The Niobrara River is an important and valuable economic and ecological resource in northern Nebraska that supports ecotourism, recreational boating, wildlife, fisheries, agriculture, and hydroelectric power. Because of its uniquely rich resources, a 122-kilometer reach of the Niobrara River was designated as a National Scenic River in 1991, which has been jointly managed by the U.S. Fish and Wildlife Service and National Park Service. To assess how the remarkable qualities of the National Scenic River may change if consumptive uses of water are increased above current levels, the U.S. Geological Survey, in cooperation with the National Park Service, initiated an investigation of how stream-channel morphology might be affected by potential decreases in summer streamflows. The study included a 65-kilometer segment in the wide, braided eastern stretch of the Niobrara National Scenic River that provides important nesting habitat for migratory bird species of concern to the Nation.
\nThe study focused on three river segments, separated at the confluences with two tributaries, Plum Creek and Long Pine Creek. With an overall temporal scope of 1988–2010 that includes a short interval preceding and a long interval following the Niobrara National Scenic River Designation Act of 1991, the study analyzed five separate time periods: 1988–93, 1994–99, 2000–3, 2004–6, and 2007–10, each of which ended with a year in which aerial photography coverage was available.
\nStreamflow duration was analyzed for one streamgage upstream from the study area and two streamgages on tributary streams within the study area. Summer streamflows (July, August, and September) were targeted for analysis because median flows of the Niobrara River are lowest during those 3 months. In addition, peak flows during the study period were used to estimate bankfull discharge, which is one determinant of channel dimensions.
\nChanges in channel morphology were examined using aerial photographs from 1993, 1999, 2003, 2006, and 2010 to measure channel width, area of islands, and incipient flood-plain surfaces, and to compute the braided index. Channel metrics were computed for each photography year and summarized by river segment. Additionally, at fixed-location cross sections, photography analysis identified localized geomorphic change to infer processes. Accuracy of geomorphic feature classification was estimated and the root-mean-square difference (RMSD) between aerial photographs was calculated to determine associated errors in channel metric calculations. The horizontal accuracy of boundaries delineated in the classification was estimated as 5 meters (m) for boundaries based on 1993 aerial photography and 4 m for all other aerial photography. The RMSD between aerial photography years ranged from 3.04 m to 4.16 m.
\nThe largest measurable changes in channel metrics were measured between 1993 and 1999 and between 1999 and 2003. Between 1993 and 1999, average total channel width increased by 9 m (3 percent) and 14 m (5 percent) in segments 2 and 3, respectively; average active channel width increased by 13 m (5 percent) in segment 3 and decreased by 6 m (4 percent) in segment 1; and incipient flood-plain-surface area increased by 40, 44, and 33 percent in segments 1, 2, and 3, respectively. Changes in channel metrics between 1999 and 2003 included a decrease in average total channel width of 14 m (5 percent) in segment 2; a decrease in active channel widths of 8 m (3 percent) and 6 m (2 percent) in segments 2 and 3, respectively; and an increase of 5 m (3 percent) in segment 1. Incipient flood-plain areas decreased by 22 and 33 percent in segments 1 and 2, respectively, and increased by 42 percent in segment 3.
\nLarge changes were measured between 1993 and 1999, and between 1999 and 2003, at many of the fixed-location cross sections. Large changes (that is, greater than 25 percent) in total channel width were measured in all three segments between 1993 and 1999 and again between 1999 and 2003; large increases were dominant between 1993 and 1999 and large decreases were dominant between 1999 and 2003. Segment 1 was the most susceptible to localized changes as there was only one period (between 2003 and 2006) in which the active channel width largely changed in fewer than 10 percent of the cross sections.
\nChanges in channel metrics generally corresponded to changes in streamflow conditions, but other than changes in incipient flood-plain area, these changes were small and were not measured in all three segments simultaneously. Increases in total channel width (except in segment 1) and incipient flood-plain area between 1993 and 1999 corresponded to increases in streamflow. Channel narrowing (except in segment 1) between 1999 and 2003 corresponded to lower summer streamflows and extended durations of very low summer streamflow. Although the pattern of low summer streamflow and extended durations of very low summer streamflow continued during the 2004–6 period and at the beginning of the 2007–10 period, no further narrowing was measured. Consistent tributary summer inflows help to explain the resistance of segments 2 and 3 to further narrowing. Because segment 1 is already much narrower than segments 2 and 3, its average current velocity is likely to be swifter and, therefore, competent to offset further effects of the processes that led to its narrowness.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165004","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Schaepe, N.J., Alexander, J.S., and Folz-Donahue, Kiernan, 2016, Effects of streamflows on stream-channel morphology in the eastern Niobrara National Scenic River, Nebraska, 1988–2010: U.S. Geological Survey Scientific Investigations Report 2016–5004, 30 p., https://dx.doi.org/10.3133/sir20165004.","productDescription":"vi, 30 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063713","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":318685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5004/sir20165004.pdf","text":"Report","size":"2.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5004"},{"id":318684,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5004/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Niobrara National Scenic River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.5523681640625,\n 42.706659563510385\n ],\n [\n -100.5523681640625,\n 42.956422511073335\n ],\n [\n -99.3218994140625,\n 42.956422511073335\n ],\n [\n -99.3218994140625,\n 42.706659563510385\n ],\n [\n -100.5523681640625,\n 42.706659563510385\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, Nebraska 68512
Four commercially available ultraviolet nitrate spectrophotometric sensors were evaluated by the U.S. Geological Survey Hydrologic Instrumentation Facility (HIF) to determine the effects of suspended sediment concentration (SSC) and colored dissolved organic matter (CDOM) on sensor accuracy. The evaluated sensors were: the Hach NITRATAX plus sc (5-millimeters (mm) path length), Hach NITRATAX plus sc (2 mm), S::CAN Spectro::lyser (5 mm), and the Satlantic SUNA V2 (5 mm). A National Institute of Standards and Technology-traceable nitrate-free sediment standard was purchased and used to create the turbid environment, and an easily made filtered tea solution was used for the CDOM test. All four sensors performed well in the test that evaluated the effect of suspended sediment on accuracy. The Hach 5 mm, Hach 2 mm, and the SUNA V2 met their respective manufacturer accuracy specifications up to concentrations of 4,500 milligrams per liter (mg/L) SSC. The S::CAN failed to meet its accuracy specifications when the SSC concentrations exceeded 4,000 mg/L. Test results from the effect of CDOM on accuracy indicated a significant skewing of data from all four sensors and showed an artificial elevation of measured nitrate to varying amounts. Of the four sensors tested, the Satlantic SUNA V2’s accuracy was affected the least in the CDOM test. The nitrate concentration measured by the SUNA V2 was approximately 24 percent higher than the actual concentration when estimated total organic carbon values exceeded 44 mg/L. Measured nitrate concentration falsely increased 49 percent when measured by the Hach 5 mm, and 75 percent when measured by the Hach 2 mm. The S::CAN’s reported nitrate concentration increased 96 percent. Path length plays an important role in the sensor’s ability to compensate measurements for matrix interferences, but does not solely determine how well a sensor can handle all interferences. The sensor’s proprietary algorithms also play a key role in matrix interference compensation. The sensors’ ability to compensate for CDOM varied significantly during the tests, even among the three with 5-mm path lengths. Results of this evaluation suggest that the proprietary algorithms of the nitrate analyzers are more effective compensating for suspended sediment, and less effective compensating for CDOM (color) when sensor path length remains constant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161014","usgsCitation":"Snazelle, T.T., 2016, The effect of suspended sediment and color on ultraviolet spectrophotometric nitrate sensors: U.S. Geological Survey Open-File Report, 2016−1014, 10 p., https://dx.doi.org/10.3133/ofr20161014.","productDescription":"Report: v,10 p.; Tables: 2-4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064543","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":318658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1014/ofr20161014.pdf","text":"Report","size":"1.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1014"},{"id":318676,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1014/table/ofr20161014_table4.xlsx","text":"Table 4 - Nitrate measurements by four ultraviolet sensors in water with a 5-mg-NL concentration with varying concentrations ofChief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2015.10.012","usgsCitation":"Gillan, J.K., Karl, J., Barger, N., Elaksher, A., and Duniway, M.C., 2016, Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery: Rangeland Ecology and Management, v. 69, no. 2, p. 95-107, https://doi.org/10.1016/j.rama.2015.10.012.","productDescription":"13 p.","startPage":"95","endPage":"107","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059477","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":318694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Shay Mesa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.6,\n 37.9\n ],\n [\n -109.6,\n 38\n ],\n [\n -109.5,\n 38\n ],\n [\n -109.5,\n 37.9\n ],\n [\n -109.6,\n 37.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56dff7b3e4b015c306fcda06","contributors":{"authors":[{"text":"Gillan, Jeffrey K.","contributorId":51656,"corporation":false,"usgs":true,"family":"Gillan","given":"Jeffrey","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":622150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karl, Jason W.","contributorId":22616,"corporation":false,"usgs":true,"family":"Karl","given":"Jason W.","affiliations":[],"preferred":false,"id":622151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barger, Nichole N.","contributorId":102392,"corporation":false,"usgs":true,"family":"Barger","given":"Nichole N.","affiliations":[],"preferred":false,"id":622152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elaksher, Ahmed","contributorId":72305,"corporation":false,"usgs":true,"family":"Elaksher","given":"Ahmed","affiliations":[],"preferred":false,"id":622153,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":622149,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168523,"text":"ofr20161017 - 2016 - Hydrologic conditions, recharge, and baseline water quality of the surficial aquifer system at Jekyll Island, Georgia, 2012-13","interactions":[],"lastModifiedDate":"2021-02-02T16:58:20.689444","indexId":"ofr20161017","displayToPublicDate":"2016-03-08T13:45:00","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":"2016-1017","title":"Hydrologic conditions, recharge, and baseline water quality of the surficial aquifer system at Jekyll Island, Georgia, 2012-13","docAbstract":"An increase of groundwater withdrawals from the surficial aquifer system on Jekyll Island, Georgia, prompted an investigation of hydrologic conditions and water quality by the U.S. Geological Survey during October 2012 through December 2013. The study demonstrated the importance of rainfall as the island’s main source of recharge to maintain freshwater resources by replenishing the water table from the effects of hydrologic stresses, primarily evapotranspiration and pumping. Groundwater-flow directions, recharge, and water quality of the water-table zone on the island were investigated by installing 26 shallow wells and three pond staff gages to monitor groundwater levels and water quality in the water-table zone. Climatic data from Brunswick, Georgia, were used to calculate potential maximum recharge to the water-table zone on Jekyll Island. A weather station located on the island provided only precipitation data. Additional meteorological data from the island would enhance potential evapotranspiration estimates for recharge calculations.
\nGroundwater levels and specific-conductance measurements showed the dependence of freshwater resources on rainfall to recharge the water-table zone of the surficial aquifer system and to influence groundwater flow on Jekyll Island. The unseasonably dry conditions during November 2012 to April 2013 induced saline water infiltration to the water-table zone from the marshland separating the Jekyll River from the island. A strong correlation (R2 = 0.97) of specific conductance to chloride concentration in water samples from wells installed in the water-table zone provided support for the determination of seasonal directions of groundwater flow by confirming salinity changes in the water-table zone. Unseasonably wet conditions during the late spring to August caused groundwater-flow reversals in some areas. The high dependence of the water-table zone in the surficial aquifer system on precipitation to replenish the aquifer with freshwater underscored the importance of monitoring groundwater levels, water quality, and water use to identify aquifer-discharge conditions that have the potential to promote seawater encroachment and degrade freshwater resources on Jekyll Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161017","collaboration":"Prepared in cooperation with the Jekyll Island Authority","usgsCitation":"Gordon, D.W., and Torak, L.J., 2016, Hydrologic conditions, recharge, and baseline water quality of the surficial aquifer system at Jekyll Island, Georgia, 2012–13: U.S. Geological Survey Open-File Report 2016–1017, 34 p., https://dx.doi.org/10.3133/ofr20161017.","productDescription":"Report: viii, 34 p.; Appendixes: 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055404","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318637,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1017/coverthb.jpg"},{"id":318641,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1017/ofr20161017_appendix3.xlsx","text":"Appendix 3. Groundwater-Level Measurements Made onDirector, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
The western United States is vulnerable to socioeconomic disruption due to extreme winter precipitation and floods. Traditionally, forecasts of precipitation and river discharge provide the basis for preparations. Herein we show that earlier event awareness may be possible through use of horizontal water vapor transport (integrated vapor transport (IVT)) forecasts. Applying the potential predictability concept to the National Centers for Environmental Prediction global ensemble reforecasts, across 31 winters, IVT is found to be more predictable than precipitation. IVT ensemble forecasts with the smallest spreads (least forecast uncertainty) are associated with initiation states with anomalously high geopotential heights south of Alaska, a setup conducive for anticyclonic conditions and weak IVT into the western United States. IVT ensemble forecasts with the greatest spreads (most forecast uncertainty) have initiation states with anomalously low geopotential heights south of Alaska and correspond to atmospheric rivers. The greater IVT predictability could provide warnings of impending storminess with additional lead times for hydrometeorological applications.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL067765","usgsCitation":"Lavers, D.A., Waliser, D.E., Ralph, F.M., and Dettinger, M.D., 2016, Predictability of horizontal water vapor transport relative to precipitation: Enhancing situational awareness for forecasting western U.S. extreme precipitation and flooding: Geophysical Research Letters, v. 43, no. 5, p. 2275-2282, https://doi.org/10.1002/2016GL067765.","productDescription":"8 p.","startPage":"2275","endPage":"2282","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074402","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl067765","text":"Publisher Index Page"},{"id":319397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-08","publicationStatus":"PW","scienceBaseUri":"56f661ade4b07d796bf770ea","contributors":{"authors":[{"text":"Lavers, David A.","contributorId":167847,"corporation":false,"usgs":false,"family":"Lavers","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":24837,"text":"Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":623809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waliser, Duane E.","contributorId":167848,"corporation":false,"usgs":false,"family":"Waliser","given":"Duane","email":"","middleInitial":"E.","affiliations":[{"id":24837,"text":"Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":623810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralph, F. Martin","contributorId":150276,"corporation":false,"usgs":false,"family":"Ralph","given":"F.","email":"","middleInitial":"Martin","affiliations":[{"id":17953,"text":"Earth Systems Research Lab, NOAA","active":true,"usgs":false}],"preferred":false,"id":623811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":623808,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70162634,"text":"sir20165009 - 2016 - Network global navigation satellite system surveys to harmonize American and Canadian datum for the Lake Champlain Basin","interactions":[],"lastModifiedDate":"2016-04-06T11:51:17","indexId":"sir20165009","displayToPublicDate":"2016-03-08T05:00:00","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":"2016-5009","title":"Network global navigation satellite system surveys to harmonize American and Canadian datum for the Lake Champlain Basin","docAbstract":"Historically high flood levels were observed during flooding in Lake Champlain and the Richelieu River from late April through May 2011. Flooding was caused by record spring precipitation and snowmelt from the third highest cumulative snowfall year on record, which included a warm, saturated late spring snowpack. Flood stage was exceeded for a total of 67 days from April 13 to June 19, 2011. During this flooding, shoreline erosion and lake flood inundation were exacerbated by wind-driven waves associated with local fetch and lake-wide seiche effects. In May 2011, a new water-surface-elevation record was set for Lake Champlain. Peak lake-level water-surface elevations varied at the three U.S. Geological Survey lake-level gages on Lake Champlain in 2011. The May 2011 peak water-surface elevations for Lake Champlain ranged from 103.20 feet above the National Geodetic Vertical Datum of 1929 at the northern end of Lake Champlain (at its outlet into the Richelieu River at Rouses Point, New York) to 103.57 feet above the National Geodetic Vertical Datum of 1929 at the southern end of the Lake in Whitehall, New York. The water-surface elevations for the Richelieu River in Canada are referenced to a different vertical datum than are those in Lake Champlain in the United States, which causes difficulty in assessing real-time flood water-surface elevations and comparing of flood peaks in the Lake Champlain Basin in the United States and Canada.
\nOn March 19, 2012, as a result of the flood event of April and May 2011, the Governments of Canada and the United States asked the International Joint Commission to draft a plan of study to examine the causes and the effects of the spring 2011 flooding on Lake Champlain and the Richelieu River and develop potential mitigation measures. Specific challenges noted by the International Lake Champlain-Richelieu River Technical Working Group (established by the International Joint Commission) included harmonization of vertical datums within the drainage basin. Harmonization of the vertical datum discrepancy is needed for flood assessment and future efforts to model the flow of water through the Lake Champlain Basin in the United States and Canada.
\nIn April 2015, the U.S. Geological Survey and Environment Canada began a joint field effort with the goal of obtaining precise elevations representing a common vertical datum for select reference marks used to determine water-surface elevations throughout Lake Champlain and the Richelieu River. To harmonize the datum difference between the United States and Canada, Global Navigation Satellite System surveys were completed at nine locations in the Lake Champlain Basin to collect simultaneous satellite data. These satellite data were processed to produce elevations for two reference marks associated with dams and seven reference marks associated with active water-level gages (lake gages in Lake Champlain and streamgages in the Richelieu River) to harmonize vertical datums throughout the Lake Champlain Basin. The Global Navigation Satellite System surveys were completed from April 14 to 16, 2015, at locations ranging from southern Lake Champlain near Whitehall, New York, to the northern end of the Richelieu River in Sorel, Quebec, at its confluence with the St. Lawrence River in Canada.
\nLake-gage water-surface elevations determined during the 3 days of surveys were converted to water-surface elevations referenced to the North American Vertical Datum of 1988 by using calculated offsets and historical water-surface elevations. In this report, an “offset” refers to the adjustment that needs to be applied to published data from a particular gage to produce elevation data referenced to the North American Vertical Datum of 1988. Offsets presented in this report can be used in the evaluation of water-surface elevations in a common datum for Lake Champlain and the Richelieu River. In addition, the water-level data referenced to the common datum (as determined from the offsets) may be used to calibrate flow models and support future modeling studies developed for Lake Champlain and the Richelieu River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165009","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Flynn, R.H., Rydlund, P.H., Jr., and Martin, D.J., 2016, Network global navigation satellite system surveys to harmonize American and Canadian datums for the Lake Champlain Basin (ver. 1.1, April 2016): U.S. Geological Survey Scientific Investigations Report 2016–5009, 17 p., https://dx.doi.org/10.3133/sir20165009.","productDescription":"Report: vii, 17 p.; Appendixes: 1-4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069015","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":319779,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5009/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5009"},{"id":318519,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5009/sir20165009.pdf","text":"Report","size":"3.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5009"},{"id":318520,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix1.zip","text":"Appendix 1","size":"13.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5009","linkHelpText":"- Global navigation satellite system data collection information"},{"id":318518,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5009/coverthb2.jpg"},{"id":318521,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix2.txt","text":"Appendix 2","size":"24 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5009","linkHelpText":"- Final coordinates for harmonization of datums"},{"id":318522,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix3.zip","text":"Appendix 3","size":"445 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5009","linkHelpText":"- Surveyor leveling information for sites with benchmarks that could not be surveyed directly with global navigation satellite systems"},{"id":318523,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix4.xlsx","text":"Appendix 4","size":"19 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5009","linkHelpText":"- Elevation offset information for benchmarks surveyed with global navigation satellite systems"}],"country":"Canada, United States","state":"New York, Quebec, Vermont","otherGeospatial":"Lake Champlain Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.278564453125,\n 43.37710501700073\n ],\n [\n -74.278564453125,\n 45.96642454131025\n ],\n [\n -72.432861328125,\n 45.96642454131025\n ],\n [\n -72.432861328125,\n 43.37710501700073\n ],\n [\n -74.278564453125,\n 43.37710501700073\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted March 8, 2016; Version 1.1: April 1, 2016","contact":"Director, New England Water Science Center
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Or visit our Web site at:
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High-water marks provide valuable data for understanding recent and historical flood events. The proper collection and recording of high-water mark data from perishable and preserved evidence informs flood assessments, research, and water resource management. Given the high cost of flooding in developed areas, experienced hydrographers, using the best available techniques, can contribute high-quality data toward efforts such as public education of flood risk, flood inundation mapping, flood frequency computations, indirect streamflow measurement, and hazard assessments.
This manual presents guidance for skilled high-water mark identification, including marks left behind in natural and man-made environments by tranquil and rapid flowing water. This manual also presents pitfalls and challenges associated with various types of flood evidence that help hydrographers identify the best high-water marks and assess the uncertainty associated with a given mark. Proficient high-water mark data collection contributes to better understanding of the flooding process and reduces risk through greater ability to estimate flood probability.
The U.S. Geological Survey, operating the Nation’s premier water data collection network, encourages readers of this manual to familiarize themselves with the art and science of high-water mark collection. The U.S. Geological survey maintains a national database at http://water.usgs.gov/floods/FEV/ that includes high-water mark information for many flood events, and local U.S. Geological Survey Water Science Centers can provide information to interested readers about participation in data collection and flood documentation efforts as volunteers or observers.
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Temperate freshwater wetlands are among the most productive terrestrial ecosystems, stimulating interest in using restored wetlands as biological carbon sequestration projects for greenhouse gas reduction programs. In this study, we used the eddy covariance technique to measure surface energy carbon fluxes from a constructed, impounded freshwater wetland during two annual periods that were 8 years apart: 2002–2003 and 2010–2011. During 2010–2011, we measured methane (CH4) fluxes to quantify the annual atmospheric carbon mass balance and its concomitant influence on global warming potential (GWP). Peak growing season fluxes of latent heat and carbon dioxide (CO2) were greater in 2002–2003 compared to 2010–2011. In 2002, the daily net ecosystem exchange reached as low as −10.6 g C m−2 d−1, which was greater than 3 times the magnitude observed in 2010 (−2.9 g C m−2 d−1). CH4 fluxes during 2010–2011 were positive throughout the year and followed a strong seasonal pattern, ranging from 38.1 mg C m−2 d−1 in the winter to 375.9 mg C m−2 d−1 during the summer. The results of this study suggest that the wetland had reduced gross ecosystem productivity in 2010–2011, likely due to the increase in dead plant biomass (standing litter) that inhibited the generation of new vegetation growth. In 2010–2011, there was a net positive GWP (675.3 g C m−2 yr−1), and when these values are evaluated as a sustained flux, the wetland will not reach radiative balance even after 500 years.
","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Hoboken, NJ","doi":"10.1002/2015JG003083","usgsCitation":"Anderson, F., Bergamaschi, B.A., Sturtevant, C., Knox, S., Hastings, L., Windham-Myers, L., Detto, M., Hestir, E.L., Drexler, J.Z., Miller, R., Matthes, J., Verfaillie, J., Baldocchi, D., Snyder, R.L., and Fujii, R., 2016, Variation of energy and carbon fluxes from a restored temperate freshwater wetland and implications for carbon market verification protocols: Journal of Geophysical Research: Biogeosciences, v. 121, no. 3, p. 777-795, https://doi.org/10.1002/2015JG003083.","productDescription":"19 p.","startPage":"777","endPage":"795","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060580","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471174,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jg003083","text":"Publisher Index 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0000-0003-3496-4919","orcid":"https://orcid.org/0000-0003-3496-4919","contributorId":167495,"corporation":false,"usgs":false,"family":"Baldocchi","given":"Dennis","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":622482,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Snyder, Richard L.","contributorId":167497,"corporation":false,"usgs":false,"family":"Snyder","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":24726,"text":"Department of Land, Air and Water Resources","active":true,"usgs":false}],"preferred":false,"id":622484,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Fujii, Roger rfujii@usgs.gov","contributorId":167499,"corporation":false,"usgs":true,"family":"Fujii","given":"Roger","email":"rfujii@usgs.gov","affiliations":[{"id":154,"text":"California Water Science 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Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.
","language":"English","publisher":"Institute of Physics and IOP Pub.","publisherLocation":"Bristol, U.K.","doi":"10.1088/1748-9326/11/3/034014","usgsCitation":"Abbott, B.W., Jeremy B. Jones, Schuur, E.A., Chapin, F., Bowden, W.B., Bret-Harte, M.S., Epstein, H.E., Flannigan, M.D., Harms, T.K., Hollingsworth, T.N., Mack, M.C., McGuire, A.D., Natali, S.M., Adrian V. Rocha, Tank, S.E., Turetsky, M.R., Vonk, J.E., Wickland, K.P., and Aiken, G.R., 2016, Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment: Environmental Research Letters, v. 11, no. 3, p. 1-13, https://doi.org/10.1088/1748-9326/11/3/034014.","productDescription":"13 p.","startPage":"1","endPage":"13","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065090","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/11/3/034014","text":"Publisher Index Page"},{"id":321285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-07","publicationStatus":"PW","scienceBaseUri":"574d644fe4b07e28b66835bb","contributors":{"authors":[{"text":"Abbott, Benjamin W.","contributorId":150799,"corporation":false,"usgs":false,"family":"Abbott","given":"Benjamin","email":"","middleInitial":"W.","affiliations":[{"id":18106,"text":"Universite de Rennes, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":629477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jeremy B. 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Limited information has been reported regarding the prevalence, pathogenicity, and genetic diversity of AMPV-4. To assess the intercontinental dispersal of this viral agent, we sequenced the fusion gene of 58 APMV-4 isolates collected in the United States, Japan and the Ukraine and compared them to all available sequences on GenBank. With only a single exception the phylogenetic clades of APMV-4 sequences were monophyletic with respect to their continents of origin (North America, Asia and Europe). Thus, we detected limited evidence for recent intercontinental dispersal of APMV-4 in this study.
","language":"English","publisher":"Elsevier Science","doi":"10.1016/j.meegid.2016.02.031","usgsCitation":"Reeves, A.B., Poulson, R.L., Muzyka, D., Ogawa, H., Imai, K., Nghia Bui, V., Hall, J.S., Pantin-Jackwood, M., Stallknecht, D.E., and Ramey, A.M., 2016, Limited evidence of intercontinental dispersal of avian paramyxovirus serotype 4 by migratory birds: Infection, Genetics and Evolution, v. 40, p. 104-108, https://doi.org/10.1016/j.meegid.2016.02.031.","productDescription":"5 p.","startPage":"104","endPage":"108","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070263","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":471177,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4844831","text":"Publisher Index Page"},{"id":318644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56dea629e4b015c306fb51df","chorus":{"doi":"10.1016/j.meegid.2016.02.031","url":"http://dx.doi.org/10.1016/j.meegid.2016.02.031","publisher":"Elsevier BV","authors":"Reeves Andrew B., Poulson Rebecca L., Muzyka Denys, Ogawa Haruko, Imai Kunitoshi, Bui Vuong Nghia, Hall Jeffrey S., Pantin-Jackwood Mary, Stallknecht David E., Ramey Andrew M.","journalName":"Infection, Genetics and Evolution","publicationDate":"6/2016","auditedOn":"3/13/2017","publiclyAccessibleDate":"3/4/2017"},"contributors":{"authors":[{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":622004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poulson, Rebecca L.","contributorId":68669,"corporation":false,"usgs":true,"family":"Poulson","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":622005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muzyka, Denys","contributorId":167372,"corporation":false,"usgs":false,"family":"Muzyka","given":"Denys","email":"","affiliations":[],"preferred":false,"id":622006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogawa, Haruko","contributorId":138522,"corporation":false,"usgs":false,"family":"Ogawa","given":"Haruko","email":"","affiliations":[],"preferred":false,"id":622065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Imai, Kunitoshi","contributorId":138523,"corporation":false,"usgs":false,"family":"Imai","given":"Kunitoshi","email":"","affiliations":[],"preferred":false,"id":622066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nghia Bui, Vuong","contributorId":138524,"corporation":false,"usgs":false,"family":"Nghia Bui","given":"Vuong","email":"","affiliations":[],"preferred":false,"id":622067,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":622068,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pantin-Jackwood, Mary","contributorId":167373,"corporation":false,"usgs":false,"family":"Pantin-Jackwood","given":"Mary","affiliations":[{"id":13585,"text":"Poultry Research Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Athens, Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":622069,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stallknecht, David E.","contributorId":20230,"corporation":false,"usgs":true,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":622070,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":622071,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70169053,"text":"70169053 - 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We studied body condition of dabbling ducks shot by hunters at public hunting areas throughout the Central Valley of California during 2006–2008 compared with condition of ducks from 1979 to 1993. These time periods coincide with habitat increases due to Central Valley Joint Venture conservation programs and changing agricultural practices; we modeled to ascertain whether body condition differed among waterfowl during these periods. Three dataset comparisons indicate that dabbling duck body mass was greater in 2006–2008 than earlier years and the increase was greater in the Sacramento Valley and Suisun Marsh than in the San Joaquin Valley, differed among species (mallard [Anas platyrhynchos], northern pintail [Anas acuta], America wigeon [Anas americana], green-winged teal [Anas crecca], and northern shoveler [Anas clypeata]), and was greater in ducks harvested late in the season. Change in body mass also varied by age–sex cohort and month for all 5 species and by September–January rainfall for all except green-winged teal. The random effect of year nested in period, and sometimes interacting with other factors, improved models in many cases. Results indicate that improved habitat conditions in the Central Valley have resulted in increased winter body mass of dabbling ducks, especially those that feed primarily on seeds, and this increase was greater in regions where area of post-harvest flooding of rice and other crops, and wetland area, has increased. Conservation programs that continue to promote post-harvest flooding and other agricultural practices that benefit wintering waterfowl and continue to restore and conserve wetlands would likely help maintain body condition of wintering dabbling ducks in the Central Valley of California.
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2016 - Assessing spring direct mortality to avifauna from wind energy facilities in the Dakotas","interactions":[],"lastModifiedDate":"2016-10-26T12:37:45","indexId":"70177902","displayToPublicDate":"2016-03-06T09:15:00","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":"Assessing spring direct mortality to avifauna from wind energy facilities in the Dakotas","docAbstract":"The Northern Great Plains (NGP) contains much of the remaining temperate grasslands, an ecosystem that is one of the most converted and least protected in the world. Within the NGP, the Prairie Pothole Region (PPR) provides important habitat for >50% of North America's breeding waterfowl and many species of shorebirds, waterbirds, and grassland songbirds. This region also has high wind energy potential, but the effects of wind energy developments on migratory and resident bird and bat populations in the NGP remains understudied. This is troubling considering >2,200 wind turbines are actively generating power in the region and numerous wind energy projects have been proposed for development in the future. Our objectives were to estimate avian and bat fatality rates for wind turbines situated in cropland- and grassland-dominated landscapes, document species at high risk to direct mortality, and assess the influence of habitat variables on waterfowl mortality at 2 wind farms in the NGP. From 10 March to 7 June 2013–2014, we completed 2,398 searches around turbines for carcasses at the Tatanka Wind Farm (TAWF) and the Edgeley-Kulm Wind Farm (EKWF) in South Dakota and North Dakota. During spring, we found 92 turbine-related mortalities comprising 33 species and documented a greater diversity of species (n = 30) killed at TAWF (predominately grassland) than at EKWF (n = 9; predominately agricultural fields). After accounting for detection rates, we estimated spring mortality of 1.86 (SE = 0.22) deaths/megawatt (MW) at TAWF and 2.55 (SE = 0.51) deaths/MW at EKWF. Waterfowl spring (Mar–Jun) fatality rates were 0.79 (SE = 0.11) and 0.91 (SE = 0.10) deaths/MW at TAWF and EKWF, respectively. Our results suggest that future wind facility siting decisions consider avoiding grassland habitats and locate turbines in pre-existing fragmented and converted habitat outside of high densities of breeding waterfowl and major migration corridors.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.1051","usgsCitation":"Graff, B.J., Jenks, J., Stafford, J.D., Jensen, K.C., and Grovenburg, T.W., 2016, Assessing spring direct mortality to avifauna from wind energy facilities in the Dakotas: Journal of Wildlife Management, v. 80, no. 4, p. 736-745, https://doi.org/10.1002/jwmg.1051.","productDescription":"10 p.","startPage":"736","endPage":"745","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066411","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":330409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Dakota","county":"Dickey County, LaMoure County, McIntosh County, McPherson County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.876708984375,\n 45.54867850352087\n ],\n [\n -99.876708984375,\n 46.64189395892872\n ],\n [\n -98.0859375,\n 46.64189395892872\n ],\n [\n -98.0859375,\n 45.54867850352087\n ],\n [\n -99.876708984375,\n 45.54867850352087\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-06","publicationStatus":"PW","scienceBaseUri":"5811c0f2e4b0f497e79a5a79","contributors":{"authors":[{"text":"Graff, Brianna J.","contributorId":176317,"corporation":false,"usgs":false,"family":"Graff","given":"Brianna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":652166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":652167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stafford, Joshua D. jstafford@usgs.gov","contributorId":4267,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":652092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jensen, Kent C.","contributorId":66530,"corporation":false,"usgs":false,"family":"Jensen","given":"Kent","email":"","middleInitial":"C.","affiliations":[{"id":16687,"text":"Department of Natural Resource Management, South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":652168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":652169,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170211,"text":"70170211 - 2016 - Supporting diverse data providers in the open water data initiative: Communicating water data quality and fitness of use","interactions":[],"lastModifiedDate":"2016-08-04T15:35:05","indexId":"70170211","displayToPublicDate":"2016-03-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Supporting diverse data providers in the open water data initiative: Communicating water data quality and fitness of use","docAbstract":"Shared, trusted, timely data are essential elements for the cooperation needed to optimize economic, ecologic, and public safety concerns related to water. The Open Water Data Initiative (OWDI) will provide a fully scalable platform that can support a wide variety of data from many diverse providers. Many of these will be larger, well-established, and trusted agencies with a history of providing well-documented, standardized, and archive-ready products. However, some potential partners may be smaller, distributed, and relatively unknown or untested as data providers. The data these partners will provide are valuable and can be used to fill in many data gaps, but can also be variable in quality or supplied in nonstandardized formats. They may also reflect the smaller partners' variable budgets and missions, be intermittent, or of unknown provenance. A challenge for the OWDI will be to convey the quality and the contextual “fitness” of data from providers other than the most trusted brands. This article reviews past and current methods for documenting data quality. Three case studies are provided that describe processes and pathways for effective data-sharing and publication initiatives. They also illustrate how partners may work together to find a metadata reporting threshold that encourages participation while maintaining high data integrity. And lastly, potential governance is proposed that may assist smaller partners with short- and long-term participation in the OWDI.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12406","usgsCitation":"Larsen, S., Hamilton, S., Lucido, J., Garner, B.D., and Young, D., 2016, Supporting diverse data providers in the open water data initiative: Communicating water data quality and fitness of use: Journal of the American Water Resources Association, v. 52, no. 4, p. 859-872, https://doi.org/10.1111/1752-1688.12406.","productDescription":"14 p.","startPage":"859","endPage":"872","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069137","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471179,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12406","text":"Publisher Index Page"},{"id":320019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-06","publicationStatus":"PW","scienceBaseUri":"570f6dbde4b0ef3b7ca356aa","contributors":{"authors":[{"text":"Larsen, Sara","contributorId":168563,"corporation":false,"usgs":false,"family":"Larsen","given":"Sara","email":"","affiliations":[{"id":25336,"text":"Western States Water Council","active":true,"usgs":false}],"preferred":false,"id":626478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamilton, Stuart","contributorId":168564,"corporation":false,"usgs":false,"family":"Hamilton","given":"Stuart","affiliations":[{"id":25337,"text":"Aquatic Informatics","active":true,"usgs":false}],"preferred":false,"id":626479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucido, Jessica M. jlucido@usgs.gov","contributorId":4695,"corporation":false,"usgs":true,"family":"Lucido","given":"Jessica M.","email":"jlucido@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":626477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garner, Bradley D. 0000-0002-6912-5093 bdgarner@usgs.gov","orcid":"https://orcid.org/0000-0002-6912-5093","contributorId":2133,"corporation":false,"usgs":true,"family":"Garner","given":"Bradley","email":"bdgarner@usgs.gov","middleInitial":"D.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":626480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, Dwane","contributorId":168541,"corporation":false,"usgs":false,"family":"Young","given":"Dwane","affiliations":[{"id":25326,"text":"U.S. Environmental Protection Agency, 1200 Pennsylvania Ave., NW, Washington, DC, USA 20460","active":true,"usgs":false}],"preferred":false,"id":626481,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70177886,"text":"70177886 - 2016 - Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites","interactions":[],"lastModifiedDate":"2017-01-17T19:17:22","indexId":"70177886","displayToPublicDate":"2016-03-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites","docAbstract":"Evapotranspiration (ET) is an important component of the water cycle – ET from the land surface returns approximately 60% of the global precipitation back to the atmosphere. ET also plays an important role in energy transport among the biosphere, atmosphere, and hydrosphere. Current regional to global and daily to annual ET estimation relies mainly on surface energy balance (SEB) ET models or statistical and empirical methods driven by remote sensing data and various climatological databases. These models have uncertainties due to inevitable input errors, poorly defined parameters, and inadequate model structures. The eddy covariance measurements on water, energy, and carbon fluxes at the AmeriFlux tower sites provide an opportunity to assess the ET modeling uncertainties. In this study, we focused on uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model for ET estimation at multiple AmeriFlux tower sites with diverse land cover characteristics and climatic conditions. The 8-day composite 1-km MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) was used as input land surface temperature for the SSEBop algorithms. The other input data were taken from the AmeriFlux database. Results of statistical analysis indicated that the SSEBop model performed well in estimating ET with an R2 of 0.86 between estimated ET and eddy covariance measurements at 42 AmeriFlux tower sites during 2001–2007. It was encouraging to see that the best performance was observed for croplands, where R2 was 0.92 with a root mean square error of 13 mm/month. The uncertainties or random errors from input variables and parameters of the SSEBop model led to monthly ET estimates with relative errors less than 20% across multiple flux tower sites distributed across different biomes. This uncertainty of the SSEBop model lies within the error range of other SEB models, suggesting systematic error or bias of the SSEBop model is within the normal range. This finding implies that the simplified parameterization of the SSEBop model did not significantly affect the accuracy of the ET estimate while increasing the ease of model setup for operational applications. The sensitivity analysis indicated that the SSEBop model is most sensitive to input variables, land surface temperature (LST) and reference ET (ETo); and parameters, differential temperature (dT), and maximum ET scalar (Kmax), particularly during the non-growing season and in dry areas. In summary, the uncertainty assessment verifies that the SSEBop model is a reliable and robust method for large-area ET estimation. The SSEBop model estimates can be further improved by reducing errors in two input variables (ETo and LST) and two key parameters (Kmax and dT).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.02.026","usgsCitation":"Chen, M., Senay, G.B., Singh, R.K., and Verdin, J.P., 2016, Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites: Journal of Hydrology, v. 536, p. 384-399, https://doi.org/10.1016/j.jhydrol.2016.02.026.","productDescription":"16 p.","startPage":"384","endPage":"399","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071555","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.02.026","text":"Publisher Index Page"},{"id":330417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"536","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5811c0f3e4b0f497e79a5a7b","chorus":{"doi":"10.1016/j.jhydrol.2016.02.026","url":"http://dx.doi.org/10.1016/j.jhydrol.2016.02.026","publisher":"Elsevier BV","authors":"Chen Mingshi, Senay Gabriel B., Singh Ramesh K., Verdin James P.","journalName":"Journal of Hydrology","publicationDate":"5/2016","auditedOn":"4/1/2016","publiclyAccessibleDate":"2/23/2016"},"contributors":{"authors":[{"text":"Chen, Mingshi mchen@usgs.gov","contributorId":4204,"corporation":false,"usgs":true,"family":"Chen","given":"Mingshi","email":"mchen@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":652237,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170216,"text":"70170216 - 2016 - The physiology of mangrove trees with changing climate","interactions":[],"lastModifiedDate":"2016-07-17T23:20:46","indexId":"70170216","displayToPublicDate":"2016-03-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"title":"The physiology of mangrove trees with changing climate","docAbstract":"Mangrove forests grow on saline, periodically flooded soils of the tropical and subtropical coasts. The tree species that comprise the mangrove are halophytes that have suites of traits that confer differing levels of tolerance of salinity, aridity, inundation and extremes of temperature. Here we review how climate change and elevated levels of atmospheric CO2 will influence mangrove forests. Tolerance of salinity and inundation in mangroves is associated with the efficient use of water for photosynthetic carbon gain which unpins anticipated gains in productivity with increasing levels of CO2. We review evidence of increases in productivity with increasing CO2, finding that enhancements in growth appear to be similar to trees in non-mangrove habitats and that gains in productivity with elevated CO2 are likely due to changes in biomass allocation. High levels of trait plasticity are observed in some mangrove species, which potentially facilitates their responses to climate change. Trait plasticity is associated with broad tolerance of salinity, aridity, low temperatures and nutrient availability. Because low temperatures and aridity place strong limits on mangrove growth at the edge of their current distribution, increasing temperatures over time and changing rainfall patterns are likely to have an important influence on the distribution of mangroves. We provide a global analysis based on plant traits and IPCC scenarios of changing temperature and aridity that indicates substantial global potential for mangrove expansion.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tree physiology: Adaptations and responses in a changing environment","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-27422-5_7","usgsCitation":"Lovelock, C.E., Krauss, K.W., Osland, M.J., Reef, R., and Ball, M.C., 2016, The physiology of mangrove trees with changing climate, chap. of Tree physiology: Adaptations and responses in a changing environment, v. 6, p. 149-179, https://doi.org/10.1007/978-3-319-27422-5_7.","productDescription":"31 p.","startPage":"149","endPage":"179","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060844","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":319976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"570e1c37e4b0ef3b7ca24c4c","contributors":{"editors":[{"text":"Meinzer, Frederick C.","contributorId":168571,"corporation":false,"usgs":false,"family":"Meinzer","given":"Frederick","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":626533,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Niinemets, Ulo","contributorId":168572,"corporation":false,"usgs":false,"family":"Niinemets","given":"Ulo","email":"","affiliations":[],"preferred":false,"id":626534,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Lovelock, Catherine E.","contributorId":64787,"corporation":false,"usgs":true,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":626520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":626518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":626519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reef, Ruth","contributorId":44826,"corporation":false,"usgs":true,"family":"Reef","given":"Ruth","email":"","affiliations":[],"preferred":false,"id":626521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ball, Marilyn C.","contributorId":7981,"corporation":false,"usgs":true,"family":"Ball","given":"Marilyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":626522,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70164631,"text":"sir20165020 - 2016 - Groundwater quality, age, and susceptibility and vulnerability to nitrate contamination with linkages to land use and groundwater flow, Upper Black Squirrel Creek Basin, Colorado, 2013","interactions":[],"lastModifiedDate":"2016-03-09T17:48:45","indexId":"sir20165020","displayToPublicDate":"2016-03-03T18:00:00","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":"2016-5020","title":"Groundwater quality, age, and susceptibility and vulnerability to nitrate contamination with linkages to land use and groundwater flow, Upper Black Squirrel Creek Basin, Colorado, 2013","docAbstract":"The Upper Black Squirrel Creek Basin is located about 25 kilometers east of Colorado Springs, Colorado. The primary aquifer is a productive section of unconsolidated deposits that overlies bedrock units of the Denver Basin and is a critical resource for local water needs, including irrigation, domestic, and commercial use. The primary aquifer also serves an important regional role by the export of water to nearby communities in the Colorado Springs area. Changes in land use and development over the last decade, which includes substantial growth of subdivisions in the Upper Black Squirrel Creek Basin, have led to uncertainty regarding the potential effects to water quality throughout the basin. In response, the U.S. Geological Survey, in cooperation with Cherokee Metropolitan District, El Paso County, Meridian Service Metropolitan District, Mountain View Electric Association, Upper Black Squirrel Creek Groundwater Management District, Woodmen Hills Metropolitan District, Colorado State Land Board, and Colorado Water Conservation Board, and the stakeholders represented in the Groundwater Quality Study Committee of El Paso County conducted an assessment of groundwater quality and groundwater age with an emphasis on characterizing nitrate in the groundwater.
\nGroundwater-quality samples were collected from 50 randomly selected wells between May and June 2013. The samples were analyzed for major ions, nutrients, dissolved gases, tritium (3H), chlorofluorocarbons (CFC-11, CFC-12, and CFC-113), and fuel products (such as benzene, toluene, ethylbenzene, and xylenes). None of the groundwater samples exceeded the U.S. Environmental Protection Agency (EPA) National Primary Drinking Water Regulations for primary maximum contaminant levels (MCL) for major ions. Secondary maximum contaminant levels, which are not health concerns and affect mainly taste, color, or odor of the water, were observed in rare instances for pH (2 samples), chloride (1 sample), iron (3 samples), and manganese (8 samples). The secondary maximum contaminant level for total dissolved solids was also exceeded for two samples.
\nNitrate (nitrite plus nitrate as nitrogen in groundwater) was elevated above the estimated background concentration of natural recharge waters of 1 milligram per liter (mg/L) in 44 of the 50 wells sampled and showed a median concentration of 5.4 mg/L. Nitrate concentrations were above the MCL of 10 mg/L in 5 of the 50 wells sampled and above half of the EPA MCL (5 mg/L) in 27 of the 50 wells sampled, which included samples above the MCL. Dissolved-oxygen concentrations exceeded 0.5 mg/L in 95 percent of reported values (40 of 42 samples) and exceeded 2.0 mg/L in 90 percent of reported values (38 of 42 samples). The oxidized conditions observed in most areas indicate that nitrate from fertilizers and animal or human waste was geochemically stable and could persist in the groundwater for decades or perhaps longer. A historical analysis of median nitrate concentrations over nearly three decades showed an increase in nitrate of approximately 1 mg/L from 4.3 to 5.4 mg/L, although the increase was not determined to be significantly different using nonparametric statistical methods.
\nMajor-ion data indicate that groundwater representative of the primary aquifer was classified as calcium-sodium bicarbonate type water. Other water samples from wells located mainly along the periphery of the primary aquifer had cation-anion compositions consistent with distinct water sources, including groundwater contributions from the underlying bedrock aquifers. The areas with differentiable water sources were located mainly where alluvial deposits were thin and geologic contacts to the underlying bedrock aquifers were relatively shallow.
\nNitrate concentrations in the groundwater were evaluated for relations to land use. An agricultural region was defined using a sequence of land satellite imagery. Groundwater flow directions interpreted from median water-table elevations measured from 2000 to 2013 were used in conjunction with cropland locations to define the agricultural region boundaries by encompassing potential pathways of nitrate transport in the groundwater from nitrogen-based fertilizers. A statistically significant higher median nitrate concentration was observed for areas inside the agricultural region (6.7 mg/L) compared to areas outside the agricultural region (2.3 mg/L), although median concentrations in both areas were below the MCL (10 mg/L). Median nitrate concentration was also significantly greater in land parcels with septic use (4.9 mg/L) compared to nonseptic parcels (1.7 mg/L). In general, agriculture or septic use was identified as the primary source of nitrate, depending on location, while commercial, county, grazing, and residential land uses were generally secondary sources of nitrate.
\nApparent groundwater ages were estimated from chlorofluorocarbons (CFC-11, CFC-12, and CFC-113) and tritium (3H) data using models that assumed piston flow and binary mixing (dilution of a young component with old, tracer-free water). The mean and median groundwater ages were about 30 years and the standard deviation was 6 years, indicating that most groundwater in the primary aquifer was “young” water that had recharged to the aquifer over the last few decades (post-1950s). The median fraction of young water was about 71 percent, and the standard deviation was 29 percent. The remaining water predated the 1950s, which may have originated from deeper geologic formations or may represent slow moving groundwater within the primary aquifer. Some of the oldest groundwater ages (older than 30 years) were observed in the upper reaches of the aquifer to the northwest where the primary aquifer is thin and intersects bedrock, supporting the hypothesis of geochemically distinct groundwater entering the primary aquifer from below. Groundwater that had reached the central part of the aquifer from upgradient areas of the basin was variable in age because of differences in flow paths and travel velocities. The groundwater age analysis showed that current (2013) land-use practices could affect water quality over decades to come, and that responses to remedial actions could be slow, especially for constituents, such as nitrate, that are stable under oxidized conditions.
\nFuel products (including acetone, benzene, diisopropyl ether, ethylbenzene, methyl acetate, methyl tertiary butyl ether (MTBE), methyl tert-pentyl ether, m- + p-xylene, o-xylene, tert-amyl alcohol, tert-butyl alcohol, tert-butyl ethyl ether, and toluene) were analyzed in groundwater from 49 of the 50 wells. Water from seven sites had detections for fuel compounds; all concentrations were below MCL. The results provided assurance of water quality and a valuable baseline to evaluate future trends of fuel constituents as the region is further developed.
\nProbability maps were developed from logistic regression models to examine the likelihood that nitrate concentrations in groundwater exceeded specified levels. Susceptibility analysis examined relations between mid-level (5.0 mg/L) nitrate concentrations and climatic, hydrologic, and geologic variables; the significant variables were identified as depth to groundwater, soil organic matter, and soil water storage to 25-centimeter (cm) depth. The vulnerability assessments included natural factors driving susceptibility but also human factors related to land use and septic use. Vulnerability to low-level (2.5 mg/L) nitrate was related to depth to groundwater, septic zoning, and soil organic matter. The results highlighted that septic zoning affected low-level nitrate concentrations. Vulnerability to mid-level (5.0 mg/L) nitrate was examined using all 50 samples and also with two data outliers removed, which showed relatively high nitrate concentrations but also anomalous water chemistry or were located beyond the primary study area. Vulnerability to mid-level (5.0 mg/L) nitrate using all 50 samples was related to depth to groundwater, land use, septic use within a 500-meter (m) radius, soil water storage to a 25-cm depth, soil organic matter, and whether a location was within the agricultural region. The mid-level (5.0 mg/L) vulnerability model using 48 samples (two outliers removed) produced the best overall fit and was related to the same variables as when using all samples except septic use. The results for mid-level vulnerability provided additional support that septic use was associated with low levels of nitrate in the groundwater. Soil properties and land use were identified as the main drivers of moderate nitrate concentrations. Probabilities of exceeding low-level nitrate concentrations were high in most areas with the lowest probabilities usually to the northwest along thin geologic deposits in the upper part of the basin.
\nThe results of this investigation offer the foundational information needed for developing best management practices to mitigate nitrate contamination, basic concepts on water quality to aid public education, and information to guide regulatory measures if policy makers determine this is warranted. Science-based decision making will require continued monitoring and analysis of water quality in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165020","collaboration":"Prepared in cooperation with Cherokee Metropolitan District, El Paso County, Meridian Service Metropolitan District, Mountain View Electric Association, Upper Black Squirrel Creek Groundwater Management District, Woodmen Hills Metropolitan District, Colorado State Land Board, Colorado Water Conservation Board, and the stakeholders represented in the Groundwater Quality Study Committee of El Paso County","usgsCitation":"Wellman, T.P., and Rupert, M.G., 2016, Groundwater quality, age, and susceptibility and vulnerability to nitrate contamination with linkages to land use and groundwater flow, Upper Black Squirrel Creek Basin, Colorado, 2013: U.S. Geological Survey Scientific Investigations Report, 2016–5020, 78 p., https://dx.doi.org/10.3133/sir20165020.","productDescription":"viii, 77 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068864","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":318534,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5020/coverthb.jpg"},{"id":318535,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5020/sir20165020.pdf","text":"Report","size":"63.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5020"}],"country":"United States","state":"Colorado","county":"El Paso","otherGeospatial":"Black Squirrel Management District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.67361450195312,\n 38.91668153637508\n ],\n [\n -104.7271728515625,\n 38.971154274048345\n ],\n [\n -104.74090576171875,\n 39.02345139405932\n ],\n [\n -104.75875854492188,\n 39.07784203269269\n ],\n [\n -104.77111816406249,\n 39.12579898118164\n ],\n [\n -104.79034423828125,\n 39.172658670429946\n ],\n [\n -104.73953247070311,\n 39.20459056764483\n ],\n [\n -104.69284057617186,\n 39.218423217141485\n ],\n [\n -104.61868286132812,\n 39.23757161784572\n ],\n [\n -104.53628540039062,\n 39.23863526469436\n ],\n [\n -104.49508666992188,\n 39.198205348894795\n ],\n [\n -104.42642211914062,\n 39.196076813671695\n ],\n [\n -104.34951782226561,\n 39.17052936145295\n ],\n [\n -104.32479858398438,\n 39.135386455771076\n ],\n [\n -104.32342529296875,\n 39.08423817730926\n ],\n [\n -104.32754516601562,\n 39.05651736286005\n ],\n [\n -104.27261352539062,\n 39.04158626095001\n ],\n [\n -104.24102783203124,\n 39.01811672409787\n ],\n [\n -104.23278808593749,\n 38.95940879245423\n ],\n [\n -104.22866821289062,\n 38.9177500315307\n ],\n [\n -104.26437377929686,\n 38.882481197550774\n ],\n [\n -104.33441162109374,\n 38.87179021382536\n ],\n [\n -104.40170288085938,\n 38.87499767781738\n ],\n [\n -104.403076171875,\n 38.72623322072787\n ],\n [\n -104.42092895507812,\n 38.6833657775237\n ],\n [\n -104.45663452148438,\n 38.65227081329621\n ],\n [\n -104.51431274414062,\n 38.65334327823747\n ],\n [\n -104.52804565429688,\n 38.67907761983558\n ],\n [\n -104.53216552734375,\n 38.71873327340352\n ],\n [\n -104.56787109374999,\n 38.749799358878526\n ],\n [\n -104.59945678710936,\n 38.805470223177466\n ],\n [\n -104.62554931640625,\n 38.841846903808985\n ],\n [\n -104.67636108398438,\n 38.922023851268925\n ],\n [\n -104.67361450195312,\n 38.91668153637508\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225
The Sauvie Island 7.5' quadrangle is situated in the Puget-Willamette Lowland northwest of downtown Portland, Oreg. This lowland, which extends from Puget Sound to west-central Oregon, is a complex structural and topographic trough between the Coast Range and the Cascade Range. Since late Eocene time, the Cascade Range has been the locus of a discontinuously active volcanic arc associated with underthrusting of oceanic lithosphere beneath the North American continent along the Cascadia Subduction Zone. The Coast Range, which occupies the fore-arc position within the Cascadia arc-trench system, consists of a complex assemblage of Eocene to Miocene volcanic and marine sedimentary rocks.
\nThe Sauvie Island quadrangle lies along the southwest margin of the Portland Basin, a 2,000-km2 topographic and structural depression. The basin boundary is an abrupt topographic break at the base of the Tualatin Mountains, which separates the Portland and Tualatin Basins. The Tualatin Mountains are underlain by lava flows of the Miocene Columbia River Basalt Group that have been folded into an asymmetric anticline. Oligocene marine sedimentary rocks, not exposed at the surface, are inferred to underlie the basalt flows. The abrupt basin boundary marks the location of the northwest-striking Portland Hills Fault Zone, which is probably an active structure.
\nThe Columbia River flows west and north through the Portland Basin at nearly sea level. The Willamette River enters the Columbia near the southeast corner of the map area. Seismic-reflection profiles and lithologic logs of water wells show as much as 550 m of late Miocene and younger sediments in the deepest part of the basin east of the quadrangle. Deposits exposed at the surface consist chiefly of Holocene and late Pleistocene fluvial and eolian sediments and man-made fill.
\nThis map contributes to a U.S. Geological Survey program to improve the geologic database for the Portland region of the Pacific Northwest urban corridor. The map and ancillary data will support assessments of seismic risk, ground-failure hazards, and resource availability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3349","usgsCitation":"Evarts, R.C., O'Connor, J.E., and Cannon, C.M., 2016, Geologic map of the Sauvie Island quadrangle, Multnomah and Columbia Counties, Oregon, and Clark County, Washington: U.S. Geological Survey Scientific Investigations Map 3349, scale 1:24,000, pamphlet 34 p., https://dx.doi.org/10.3133/sim3349.","productDescription":"Pamphlet: iv, 34 p.; 1 Plate: 40.00 x 34.00 inches; Database; Metadata; Read Me; Shape Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049408","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":318448,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_db.zip","size":"4.8 MB","linkFileType":{"id":6,"text":"zip"}},{"id":318443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3349/coverthb.jpg"},{"id":318449,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3349/metadata/"},{"id":318447,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_shp.zip","text":"Shape Files","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"}},{"id":318445,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_pamphlet.pdf","text":"Pamphlet","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3349 Pamphlet PDF"},{"id":318446,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_readme.pdf","size":"177 KB","linkFileType":{"id":2,"text":"txt"}},{"id":318444,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_sheet1.pdf","text":"Sheet 1","size":"74 MB","description":"SIM 3349 Map PDF"},{"id":399013,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104040.htm"}],"scale":"24000","country":"United States","state":"Oregon, Washington","county":"Clark County, Columbia County, Multnomah County","otherGeospatial":"Sauvie Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.875,\n 45.625\n ],\n [\n -122.875,\n 45.75\n ],\n [\n -122.75,\n 45.75\n ],\n [\n -122.75,\n 45.625\n ],\n [\n -122.875,\n 45.625\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
http://geomaps.wr.usgs.gov/gmeg/
A model for preferential flow in macropores is based on the short-range spatial distribution of soil matrix infiltrability. It uses elementary areas at two different scales. One is the traditional representative elementary area (REA), which includes a sufficient heterogeneity to typify larger areas, as for measuring field-scale infiltrability. The other, called an elementary matrix area (EMA), is smaller, but large enough to represent the local infiltrability of soil matrix material, between macropores. When water is applied to the land surface, each EMA absorbs water up to the rate of its matrix infiltrability. Excess water flows into a macropore, becoming preferential flow. The land surface then can be represented by a mesoscale (EMA-scale) distribution of matrix infiltrabilities. Total preferential flow at a given depth is the sum of contributions from all EMAs. Applying the model, one case study with multi-year field measurements of both preferential and diffuse fluxes at a specific depth was used to obtain parameter values by inverse calculation. The results quantify the preferential–diffuse partition of flow from individual storms that differed in rainfall amount, intensity, antecedent soil water, and other factors. Another case study provided measured values of matrix infiltrability to estimate parameter values for comparison and illustrative predictions. These examples give a self-consistent picture from the combination of parameter values, directions of sensitivities, and magnitudes of differences caused by different variables. One major practical use of this model is to calculate the dependence of preferential flow on climate-related factors, such as varying soil wetness and rainfall intensity.
","language":"English","publisher":"ACSESS","doi":"10.2136/vzj2015.05.0079","usgsCitation":"Nimmo, J.R., 2016, Quantitative framework for preferential flow initiation and partitioning: Vadose Zone Journal, v. 15, no. 2, https://doi.org/10.2136/vzj2015.05.0079.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069590","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":318537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-08","publicationStatus":"PW","scienceBaseUri":"56d96034e4b015c306f726de","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":621772,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70168798,"text":"70168798 - 2016 - A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags","interactions":[],"lastModifiedDate":"2017-01-12T11:06:16","indexId":"70168798","displayToPublicDate":"2016-03-03T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags","docAbstract":"Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade−1) and a widening of the synchronized period (29 d decade−1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.1727","usgsCitation":"Letcher, B., Hocking, D., O'Neil, K., Whiteley, A.R., Nislow, K., and O’Donnell, M., 2016, A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags: PeerJ, v. 4, e1727: 26 p., https://doi.org/10.7717/peerj.1727.","productDescription":"e1727: 26 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072906","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":471182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.1727","text":"Publisher Index Page"},{"id":318531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-29","publicationStatus":"PW","scienceBaseUri":"56d96027e4b015c306f726ad","contributors":{"authors":[{"text":"Letcher, Benjamin H. 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":167313,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":621791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hocking, Daniel 0000-0003-1889-9184 dhocking@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-9184","contributorId":149618,"corporation":false,"usgs":true,"family":"Hocking","given":"Daniel","email":"dhocking@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Neil, Kyle","contributorId":82491,"corporation":false,"usgs":true,"family":"O'Neil","given":"Kyle","affiliations":[],"preferred":false,"id":621793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":621794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nislow, Keith H.","contributorId":60106,"corporation":false,"usgs":true,"family":"Nislow","given":"Keith H.","affiliations":[],"preferred":false,"id":621795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Matthew 0000-0002-9089-2377 mjodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":167315,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Matthew","email":"mjodonnell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621796,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159789,"text":"ofr20151221 - 2016 - Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2012–2013","interactions":[],"lastModifiedDate":"2016-03-02T12:49:36","indexId":"ofr20151221","displayToPublicDate":"2016-03-02T13:30:00","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":"2015-1221","title":"Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2012–2013","docAbstract":"The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in northeastern Arizona because of continued water requirements for industrial and municipal use by a growing population and because of low precipitation in the arid climate of the Black Mesa area. Precipitation in the area typically is between 6 and 14 inches per year.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from January 2012 to September 2013. The monitoring program includes measurements of (1) groundwater withdrawals, (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry.
In calendar year 2012, total groundwater withdrawals were 4,010 acre-ft, industrial withdrawals were 1,370 acre-ft, and municipal withdrawals were 2,640 acre-ft. Total withdrawals during 2012 were about 45 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline. From 2011 to 2012 total withdrawals decreased by 10 percent; industrial withdrawals decreased by approximately 1 percent, and total municipal withdrawals decreased by 15 percent.
From 2012 to 2013, annually measured water levels in the Black Mesa area declined in 6 of 16 wells that were available for comparison in the unconfined areas of the N aquifer, and the median change was 0.8 feet. Water levels declined in 5 of 16 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was 0.3 feet. From the prestress period (prior to 1965) to 2013, the median water-level change for 34 wells in both the confined and unconfined areas was -13.5 feet; the median water-level changes were -0.8 feet for 16 wells measured in the unconfined areas and -51.0 feet for 16 wells measured in the confined area.
Spring flow was measured at four springs in 2013; Burro, Unnamed Spring near Dennehotso, Moenkopi School, and Pasture Canyon Springs. Flow fluctuated during the period of record for Burro and Unnamed Springs near Dennehotso, but a decreasing trend was apparent at Moenkopi School Spring and Pasture Canyon Spring. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Unnamed Spring near Dennehotso has fluctuated for the period of record at each spring. Trend analysis for discharge at Moenkopi School and Pasture Canyon Springs showed a decreasing trend.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2013), Dinnebito Wash near Sand Springs 09401110 (1993 to 2013), Polacca Wash near Second Mesa 09400568 (1994 to 2013), and Pasture Canyon Springs 09401265 (2004 to 2013). Median winter flows (November through February) from these sites for each water year were used as an index of the amount of groundwater discharge. For the period of record of each streamflow-gaging station, the median winter flows have generally remained constant, which suggests no change in groundwater discharge.
In 2013, water samples collected from 12 wells and 4 springs in the Black Mesa area were analyzed for selected chemical constituents, and the results were compared with previous analyses. Concentrations of dissolved solids, chloride, and sulfate have varied at all 12 wells for the period of record, but neither increasing nor decreasing trends over time were found. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 13 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly since the early 1980s. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record with no increasing or decreasing trend in the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151221","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs and the Arizona Department of Water Resources","usgsCitation":"Macy, J.P., and Truini, Margot, 2016, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2012–2013: U.S. Geological Survey Open-File Report 2015–1221, 43 p., https://dx.doi.org/10.3133/ofr20151221.","productDescription":"vi, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-01-01","ipdsId":"IP-059312","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":318423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1221/coverthb.jpg"},{"id":318424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1221/ofr20151221.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1221 PDF"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.3,\n 35.3\n ],\n [\n -111.3,\n 37\n ],\n [\n -109.3,\n 37\n ],\n [\n -109.3,\n 35.3\n ],\n [\n -111.3,\n 35.3\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
In this study, we investigate the fluvial, sedimentary, and volcanic history of Margaritifer basin and the Uzboi-Ladon-Morava (ULM) outflow channel system. This network of valleys and basins spans more than 8000 km in length, linking the fluvially dissected southern highlands and Argyre Basin with the northern lowlands via Ares Vallis. Compositionally, thermophysically, and morphologically distinct geologic units are identified and are used to place critical relative stratigraphic constraints on the timing of geologic processes in Margaritifer basin. Our analyses show that fluvial activity was separated in time by significant episodes of geologic activity, including the widespread volcanic resurfacing of Margaritifer basin and the formation of chaos terrain. The most recent fluvial activity within Margaritifer basin appears to terminate at a region of chaos terrain, suggesting possible communication between surface and subsurface water reservoirs. We conclude with a discussion of the implications of these observations on our current knowledge of Martian hydrologic evolution in this important region.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JE004938","usgsCitation":"Salvatore, M.R., Kraft, M.D., Edwards, C., and Christensen, P.R., 2016, The geologic history of Margaritifer basin, Mars: Journal of Geophysical Research E: Planets, v. 121, no. 3, p. 273-295, https://doi.org/10.1002/2015JE004938.","productDescription":"23 p.","startPage":"273","endPage":"295","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069142","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":471186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015je004938","text":"Publisher Index Page"},{"id":318497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-05","publicationStatus":"PW","scienceBaseUri":"56d80eb5e4b015c306f5ea20","contributors":{"authors":[{"text":"Salvatore, M. R.","contributorId":167279,"corporation":false,"usgs":false,"family":"Salvatore","given":"M.","email":"","middleInitial":"R.","affiliations":[{"id":24673,"text":"University of Michigan-Dearborne","active":true,"usgs":false}],"preferred":false,"id":621666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraft, M. D.","contributorId":167280,"corporation":false,"usgs":false,"family":"Kraft","given":"M.","email":"","middleInitial":"D.","affiliations":[{"id":24674,"text":"Arizona State University; Western Washington University","active":true,"usgs":false}],"preferred":false,"id":621667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Christopher cedwards@usgs.gov","contributorId":147768,"corporation":false,"usgs":true,"family":"Edwards","given":"Christopher","email":"cedwards@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":621665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, P. R.","contributorId":7819,"corporation":false,"usgs":false,"family":"Christensen","given":"P.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":621668,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168783,"text":"70168783 - 2016 - Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan","interactions":[],"lastModifiedDate":"2021-08-24T15:54:40.292443","indexId":"70168783","displayToPublicDate":"2016-03-02T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan","title":"Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan","docAbstract":"Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term “tracer” transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.5b05378","usgsCitation":"Safaie, A., Wendzel, A., Ge, Z., Nevers, M., Whitman, R.L., Corsi, S., and Phanikumar, M., 2016, Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan: Environmental Science & Technology, v. 50, no. 5, p. 2442-2449, https://doi.org/10.1021/acs.est.5b05378.","productDescription":"8 p.","startPage":"2442","endPage":"2449","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069953","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":318495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan, Ogden Dunes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1,\n 41.5\n ],\n [\n -87.1,\n 41.75\n ],\n [\n -87.25,\n 41.75\n ],\n [\n -87.25,\n 41.5\n ],\n [\n -87.1,\n 41.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-15","publicationStatus":"PW","scienceBaseUri":"56d80ea9e4b015c306f5e9ec","chorus":{"doi":"10.1021/acs.est.5b05378","url":"http://dx.doi.org/10.1021/acs.est.5b05378","publisher":"American Chemical Society (ACS)","authors":"Safaie Ammar, Wendzel Aaron, Ge Zhongfu, Nevers Meredith B., Whitman Richard L., Corsi Steven R., Phanikumar Mantha S.","journalName":"Environmental Science & Technology","publicationDate":"3/2016"},"contributors":{"authors":[{"text":"Safaie, Ammar","contributorId":167285,"corporation":false,"usgs":false,"family":"Safaie","given":"Ammar","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":621744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wendzel, Aaron","contributorId":167286,"corporation":false,"usgs":false,"family":"Wendzel","given":"Aaron","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":621745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ge, Zhongfu","contributorId":139463,"corporation":false,"usgs":false,"family":"Ge","given":"Zhongfu","email":"","affiliations":[{"id":12773,"text":"American Bureau of Shipping, Corporate Marine Technology","active":true,"usgs":false}],"preferred":false,"id":621746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":621743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":621747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":150657,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":621749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":621748,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169107,"text":"70169107 - 2016 - Effect of wastewater treatment facility closure on endocrine disrupting chemicals in a Coastal Plain stream","interactions":[],"lastModifiedDate":"2018-08-10T10:05:13","indexId":"70169107","displayToPublicDate":"2016-03-02T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3249,"text":"Remediation Journal","active":true,"publicationSubtype":{"id":10}},"title":"Effect of wastewater treatment facility closure on endocrine disrupting chemicals in a Coastal Plain stream","docAbstract":"Wastewater treatment facility (WWTF) closures are rare environmental remediation events; offering unique insight into contaminant persistence, long-term wastewater impacts, and ecosystem recovery processes. The U.S. Geological Survey assessed the fate of select endocrine disrupting chemicals (EDC) in surface water and streambed sediment one year before and one year after closure of a long-term WWTF located within the Spirit Creek watershed at Fort Gordon, Georgia. Sample sites included a WWTF-effluent control located upstream from the outfall, three downstream effluent-impacted sites located between the outfall and Spirit Lake, and one downstream from the lake's outfall. Prior to closure, the 2.2-km stream segment downstream from the WWTF outfall was characterized by EDC concentrations significantly higher (α = 0.05) than at the control site; indicating substantial downstream transport and limited in-stream attenuation of EDC, including pharmaceuticals, estrogens, alkylphenol ethoxylate (APE) metabolites, and organophosphate flame retardants (OPFR). Wastewater-derived pharmaceutical, APE metabolites, and OPFR compounds were also detected in the outflow of Spirit Lake, indicating the potential for EDC transport to aquatic ecosystems downstream of Fort Gordon under effluent discharge conditions. After the WWTF closure, no significant differences in concentrations or numbers of detected EDC compounds were observed between control and downstream locations. The results indicated EDC pseudo-persistence under preclosure, continuous supply conditions, with rapid attenuation following WWTF closure. Low concentrations of EDC at the control site throughout the study and comparable concentrations in downstream locations after WWTF closure indicated additional, continuing, upstream contaminant sources within the Spirit Creek watershed.
","language":"English","publisher":"Wiley","publisherLocation":"New York, NY","doi":"10.1002/rem.21455","usgsCitation":"Bradley, P.M., Journey, C.A., and Clark, J.M., 2016, Effect of wastewater treatment facility closure on endocrine disrupting chemicals in a Coastal Plain stream: Remediation Journal, v. 26, no. 2, p. 9-24, https://doi.org/10.1002/rem.21455.","productDescription":"16 p.","startPage":"9","endPage":"24","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071584","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Spirit Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.14048385620117,\n 33.37268517076214\n ],\n [\n -82.13722229003906,\n 33.37232677960624\n ],\n [\n -82.13644981384277,\n 33.373330271121596\n ],\n [\n -82.13747978210449,\n 33.37655570115267\n ],\n [\n -82.1389389038086,\n 33.3804977309726\n ],\n [\n -82.14177131652832,\n 33.38142945736583\n ],\n [\n -82.14571952819824,\n 33.382432843855234\n ],\n [\n -82.14923858642578,\n 33.38515626310354\n ],\n [\n -82.15018272399902,\n 33.38644627402568\n ],\n [\n -82.15344429016113,\n 33.38737793667645\n ],\n [\n -82.15524673461914,\n 33.38809459345993\n ],\n [\n -82.15644836425781,\n 33.38981454563582\n ],\n [\n -82.15696334838867,\n 33.39146280120461\n ],\n [\n -82.15696334838867,\n 33.392896041511285\n ],\n [\n -82.15893745422363,\n 33.39389929566411\n ],\n [\n -82.16116905212402,\n 33.39461589868319\n ],\n [\n -82.16176986694336,\n 33.39511751728097\n ],\n [\n -82.16357231140135,\n 33.39511751728097\n ],\n [\n -82.1641731262207,\n 33.39382763503726\n ],\n [\n -82.16297149658203,\n 33.3923227482246\n ],\n [\n -82.16082572937012,\n 33.39153446378123\n ],\n [\n -82.15953826904297,\n 33.38981454563582\n ],\n [\n -82.15902328491211,\n 33.387951262575854\n ],\n [\n -82.15799331665038,\n 33.385944605385994\n ],\n [\n -82.15361595153809,\n 33.38465458702014\n ],\n [\n -82.15198516845703,\n 33.38264785373944\n ],\n [\n -82.15009689331053,\n 33.38071274564174\n ],\n [\n -82.14752197265625,\n 33.379709339303815\n ],\n [\n -82.14503288269043,\n 33.37906428625834\n ],\n [\n -82.14340209960938,\n 33.37727244713804\n ],\n [\n -82.14194297790527,\n 33.37612565072615\n ],\n [\n -82.14168548583984,\n 33.374262074305484\n ],\n [\n -82.14125633239746,\n 33.372900204746884\n ],\n [\n -82.14048385620117,\n 33.37268517076214\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-02","publicationStatus":"PW","scienceBaseUri":"56ed26b0e4b0f59b85db09f4","contributors":{"authors":[{"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":622958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","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":false,"id":622959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","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":622960,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159457,"text":"sir20155159 - 2016 - Application of hydrogeology and groundwater-age estimates to assess the travel time of groundwater at the site of a landfill to the Mahomet Aquifer, near Clinton, Illinois","interactions":[],"lastModifiedDate":"2016-03-02T13:44:50","indexId":"sir20155159","displayToPublicDate":"2016-03-02T10:30:00","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":"2015-5159","title":"Application of hydrogeology and groundwater-age estimates to assess the travel time of groundwater at the site of a landfill to the Mahomet Aquifer, near Clinton, Illinois","docAbstract":"The U.S. Geological Survey used interpretations of hydrogeologic conditions and tritium-based groundwater age estimates to assess the travel time of groundwater at a landfill site near Clinton, Illinois (the “Clinton site”) where a chemical waste unit (CWU) was proposed to be within the Clinton landfill unit #3 (CLU#3). Glacial deposits beneath the CWU consist predominantly of low-permeability silt- and clay-rich till interspersed with thin (typically less than 2 feet in thickness) layers of more permeable deposits, including the Upper and Lower Radnor Till Sands and the Organic Soil unit. These glacial deposits are about 170 feet thick and overlie the Mahomet Sand Member of the Banner Formation. The Mahomet aquifer is composed of the Mahomet Sand Member and is used for water supply in much of east-central Illinois.
Eight tritium analyses of water from seven wells were used to evaluate the overall age of recharge to aquifers beneath the Clinton site. Groundwater samples were collected from six monitoring wells on or adjacent to the CLU#3 that were open to glacial deposits above the Mahomet aquifer (the upper and lower parts of the Radnor Till Member and the Organic Soil unit) and one proximal production well (approximately 0.5 miles from the CLU#3) that is screened in the Mahomet aquifer. The tritium-based age estimates were computed with a simplifying, piston-flow assumption: that groundwater moves in discrete packets to the sampled interval by advection, without hydrodynamic dispersion or mixing.
Tritium concentrations indicate a recharge age of at least 59 years (pre-1953 recharge) for water sampled from deposits below the upper part of the Radnor Till Member at the CLU#3, with older water expected at progressively greater depth in the tills. The largest tritium concentration from a well sampled by this study (well G53S; 0.32 ± 0.10 tritium units) was in groundwater from a sand deposit in the upper part of the Radnor Till Member; the shallowest permeable unit sampled by this study. That result indicated that nearly all groundwater sampled from well G53S entered the aquifer as recharge before 1953. Tritium was detected in a trace concentration in one sample from a second monitoring well open to the upper part of the Radnor Till Member (well G07S; 0.11 ± 0.09 tritium units), and not detected in samples collected from two monitoring wells open to a sand deposit in the lower part of the Radnor Till Member, from two samples collected from two monitoring wells open to the Organic Soil unit, and in two samples collected from a production well screened in the middle of the Mahomet aquifer (a groundwater sample and a sequential replicate sample). The lack of tritium in five of the six groundwater samples collected from the shallow permeable units beneath CLU#3 site and the two samples from the one Mahomet aquifer well indicates an absence of post-1952 recharge. Groundwater-flow paths that could contribute post-1952 recharge to the lower part of the Radnor Till Member, the Organic Soil unit, or the Mahomet aquifer at the CLU#3 are not indicated by these data.
Hypothetical two-part mixtures of tritium-dead, pre-1953 recharge water and decay-corrected tritium concentrations in post-1952 recharge were computed and compared with tritium analyses in groundwater sampled from monitoring wells at the CLU#3 site to evaluate whether tritium concentrations in groundwater could be represented by mixtures involving some post-1952 recharge. Results from the hypothetical two-part mixtures indicate that groundwater from monitoring well (G53S) was predominantly composed of pre-1953 recharge and that if present, younger, post-1955 recharge, contributed less than 2.5 percent to that sample. The hypothetical two-part mixing results also indicated that very small amounts of post-1952 recharge composing less than about 2.5 percent of the sample volume could not be distinguished in groundwater samples with tritium concentrations less than about 0.15 TU.
The piston-flow based age of recharge determined from the tritium concentration in the groundwater sample from monitoring well G53S yielded an estimated maximum vertical velocity from the land surface to the upper part of the Radnor Till Member of 0.85 feet per year or less. This velocity, ifassumed to apply to the remaining glacial till deposits above the Mahomet aquifer, indicates that recharge flows through the 170 feet of glacial deposits between the base of the proposed chemical waste unit and the top of the Mahomet aquifer in a minimum of 200 years or longer. Analysis of hydraulic data from the site, constrained by a tritium-age based maximum groundwater velocity estimate, computed minimum estimates of effective porosity that range from about 0.021 to 0.024 for the predominantly till deposits above the Mahomet aquifer.
Estimated rates of transport of recharge from land surface to the Mahomet aquifer for the CLU#3 site computed using the Darcy velocity equation with site-specific data were about 260 years or longer. The Darcy velocity-based estimates were computed using values that were based on tritium data, estimates of vertical velocity and effective porosity and available site-specific data. Solution of the Darcy velocity equation indicated that maximum vertical groundwater velocities through the deposits above the aquifer were 0.41 or 0.61 feet per year, depending on the site-specific values of vertical hydraulic conductivity (laboratory triaxial test values) and effective porosity used for the computation. The resulting calculated minimum travel times for groundwater to flow from the top of the Berry Clay Member (at the base of the proposed chemical waste unit) to the top of the Mahomet aquifer ranged from about 260 to 370 years, depending on the velocity value used in the calculation. In comparison, plausible travel times calculated using vertical hydraulic conductivity values from a previously published regional groundwater flow model were either slightly less than or longer than those calculated using site data and ranged from 230 to 580 years.
Tritium data from 1996 to 2011 USGS regional sampling of groundwater from domestic wells in the confined part of the Mahomet aquifer—which are 2.5 to about 40 miles from the Clinton site—were compared with site-specific data from a production well at the Clinton site. Tritium-based groundwater-age estimates indicated predominantly pre- 1953 recharge dates for USGS and other prior regional samples of groundwater from domestic wells in the Mahomet aquifer. These results agreed with the tritium-based, pre-1953 recharge age estimated for a groundwater sample and a sequential replicate sample from a production well in the confined part of the Mahomet aquifer beneath the Clinton site.
The regional tritium-based groundwater age estimates also were compared with pesticide detections in samples from distal domestic wells in the USGS regional network that are about 2.5 to 40 miles from the Clinton site to identify whether very small amounts of post-1952 recharge have in places reached confined parts of the Mahomet aquifer at locations other than the Clinton site in an approximately 2,000 square mile area of the Mahomet aquifer. Very small amounts of post-1952 recharge were defined in this analysis as less than about 2.5 percent of the total recharge contributing to a groundwater sample, based on results from the two-part mixing analysis of tritium data from the Clinton site. Pesticide-based groundwater-age estimates based on 22 detections of pesticides (13 of these detections were estimated concentrations), including atrazine, deethylatrazine (2-Chloro-4-isopropylamino-6-amino- s-triazine), cyanazine, diazinon, metolachlor, molinate, prometon, and trifluralin in groundwater samples from 10 domestic wells 2.5 to about 40 miles distant from the Clinton site indicate that very small amounts of post-1956 to post-1992 recharge can in places reach the confined part of the Mahomet aquifer in other parts of central Illinois. The relative lack of tritium in these samples indicate that the amounts of post-1956 to post-1992 recharge contributing to the 10 domestic wells were a very small part of the overall older groundwater sampled from those wells.
The flow process by which very small amounts of pesticide-bearing groundwater reached the screened intervals of the 10 domestic wells could not be distinguished between well-integrity related infiltration and natural hydrogeologic features. Potential explanations include: (1) infiltration through man-made avenues in or along the well, (2) flow of very small amounts of post-1956 to post-1992 recharge through sparsely distributed natural permeable aspects of the glacial till and diluted by mixing with older groundwater, or (3) a combination of both processes.
Presuming the domestic wells sampled by the USGS in 1996–2011 in the regional study of the confined part of the Mahomet aquifer are adequately sealed and produce groundwater that is representative of aquifer conditions, the regional tritium and pesticide-based groundwater-age results indicate substantial heterogeneity in the glacial stratigraphy above the Mahomet aquifer. The pesticide-based groundwater-age estimates from the domestic wells distant from the Clinton site also indicate that parts of the Mahomet aquifer with the pesticide detections can be susceptible to contaminant sources at the land surface. The regional pesticide and tritium results from the domestic wells further indicate that a potential exists for possible contaminants from land surface to be transported through the glacial drift deposits that confine the Mahomet aquifer in other parts of central Illinois at faster rates than those computed for recharge at the Clinton site, including CLU#3. This analysis indicates the potential value of sub-microgram-per-liter level concentrations of land-use derived indicators of modern recharge to indicate the presence of very small amounts of modern, post-1952 age recharge in overall older, pre-1953 age groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155159","usgsCitation":"Kay, R.T., and Buszka, P.M., 2016, Application of hydrogeology and groundwater-age estimates to assess the travel time of groundwater at the site of a landfill to the Mahomet Aquifer, near Clinton, Illinois, with a section on Regional Indications of Recharge to the Mahomet Aquifer from Previously Collected Tritium and Pesticide Data, by Buszka, P.M. and Morrow, W.S.: U.S. Geological Survey Scientific Investigations Report 2015–5159, 54 p., https://dx.doi.org/10.3133/sir20155159.\n","productDescription":"vii, 54 p.","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-038616","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":314192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5159/coverthb.jpg"},{"id":314193,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5159/sir20155159.pdf","text":"Report","size":"1.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5159"}],"country":"United States","state":"Illinois","city":"Clinton","otherGeospatial":"Mahomet Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.96428108215332,\n 40.107618711896095\n ],\n [\n -88.96428108215332,\n 40.117793139514546\n ],\n [\n -88.94694328308105,\n 40.117793139514546\n ],\n [\n -88.94694328308105,\n 40.107618711896095\n ],\n [\n -88.96428108215332,\n 40.107618711896095\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N. Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov/
We describe high-resolution gravity and seismic refraction surveys acquired to determine the thickness of valley-fill deposits and to delineate geologic structures that might influence groundwater flow beneath the Smoke Tree Wash area in Joshua Tree National Park. These surveys identified a sedimentary basin that is fault-controlled. A profile across the Smoke Tree Wash fault zone reveals low gravity values and seismic velocities that coincide with a mapped strand of the Smoke Tree Wash fault. Modeling of the gravity data reveals a basin about 2–2.5 km long and 1 km wide that is roughly centered on this mapped strand, and bounded by inferred faults. According to the gravity model the deepest part of the basin is about 270 m, but this area coincides with low velocities that are not characteristic of typical basement complex rocks. Most likely, the density contrast assumed in the inversion is too high or the uncharacteristically low velocities represent highly fractured or weathered basement rocks, or both. A longer seismic profile extending onto basement outcrops would help differentiate which scenario is more accurate. The seismic velocities also determine the depth to water table along the profile to be about 40–60 m, consistent with water levels measured in water wells near the northern end of the profile.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161027","usgsCitation":"Langenheim, V.E., Rymer, M.J., Catchings, R.D., Goldman, M.R., Watt, J.T., Powell, R.E., and Matti, J.C., 2016, High-resolution gravity and seismic-refraction surveys of the Smoke Tree Wash Area, Joshua Tree National Park, California: U.S. Geological Survey Open-File Report 2016–1027, 15 p., https://dx.doi.org/10.3133/ofr20161027.","productDescription":"Report: iii, 15 p.; Dataset; Metadata; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070548","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":318441,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027_readme.txt","size":"4 KB","linkFileType":{"id":2,"text":"txt"}},{"id":318440,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027_metadata.txt","size":"10 KB","linkFileType":{"id":2,"text":"txt"}},{"id":318439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027.pdf","text":"Report","size":"700 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1027 Report PDF"},{"id":318438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1027/coverthb.jpg"},{"id":318442,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027_iso_all.txt","text":"Gravity Data","size":"11 KB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"California","otherGeospatial":"Joshua Tree National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.8745,\n 33.7498\n ],\n [\n -115.8745,\n 33.8402\n ],\n [\n -115.7667,\n 33.8402\n ],\n [\n -115.7667,\n 33.7498\n ],\n [\n -115.8745,\n 33.7498\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
http://geomaps.wr.usgs.gov/gmeg/