Lake Houston, an important water resource for the Houston, Texas, area, receives inflows from seven major tributaries that compose the San Jacinto River Basin upstream from the reservoir. The effects of different inflows from the watersheds drained by these tributaries on the residence time of water in Lake Houston and closely associated physical and chemical properties including lake elevation, salinity, and water temperature are not well known. Accordingly, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, developed a three-dimensional hydrodynamic model of Lake Houston as a tool for evaluating the effects of different inflows on residence time of water in the lake and associated physical and chemical properties. The Environmental Fluid Dynamics Code (EFDC), a grid-based, surface-water modeling package for simulating three-dimensional circulation, mass transport, sediments, and biogeochemical processes, was used to develop the model of Lake Houston. The Lake Houston EFDC model was developed and calibrated by using 2009 data and verified by using 2010 data. Three statistics (mean error, root mean square error, and the Nash-Sutcliffe model efficiency coefficient) were used to evaluate how well the Lake Houston EFDC model simulated lake elevation, salinity, and water temperature. The residence time of water in reservoirs is associated with various physical and chemical properties (including lake elevation, salinity, and water temperature). Simulated and measured lake-elevation values were compared at USGS reservoir station 08072000 Lake Houston near Sheldon, Tex. The accuracy of simulated salinity and water temperature values was assessed by using the salinity (computed from measured specific conductance) and water temperature at two USGS monitoring stations: 295826095082200 Lake Houston south Union Pacific Railroad Bridge near Houston, Tex., and 295554095093401 Lake Houston at mouth of Jack’s Ditch near Houston, Tex. Specific conductance and water temperature were measured at as many as four different depths at each of the two monitoring stations during 2009 and then used for assessing the accuracy of simulated values of salinity and water temperature during 2010. The performance evaluation statistics indicate that the model performed satisfactorily. The calibrated model was used to simulate two possible inflow scenarios to evaluate the changes in the residence time of water in Lake Houston. The two scenarios tested were an increased inflow of approximately 300 cubic feet per second for 1 month (May 2010) from two watersheds: the West Fork San Jacinto River and Luce Bayou. These scenarios were chosen to mimic the effects of possible small releases or diversions of water from outside the San Jacinto River Basin into the basin (or directly into the lake) on the residence time of water in Lake Houston. During the time of increased inflow for the two scenarios tested, maximum residence time decreased slightly from approximately 106 to 97 days.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155153","collaboration":"Prepared in cooperation with the City of Houston","usgsCitation":"Rendon, S.H., and Lee, M.T., 2015, Simulation of the effects of different inflows on hydrologic conditions in Lake Houston with a three-dimensional hydrodynamic model, Houston, Texas, 2009–10: U.S. Geological Survey Scientific Investigations Report 2015–5153, 42 p., https://dx.doi.org/10.3133/sir20155153.","productDescription":"vi, 42 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060635","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":311980,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5153/sir20155153.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5153"},{"id":311979,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5153/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Lake Houston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.99578857421875,\n 29.90256760730233\n ],\n [\n -95.99578857421875,\n 30.62845887475364\n ],\n [\n -95.10040283203125,\n 30.62845887475364\n ],\n [\n -95.10040283203125,\n 29.90256760730233\n ],\n [\n -95.99578857421875,\n 29.90256760730233\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
http://tx.usgs.gov/
The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to ‘smart’ interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/sdata.2015.66","usgsCitation":"Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J., 2015, The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes: Scientific Data, v. 2, Article 150066: 21 p., https://doi.org/10.1038/sdata.2015.66.","productDescription":"Article 150066: 21 p.","ipdsId":"IP-066224","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/sdata.2015.66","text":"Publisher Index Page"},{"id":341859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-08","publicationStatus":"PW","scienceBaseUri":"592e84bbe4b092b266f10d3d","contributors":{"authors":[{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Pete","contributorId":192379,"corporation":false,"usgs":false,"family":"Peterson","given":"Pete","affiliations":[],"preferred":false,"id":696432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landsfeld, Martin","contributorId":192380,"corporation":false,"usgs":false,"family":"Landsfeld","given":"Martin","affiliations":[],"preferred":false,"id":696433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pedreros, Diego 0000-0001-9943-7373 pedreros@usgs.gov","orcid":"https://orcid.org/0000-0001-9943-7373","contributorId":4195,"corporation":false,"usgs":true,"family":"Pedreros","given":"Diego","email":"pedreros@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696371,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":145830,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696376,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shukla, Shraddhanand","contributorId":145802,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":696372,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":696373,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rowland, James 0000-0003-4837-3511 rowland@usgs.gov","orcid":"https://orcid.org/0000-0003-4837-3511","contributorId":145846,"corporation":false,"usgs":true,"family":"Rowland","given":"James","email":"rowland@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696375,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harrison, Laura","contributorId":78859,"corporation":false,"usgs":true,"family":"Harrison","given":"Laura","affiliations":[],"preferred":false,"id":696374,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hoell, Andrew","contributorId":145803,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":696434,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Michaelsen, Joel","contributorId":149202,"corporation":false,"usgs":false,"family":"Michaelsen","given":"Joel","affiliations":[],"preferred":false,"id":696435,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70158994,"text":"sir20155147 - 2015 - Characterization of hydrology and water quality of Piceance Creek in the Alkali Flat area, Rio Blanco County, Colorado, March 2012","interactions":[],"lastModifiedDate":"2015-12-07T14:55:23","indexId":"sir20155147","displayToPublicDate":"2015-12-07T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5147","title":"Characterization of hydrology and water quality of Piceance Creek in the Alkali Flat area, Rio Blanco County, Colorado, March 2012","docAbstract":"Previous studies by the U.S. Geological Survey identified Alkali Flat as an area of groundwater upwelling, with increases in concentrations of total dissolved solids, and streamflow loss, but additional study was needed to better characterize these observations. The U.S. Geological Survey, in cooperation with the Bureau of Land Management, White River Field Office, conducted a study to characterize the hydrology and water quality of Piceance Creek in the Alkali Flat area of Rio Blanco County, Colorado.
\nWater-quality samples were collected at five springs on March 27, 2012, to determine field properties, major ions, trace elements, and stable isotopes of water. Major-ion and trace-element chemistry indicated that the springs sampled as part of this study were likely recharged by the bedrock aquifer. Isotopic values for the springs plotted close to that of groundwater from the Parachute Creek Member of the Green River Formation, and the isotopic values from both of these sources are similar to the values for Grand Mesa snow. Based on fluoride, lithium, and strontium concentrations, one spring appeared to have different source water than the other four springs. The spring also had higher concentrations of calcium, magnesium, and sulfate relative to the other four springs. Trace-element and major-ion data indicate that this spring was sourced from the Uinta Formation. It was likely the other four springs were primarily sourced from the lower part of the Parachute Creek Member of the Green River Formation as indicated by low sulfate concentrations and high fluoride, lithium, and boron concentrations.
\nWater-quality samples were collected at 16 surface-water-quality sites on March 14, 2012, to determine field properties, major ions, and trace elements. Sodium was the dominant cation and concentrations increased steadily from upstream to downstream along the study reach. Calcium, magnesium, and potassium concentrations remained relatively stable along the study reach. Strontium concentrations were relatively stable along the study reach, whereas boron and lithium concentrations increased appreciably at site PC22031 and remained elevated to the end of the study reach.
\nLoading profiles were used to further refine areas of spring and groundwater input and streamflow gains and losses. Although there was a minor gain in streamflow from sites PC21543 to PC21816 (58 to 59 cubic feet per second (ft3/s) during March 2014), the observed increase in dissolved solids load indicated groundwater contribution to Piceance Creek between these two sites. From sites PC22737 to PC22980, dissolved solids load decreased, which was not observed in concentration profiles and indicated that streamflow loss occurred between these two sites. Barium, boron, lithium, and strontium loads showed similar patterns to that of the major ions along the study reach and indicated similar areas of groundwater gain and loss. Boron and lithium load were not observed to decrease in a similar pattern to that of barium and strontium load which would suggest the contribution to the stream from sources with similar chemistry to that of spring sites PCSP2 through PCSP5. Sodium, chloride, and bicarbonate loads increased and decreased along the study reach in a pattern similar to that of dissolved solids load. A chemical mass balance was used to estimate the amount of groundwater and (or) spring water that contributed to the observed changes in water quality along Piceance Creek. This analysis indicated only 5 percent spring water would need to reach Piceance Creek to result in the observed changes in water quality.
\nInstantaneous streamflow was measured from sites PC20133 to PC23721 during field reconnaissance (February 2012) and during synoptic sampling (March 2012). During both February and March, the study reach from sites PC20133 to PC23721 was a losing reach with net losses that ranged from 0.5 ft3/s (February) to 3 ft3/s (March). Observed changes in streamflow along the study reach helped to depict interactions between groundwater and surface water in the Alkali Flat area.
\nWater-quality samples were collected at five surface-water sites in December 2010 that were sampled as part of a previous USGS study in 2000. Water-quality data collected during December 2010 showed no appreciable difference from water-quality data collected during December 2000 at the five sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20155147","collaboration":"Prepared in cooperation with the Bureau of Land Management, White River Field Office","usgsCitation":"Thomas, J.C., 2015, Characterization of hydrology and water quality of Piceance Creek in the Alkali Flat area, Rio Blanco County, Colorado, March 2012: U.S. Geological Survey Scientific Investigations Report 2015–5147, 23 p., https://dx.doi.org/10.3133/sir20155147.","productDescription":"iv, 23 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065008","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":311970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5147/sir20155147.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5147"},{"id":311969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5147/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Rio Blanco County","otherGeospatial":"Alkali Flat Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109,\n 39\n ],\n [\n -109,\n 40.1\n ],\n [\n -107.8,\n 40.1\n ],\n [\n -107.8,\n 39\n ],\n [\n -109,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
http://co.water.usgs.gov
We use a dated sediment core from Lake Whittington (USA) in the lower Mississippi River to reconstruct linkages in the carbon cycling and fluvial sediment dynamics over the past 80 years. Organic carbon (OC) sources were characterized using bulk (δ13C, ramped pyrolysis-oxidation (PyrOx) 14C, δ15N, and TN:OC ratios) and compound-specific (lignin phenols and fatty acids, including δ13C and 14C of the fatty acids) analyses. Damming of the Missouri River in the 1950s, other hydrological modifications to the river, and soil conservation measures resulted in reduced net OC export, in spite of increasing OC concentrations. Decreasing δ13C values coincided with increases in δ15N, TN:OC ratios, long-chain fatty acids, and lignin-phenol concentrations, suggesting increased inputs of soil-derived OC dominated by C3 vegetation, mainly resulting from changes in farming practices and crop distribution. However, ramped PyrOx 14C showed no discernible differences downcore in thermochemical stability, indicating a limited impact on soil OC turnover.
","language":"English","publisher":"AGU","doi":"10.1002/2015GL065595","usgsCitation":"Bianchi, T.S., Galy, V., Rosenheim, B.E., Shields, M., Cui, X., and Van Metre, P., 2015, Paleoreconstruction of organic carbon inputs to an oxbow lake in the Mississippi River watershed: Effects of dam construction and land use change on regional inputs: Geophysical Research Letters, v. 42, no. 19, p. 7983-7991, https://doi.org/10.1002/2015GL065595.","productDescription":"9 p.","startPage":"7983","endPage":"7991","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066306","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":471580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl065595","text":"Publisher Index Page"},{"id":311893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Lake Whittington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.15837097167967,\n 33.65420905128059\n ],\n [\n -91.15837097167967,\n 33.72334023851457\n ],\n [\n -91.02739334106445,\n 33.72334023851457\n ],\n [\n -91.02739334106445,\n 33.65420905128059\n ],\n [\n -91.15837097167967,\n 33.65420905128059\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"19","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-10","publicationStatus":"PW","scienceBaseUri":"566167b9e4b06a3ea36c5663","contributors":{"authors":[{"text":"Bianchi, Thomas S.","contributorId":150225,"corporation":false,"usgs":false,"family":"Bianchi","given":"Thomas","email":"","middleInitial":"S.","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":581051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galy, Valier","contributorId":150226,"corporation":false,"usgs":false,"family":"Galy","given":"Valier","email":"","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":581052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenheim, Brad E.","contributorId":150227,"corporation":false,"usgs":false,"family":"Rosenheim","given":"Brad","email":"","middleInitial":"E.","affiliations":[{"id":12607,"text":"Univ of South florida, School of Geosciences, Tampa FL","active":true,"usgs":false}],"preferred":false,"id":581053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shields, Michael","contributorId":150228,"corporation":false,"usgs":false,"family":"Shields","given":"Michael","email":"","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":581054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cui, Xingquan","contributorId":150229,"corporation":false,"usgs":false,"family":"Cui","given":"Xingquan","email":"","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":581055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Metre, Peter C. pcvanmet@usgs.gov","contributorId":486,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581050,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159917,"text":"70159917 - 2015 - Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach","interactions":[],"lastModifiedDate":"2019-06-03T13:22:56","indexId":"70159917","displayToPublicDate":"2015-12-03T14:30:00","publicationYear":"2015","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":"Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach","docAbstract":"Whether a waterway is temporary or permanent influences regulatory protection guidelines, however, classification can be subjective due to a combination of factors, including time of year, antecedent moisture conditions, and previous experience of the field investigator. Our objective was to develop a standardized protocol using publicly available spatial information to classify ephemeral, intermittent, and perennial streams. Our hypothesis was that field observations of flow along the stream channel could be compared to results from a hydrologic model, providing an objective method of how these stream reaches can be identified. Flow-state sensors were placed at ephemeral, intermittent, and perennial stream reaches from May to December 2011 in the Appalachian coal basin of eastern Kentucky. This observed flow record was then used to calibrate the simulated saturation deficit in each channel reach based on the topographic wetness index used by TOPMODEL. Saturation deficit values were categorized as flow or no-flow days, and the simulated record of streamflow was compared to the observed record. The hydrologic model was more accurate for simulating flow during the spring and fall seasons. However, the model effectively identified stream reaches as intermittent and perennial in each of the two basins.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12352","usgsCitation":"Williamson, T., Agouridis, C.T., Barton, C.D., Villines, J.A., and Lant, J.G., 2015, Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach: Journal of the American Water Resources Association, v. 51, no. 6, p. 1739-1759, https://doi.org/10.1111/1752-1688.12352.","productDescription":"21 p.","startPage":"1739","endPage":"1759","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051282","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":311879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-18","publicationStatus":"PW","scienceBaseUri":"566167b7e4b06a3ea36c5655","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agouridis, Carmen T. 0000-0001-9580-6143","orcid":"https://orcid.org/0000-0001-9580-6143","contributorId":150223,"corporation":false,"usgs":false,"family":"Agouridis","given":"Carmen","email":"","middleInitial":"T.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barton, Christopher D.","contributorId":150222,"corporation":false,"usgs":false,"family":"Barton","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villines, Jonathan A.","contributorId":150224,"corporation":false,"usgs":false,"family":"Villines","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lant, Jeremiah G. 0000-0001-6688-4820 jlant@usgs.gov","orcid":"https://orcid.org/0000-0001-6688-4820","contributorId":4912,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","email":"jlant@usgs.gov","middleInitial":"G.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581042,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159003,"text":"sir20155151 - 2015 - Regression Equations for Monthly and Annual Mean and Selected Percentile Streamflows for Ungaged Rivers in Maine","interactions":[],"lastModifiedDate":"2015-12-31T10:46:01","indexId":"sir20155151","displayToPublicDate":"2015-12-03T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5151","title":"Regression Equations for Monthly and Annual Mean and Selected Percentile Streamflows for Ungaged Rivers in Maine","docAbstract":"In an effort to delineate hydrologic conditions in Maine, the U.S. Geological Survey, in cooperation with the Maine Department of Transportation, used streamflow data to develop dependent variables for 130 regression equations for estimating monthly and annual mean and 1, 5, 10, 25, 50, 75, 90, 95, and 99 percentile streamflows for ungaged, unregulated rivers in Maine. Daily streamflow data from 24 rural unregulated basins with drainage areas between 14.9 and 1,419 square miles in Maine and northern New Hampshire were used in the derivation of the equations. Streamflow data collected from October 1, 1982, through September 30, 2012, were used to derive the dependent variables for this study to represent current [2015] hydrologic conditions in Maine and northern New Hampshire. Weighted least squares regression techniques were used to derive the final coefficients and measures of uncertainty for the regression equations. Eight basin characteristics serve as the explanatory variables: drainage area, distance from the coast, mean and maximum basin elevation, mean basin slope, mean basin percentage of hydrologic soil group A, fraction of sand and gravel aquifers, and percentage of open water.
\nThe largest average errors of prediction are associated with regression equations for the lowest streamflows derived for months during which the lowest streamflows of the year occur (such as the 5 and 1 monthly percentiles for August and September). The regression equations have been derived on the basis of streamflow and basin characteristics data for unregulated, rural drainage basins without substantial streamflow or drainage modifications (for example, diversions and (or) regulation by dams or reservoirs, tile drainage, irrigation, channelization, and impervious paved surfaces), therefore using the equations for regulated or urbanized basins with substantial streamflow or drainage modifications will yield results of unknown error. Input basin characteristics derived using techniques or datasets other than those documented in this report or using values outside the ranges used to develop these regression equations also will yield results of unknown error.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155151","collaboration":"Prepared in cooperation with the Maine Department of Transportation","usgsCitation":"Dudley, R.W., 2015, Regression equations for monthly and annual mean and selected percentile streamflows for ungaged rivers in Maine (ver. 1.1, December 21, 2015): U.S. Geological Survey Scientific Investigations Report 2015–5151, 35 p., https://dx.doi.org/10.3133/sir20155151.","productDescription":"viii, 35 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066284","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":311685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5151/sir20155151.pdf","text":"Report","size":"8.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5151"},{"id":312572,"rank":3,"type":{"id":25,"text":"Version 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\"}}]}","edition":"Version 1: Originally posted December 3, 2015; Version 1.1: December 21, 2015","contact":"Director, New England Water Science Center
U.S. Geological Survey
196 Whitten Road
Augusta, ME 04330
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As Arctic regions warm and frozen soils thaw, the large organic carbon pool stored in permafrost becomes increasingly vulnerable to decomposition or transport. The transfer of newly mobilized carbon to the atmosphere and its potential influence upon climate change will largely depend on the degradability of carbon delivered to aquatic ecosystems. Dissolved organic carbon (DOC) is a key regulator of aquatic metabolism, yet knowledge of the mechanistic controls on DOC biodegradability is currently poor due to a scarcity of long-term data sets, limited spatial coverage of available data, and methodological diversity. Here, we performed parallel biodegradable DOC (BDOC) experiments at six Arctic sites (16 experiments) using a standardized incubation protocol to examine the effect of methodological differences commonly used in the literature. We also synthesized results from 14 aquatic and soil leachate BDOC studies from across the circum-arctic permafrost region to examine pan-arctic trends in BDOC.
An increasing extent of permafrost across the landscape resulted in higher DOC losses in both soil and aquatic systems. We hypothesize that the unique composition of (yedoma) permafrost-derived DOC combined with limited prior microbial processing due to low soil temperature and relatively short flow path lengths and transport times, contributed to a higher overall terrestrial and freshwater DOC loss. Additionally, we found that the fraction of BDOC decreased moving down the fluvial network in continuous permafrost regions, i.e. from streams to large rivers, suggesting that highly biodegradable DOC is lost in headwater streams. We also observed a seasonal (January–December) decrease in BDOC in large streams and rivers, but saw no apparent change in smaller streams or soil leachates. We attribute this seasonal change to a combination of factors including shifts in carbon source, changing DOC residence time related to increasing thaw-depth, increasing water temperatures later in the summer, as well as decreasing hydrologic connectivity between soils and surface water as the thaw season progresses. Our results suggest that future climate warming-induced shifts of continuous permafrost into discontinuous permafrost regions could affect the degradation potential of thaw-released DOC, the amount of BDOC, as well as its variability throughout the Arctic summer. We lastly recommend a standardized BDOC protocol to facilitate the comparison of future work and improve our knowledge of processing and transport of DOC in a changing Arctic.
Lakes are prevalent in the Arctic and thus play a key role in regional hydrology. Since many Arctic lakes are shallow and ice grows thick (historically 2-m or greater), seasonal ice commonly freezes to the lake bed (bedfast ice) by winter's end. Bedfast ice fundamentally alters lake energy balance and melt-out processes compared to deeper lakes that exceed the maximum ice thickness (floating ice) and maintain perennial liquid water below floating ice. Our analysis of lakes in northern Alaska indicated that ice-out of bedfast ice lakes occurred on average 17 days earlier (22-June) than ice-out on adjacent floating ice lakes (9-July). Earlier ice-free conditions in bedfast ice lakes caused higher open-water evaporation, 28% on average, relative to floating ice lakes and this divergence increased in lakes closer to the coast and in cooler summers. Water isotopes (18O and 2H) indicated similar differences in evaporation between these lake types. Our analysis suggests that ice regimes created by the combination of lake depth relative to ice thickness and associated ice-out timing currently cause a strong hydrologic divergence among Arctic lakes. Thus understanding the distribution and dynamics of lakes by ice regime is essential for predicting regional hydrology. An observed regime shift in lakes to floating ice conditions due to thinner ice growth may initially offset lake drying because of lower evaporative loss from this lake type. This potential negative feedback caused by winter processes occurs in spite of an overall projected increase in evapotranspiration as the Arctic climate warms.
","language":"English","publisher":"AGU","doi":"10.1002/2015WR017362","usgsCitation":"Arp, C.D., Jones, B.M., Liljedahl, A.K., Hinkel, K., and Welker, J.A., 2015, Depth, ice thickness, and ice-out timing cause divergent hydrologic responses among Arctic lakes: Water Resources Research, v. 51, no. 12, p. 9379-9401, https://doi.org/10.1002/2015WR017362.","productDescription":"23 p.","startPage":"9379","endPage":"9401","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064849","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":471586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017362","text":"Publisher Index Page"},{"id":311769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.18115234375,\n 68.4072675680943\n ],\n [\n -158.18115234375,\n 72.22210088942214\n ],\n [\n -147.8759765625,\n 72.22210088942214\n ],\n [\n -147.8759765625,\n 68.4072675680943\n ],\n [\n -158.18115234375,\n 68.4072675680943\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-07","publicationStatus":"PW","scienceBaseUri":"565ec4afe4b071e7ea54440b","contributors":{"authors":[{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":580787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":580786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liljedahl, Anna K. 0000-0001-7114-6443","orcid":"https://orcid.org/0000-0001-7114-6443","contributorId":150135,"corporation":false,"usgs":false,"family":"Liljedahl","given":"Anna","email":"","middleInitial":"K.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":580788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinkel, Kenneth M.","contributorId":64170,"corporation":false,"usgs":true,"family":"Hinkel","given":"Kenneth M.","affiliations":[],"preferred":false,"id":580789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welker, Jeffery A.","contributorId":150136,"corporation":false,"usgs":false,"family":"Welker","given":"Jeffery","email":"","middleInitial":"A.","affiliations":[{"id":12492,"text":"UAA Alaska Natural Heritage Program & Biological Sciences Department","active":true,"usgs":false}],"preferred":false,"id":580790,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160657,"text":"70160657 - 2015 - Non-invasive flow path characterization in a mining-impacted wetland","interactions":[],"lastModifiedDate":"2018-09-04T15:29:32","indexId":"70160657","displayToPublicDate":"2015-12-01T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Non-invasive flow path characterization in a mining-impacted wetland","docAbstract":"Time-lapse electrical resistivity (ER) was used to capture the dilution of a seasonal pulse of acid mine drainage (AMD) contamination in the subsurface of a wetland downgradient of the abandoned Pennsylvania mine workings in central Colorado. Data were collected monthly from mid-July to late October of 2013, with an additional dataset collected in June of 2014. Inversion of the ER data shows the development through time of multiple resistive anomalies in the subsurface, which corroborating data suggest are driven by changes in total dissolved solids (TDS) localized in preferential flow pathways. Sensitivity analyses on a synthetic model of the site suggest that the anomalies would need to be at least several meters in diameter to be adequately resolved by the inversions. The existence of preferential flow paths would have a critical impact on the extent of attenuation mechanisms at the site, and their further characterization could be used to parameterize reactive transport models in developing quantitative predictions of remediation strategies.
","language":"English","publisher":"Elsevier","publisherLocation":"New York","doi":"10.1016/j.jconhyd.2015.10.002","usgsCitation":"Bethune, J., Randell, J., Runkel, R.L., and Singha, K., 2015, Non-invasive flow path characterization in a mining-impacted wetland: Journal of Contaminant Hydrology, v. 183, p. 29-39, https://doi.org/10.1016/j.jconhyd.2015.10.002.","productDescription":"11 p.","startPage":"29","endPage":"39","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066981","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2015.10.002","text":"Publisher Index Page"},{"id":312932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.24603271484375,\n 39.257778150283336\n ],\n [\n -106.24603271484375,\n 39.85915479295669\n ],\n [\n -105.08697509765625,\n 39.85915479295669\n ],\n [\n -105.08697509765625,\n 39.257778150283336\n ],\n [\n -106.24603271484375,\n 39.257778150283336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56826b46e4b0a04ef4925b88","contributors":{"authors":[{"text":"Bethune, James","contributorId":150889,"corporation":false,"usgs":false,"family":"Bethune","given":"James","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":583484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Randell, Jackie","contributorId":150890,"corporation":false,"usgs":false,"family":"Randell","given":"Jackie","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":583485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini","contributorId":76733,"corporation":false,"usgs":true,"family":"Singha","given":"Kamini","affiliations":[],"preferred":false,"id":583486,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160371,"text":"70160371 - 2015 - Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","interactions":[],"lastModifiedDate":"2015-12-23T11:00:01","indexId":"70160371","displayToPublicDate":"2015-12-01T12:00:00","publicationYear":"2015","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":"Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","docAbstract":"Growing use of two-dimensional (2-D) hydraulic models has created a need for high resolution data to support flood volume estimates, floodplain specific engineering data, and accurate flood inundation scenarios. Elevation data are a critical input to these models that guide the flood-wave across the landscape allowing the computation of valuable engineering specific data that provides a better understanding of flooding impacts on structures, debris movement, bed scour, and direction. High resolution elevation data are becoming publicly available that can benefit the 2-D flood modeling community. Comparison of these newly available data with legacy data suggests that better modeling outcomes are achieved by using 3D Elevation Program (3DEP) lidar point data and the derived 1 m Digital Elevation Model (DEM) product relative to the legacy 3 m, 10 m, or 30 m products currently available in the U.S. Geological Survey (USGS) National Elevation Dataset. Within the low topographic relief of a coastal floodplain, the newer 3DEP data better resolved elevations within the forested and swampy areas achieving simulations that compared well with a historic flooding event. Results show that the 1 m DEM derived from 3DEP lidar source provides a more conservative estimate of specific energy, static pressure, and impact pressure for grid elements at maximum flow relative to the legacy DEM data. Better flood simulations are critically important in coastal floodplains where climate change driven storm frequency and sea level rise will contribute to more frequent flooding events.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jhydrol.2015.10.051","usgsCitation":"Witt, E.C., 2015, Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain: Journal of Hydrology, v. 531, no. 3, p. 759-767, https://doi.org/10.1016/j.jhydrol.2015.10.051.","productDescription":"9 p.","startPage":"759","endPage":"767","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066431","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":312794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","city":"Greenville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3298454284668,\n 35.628488848361336\n ],\n [\n -77.32804298400879,\n 35.60330002507124\n ],\n [\n -77.36005783081055,\n 35.604346810028304\n ],\n [\n -77.37645149230957,\n 35.61174370007563\n ],\n [\n -77.37722396850586,\n 35.62583776685229\n ],\n [\n -77.3298454284668,\n 35.628488848361336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"531","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567bd3bbe4b0a04ef491a1f9","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":582830,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70161741,"text":"70161741 - 2015 - Fire effects on aquatic ecosystems: An assessment of the current state of the science","interactions":[],"lastModifiedDate":"2025-06-25T13:19:04.034953","indexId":"70161741","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Fire effects on aquatic ecosystems: An assessment of the current state of the science","docAbstract":"Fire is a prevalent feature of many landscapes and has numerous and complex effects on geological, hydrological, ecological, and economic systems. In some regions, the frequency and intensity of wildfire have increased in recent years and are projected to escalate with predicted climatic and landuse changes. In addition, prescribed burns continue to be used in many parts of the world to clear vegetation for development projects, encourage desired vegetation, and reduce fuel loads. Given the prevalence of fire on the landscape, authors of papers in this special series examine the complexities of fire as a disturbance shaping freshwater ecosystems and highlight the state of the science. These papers cover key aspects of fire effects that range from vegetation loss and recovery in watersheds to effects on hydrology and water quality with consequences for communities (from algae to fish), food webs, and ecosystem processes (e.g., organic matter subsidies, nutrient cycling) across a range of scales. The results presented in this special series of articles expand our knowledge of fire effects in different biomes, water bodies, and geographic regions, encompassing aquatic population, community, and ecosystem responses. In this overview, we summarize each paper and emphasize its contributions to knowledge on fire ecology and freshwater ecosystems. This overview concludes with a list of 7 research foci that are needed to further our knowledge of fire effects on aquatic ecosystems, including research on: 1) additional biomes and geographic regions; 2) additional habitats, including wetlands and lacustrine ecosystems; 3) different fire severities, sizes, and spatial configurations; and 4) additional response variables (e.g., ecosystem processes) 5) over long (>5 y) time scales 6) with more rigorous study designs and data analyses, and 7) consideration of the effects of fire management practices and policies on aquatic ecosystems.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/684073","usgsCitation":"Bixby, R.J., Cooper, S., Gresswell, R.E., Brown, L.E., Dahm, C.N., and Dwire, K.A., 2015, Fire effects on aquatic ecosystems: An assessment of the current state of the science: Freshwater Science, v. 34, no. 4, p. 1340-1350, https://doi.org/10.1086/684073.","productDescription":"11 p.","startPage":"1340","endPage":"1350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068454","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471611,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/5q9165nf","text":"External Repository"},{"id":381478,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568cf741e4b0e7a44bc0f156","contributors":{"authors":[{"text":"Bixby, Rebecca J.","contributorId":147389,"corporation":false,"usgs":false,"family":"Bixby","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":16834,"text":"Dept. of Biology and Museum of Southwestern Biology, Univ of NM","active":true,"usgs":false}],"preferred":false,"id":807071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooper, Scott D.","contributorId":152035,"corporation":false,"usgs":false,"family":"Cooper","given":"Scott D.","affiliations":[{"id":18860,"text":"Department of Ecology, Evolution, and Marine Biology and Marine Science Institute University of California","active":true,"usgs":false}],"preferred":false,"id":807072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":587615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Lee E.","contributorId":152036,"corporation":false,"usgs":false,"family":"Brown","given":"Lee","email":"","middleInitial":"E.","affiliations":[{"id":18861,"text":"School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":807073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahm, Clifford N.","contributorId":152037,"corporation":false,"usgs":false,"family":"Dahm","given":"Clifford","email":"","middleInitial":"N.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":587619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dwire, Kathleen A.","contributorId":225615,"corporation":false,"usgs":false,"family":"Dwire","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":41171,"text":"US Forest Service, Rocky Mountain Research Station, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":807075,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174840,"text":"70174840 - 2015 - Monitoring changes in seismic velocity related to an ongoing rapid inflation event at Okmok volcano, Alaska","interactions":[],"lastModifiedDate":"2022-11-02T14:52:07.249021","indexId":"70174840","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring changes in seismic velocity related to an ongoing rapid inflation event at Okmok volcano, Alaska","docAbstract":"Okmok is one of the most active volcanoes in the Aleutian Arc. In an effort to improve our ability to detect precursory activity leading to eruption at Okmok, we monitor a recent, and possibly ongoing, GPS-inferred rapid inflation event at the volcano using ambient noise interferometry (ANI). Applying this method, we identify changes in seismic velocity outside of Okmok’s caldera, which are related to the hydrologic cycle. Within the caldera, we observe decreases in seismic velocity that are associated with the GPS-inferred rapid inflation event. We also determine temporal changes in waveform decorrelation and show a continual increase in decorrelation rate over the time associated with the rapid inflation event. Themagnitude of relative velocity decreases and decorrelation rate increases are comparable to previous studies at Piton de la Fournaise that associate such changes with increased production of volatiles and/ormagmatic intrusion within the magma reservoir and associated opening of fractures and/or fissures. Notably, the largest decrease in relative velocity occurs along the intrastation path passing nearest to the center of the caldera. This observation, along with equal amplitude relative velocity decreases revealed via analysis of intracaldera autocorrelations, suggests that the inflation sourcemay be located approximately within the center of the caldera and represent recharge of shallow magma storage in this location. Importantly, there is a relative absence of seismicity associated with this and previous rapid inflation events at Okmok. Thus, these ANI results are the first seismic evidence of such rapid inflation at the volcano.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB011939","usgsCitation":"Bennington, N., Haney, M.M., De Angelis, S., Thurber, C., and Freymueller, J., 2015, Monitoring changes in seismic velocity related to an ongoing rapid inflation event at Okmok volcano, Alaska: Journal of Geophysical Research, v. 120, no. 8, p. 5664-5676, https://doi.org/10.1002/2015JB011939.","productDescription":"13 p.","startPage":"5664","endPage":"5676","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068858","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb011939","text":"Publisher Index Page"},{"id":325374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Okmok Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.25928811603328,\n 53.48606857460288\n ],\n [\n -168.25928811603328,\n 53.35666372572206\n ],\n [\n -168.0005045660394,\n 53.35666372572206\n ],\n [\n -168.0005045660394,\n 53.48606857460288\n ],\n [\n -168.25928811603328,\n 53.48606857460288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","scienceBaseUri":"578dfdb4e4b0f1bea0e0f8a3","contributors":{"authors":[{"text":"Bennington, Ninfa","contributorId":49699,"corporation":false,"usgs":true,"family":"Bennington","given":"Ninfa","affiliations":[],"preferred":false,"id":642731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":642730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Angelis, Silvio","contributorId":172953,"corporation":false,"usgs":false,"family":"De Angelis","given":"Silvio","affiliations":[{"id":27128,"text":"Univ. of Liverpool","active":true,"usgs":false}],"preferred":false,"id":642732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurber, Clifford","contributorId":44067,"corporation":false,"usgs":true,"family":"Thurber","given":"Clifford","affiliations":[],"preferred":false,"id":642733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freymueller, Jeff","contributorId":82190,"corporation":false,"usgs":true,"family":"Freymueller","given":"Jeff","affiliations":[],"preferred":false,"id":642734,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184995,"text":"70184995 - 2015 - Influence of grazing and land use on stream-channel characteristics among small dairy farms in the Eastern United States","interactions":[],"lastModifiedDate":"2017-03-13T12:52:54","indexId":"70184995","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5316,"text":"Renewable Agriculture and Food Systems","active":true,"publicationSubtype":{"id":10}},"title":"Influence of grazing and land use on stream-channel characteristics among small dairy farms in the Eastern United States","docAbstract":"Rotational grazing (RG) is a livestock management practice that rotates grazing cattle on a scale of hours to days among small pastures termed paddocks. It may beneficially affect stream channels, relative to other livestock management practices. Such effects and other beneficial effects on hydrology are important to RG's potential to provide a highly multifunctional mode of livestock farming. Previous comparisons of effects of RG and confinement dairy (CD) on adjoining streams have been restricted in scale and scope. We examined 11 stream-channel characteristics on a representative sample of 37 small dairy farms that used either RG or CD production methods. Our objectives were: (1) to compare channel characteristics on RG and CD farms, as these production methods are implemented in practice, in New York, Pennsylvania and Wisconsin, USA; and (2) to examine land use on these farms that may affect stream-channel characteristics. To help interpret channel characteristic findings, we examined on-farm land use in riparian areas 50 m in width along both sides of stream reaches and whole-farm land use. In all states, stream-channel characteristics on RG and CD farms did not differ. Whole-farm land use differed significantly between farm types; CD farms allocated more land to annual row crops, whereas RG farms allocated more land to pasture and grassland. However, land cover in 50 m riparian areas was not different between farm types within states; in particular, many RG and CD farms had continuously grazed pastures in riparian areas, typically occupied by juvenile and non-lactating cows, which may have contributed sediment and nutrients to streams. This similarity in riparian management practices may explain the observed similarity of farm types with respect to stream-channel characteristics. To realize the potential benefits of RG on streams, best management practices that affect stream-channel characteristics, such as protection of riparian areas, may improve aggregate effects of RG on stream quality and also enhance other environment, economic and social benefits of RG.
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\"}}]}","volume":"11","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425c2e4b0dc0b45b453fb","contributors":{"authors":[{"text":"LeDee, Olivia E. 0000-0002-7791-5829","orcid":"https://orcid.org/0000-0002-7791-5829","contributorId":199985,"corporation":false,"usgs":true,"family":"LeDee","given":"Olivia E.","affiliations":[],"preferred":false,"id":721147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":720531,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189516,"text":"70189516 - 2015 - The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3","interactions":[],"lastModifiedDate":"2018-09-04T15:40:41","indexId":"70189516","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3","title":"The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3","docAbstract":"Methylation of tracer and ambient mercury (200Hg and 202Hg, respectively) equilibrated with four different natural organic matter (NOM) isolates was investigated in vivo using the Hg-methylating sulfate-reducing bacterium Desulfobulbus propionicus 1pr3. Desulfobulbus cultures grown fermentatively with environmentally representative concentrations of dissolved NOM isolates, Hg[II], and HS− were assayed for absolute methylmercury (MeHg) concentration and conversion of Hg(II) to MeHg relative to total unfiltered Hg(II). Results showed the 200Hg tracer was methylated more efficiently in the presence of hydrophobic NOM isolates than in the presence of transphilic NOM, or in the absence of NOM. Different NOM isolates were associated with variable methylation efficiencies for either the 202Hg tracer or ambient 200Hg. One hydrophobic NOM, F1 HpoA derived from dissolved organic matter from the Florida Everglades, was equilibrated for different times with Hg tracer, which resulted in different methylation rates. A 5 day equilibration with F1 HpoA resulted in more MeHg production than either the 4 h or 30 day equilibration periods, suggesting a time dependence for NOM-enhanced Hg bioavailability for methylation.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmicb.2015.01389","usgsCitation":"Moreau, J.W., Gionfriddo, C.M., Krabbenhoft, D.P., Ogorek, J.M., DeWild, J.F., Aiken, G.R., and Roden, E.E., 2015, The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3: Frontiers in Microbiology, v. 6, p. 1-15, https://doi.org/10.3389/fmicb.2015.01389.","productDescription":"Article 1389; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-070733","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2015.01389","text":"Publisher Index Page"},{"id":343858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"5969d82ce4b0d1f9f060a197","contributors":{"authors":[{"text":"Moreau, John W.","contributorId":151017,"corporation":false,"usgs":false,"family":"Moreau","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":18167,"text":"University of Melbourne, Melbour","active":true,"usgs":false}],"preferred":false,"id":704997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gionfriddo, Caitlin M.","contributorId":194676,"corporation":false,"usgs":false,"family":"Gionfriddo","given":"Caitlin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":704998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":705002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roden, Eric E.","contributorId":127525,"corporation":false,"usgs":false,"family":"Roden","given":"Eric","email":"","middleInitial":"E.","affiliations":[{"id":7009,"text":"Department of Geoscience and NASA Astrobiology Institute, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":705003,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70184232,"text":"70184232 - 2015 - Hydrologic implications of GRACE satellite data in the Colorado River Basin","interactions":[],"lastModifiedDate":"2018-01-30T18:44:55","indexId":"70184232","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic implications of GRACE satellite data in the Colorado River Basin","docAbstract":"Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km3 during 1986–1990 and by 102 km3 during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km3) during 2010–2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018090","usgsCitation":"Scanlon, B., Zhang, Z., Reedy, R.C., Pool, D.R., Save, H., Long, D., Chen, J., Wolock, D.M., Conway, B.D., and Winester, D., 2015, Hydrologic implications of GRACE satellite data in the Colorado River Basin: Water Resources Research, v. 51, no. 12, p. 9891-9903, https://doi.org/10.1002/2015WR018090.","productDescription":"13 p.","startPage":"9891","endPage":"9903","ipdsId":"IP-070650","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018090","text":"Publisher Index Page"},{"id":336855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Colorado River Basin","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-24","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f3","contributors":{"authors":[{"text":"Scanlon, Bridget R.","contributorId":74093,"corporation":false,"usgs":true,"family":"Scanlon","given":"Bridget R.","affiliations":[],"preferred":false,"id":680670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Zizhan","contributorId":187508,"corporation":false,"usgs":false,"family":"Zhang","given":"Zizhan","email":"","affiliations":[],"preferred":false,"id":680671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reedy, Robert C.","contributorId":187509,"corporation":false,"usgs":false,"family":"Reedy","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":680672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pool, Donald R. drpool@usgs.gov","contributorId":1121,"corporation":false,"usgs":true,"family":"Pool","given":"Donald","email":"drpool@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Save, Himanshu","contributorId":187510,"corporation":false,"usgs":false,"family":"Save","given":"Himanshu","email":"","affiliations":[],"preferred":false,"id":680673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Di","contributorId":187511,"corporation":false,"usgs":false,"family":"Long","given":"Di","email":"","affiliations":[],"preferred":false,"id":680674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, Jianli","contributorId":187512,"corporation":false,"usgs":false,"family":"Chen","given":"Jianli","email":"","affiliations":[],"preferred":false,"id":680675,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":680676,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conway, Brian D.","contributorId":187513,"corporation":false,"usgs":false,"family":"Conway","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":680677,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Winester, Daniel","contributorId":187514,"corporation":false,"usgs":false,"family":"Winester","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":680678,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70196071,"text":"70196071 - 2015 - Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","interactions":[],"lastModifiedDate":"2018-09-13T16:50:34","indexId":"70196071","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","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":"Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","docAbstract":"The SPARROW (SPAtially Referenced Regression on Watershed attributes) model was used to simulate annual phosphorus loads and concentrations in unmonitored stream reaches in California, U.S., and portions of Nevada and Oregon. The model was calibrated using de-trended streamflow and phosphorus concentration data at 80 locations. The model explained 91% of the variability in loads and 51% of the variability in yields for a base year of 2002. Point sources, geological background, and cultivated land were significant sources. Variables used to explain delivery of phosphorus from land to water were precipitation and soil clay content. Aquatic loss of phosphorus was significant in streams of all sizes, with the greatest decay predicted in small- and intermediate-sized streams. Geological sources, including volcanic rocks and shales, were the principal control on concentrations and loads in many regions. Some localized formations such as the Monterey shale of southern California are important sources of phosphorus and may contribute to elevated stream concentrations. Many of the larger point source facilities were located in downstream areas, near the ocean, and do not affect inland streams except for a few locations. Large areas of cultivated land result in phosphorus load increases, but do not necessarily increase the loads above those of geological background in some cases because of local hydrology, which limits the potential of phosphorus transport from land to streams.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12326","usgsCitation":"Domagalski, J.L., and Saleh, D., 2015, Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling: Journal of the American Water Resources Association, v. 51, no. 6, p. 1463-1486, https://doi.org/10.1111/1752-1688.12326.","productDescription":"24 p.","startPage":"1463","endPage":"1486","ipdsId":"IP-052538","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":352579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2015-07-14","publicationStatus":"PW","scienceBaseUri":"5afeeb20e4b0da30c1bfc64a","contributors":{"authors":[{"text":"Domagalski, Joseph L. 0000-0002-6032-757X joed@usgs.gov","orcid":"https://orcid.org/0000-0002-6032-757X","contributorId":1330,"corporation":false,"usgs":true,"family":"Domagalski","given":"Joseph","email":"joed@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saleh, Dina 0000-0002-1406-9303 dsaleh@usgs.gov","orcid":"https://orcid.org/0000-0002-1406-9303","contributorId":939,"corporation":false,"usgs":true,"family":"Saleh","given":"Dina","email":"dsaleh@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731208,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220207,"text":"70220207 - 2015 - A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water","interactions":[],"lastModifiedDate":"2021-04-27T14:29:52.674829","indexId":"70220207","displayToPublicDate":"2015-11-30T08:31:30","publicationYear":"2015","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":"A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water","docAbstract":"Groundwater has a predictable thermal signature that can be used to locate discrete zones of discharge to surface water. As climate warms, surface water with strong groundwater influence will provide habitat stability and refuge for thermally stressed aquatic species, and is therefore critical to locate and protect. Alternatively, these discrete seepage locations may serve as potential point sources of contaminants from polluted aquifers. This study compares two increasingly common heat tracing methods to locate discrete groundwater discharge: direct-contact measurements made with fiber-optic distributed temperature sensing (FO-DTS) and remote sensing measurements collected with thermal infrared (TIR) cameras. FO-DTS is used to make high spatial resolution (typically m) thermal measurements through time within the water column using temperature-sensitive cables. The spatialtemporal data can be analyzed with statistical measures to reveal zones of groundwater influence, however, the personnel requirements, time to install, and time to georeference the cables can be burdensome, and the control units need constant calibration. In contrast, TIR data collection, either from handheld, airborne, or satellite platforms, can quickly capture point-in-time evaluations of groundwater seepage zones across large scales. However the remote nature of TIR measurements means they can be adversely influenced by a number of environmental and physical factors, and the measurements are limited to the surface skin temperature of water features. We present case studies from a range of lentic to lotic aquatic systems to identify capabilities and limitations of both technologies and highlight situations in which one or the other might be a better instrument choice for locating groundwater discharge. FO-DTS performs well in all systems across seasons, but data collection was limited spatially by practical considerations of cable installation. TIR is found to consistently locate groundwater seepage zones above and along the streambank, but submerged seepage zones are only well identified in shallow systems (e.g. <0.5 m depth) with moderate flow. Winter data collection, when groundwater is relatively warm and buoyant, increases the water surface expression of discharge zones in shallow systems.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2015.09.059","usgsCitation":"Hare, D.K., Briggs, M., Rosenberry, D., Boutt, D., and Lane, J., 2015, A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water: Journal of Hydrology, v. 530, p. 153-166, https://doi.org/10.1016/j.jhydrol.2015.09.059.","productDescription":"14 p.","startPage":"153","endPage":"166","ipdsId":"IP-068976","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":471620,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2015.09.059","text":"Publisher Index Page"},{"id":385322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, Michigan, Montana, New York, Pennsylvania","otherGeospatial":"Delaware River, Higgins, Lake, Quashnet River, Red Rocks Lake, Tidmarsh Farms","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.79179382324219,\n 44.41269287945535\n ],\n [\n -84.64210510253906,\n 44.41269287945535\n ],\n [\n -84.64210510253906,\n 44.520989167323734\n ],\n [\n -84.79179382324219,\n 44.520989167323734\n ],\n [\n -84.79179382324219,\n 44.41269287945535\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.91154479980467,\n 44.58582159355544\n ],\n [\n -111.66229248046874,\n 44.58582159355544\n ],\n [\n -111.66229248046874,\n 44.67182693970573\n ],\n [\n -111.91154479980467,\n 44.67182693970573\n ],\n [\n -111.91154479980467,\n 44.58582159355544\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.37513732910156,\n 41.83733944214672\n ],\n [\n -75.16159057617188,\n 41.83733944214672\n ],\n [\n -75.16159057617188,\n 41.99624282178583\n ],\n [\n -75.37513732910156,\n 41.99624282178583\n ],\n [\n -75.37513732910156,\n 41.83733944214672\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.64105987548828,\n 41.828386176902555\n ],\n [\n -70.54630279541016,\n 41.828386176902555\n ],\n [\n -70.54630279541016,\n 41.908664970834444\n ],\n [\n -70.64105987548828,\n 41.908664970834444\n ],\n [\n -70.64105987548828,\n 41.828386176902555\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.55746078491211,\n 41.58026831154093\n ],\n [\n -70.50750732421875,\n 41.58026831154093\n ],\n [\n -70.50750732421875,\n 41.62044728626882\n ],\n [\n -70.55746078491211,\n 41.62044728626882\n ],\n [\n -70.55746078491211,\n 41.58026831154093\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"530","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hare, Danielle K","contributorId":257636,"corporation":false,"usgs":false,"family":"Hare","given":"Danielle","email":"","middleInitial":"K","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":814761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":257638,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":814763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boutt, Dave","contributorId":257639,"corporation":false,"usgs":false,"family":"Boutt","given":"Dave","affiliations":[{"id":52076,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":814764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814766,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70164522,"text":"70164522 - 2015 - Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions","interactions":[],"lastModifiedDate":"2018-08-09T12:27:41","indexId":"70164522","displayToPublicDate":"2015-11-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions","docAbstract":"Observations of elemental mercury (Hg0) at sites in North America and Europe show large decreases (∼1–2% y−1) from 1990 to present. Observations in background northern hemisphere air, including Mauna Loa Observatory (Hawaii) and CARIBIC (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container) aircraft flights, show weaker decreases (<1% y−1). These decreases are inconsistent with current global emission inventories indicating flat or increasing emissions over that period. However, the inventories have three major flaws: (i) they do not account for the decline in atmospheric release of Hg from commercial products; (ii) they are biased in their estimate of artisanal and small-scale gold mining emissions; and (iii) they do not properly account for the change in Hg0/HgII speciation of emissions from coal-fired utilities after implementation of emission controls targeted at SO2 and NOx. We construct an improved global emission inventory for the period 1990 to 2010 accounting for the above factors and find a 20% decrease in total Hg emissions and a 30% decrease in anthropogenic Hg0 emissions, with much larger decreases in North America and Europe offsetting the effect of increasing emissions in Asia. Implementation of our inventory in a global 3D atmospheric Hg simulation [GEOS-Chem (Goddard Earth Observing System-Chemistry)] coupled to land and ocean reservoirs reproduces the observed large-scale trends in atmospheric Hg0 concentrations and in HgII wet deposition. The large trends observed in North America and Europe reflect the phase-out of Hg from commercial products as well as the cobenefit from SO2 and NOx emission controls on coal-fired utilities.
\n","language":"English","publisher":"The Academy","publisherLocation":"Washington, D.C.","doi":"10.1073/pnas.1516312113","usgsCitation":"Zhang, Y., Jacob, D.J., Horowitz, H.M., Chen, L., Amos, H.M., Krabbenhoft, D.P., Slemr, F., St. Louis, V.L., and Elsie M. Sunderland, 2015, Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions: Proceedings of the National Academy of Sciences, v. 133, no. 3, p. 526-531, https://doi.org/10.1073/pnas.1516312113.","productDescription":"6 p.","startPage":"526","endPage":"531","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070993","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471622,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1516312113","text":"Publisher Index Page"},{"id":316735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"133","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-04","publicationStatus":"PW","scienceBaseUri":"56bb1bc8e4b08d617f654e36","contributors":{"authors":[{"text":"Zhang, Yanxu","contributorId":156387,"corporation":false,"usgs":false,"family":"Zhang","given":"Yanxu","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacob, Daniel J.","contributorId":156388,"corporation":false,"usgs":false,"family":"Jacob","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horowitz, Hannah M.","contributorId":156389,"corporation":false,"usgs":false,"family":"Horowitz","given":"Hannah","email":"","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Long","contributorId":156390,"corporation":false,"usgs":false,"family":"Chen","given":"Long","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amos, Helen M.","contributorId":156391,"corporation":false,"usgs":false,"family":"Amos","given":"Helen","email":"","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597727,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597722,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slemr, Franz","contributorId":156392,"corporation":false,"usgs":false,"family":"Slemr","given":"Franz","email":"","affiliations":[{"id":12534,"text":"Max-Planck-Institute for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":597728,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"St. Louis, Vincent L.","contributorId":156393,"corporation":false,"usgs":false,"family":"St. Louis","given":"Vincent","email":"","middleInitial":"L.","affiliations":[{"id":12980,"text":"Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":597729,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Elsie M. Sunderland","contributorId":156394,"corporation":false,"usgs":false,"family":"Elsie M. Sunderland","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597730,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70159804,"text":"70159804 - 2015 - Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012","interactions":[],"lastModifiedDate":"2017-10-12T20:00:47","indexId":"70159804","displayToPublicDate":"2015-11-24T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012","docAbstract":"
Changes in the seasonality and timing of annual peak streamflow in the north-central USA are likely because of changes in precipitation and temperature regimes. A source of long-term information about flood events across the study area is the U.S. Geological Survey peak streamflow database. However, one challenge of answering climate-related questions with this dataset is that even in snowmelt-dominated areas, it is a mixed population of snowmelt/spring rain generated peaks and summer/fall rain generated peaks. Therefore, a process was developed to divide the annual peaks into two populations, or seasons, snowmelt/spring, and summer/fall. The two series were then tested for the hypotheses that because of changes in precipitation regimes, the odds of summer/fall peaks have increased and, because of temperature changes, snowmelt/spring peaks happen earlier. Over climatologically and geographically similar regions in the north-central USA, logistic regression was used to model the odds of getting a summer/fall peak. When controlling for antecedent wet and dry conditions and geographical differences, the odds of summer/fall peaks occurring have increased across the study area. With respect to timing within the seasons, trend analysis showed that in northern portions of the study region, snowmelt/spring peaks are occurring earlier. The timing of snowmelt/spring peaks in three regions in the northern part of the study area is earlier by 8.7– 14.3 days. These changes have implications for water interests, such as potential changes in lead-time for flood forecasting or changes in the operation of flood-control dams.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/hyp.10693","usgsCitation":"Ryberg, K.R., Akyuz, F.A., Wiche, G.J., and Lin, W., 2015, Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012: Hydrological Processes, v. 30, no. 8, p. 1208-1218, https://doi.org/10.1002/hyp.10693.","productDescription":"11 p.","startPage":"1208","endPage":"1218","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1910-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-059283","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":311699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.7353515625,\n 48.574789910928864\n ],\n [\n -91.23046875,\n 43.45291889355465\n ],\n [\n -90.263671875,\n 42.00032514831621\n ],\n [\n -91.4501953125,\n 40.38002840251183\n ],\n [\n -90.8349609375,\n 39.13006024213511\n ],\n [\n -102.1728515625,\n 38.61687046392973\n ],\n [\n -105.77636718749999,\n 38.92522904714054\n ],\n [\n -109.4677734375,\n 45.01141864227728\n ],\n [\n -113.09326171875,\n 48.99463598353408\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -93.7353515625,\n 48.574789910928864\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-11","publicationStatus":"PW","scienceBaseUri":"56558a32e4b071e7ea53dedf","chorus":{"doi":"10.1002/hyp.10693","url":"http://dx.doi.org/10.1002/hyp.10693","publisher":"Wiley-Blackwell","authors":"Ryberg Karen R., Akyüz F. Adnan, Wiche Gregg J., Lin Wei","journalName":"Hydrological Processes","publicationDate":"11/11/2015","auditedOn":"4/11/2016"},"contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akyuz, F. Adnan","contributorId":140760,"corporation":false,"usgs":false,"family":"Akyuz","given":"F.","email":"","middleInitial":"Adnan","affiliations":[{"id":13555,"text":"North Dakota Climate Office","active":true,"usgs":false}],"preferred":false,"id":580538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiche, Gregg J. gjwiche@usgs.gov","contributorId":1675,"corporation":false,"usgs":true,"family":"Wiche","given":"Gregg","email":"gjwiche@usgs.gov","middleInitial":"J.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lin, Wei","contributorId":93805,"corporation":false,"usgs":true,"family":"Lin","given":"Wei","email":"","affiliations":[],"preferred":false,"id":580537,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70158939,"text":"sir20155150 - 2015 - Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California","interactions":[],"lastModifiedDate":"2016-01-07T10:17:48","indexId":"sir20155150","displayToPublicDate":"2015-11-24T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5150","title":"Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California","docAbstract":"The Borrego Valley is a small valley (110 square miles) in the northeastern part of San Diego County, California. Although the valley is about 60 miles northeast of city of San Diego, it is separated from the Pacific Ocean coast by the mountains to the west and is mostly within the boundaries of Anza-Borrego Desert State Park. From the time the basin was first settled, groundwater has been the only source of water to the valley. Groundwater is used for agricultural, recreational, and municipal purposes. Over time, groundwater withdrawal through pumping has exceeded the amount of water that has been replenished, causing groundwater-level declines of more than 100 feet in some parts of the basin. Continued pumping has resulted in an increase in pumping lifts, reduced well efficiency, dry wells, changes in water quality, and loss of natural groundwater discharge. As a result, the U.S. Geological Survey began a cooperative study of the Borrego Valley with the Borrego Water District (BWD) in 2009. The purpose of the study was to develop a greater understanding of the hydrogeology of the Borrego Valley Groundwater Basin (BVGB) and to provide tools to help evaluate the potential hydrologic effects of future development. The objectives of the study were to (1) improve the understanding of groundwater conditions and land subsidence, (2) incorporate this improved understanding into a model that would assist in the management of the groundwater resources in the Borrego Valley, and (3) use this model to test several management scenarios. This model provides the capability for the BWD and regional stakeholders to quantify the relative benefits of various options for increasing groundwater storage. The study focuses on the period 1945–2010, with scenarios 50 years into the future.
\nThis report documents and presents (1) an analysis of the conceptual model, (2) a description of the hydrologic features, (3) a compilation and analysis of water-quality data, (4) the measurement and analysis of land subsidence by using geophysical and remote sensing techniques, (5) the development and calibration of a two-dimensional borehole-groundwater-flow model to estimate aquifer hydraulic conductivities, (6) the development and calibration of a three-dimensional (3-D) integrated hydrologic flow model, (7) a water-availability analysis with respect to current climate variability and land use, and (8) potential future management scenarios. The integrated hydrologic model, referred to here as the “Borrego Valley Hydrologic Model” (BVHM), is a tool that can provide results with the accuracy needed for making water-management decisions, although potential future refinements and enhancements could further improve the level of spatial and temporal resolution and model accuracy. Because the model incorporates time-varying inflows and outflows, this tool can be used to evaluate the effects of temporal changes in recharge and pumping and to compare the relative effects of different water-management scenarios on the aquifer system. Overall, the development of the hydrogeologic and hydrologic models, data networks, and hydrologic analysis provides a basis for assessing surface and groundwater availability and potential water-resource management guidelines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155150","collaboration":"Prepared in cooperation with the Borrego Water District","usgsCitation":"Faunt, C.C., Stamos, C.L., Flint, L.E., Wright, M.T., Burgess, M.K., Sneed, Michelle, Brandt, Justin, Martin, Peter, and Coes, A.L., 2015, Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California: U.S. Geological Survey Scientific Investigations Report 2015–5150, 135 p., https://dx.doi.org/10.3133/sir20155150.","productDescription":"xiv, 135 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-024573","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":311633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150.pdf","text":"Report","size":"21.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5150"},{"id":311632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5150/coverthb.jpg"},{"id":311671,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://dx.doi.org/10.5066/F7S180J9","text":"Borrego Valley Groundwater Conditions"},{"id":314004,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150_input.zip","text":"Model Input","size":"420 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5150 Model Input files"},{"id":314005,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150_output.zip","text":"Model Output","size":"45 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5150 Model Output files"}],"country":"United States","state":"California","otherGeospatial":"Borrego Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.54708862304686,\n 32.89342578969234\n ],\n [\n -116.54708862304686,\n 33.34659043589842\n ],\n [\n -115.73272705078124,\n 33.34659043589842\n ],\n [\n -115.73272705078124,\n 32.89342578969234\n ],\n [\n -116.54708862304686,\n 32.89342578969234\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Drill-core samples from a sandstone-hosted uranium (U) deposit in Wyoming were characterized to determine the abundance and distribution of uranium following in-situ recovery (ISR) mining with oxygen- and carbon dioxide-enriched water. Concentrations of uranium, collected from ten depth intervals, ranged from 5 to 1920 ppm. A composite sample contained 750 ppm uranium with an average oxidation state of 54% U(VI) and 46% U(IV). Scanning electron microscopy (SEM) indicated rare high uranium (∼1000 ppm U) in spatial association with P/Ca and Si/O attributed to relict uranium minerals, possibly coffinite, uraninite, and autunite, trapped within low permeability layers bypassed during ISR mining. Fission track analysis revealed lower but still elevated concentrations of U in the clay/silica matrix and organic matter (several 10 s ppm) and yet higher concentrations associated with Fe-rich/S-poor sites, likely iron oxides, on altered chlorite or euhedral pyrite surfaces (but not on framboidal pyrite). Organic C (<1.62%), total S (<0.31%), and P (<0.03%) were in low abundance relative to the overall bulk composition. Microbial community analysis showed a diverse group of bacteria present with a wide range of putative metabolisms, and provides evidence for a variety of redox microenvironments co-existing in core samples. Although the uranium minerals persisting in low permeability areas in association with organic carbon were less affected by oxidizing solutions during mining, the likely sequestration of uranium within labile iron oxides following mining and sensitivity to changes in redox conditions requires careful attention during groundwater restoration.
\n\n
A groundwater-flow model was developed for the Bad River Watershed and surrounding area by using the U.S. Geological Survey (USGS) finite-difference code MODFLOW-NWT. The model simulates steady-state groundwater-flow and base flow in streams by using the streamflow routing (SFR) package. The objectives of this study were to: (1) develop an improved understanding of the groundwater-flow system in the Bad River Watershed at the regional scale, including the sources of water to the Bad River Band of Lake Superior Chippewa Reservation (Reservation) and groundwater/surface-water interactions; (2) provide a quantitative platform for evaluating future impacts to the watershed, which can be used as a starting point for more detailed investigations at the local scale; and (3) identify areas where more data are needed. This report describes the construction and calibration of the groundwater-flow model that was subsequently used for analyzing potential locations for the collection of additional field data, including new observations of water-table elevation for refining the conceptualization and corresponding numerical model of the hydrogeologic system.
\nThe study area can be conceptually divided into three primary hydrogeologic environments. The first encompasses the southern uplands with relatively low topographic relief, where groundwater-flow is unconfined and occurs primarily in sandy till and glacial outwash overlying Archean-aged crystalline bedrock. The second includes a transitional area of higher topographic relief and shallow depth to bedrock, in the vicinity of ridges formed by steeply dipping, early-Proterozoic aged metasedimentary units of the Marquette Range Supergroup (including the Ironwood Formation), and late-Proterozoic igneous units associated with the Midcontinent Rift System (MRS). Groundwater-flow in this area likely occurs primarily through connected networks of bedrock fractures that are not well characterized, and also in isolated pockets of Quaternary deposits. The third and last hydrogeologic environment includes lowlands along Lake Superior where a deep sandstone aquifer is confined by thick deposits of clay-rich till.
\nModel input was compiled by using both published and unpublished data. Constant flux boundary conditions for the model perimeter were developed from a regional analytic element model described in appendix 1 of this report. Pumping from 26 high-capacity wells within the model area was included. The SFR stream network was developed from the National Hydrography Dataset (NHDPlus Version 2) and hydrography from the Wisconsin Department of Natural Resources (WDNR). Hydraulic conductivity values were determined for each model cell by interpolation from a network of pilot points, within zones representing major hydrogeologic units.
\nRecharge to the groundwater system was estimated on a cell-by-cell basis by using the Soil Water Balance code (SWB), with gridded daily temperature and precipitation data for the period 1980–2011, and GIS coverages of soil and land-surface conditions. Estimated recharge varies considerably, following spatial patterns in the precipitation and soil hydrologic group inputs. The lowest recharge values occur in the Superior lowlands, whereas the highest values occur in the upland areas, especially those underlain by sandy soils, and in the vicinity of bedrock hills.
\nThe model was calibrated to groundwater-levels and base flows obtained from the USGS National Water Information System (NWIS) database, and groundwater-levels obtained from the WDNR and Band River Band well-construction databases. Calibration was performed via nonlinear regression by using the parameter-estimation software suite PEST. Groundwater levels and base-flow observations in the calibration dataset were well simulated by the calibrated model, with reasonable values of hydraulic conductivity. The pilot-point parameters that were most constrained by observations during model calibration coincided with the locations containing the most wells (head observations)—especially the population centers of Ashland, Mellen, and other communities along the major highway corridors.
\nResults from the calibrated model illustrate differences in the nature of groundwater-flow within the watershed. In the southern part of the watershed, where bedrock is shallow, groundwater flow paths are relatively short, extending from local recharge areas to adjacent first and second-order streams. In contrast, laterally continuous deposits of clay-rich till covering the Superior Lowlands isolate most smaller streams from the sandstone aquifer, allowing for longer flow paths toward larger streams such as the Bad, Marengo, and White Rivers. Approximately three-quarters of all first-order stream cells were dry in the Superior Lowlands, compared to only half of first-order stream cells in the southern bedrock uplands.
\nThe model was used to delineate the groundwatershed for the Bad and Kakagon Rivers. “Groundwatershed” is defined as the area contributing groundwater discharge to one of these streams and their tributaries. The groundwatershed was found to align closely with the surface-watershed, with the most notable exception occurring along the southwestern half of Birch Hill, where surface water drains southwest towards the Potato River, and groundwater flows north and east towards Lake Superior. Similarly, the contributing area of groundwater-flow to the Reservation was delineated. Results indicate the off-Reservation groundwater contributing area to be limited in comparison to the extent of the watershed, extending southward into the highlands underlain by MRS igneous rock units, but not further into the area underlain by the Marquette Range Supergroup.
\nStable isotope samples were collected from 54 wells within the watershed, to investigate sources of groundwater. Oxygen-18 (δ 18O) values lower than -13.0 per mil were documented in the sampling, and likely indicate the presence of recharge water from the last glacial period (>9,500 years old) beneath the northern portion of the Reservation, in the vicinity of Odanah, Wisconsin.
\nFinally, a new data-worth analysis of potential new monitoring-well locations was performed by using the model. The relative worth of new measurements was evaluated based on their ability to increase confidence in model predictions of groundwater levels and base flows at 35 locations, under the condition of a proposed open-pit iron mine. Results of the new data-worth analysis, and other inputs and outputs from the Bad River model, are available through an online dynamic web mapping service at (http://wim.usgs.gov/badriver/).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155162","collaboration":"Prepared in cooperation with the Bad River Band of Lake Superior Chippewa; U.S. Bureau of Indian Affairs","usgsCitation":"Leaf, A.T., Fienen, M.N., Hunt, R.J., and Buchwald, C.A., 2015, Groundwater/Surface-Water Interactions in the Bad\n River Watershed, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2015–5162, 110 p., https://dx.doi.org/10.3133/sir20155162.","productDescription":"viii, 110 p.","numberOfPages":"122","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061535","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":311584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5162/coverthb.jpg"},{"id":311585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5162/sir20155162.pdf","text":"Report","size":"24.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015=5162"},{"id":332726,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7Z0368H","text":"MODFLOW-NWT model used to evaluate groundwater/surface-water interactions in the Bad River Watershed, Wisconsin"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bad River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.06842041015625,\n 46.36777895261494\n ],\n [\n -91.06842041015625,\n 46.76996843356982\n ],\n [\n -90.43121337890625,\n 46.76996843356982\n ],\n [\n -90.43121337890625,\n 46.36777895261494\n ],\n [\n -91.06842041015625,\n 46.36777895261494\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
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In this study, water and whole rock samples from hydraulically fractured wells in the Marcellus Shale (Middle Devonian), and water from conventional wells producing from Upper Devonian sandstones were analyzed for lithium concentrations and isotope ratios (δ7Li). The distribution of lithium concentrations in different mineral groups was determined using sequential extraction. Structurally bound Li, predominantly in clays, accounted for 75-91 wt. % of total Li, whereas exchangeable sites and carbonate cement contain negligible Li (< 3%). Up to 20% of the Li is present in the oxidizable fraction (organic matter and sulfides). The δ7Li values for whole rock shale in Greene Co., Pennsylvania, and Tioga Co., New York, ranged from -2.3 to + 4.3‰, similar to values reported for other shales in the literature. The δ7Li values in shale rocks with stratigraphic depth record progressive weathering of the source region; the most weathered and clay-rich strata with isotopically light Li are found closest to the top of the stratigraphic section. Diagenetic illite-smectite transition could also have partially affected the bulk Li content and isotope ratios of the Marcellus Shale.
\nIn Greene Co., southwest Pennsylvania, the Upper Devonian sandstone formation waters have δ7Li values of + 14.6 ± 1.2 (2SD, n = 25), and are distinct from Marcellus Shale formation waters which have δ7Li of + 10.0 ± 0.8 (2SD, n = 12). These two formation waters also maintain distinctive 87Sr/86Sr ratios suggesting hydrologic separation between these units. Applying temperature-dependent illitilization model to Marcellus Shale, we found that Li concentration in clay minerals increased with Li concentration in pore fluid during diagenetic illite-smectite transition. Samples from north central PA show a much smaller range in both δ7Li and 87Sr/86Sr than in southwest Pennsylvania. Spatial variations in Li and δ7Li values show that Marcellus formation waters are not homogeneous across the Appalachian Basin. Marcellus formation waters in the northeastern Pennsylvania portion of the basin show a much smaller range in both δ7Li and 87Sr/86Sr, suggesting long term, cross-formational fluid migration in this region. Assessing the impact of potential mixing of fresh water with deep formation water requires establishment of a geochemical and isotopic baseline in the shallow, fresh water aquifers, and site specific characterization of formation water, followed by long-term monitoring, particularly in regions of future shale gas development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2015.11.003","usgsCitation":"Phan, T.T., Capo, R.C., Stewart, B.W., Macpherson, G., Rowan, E.L., and Hammack, R.W., 2015, Factors controlling Li concentration and isotopic composition in formation waters and host rocks of Marcellus Shale, Appalachian Basin: Chemical Geology, v. 420, p. 162-179, https://doi.org/10.1016/j.chemgeo.2015.11.003.","productDescription":"18 p.","startPage":"162","endPage":"179","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068352","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":471632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1397544","text":"Publisher Index Page"},{"id":311641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Pennsylvania","county":"Greene 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quantitative precipitation estimates, data acquisition, and processing for the DuPage County, Illinois, streamflow-simulation modeling system","docAbstract":"Next-Generation Radar (NEXRAD) has become an integral component in the estimation of precipitation (Kitzmiller and others, 2013). The high spatial and temporal resolution of NEXRAD has revolutionized the ability to estimate precipitation across vast regions, which is especially beneficial in areas without a dense rain-gage network. With the improved precipitation estimates, hydrologic models can produce reliable streamflow forecasts for areas across the United States. NEXRAD data from the National Weather Service (NWS) has been an invaluable tool used by the U.S. Geological Survey (USGS) for numerous projects and studies; NEXRAD data processing techniques similar to those discussed in this Fact Sheet have been developed within the USGS, including the NWS Quantitative Precipitation Estimates archive developed by Blodgett (2013).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153076","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Ortel, T.W., and Spies, R.R., 2015, NEXRAD Quantitative precipitation estimates, data acquisition, and processing for the DuPage County, Illinois, streamflow-simulation modeling system: U.S. Geological Survey Fact Sheet 2015–3076, 2 p., https://dx.doi.org/10.3133/fs20153076.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057259","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":311538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3076/coverthb.jpg"},{"id":311539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3076/fs20153076.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3076"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.49212646484374,\n 41.281934557995356\n ],\n [\n -88.49212646484374,\n 42.04929263868686\n ],\n [\n -87.6104736328125,\n 42.04929263868686\n ],\n [\n -87.6104736328125,\n 41.281934557995356\n ],\n [\n -88.49212646484374,\n 41.281934557995356\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801–2347
Phone: (217) 328–USGS (8747)
http://il.water.usgs.gov/