{"id":299746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1236/pdf/ofr2014-1236.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5530cf1ae4b0b22a15806131","contributors":{"authors":[{"text":"Jelinski, Jim","contributorId":138570,"corporation":false,"usgs":false,"family":"Jelinski","given":"Jim","email":"","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":537870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clayton, Christopher S. cclayton@usgs.gov","contributorId":5506,"corporation":false,"usgs":true,"family":"Clayton","given":"Christopher","email":"cclayton@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":537869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fulford, Janice M. jfulford@usgs.gov","contributorId":991,"corporation":false,"usgs":true,"family":"Fulford","given":"Janice","email":"jfulford@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":537871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70141192,"text":"sir20155018 - 2015 - Dissolved-solids loads discharged from irrigated areas near Manila, Utah, May 2007-October 2012, and relation of loads to selected variables","interactions":[],"lastModifiedDate":"2017-01-03T16:46:59","indexId":"sir20155018","displayToPublicDate":"2015-04-16T15:30:00","publicationYear":"2015","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":"2015-5018","title":"Dissolved-solids loads discharged from irrigated areas near Manila, Utah, May 2007-October 2012, and relation of loads to selected variables","docAbstract":"

The Manila/Washam Salinity Project (MWSP) is a cooperative effort by the Natural Resources Conservation Service (NRCS) and local farmers and ranchers to reduce the transport of dissolved solids to Flaming Gorge Reservoir from irrigated agricultural lands near Manila, Utah. To estimate dissolved-solids loads from the MWSP area, discharge and water quality from Birch Spring Draw and other selected outflows and inflows were monitored from May 2007 to October 2012. An average annual May–April streamflow of 5,960 acre-feet discharged from Birch Spring Draw at site BSD-2 to Flaming Gorge Reservoir during 2007–12, containing an average dissolved-solids load of 14,660 tons. An average May–April net dissolved-solids load of 24,300 tons per year discharged from the MWSP area, estimated from the relation between streamflow and dissolved-solids concentration at site BSD-2 and other measured inflows and outflows.

\n

The amount of precipitation and water available for irrigation are important factors affecting the dissolved-solids load in outflow from the MWSP area. Net dissolved-solids load discharged from the MWSP area increased with increasing canal streamflow and precipitation measured at Manila during the irrigation season, from May to October, each year. The net tons of dissolved solids discharged from the MWSP area per acre-foot of canal water increased with increasing irrigation season precipitation during May 2007–October 2012.

\n

Irrigation improvements began to be implemented in 2007 to reduce dissolved-solids loads discharged from the MWSP area. The theoretical annual net dissolved-solids load where the cumulative NRCS calculated dissolved-solids load reduction is added to the net MWSP dissolved-solids load is what would be expected if there was no irrigation improvement in the area associated with the MWSP. The theoretical data points lie very near the baseline representing the pre-MWSP dissolved-solids load to canal streamflow relation. The proximity of the theoretical data points to the baseline shows that the NRCS calculations of reduction in dissolved-solids load are generally supported by the data collected during this study.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155018","collaboration":"Prepared in cooperation with the Colorado River Basin Salinity Control Forum","usgsCitation":"Thiros, S.A., and Gerner, S.J., 2015, Dissolved-solids loads discharged from irrigated areas near Manila, Utah, May 2007-October 2012, and relation of loads to selected variables: U.S. Geological Survey Scientific Investigations Report 2015-5018, vi, 34 p., https://doi.org/10.3133/sir20155018.","productDescription":"vi, 34 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2007-05-01","temporalEnd":"2012-10-31","ipdsId":"IP-056819","costCenters":[{"id":610,"text":"Utah Water Science 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A better understanding is needed of how hydrological and biogeochemical processes control dissolved organic carbon (DOC) concentrations and dissolved organic matter (DOM) composition from headwaters downstream to large rivers. We examined a large DOM dataset from the National Water Information System of the US Geological Survey, which represents approximately 100 000 measurements of DOC concentration and DOM composition at many sites along rivers across the United States. Application of quantile regression revealed a tendency towards downstream spatial and temporal homogenization of DOC concentrations and a shift from dominance of aromatic DOM in headwaters to more aliphatic DOM downstream. The DOC concentration–discharge (C-Q) relationships at each site revealed a downstream tendency towards a slope of zero. We propose that despite complexities in river networks that have driven many revisions to the River Continuum Concept, rivers show a tendency towards chemostasis (C-Q slope of zero) because of a downstream shift from a dominance of hydrologic drivers that connect terrestrial DOM sources to streams in the headwaters towards a dominance of instream and near-stream biogeochemical processes that result in preferential losses of aromatic DOM and preferential gains of aliphatic DOM.

","language":"English","publisher":"National Research Council Canada","publisherLocation":"Ottawa, Canada","doi":"10.1139/cjfas-2014-0400","collaboration":"Federal Program","usgsCitation":"Creed, I., McKnight, D.M., Pellerin, B., Green, M., Bergamaschi, B.A., Aiken, G.R., Burns, D.A., Findlay, S.E., Shanley, J.B., Striegl, R.G., Aulenbach, B.T., Clow, D.W., Laudon, H., McGlynn, B.L., McGuire, K.J., Smith, R.A., and Stackpoole, S.M., 2015, The river as a chemostat: fresh perspectives on dissolved organic matter flowing down the river continuum: Canadian Journal of Fisheries and Aquatic Sciences, v. 72, no. 8, p. 1272-1285, https://doi.org/10.1139/cjfas-2014-0400.","productDescription":"14 p.","startPage":"1272","endPage":"1285","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049675","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National 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Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Critical metals in manganese nodules from the Cook Islands EEZ, abundances and distributions","docAbstract":"

The Cook Islands (CIs) Exclusive Economic Zone (EEZ) encompasses 1,977,000 km2 and includes the Penrhyn and Samoa basins abyssal plains where manganese nodules flourish due to the availability of prolific nucleus material, slow sedimentation rates, and strong bottom currents. A group of CIs nodules was analyzed for mineralogical and chemical composition, which include many critical metals not before analyzed for CIs nodules. These nodules have varying sizes and nuclei material; however all are composed predominantly of δ-MnO2 and X-ray amorphous iron oxyhydroxide. The mineralogy, Fe/Mn ratios, rare earth element contents, and slow growth rates (mean 1.9 mm/106 years) reflect formation primarily by hydrogenetic precipitation. The paucity of diagenetic input can be explained by low primary productivity at the surface and resultant low organic matter content in seafloor sediment, producing oxic seafloor and sub-seafloor environments. The nodules contain high mean contents of Co (0.41%), Ni (0.38%), Ti (1.20%), and total rare earth elements plus yttrium (REY; 0.167%), and also high contents of Mo, Nb, V, W, and Zr.

\n

Compiled data from a series of four cruises by the Japan International Cooperation Agency and the Mining agency of Japan from 1985 to 2000 were used to generate a map that defines the statistical distribution of nodule abundance throughout the EEZ, except the Manihiki Plateau. The abundance distribution map shows a belt of high nodule abundance (19–45 kg/m2) that starts in the southeast corner of the EEZ, runs northwest, and also bifurcates into a SW trending branch. Small, isolated areas contain abundances of nodules of up to 58 kg/m2. Six ~ 20,000 km2 areas of particularly high abundance were chosen to represent potential exploration areas, and maps for metal concentration were generated to visualize metal distribution and to extrapolate estimated metal tonnages within the six sites and the EEZ as a whole. Grades for Mn, Cu, and Ni are low in CIs nodules in areas of high abundance; however, Ti, Co, and REY show high contents where nodule abundances are high. Of the six areas identified to represent a range of metal contents, one at the northern end of the N-S abundance main belt optimizes the most metals and would yield the highest dry metric tons for Mn (61,002,292), Ni (1,247,834), Mo (186,166), V (356,247), W (30,215), and Zr (195,323). When compared with the Clarion–Clipperton Zone, the CIs nodules show higher nodule abundances (> 25 kg/m2 over ~ 123,844 km2), and are more enriched in the green-tech, high-tech, and energy metals Co, Ti, Te, Nb, REY, Pt, and Zr. The CIs EEZ shows a significant resource potential for these critical metals due to their high prices, high demand, and the high nodule abundance, which will allow for a smaller footprint for a 20-year mine site and therefore smaller environmental impact.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2014.12.011","usgsCitation":"Hein, J.R., Spinardi, F., Okamoto, N., Mizell, K., Thorburn, D., and Tawake, A., 2015, Critical metals in manganese nodules from the Cook Islands EEZ, abundances and distributions: Ore Geology Reviews, v. 68, p. 97-116, https://doi.org/10.1016/j.oregeorev.2014.12.011.","productDescription":"20 p.","startPage":"97","endPage":"116","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059336","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":299720,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cook Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.20263671875,\n -21.616579336740593\n ],\n [\n -159.49951171875,\n -21.616579336740593\n ],\n [\n -159.49951171875,\n -20.776659051878816\n ],\n [\n -160.20263671875,\n -20.776659051878816\n ],\n [\n -160.20263671875,\n -21.616579336740593\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"68","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5530cf1ee4b0b22a15806137","contributors":{"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":2828,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":545016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spinardi, Francesca fspinardi@usgs.gov","contributorId":4916,"corporation":false,"usgs":true,"family":"Spinardi","given":"Francesca","email":"fspinardi@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":545017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Okamoto, Nobuyuki","contributorId":140284,"corporation":false,"usgs":false,"family":"Okamoto","given":"Nobuyuki","email":"","affiliations":[{"id":13441,"text":"Sea-Floor Mineral Resources R&D Division, Metals Mining Technology Dept., JOGMEC, 2-10-1 Toranomon, Minato-ku, Tokyo 105-0001, Japan","active":true,"usgs":false}],"preferred":false,"id":545018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":545019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorburn, Darryl","contributorId":140285,"corporation":false,"usgs":false,"family":"Thorburn","given":"Darryl","email":"","affiliations":[{"id":13442,"text":"Seabed Minerals Authority, Avarua, Rarotonga, Cook Islands","active":true,"usgs":false}],"preferred":false,"id":545020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tawake, Akuila","contributorId":140286,"corporation":false,"usgs":false,"family":"Tawake","given":"Akuila","email":"","affiliations":[{"id":13443,"text":"SOPAC Division of the SPC, Private Mail Bag, GPO, Suva, Fiji Islands","active":true,"usgs":false}],"preferred":false,"id":545021,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}