Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2014 (October 1, 2013, through September 30, 2014) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board in the cooperative study. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2014 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2014.
The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 23 cubic feet per second to the reservoir during WY 2014. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.35 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,200,000 kilograms of sodium and 2,100,000 kilograms of chloride to the Scituate Reservoir during WY 2014; sodium and chloride yields for the tributaries ranged from 7,700 to 45,000 kilograms per year per square mile and from 12,000 to 75,000 kilograms per year per square mile, respectively.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24 milligrams per liter, median nitrite concentration was 0.002 milligrams per liter as nitrogen (N), median nitrate concentration was 0.01 milligrams per liter as N, median orthophosphate concentration was 0.07 milligrams per liter as phosphate, and median concentrations of total coliform bacteria and Escherichia coli were 320 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 62 kilograms per day (42 kilograms per day per square mile), 19 grams per day (6.1 grams per day per square mile), 79 grams per day (36 grams per day per square mile), 380 grams per day (150 grams per day per square mile), 13,000 million colony forming units per day (8,300 million colony forming units per day per square mile), and 1,000 million colony forming units per day (470 million colony forming units per day per square mile), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161051","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2016, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2014: U.S. Geological Survey Open-File Report 2016–1051, 31 p., https://dx.doi.org/10.3133/ofr20161051.","productDescription":"Report: v, 31 p.; Appendix 1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069938","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":320747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051.pdf","text":"Report","size":"11.1 (MB)","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2016-1051"},{"id":320748,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051_appendix1.xlsx","text":"Appendix 1","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1","linkHelpText":"Appendix 1. Water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, Rhode Island, water year 2014. Excel (30 KB)"},{"id":320746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1051/coverthb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.7572021484375,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.738784653087464\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
or visit our Web site at:
http://newengland.water.usgs.gov
The U.S. Corn Belt is one of the most intensive agricultural regions of the world and is drained by the Upper Mississippi River (UMR), which forms one of the largest drainage basins in the U.S. While the effects of agricultural nitrate (NO3-) on water quality in the UMR have been well documented, its impact on the production of nitrous oxide (N2O) has not been reported. Using a novel equilibration technique, we present the largest data set of freshwater dissolved N2O concentrations (0.7 to 6 times saturation) and examine the controls on its variability over a 350 km reach of the UMR. Driven by a supersaturated water column, the UMR was an important atmospheric N2O source (+68 mg N2ONm-2 yr-1) that varies nonlinearly with the NO3-concentration. Our analyses indicated that a projected doubling of the NO3-concentration by 2050 would cause dissolved N2O concentrations and emissions to increase by about 40%.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL068710","usgsCitation":"Turner, P., Griffis, T., Baker, J., Lee, X., Crawford, J.T., Loken, L., and Venterea, R., 2016, Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River: Geophysical Research Letters, v. 43, no. 9, p. 4400-4407, https://doi.org/10.1002/2016GL068710.","productDescription":"8 p.","startPage":"4400","endPage":"4407","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071258","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471012,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068710","text":"Publisher Index Page"},{"id":321112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","volume":"43","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"5734499ce4b0dae0d5dd6903","contributors":{"authors":[{"text":"Turner, P.A.","contributorId":169214,"corporation":false,"usgs":false,"family":"Turner","given":"P.A.","email":"","affiliations":[{"id":25441,"text":"University of Minnesota, Department of Soil, Water and Climate","active":true,"usgs":false}],"preferred":false,"id":628997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffis, T.J.","contributorId":169215,"corporation":false,"usgs":false,"family":"Griffis","given":"T.J.","email":"","affiliations":[{"id":25442,"text":"U.S. Department of Agriculture - Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":628998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, J.M.","contributorId":169216,"corporation":false,"usgs":false,"family":"Baker","given":"J.M.","email":"","affiliations":[{"id":25443,"text":"Yale University, School of Forestry and Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":628999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, X.","contributorId":169217,"corporation":false,"usgs":false,"family":"Lee","given":"X.","email":"","affiliations":[{"id":25444,"text":"Yale-Nanjing University of Information, Science and Technology","active":true,"usgs":false}],"preferred":false,"id":629000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":628996,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loken, Luke C. lloken@usgs.gov","contributorId":169218,"corporation":false,"usgs":true,"family":"Loken","given":"Luke C.","email":"lloken@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629001,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Venterea, R.T.","contributorId":53994,"corporation":false,"usgs":true,"family":"Venterea","given":"R.T.","email":"","affiliations":[],"preferred":false,"id":629002,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170902,"text":"70170902 - 2016 - The ecology of methane in streams and rivers: Patterns, controls, and global significance","interactions":[],"lastModifiedDate":"2016-05-11T10:34:05","indexId":"70170902","displayToPublicDate":"2016-05-11T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of methane in streams and rivers: Patterns, controls, and global significance","docAbstract":"Streams and rivers can substantially modify organic carbon (OC) inputs from terrestrial landscapes, and much of this processing is the result of microbial respiration. While carbon dioxide (CO2) is the major end-product of ecosystem respiration, methane (CH4) is also present in many fluvial environments even though methanogenesis typically requires anoxic conditions that may be scarce in these systems. Given recent recognition of the pervasiveness of this greenhouse gas in streams and rivers, we synthesized existing research and data to identify patterns and drivers of CH4, knowledge gaps, and research opportunities. This included examining the history of lotic CH4 research, creating a database of concentrations and fluxes (MethDB) to generate a global-scale estimate of fluvial CH4 efflux, and developing a conceptual framework and using this framework to consider how human activities may modify fluvial CH4 dynamics. Current understanding of CH4 in streams and rivers has been strongly influenced by goals of understanding OC processing and quantifying the contribution of CH4 to ecosystem C fluxes. Less effort has been directed towards investigating processes that dictate in situ CH4 production and loss. CH4 makes a meager contribution to watershed or landscape C budgets, but streams and rivers are often significant CH4 sources to the atmosphere across these same spatial extents. Most fluvial systems are supersaturated with CH4 and we estimate an annual global emission of 26.8 Tg CH4, equivalent to ~15-40% of wetland and lake effluxes, respectively. Less clear is the role of CH4 oxidation, methanogenesis, and total anaerobic respiration to whole ecosystem production and respiration. Controls on CH4 generation and persistence can be viewed in terms of proximate controls that influence methanogenesis (organic matter, temperature, alternative electron acceptors, nutrients) and distal geomorphic and hydrologic drivers. Multiple controls combined with its extreme redox status and low solubility result in high spatial and temporal variance of CH4 in fluvial environments, which presents a substantial challenge for understanding its larger-scale dynamics. Further understanding of CH4 production and consumption, anaerobic metabolism, and ecosystem energetics in streams and rivers can be achieved through more directed studies and comparison with knowledge from terrestrial, wetland, and aquatic disciplines.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-1027.1","usgsCitation":"Stanley, E.H., Casson, N.J., Christel, S.T., Crawford, J.T., Loken, L., and Oliver, S., 2016, The ecology of methane in streams and rivers: Patterns, controls, and global significance: Ecological Monographs, v. 86, no. 2, p. 146-171, https://doi.org/10.1890/15-1027.1.","productDescription":"16 p.","startPage":"146","endPage":"171","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066395","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471013,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10680/1574","text":"External Repository"},{"id":321111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-07","publicationStatus":"PW","scienceBaseUri":"5734499de4b0dae0d5dd690d","contributors":{"authors":[{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":629004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christel, Samuel T.","contributorId":169272,"corporation":false,"usgs":false,"family":"Christel","given":"Samuel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":629006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":629003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loken, Luke C. lloken@usgs.gov","contributorId":169218,"corporation":false,"usgs":true,"family":"Loken","given":"Luke C.","email":"lloken@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":629008,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188601,"text":"70188601 - 2016 - A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches","interactions":[],"lastModifiedDate":"2017-06-16T12:23:37","indexId":"70188601","displayToPublicDate":"2016-05-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches","docAbstract":"The September 16, 2015 Illapel, Chile earthquake\ntriggered a large tsunami, causing both economic losses and\nfatalities. To study the coastal effects of this earthquake, and to\nunderstand how such hazards might be accurately modeled in the\nfuture, different finite fault models of the Illapel rupture are used to\ndefine the initial condition for tsunami simulation. The numerical\ncode Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE)\nis employed to model the tsunami evolution through the Pacific\nOcean. Because only a short time is available for emergency\nresponse, and since the earthquake and tsunami sources are close to\nthe coast, gaining a rapid understanding of the near-field run-up\nbehavior is highly relevant to Chile. Therefore, an analytical\nsolution of the 2 ? 1 D shallow water wave equations is considered.\nWith this solution, we show that we can quickly estimate the\nrun-up distribution along the coastline, to first order. After the\nearthquake and tsunami, field observations were measured in the\nsurrounded coastal region, where the tsunami resulted in significant\nrun-up. First, we compare the analytical and numerical solutions to\ntest the accuracy of the analytical approach and the field observations,\nimplying the analytic approach can accurately model tsunami\nrun-up after an earthquake, without sacrificing the time necessary\nfor a full numerical inversion. Then, we compare both with field\nrun-up measurements. We observe the consistency between the two\napproaches. To complete the analysis, a tsunami source inversion is\nperformed using run-up field measurements only. These inversion\nresults are compared with seismic models, and are shown to capture\nthe broad-scale details of those models, without the necessity of the\ndetailed data sets they invert.","language":"English","publisher":"SpringerLink","doi":"10.1007/s00024-016-1305-0","usgsCitation":"Fuentes, M., Riquelme, S., Hayes, G.P., Medina, M., Melgar, D., Vargas, G., Gonzalez, J., and Villalobos, A., 2016, A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches: Pure and Applied Geophysics, v. 173, p. 1847-1858, https://doi.org/10.1007/s00024-016-1305-0.","productDescription":"12 p. 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2016 - POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:50:15","indexId":"70170912","displayToPublicDate":"2016-05-10T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","docAbstract":"A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2016.03.025","usgsCitation":"Chaney, N.W., Wood, E.F., McBratney, A., Hempel, J.W., Nauman, T.W., Brungard, C.W., and Odgers, N.P., 2016, POLARIS: A 30-meter probabilistic soil series map of the contiguous United States: Geoderma, v. 274, p. 54-67, https://doi.org/10.1016/j.geoderma.2016.03.025.","productDescription":"14 p.","startPage":"54","endPage":"67","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069596","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geoderma.2016.03.025","text":"Publisher Index Page"},{"id":321091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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USA","active":true,"usgs":false}],"preferred":false,"id":629053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McBratney, Alexander B","contributorId":169245,"corporation":false,"usgs":false,"family":"McBratney","given":"Alexander B","affiliations":[{"id":25455,"text":"Department of Environmental Sciences, Faculty of Agriculture and Environment, The University of Sydney, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":629055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hempel, Jonathan W","contributorId":169244,"corporation":false,"usgs":false,"family":"Hempel","given":"Jonathan","email":"","middleInitial":"W","affiliations":[{"id":25454,"text":"National Soil Survey Center, NRCS, Lincoln, Nebraska, USA","active":true,"usgs":false}],"preferred":false,"id":629054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629051,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brungard, Colby W.","contributorId":99488,"corporation":false,"usgs":true,"family":"Brungard","given":"Colby","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":629056,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Odgers, Nathan P","contributorId":169246,"corporation":false,"usgs":false,"family":"Odgers","given":"Nathan","email":"","middleInitial":"P","affiliations":[{"id":25454,"text":"National Soil Survey Center, NRCS, Lincoln, Nebraska, USA","active":true,"usgs":false}],"preferred":false,"id":629057,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70171093,"text":"70171093 - 2016 - Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources","interactions":[],"lastModifiedDate":"2016-09-06T14:03:13","indexId":"70171093","displayToPublicDate":"2016-05-10T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources","docAbstract":"In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1457","usgsCitation":"Palmquist, K.A., Schlaepfer, D., Bradford, J.B., and Lauenroth, W.K., 2016, Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources: Ecology, v. 97, no. 9, p. 2342-2354, https://doi.org/10.1002/ecy.1457.","productDescription":"13 p.","startPage":"2342","endPage":"2354","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066807","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5740354de4b07e28b65e9697","contributors":{"authors":[{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629843,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, Willliam K.","contributorId":169518,"corporation":false,"usgs":false,"family":"Lauenroth","given":"Willliam","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629845,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186267,"text":"70186267 - 2016 - Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","interactions":[],"lastModifiedDate":"2017-04-03T12:50:32","indexId":"70186267","displayToPublicDate":"2016-05-09T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5361,"text":"California Archaeology","active":true,"publicationSubtype":{"id":10}},"title":"Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","docAbstract":"Archaeological investigations at prehistoric site CA-MRN-254 at the Dominican University of California in Marin County, California, revealed evidence of Native American occupation spanning the past 1,800 years. A dominant source of food for the inhabitants in the San Francisco Bay area was the intertidal, quiet-water dwelling blue mussel (Mytilus trossulus), although rare occurrences of the open coast-dwelling California mussel (Mytilus californianus) suggest that this species was also utilized sporadically. On rare occasions, cultural horizons at this site contain abundant sediment-filled casts of the smaller mussel Modiolus sp. These casts were formed soon after death when the shells filled with sediment and were roasted along with living bivalve shellfish for consumption. Thin sections of these mussel casts display sedimentological and microbiological constituents that shed light on the paleoenvironmental conditions when they were alive. Fine-grained sediment and pelletal muds comprising these casts suggest that the mussels were collected in a low energy, inner bay environment. The rare presence of the diatoms Triceratium dubium and Thalassionema nitzschioides indicate more normal marine (35 psu) and possibly warmer conditions than presently exist in San Francisco Bay. Radiocarbon dating of charcoal associated with the mussel casts containing these diatoms correlates with a 600-year period of warming from ca. A.D. 700–1300, known as the Medieval Climatic Anomaly. Results of this mussel cast study demonstrate that they have great potential for providing paleoenvironmental information at this and other archaeological sites.
","language":"English","publisher":"Society for California Archaeology","publisherLocation":"Chico, CA","doi":"10.1080/1947461X.2016.1176367","usgsCitation":"McGann, M., Starratt, S.W., Powell, C.L., and Bieling, D.G., 2016, Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California: California Archaeology, v. 8, no. 1, p. 63-90, https://doi.org/10.1080/1947461X.2016.1176367.","productDescription":"28 p.","startPage":"63","endPage":"90","ipdsId":"IP-079316","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Rafael","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.51884460449217,\n 37.97786403627176\n ],\n [\n -122.51609802246092,\n 37.97786403627176\n ],\n [\n -122.51609802246092,\n 37.979555414681506\n ],\n [\n -122.51884460449217,\n 37.979555414681506\n ],\n [\n -122.51884460449217,\n 37.97786403627176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"58e35f7fe4b09da67997ecad","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":688076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":688077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Charles L. II 0000-0002-1913-555X cpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-1913-555X","contributorId":3243,"corporation":false,"usgs":true,"family":"Powell","given":"Charles","suffix":"II","email":"cpowell@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":688078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bieling, David G","contributorId":190292,"corporation":false,"usgs":false,"family":"Bieling","given":"David","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":688079,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169357,"text":"sir20165036 - 2016 - Flood-inundation maps for the East Fork White River at Shoals, Indiana","interactions":[],"lastModifiedDate":"2016-05-18T09:55:41","indexId":"sir20165036","displayToPublicDate":"2016-05-06T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5036","title":"Flood-inundation maps for the East Fork White River at Shoals, Indiana","docAbstract":"Digital flood-inundation maps for a 5.9-mile reach of the East Fork White River at Shoals, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the East Fork White River at Shoals, Ind. (USGS station number 03373500). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS AHPS site SHLI3). NWS AHPS forecast peak stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
Flood profiles were computed for the East Fork White River reach by means of a one-dimensional, step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating no. 43.0) at USGS streamgage 03373500, East Fork White River at Shoals, Ind. The calibrated hydraulic model was then used to compute 26 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (10 ft) to the highest stage of the current stage-discharge rating curve (35 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM), derived from light detection and ranging (lidar) data, to delineate the area flooded at each water level. The areal extent of the 24-ft flood-inundation map was verified with photographs from a flood event on July 20, 2015.
The availability of these maps, along with information on the Internet regarding current stage from the USGS streamgage at East Fork White River at Shoals, Ind., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
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U.S. Geological Survey
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Hydrologic and hydraulic analyses were done for selected reaches of five streams in and near Shelby, Richland County, Ohio. The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, conducted these analyses on the Black Fork Mohican River and four tributaries: Seltzer Park Creek, Seltzer Park Tributary, Tuby Run, and West Branch. Drainage areas of the four stream reaches studied range from 0.51 to 60.3 square miles. The analyses included estimation of the 10-, 2-, 1-, and 0.2-percent annual-exceedance probability (AEP) flood-peak discharges using the USGS Ohio StreamStats application. Peak discharge estimates, along with cross-sectional and hydraulic structure geometries, and estimates of channel roughness coefficients were used as input to step-backwater models. The step-backwater water models were used to determine water-surface elevation profiles of four flood-peak discharges and a regulatory floodway. This study involved the installation of, and data collection at, a streamflow-gaging station (Black Fork Mohican River at Shelby, Ohio, 03129197), precipitation gage (Rain gage at Reservoir Number Two at Shelby, Ohio, 405209082393200), and seven submersible pressure transducers on six selected river reaches. Two precipitation-runoff models, one for the winter events and one for nonwinter events for the headwaters of the Black Fork Mohican River, were developed and calibrated using the data collected. With the exception of the runoff curve numbers, all other parameters used in the two precipitation-runoff models were identical. The Nash-Sutcliffe model efficiency coefficients were 0.737, 0.899, and 0.544 for the nonwinter events and 0.850 and 0.671 for the winter events. Both of the precipitation-runoff models underestimated the total volume of water, with residual runoff ranging from -0.27 inches to -1.53 inches. The results of this study can be used to assess possible mitigation options and define flood hazard areas that will contribute to the protection of life and property. This study could also assist emergency managers, community officials, and residents in determining when flooding may occur and planning evacuation routes during a flood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155187","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District","usgsCitation":"Huitger, C.A, Ostheimer, C.J., and Koltun, G.F., 2016, Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio: U.S. Geological Survey Scientific Investigations Report 2015–5187, 39 p., 2 appendixes, https://dx.doi.org/10.3133/sir20155187.","productDescription":"Report: vi, 39 p.; 5 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060945","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":320916,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-1.csv","text":"Appendix 1 - Table 1-1","size":"84.1 KB csv","description":"SIR 2015-5187"},{"id":320915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5187/sir20155187.pdf","text":"Report","size":"1.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5187"},{"id":320917,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-2.csv","text":"Appendix 1 - Table 1-2","size":"62 KB csv","description":"SIR 2015-5187"},{"id":320914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5187/coverthb.jpg"},{"id":320919,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-4.csv","text":"Appendix 1 - Table 1-4","size":"50 KB csv","description":"SIR 2015-5187"},{"id":320918,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-3.csv","text":"Appendix 1 - Table 1-3","size":"19 KB csv","description":"SIR 2015-5187"},{"id":320920,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-5.csv","text":"Appendix 1 - Table 1-5","size":"22 KB csv","description":"SIR 2015-5187"}],"country":"United States","state":"Ohio","city":"Shelby","otherGeospatial":"Black Fork Mohican River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.70902633666992,\n 40.83563216247778\n ],\n [\n -82.70902633666992,\n 40.91934991356069\n ],\n [\n -82.61959075927734,\n 40.91934991356069\n ],\n [\n -82.61959075927734,\n 40.83563216247778\n ],\n [\n -82.70902633666992,\n 40.83563216247778\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio Water Science Center
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Hurricane Sandy made landfall in Barnegat Bay, October, 29, 2012, damaging shorelines and infrastructure. Estuarine sediment chemistry and toxicity were investigated before and after to evaluate potential environmental health impacts and to establish post-event baseline sediment-quality conditions. Trace element concentrations increased throughout Barnegat Bay up to two orders of magnitude, especially north of Barnegat Inlet, consistent with northward redistribution of silt. Loss of organic compounds, clay, and organic carbon is consistent with sediment winnowing and transport through the inlets and sediment transportmodeling results. The number of sites exceeding sediment quality guidance levels for trace elements tripled post-Sandy. Sediment toxicity post-Sandy was mostly unaffected relative to pre-Sandy conditions, but at the site with the greatest relative increase for trace elements, survival rate of the test amphipod decreased (indicating degradation). This study would not have been possible without comprehensive baseline data enabling the evaluation of storm-derived changes in sediment quality.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.018","usgsCitation":"Romanok, K., Szabo, Z., Reilly, T.J., Defne, Z., and Ganju, N., 2016, Sediment chemistry and toxicity in Barnegat Bay, New Jersey: Pre- and post-Hurricane Sandy, 2012–13: Marine Pollution Bulletin, v. 107, no. 2, p. 472-488, https://doi.org/10.1016/j.marpolbul.2016.04.018.","productDescription":"17 p.","startPage":"472","endPage":"488","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068252","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":321463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.97894287109375,\n 39.14710270770074\n ],\n [\n -74.97894287109375,\n 40.41349604970198\n ],\n [\n -74.00390625,\n 40.41349604970198\n ],\n [\n -74.00390625,\n 39.14710270770074\n ],\n [\n -74.97894287109375,\n 39.14710270770074\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57403559e4b07e28b65e9705","contributors":{"authors":[{"text":"Romanok, Kristin M. 0000-0002-8472-8765 kromanok@usgs.gov","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":169543,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M. ","email":"kromanok@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":138827,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"preferred":true,"id":629967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":629968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":149613,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":629969,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170609,"text":"sir20165056 - 2016 - Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2016-10-24T13:54:47","indexId":"sir20165056","displayToPublicDate":"2016-05-05T18:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5056","title":"Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","docAbstract":"The U.S. Geological Survey and Idaho Department of Environmental Quality Idaho National Laboratory (INL) Oversight Program in cooperation with the U.S. Department of Energy determined background concentrations of selected chemical and radiochemical constituents in the eastern Snake River Plain aquifer to aid with ongoing cleanup efforts at the INL. Chemical and radiochemical constituents including calcium, magnesium, sodium, potassium, silica, chloride, sulfate, fluoride, bicarbonate, chromium, nitrate, tritium, strontium-90, chlorine-36, iodine-129, plutonium-238, plutonium-239, -240 (undivided), americium-241, technetium-99, uranium-234, uranium-235, and uranium-238 were selected for the background study because they were either not analyzed in earlier studies or new data became available to give a more recent determination of background concentrations. Samples of water collected from wells and springs at and near the INL that were not believed to be influenced by wastewater disposal were used to identify background concentrations. Groundwater in the eastern Snake River Plain aquifer at and near the INL was divided into two major water types (western tributary and eastern regional) based on concentrations of lithium less than and greater than 5 micrograms per liter (μg/L). Median concentrations for each constituent were used to define the upper limit of background.
\nThe upper limit of background concentrations for inorganic chemicals for western tributary water was 40.7 milligrams per liter (mg/L) for calcium, 15.3 mg/L for magnesium, 8.30 mg/L for sodium, 2.32 mg/L for potassium, 23.1 mg/L for silica, 11.8 mg/L for chloride, 21.4 mg/L for sulfate, 0.20 mg/L for fluoride, 176 mg/L for bicarbonate, 4.00 μg/L for chromium, and 0.655 mg/L for nitrate.
\nThe upper limit of background concentrations for inorganic chemicals for eastern regional water was 34.05 mg/L for calcium, 13.85 mg/L for magnesium, 14.85 mg/L for sodium, 3.22 mg/L for potassium, 31.0 mg/L for silica, 14.15 mg/L for chloride, 20.2 mg/L for sulfate, 0.4675 mg/L for fluoride, 165 mg/L for bicarbonate, 3.00 μg/L for chromium, and 0.995 mg/L for nitrate.
\nThe upper limit of background concentrations for radiochemical constituents for western tributary water was 34.15 ±2.35 picocuries per liter (pCi/L) for tritium, 0.00098 ±0.00006 pCi/L for chlorine-36, 0.000011 ±0.000005 pCi/L for iodine-129, <0.0000054 pCi/L for technetium-99, 0 pCi/L for strontium-90, plutonium-238, plutonium-239, -240 (undivided), and americium-241, 1.36 pCi/L with undetermined uncertainty for uranium-234, 0.025 ±0.001 pCi/L for uranium-235, and 0.541 ±0.001 pCi/L for uranium-238.
\nThe upper limit of background concentrations for radiochemical constituents for eastern regional water was 5.43 ±0.574 pCi/L for tritium, 0.0002048 ±0.0000054 pCi/L for chlorine-36, 0.000000865 ±0.000000015 pCi/L for iodine-129, <0.0000054 pCi/L for technetium-99, 0 pCi/L for strontium-90, plutonium-238, plutonium-239, -240 (undivided), and americium-241, 1.32 ±0.77 pCi/L for uranium-234, 0.016 ±0.012 pCi/L for uranium-235, and 0.477 ±0.044 pCi/L for uranium-238.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165056","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Bartholomay, R.C., and Hall, L.F., 2016, Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2016–5056, (DOE/ID-22237), 19 p.,\nhttps://dx.doi.org/10.3133/sir20165056.","productDescription":"Report: v, 19 p.; Appendixes A-C","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065188","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":321010,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5056 Report PDF"},{"id":321011,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixa.xlsx","text":"Appendix A","size":"36 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix A"},{"id":321009,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5056/coverthb.jpg"},{"id":321012,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixb.xlsx","text":"Appendix B","size":"75 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix B"},{"id":321013,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixc.xlsx","text":"Appendix C","size":"81 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix C"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.75,\n 44.25\n ],\n [\n -113.75,\n 43.30\n ],\n [\n -112.25,\n 43.30\n ],\n [\n -112.25,\n 44.25\n ],\n [\n -113.75,\n 44.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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A groundwater-flow model was developed to improve understanding of water resources on the Kitsap Peninsula. The Kitsap Peninsula is in the Puget Sound lowland of west-central Washington, is bounded by Puget Sound on the east and by Hood Canal on the west, and covers an area of about 575 square miles. The peninsula encompasses all of Kitsap County, Mason County north of Hood Canal, and part of Pierce County west of Puget Sound. The peninsula is surrounded by saltwater, and the hydrologic setting is similar to that of an island. The study area is underlain by a thick sequence of unconsolidated glacial and interglacial deposits that overlie sedimentary and volcanic bedrock units that crop out in the central part of the study area. Twelve hydrogeologic units consisting of aquifers, confining units, and an underlying bedrock unit form the basis of the groundwater-flow model.
Groundwater flow on the Kitsap Peninsula was simulated using the groundwater-flow model, MODFLOW‑NWT. The finite difference model grid comprises 536 rows, 362 columns, and 14 layers. Each model cell has a horizontal dimension of 500 by 500 feet, and the model contains a total of 1,227,772 active cells. Groundwater flow was simulated for transient conditions. Transient conditions were simulated for January 1985–December 2012 using annual stress periods for 1985–2004 and monthly stress periods for 2005–2012. During model calibration, variables were adjusted within probable ranges to minimize differences between measured and simulated groundwater levels and stream baseflows. As calibrated to transient conditions, the model has a standard deviation for heads and flows of 47.04 feet and 2.46 cubic feet per second, respectively.
Simulated inflow to the model area for the 2005–2012 period from precipitation and secondary recharge was 585,323 acre-feet per year (acre-ft/yr) (93 percent of total simulated inflow ignoring changes in storage), and simulated inflow from stream and lake leakage was 43,905 acre-ft/yr (7 percent of total simulated inflow). Simulated outflow from the model primarily was through discharge to streams, lakes, springs, seeps, and Puget Sound (594,595 acre-ft/yr; 95 percent of total simulated outflow excluding changes in storage) and through withdrawals from wells (30,761 acre-ft/yr; 5 percent of total simulated outflow excluding changes in storage).
Six scenarios were formulated with input from project stakeholders and were simulated using the calibrated model to provide representative examples of how the model could be used to evaluate the effects on water levels and stream baseflows of potential changes in groundwater withdrawals, in consumptive use, and in recharge. These included simulations of a steady-state system, no-pumping and return flows, 15-percent increase in current withdrawals in all wells, 80-percent decrease in outdoor water to simulate effects of conservation efforts, 15-percent decrease in recharge from precipitation to simulate a drought, and particle tracking to determine flow paths.
Changes in water-level altitudes and baseflow amounts vary depending on the stress applied to the system in these various scenarios. Reducing recharge by 15 percent between 2005 and 2012 had the largest effect, with water-level altitudes declining throughout the model domain and baseflow amounts decreasing by as much as 18 percent compared to baseline conditions. Changes in pumping volumes had a smaller effect on the model. Removing all pumping and resulting return flows caused increased water-level altitudes in many areas and increased baseflow amounts of between 1 and 3 percent.
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Streams and adjacent terrestrial ecosystems are characterized by permeable boundaries that are crossed by resource subsidies. Although the importance of these subsidies for riverine ecosystems is increasingly recognized, little is known about how they may be influenced by global environmental change. Drawing from available evidence, in this review we propose a conceptual framework to evaluate the effects of global change on the quality and spatiotemporal dynamics of stream–terrestrial subsidies. We illustrate how changes to hydrological and temperature regimes, atmospheric CO2 concentration, land use and the distribution of nonindigenous species can influence subsidy fluxes by affecting the biology and ecology of donor and recipient systems and the physical characteristics of stream–riparian boundaries. Climate-driven changes in the physiology and phenology of organisms with complex life cycles will influence their development time, body size and emergence patterns, with consequences for adjacent terrestrial consumers. Also, novel species interactions can modify subsidy dynamics via complex bottom-up and top-down effects. Given the seasonality and pulsed nature of subsidies, alterations of the temporal and spatial synchrony of resource availability to consumers across ecosystems are likely to result in ecological mismatches that can scale up from individual responses, to communities, to ecosystems. Similarly, altered hydrology, temperature, CO2 concentration and land use will modify the recruitment and quality of riparian vegetation, the timing of leaf abscission and the establishment of invasive riparian species. Along with morphological changes to stream–terrestrial boundaries, these will alter the use and fluxes of allochthonous subsidies associated with stream ecosystems. Future research should aim to understand how subsidy dynamics will be affected by key drivers of global change, including agricultural intensification, increasing water use and biotic homogenization. Our conceptual framework based on the match–mismatch between donor and recipient organisms may facilitate understanding of the multiple effects of global change and aid in the development of future research questions.
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\"}}]}","volume":"563-564","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572c609ae4b09acee752ef84","contributors":{"authors":[{"text":"Haack, Sheridan K. skhaack@usgs.gov","contributorId":1982,"corporation":false,"usgs":true,"family":"Haack","given":"Sheridan","email":"skhaack@usgs.gov","middleInitial":"K.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duris, Joseph W. jwduris@usgs.gov","contributorId":169110,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph W.","email":"jwduris@usgs.gov","affiliations":[],"preferred":false,"id":628464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":628466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":628467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Heather E.","contributorId":207837,"corporation":false,"usgs":false,"family":"Johnson","given":"Heather E.","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":744847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Oster, Ryan J. roster@usgs.gov","contributorId":5483,"corporation":false,"usgs":true,"family":"Oster","given":"Ryan","email":"roster@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":628470,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170861,"text":"70170861 - 2016 - Modeling suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in North and South America’s coastal waters","interactions":[],"lastModifiedDate":"2016-07-07T10:09:23","indexId":"70170861","displayToPublicDate":"2016-05-05T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in North and South America’s coastal waters","docAbstract":"We used two common correlative species-distribution models to predict suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in the western Atlantic and eastern Pacific Oceans. The Generalized Linear Model (GLM) and the Maximum Entropy (Maxent) model were applied using the Software for Assisted Habitat Modeling. We compared models developed using native occurrences, using non-native occurrences, and using both native and non-native occurrences. Models were trained using occurrence data collected before 2010 and evaluated with occurrence data collected from the invaded range during or after 2010. We considered a total of 22 marine environmental variables. Models built with non-native only or both native and non-native occurrence data outperformed those that used only native occurrences. Evaluation metrics based on the independent test data were highest for models that used both native and non-native occurrences. Bathymetry was the strongest environmental predictor for all models and showed increasing suitability as ocean floor depth decreased, with salinity ranking the second strongest predictor for models that used native and both native and non-native occurrences, indicating low habitat suitability for salinities <30. Our model results also suggest that red lionfish could continue to invade southern latitudes in the western Atlantic Ocean and may establish localized populations in the eastern Pacific Ocean. We reiterate the importance in the choice of the training data source (native, non-native, or native/non-native) used to develop correlative species distribution models for invasive species.
\nIt is commonly recognized that suspended-sediment concentrations in rivers can change rapidly in time and independently of water discharge during important sediment‑transporting events (for example, during floods); thus, suspended-sediment measurements at closely spaced time intervals are necessary to characterize suspended‑sediment loads. Because the manual collection of sufficient numbers of suspended-sediment samples required to characterize this variability is often time and cost prohibitive, several “surrogate” techniques have been developed for in situ measurements of properties related to suspended-sediment characteristics (for example, turbidity, laser-diffraction, acoustics). Herein, we present a new physically based method for the simultaneous measurement of suspended-silt-and-clay concentration, suspended-sand concentration, and suspended‑sand median grain size in rivers, using multi‑frequency arrays of single-frequency side‑looking acoustic-Doppler profilers. The method is strongly grounded in the extensive scientific literature on the incoherent scattering of sound by random suspensions of small particles. In particular, the method takes advantage of theory that relates acoustic frequency, acoustic attenuation, acoustic backscatter, suspended-sediment concentration, and suspended-sediment grain-size distribution. We develop the theory and methods, and demonstrate the application of the method at six study sites on the Colorado River and Rio Grande, where large numbers of suspended-sediment samples have been collected concurrently with acoustic attenuation and backscatter measurements over many years. The method produces acoustical measurements of suspended-silt-and-clay and suspended-sand concentration (in units of mg/L), and acoustical measurements of suspended-sand median grain size (in units of mm) that are generally in good to excellent agreement with concurrent physical measurements of these quantities in the river cross sections at these sites. In addition, detailed, step-by-step procedures are presented for the general river application of the method.
Quantification of errors in sediment-transport measurements made using this acoustical method is essential if the measurements are to be used effectively, for example, to evaluate uncertainty in long-term sediment loads and budgets. Several types of error analyses are presented to evaluate (1) the stability of acoustical calibrations over time, (2) the effect of neglecting backscatter from silt and clay, (3) the bias arising from changes in sand grain size, (4) the time-varying error in the method, and (5) the influence of nonrandom processes on error. Results indicate that (1) acoustical calibrations can be stable for long durations (multiple years), (2) neglecting backscatter from silt and clay can result in unacceptably high bias, (3) two frequencies are likely required to obtain sand-concentration measurements that are unbiased by changes in grain size, depending on site-specific conditions and acoustic frequency, (4) relative errors in silt-and-clay- and sand-concentration measurements decrease substantially as concentration increases, and (5) nonrandom errors may arise from slow changes in the spatial structure of suspended sediment that affect the relations between concentration in the acoustically ensonified part of the cross section and concentration in the entire river cross section. Taken together, the error analyses indicate that the two-frequency method produces unbiased measurements of suspended-silt-and-clay and sand concentration, with errors that are similar to, or larger than, those associated with conventional sampling methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1823","usgsCitation":"Topping, D.J., and Wright, S.A., 2016, Long-term continuous acoustical suspended-sediment measurements in rivers—Theory, application, bias, and error: U.S. Geological Survey Professional Paper 1823, 98 p.,\nhttps://dx.doi.org/10.3133/pp1823.","productDescription":"xii, 97 p.","numberOfPages":"114","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062803","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":320792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1823/coverthb.jpg"},{"id":320827,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1823/pp1823.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1823 Report PDF"}],"country":"United States","state":"Arizona, Texas","otherGeospatial":"Colorado River, Grand Canyon National Park; Rio Grande, Big Bend National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5384521484375,\n 36.01578220325809\n ],\n [\n -112.5384521484375,\n 36.41907231092499\n ],\n [\n -111.86553955078124,\n 36.41907231092499\n ],\n [\n -111.86553955078124,\n 36.01578220325809\n ],\n [\n -112.5384521484375,\n 36.01578220325809\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.76174926757812,\n 28.96489485992114\n ],\n [\n -103.76174926757812,\n 29.410890376109\n ],\n [\n -102.82241821289062,\n 29.410890376109\n ],\n [\n -102.82241821289062,\n 28.96489485992114\n ],\n [\n -103.76174926757812,\n 28.96489485992114\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f7","contributors":{"authors":[{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":715,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":626542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626543,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169399,"text":"ofr20161054 - 2016 - Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","interactions":[],"lastModifiedDate":"2016-05-04T15:49:10","indexId":"ofr20161054","displayToPublicDate":"2016-05-04T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1054","title":"Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","docAbstract":"
The Storm 3 is a browser-based data logger manufactured by WaterLOG/Xylem Incorporated that operates over a temperature range of −40 to 60 degrees Celsius (°C). A Storm logger with no built-in telemetry (Storm3-00) and a logger with built-in cellular modem (Storm3-03) were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to the manufacturer’s specifications with bench tests, for recording data over the device’s operating temperature range with temperature chamber tests, and for field performance with an outdoor deployment test.
\nThe procedures followed and the results obtained from the testing are described in this publication. The device met most of the manufacturer’s stated specifications. An exception was power consumption, which was about 10 percent above the manufacturer’s specifications. It was also observed that enabling WiFi doubles the Storm 3’s power consumption. In addition, several logging errors were made by two units during deployment testing, but it could not be determined whether these errors were the fault of the Storm or of an attached sensor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161054","usgsCitation":"Kunkle, G.A., 2016, Evaluation of the Storm 3 data logger manufactured by Waterlog/Xylem Incorporated—Results of Bench, Temperature, and Field Deployment Testing: U.S. Geological Survey Open-File Report 2016–1054, 9 p., https://dx.doi.org/10.3133/ofr20161054.","productDescription":"iii, 9 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069059","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":320970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1054/ofr20161054.pdf","text":"Report","size":"373 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1054"},{"id":320969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1054/coverthb.jpg","description":"OFR 2016-1054"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
Although initially viewed as oases within a barren deep ocean, hydrothermal vent and methane seep communities are now recognized to interact with surrounding ecosystems on the sea floor and in the water column, and to affect global geochemical cycles. The importance of understanding these interactions is growing as the potential rises for disturbance from oil and gas extraction, seabed mining and bottom trawling. Here we synthesize current knowledge of the nature, extent and time and space scales of vent and seep interactions with background systems. We document an expanded footprint beyond the site of local venting or seepage with respect to elemental cycling and energy flux, habitat use, trophic interactions, and connectivity. Heat and energy are released, global biogeochemical and elemental cycles are modified, and particulates are transported widely in plumes. Hard and biotic substrates produced at vents and seeps are used by “benthic background” fauna for attachment substrata, shelter, and access to food via grazing or through position in the current, while particulates and fluid fluxes modify planktonic microbial communities. Chemosynthetic production provides nutrition to a host of benthic and planktonic heterotrophic background species through multiple horizontal and vertical transfer pathways assisted by flow, gamete release, animal movements, and succession, but these pathways remain poorly known. Shared species, genera and families indicate that ecological and evolutionary connectivity exists among vents, seeps, organic falls and background communities in the deep sea; the genetic linkages with inactive vents and seeps and background assemblages however, are practically unstudied. The waning of venting or seepage activity generates major transitions in space and time that create links to surrounding ecosystems, often with identifiable ecotones or successional stages. The nature of all these interactions is dependent on water depth, as well as regional oceanography and biodiversity. Many ecosystem services are associated with the interactions and transitions between chemosynthetic and background ecosystems, for example carbon cycling and sequestration, fisheries production, and a host of non-market and cultural services. The quantification of the sphere of influence of vents and seeps could be beneficial to better management of deep-sea environments in the face of growing industrialization.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2016.00072","usgsCitation":"Levin, L.A., Baco, A., Bowden, D., Colaco, A., Cordes, E.E., Cunha, M., Demopoulos, A.W., Gobin, J., Grupe, B., Le, J., Metaxas, A., Netburn, A., Rouse, G., Thurber, A., Tunnicliffe, V., Van Dover, C., Vanreusel, A., and Watling, L., 2016, Hydrothermal vents and methane seeps: Rethinking the sphere of influence: Frontiers in Marine Science, v. 3, art72: 23 p., https://doi.org/10.3389/fmars.2016.00072.","productDescription":"art72: 23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073011","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471022,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2016.00072","text":"Publisher Index Page"},{"id":320952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-19","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f4","contributors":{"authors":[{"text":"Levin, Lisa A.","contributorId":12372,"corporation":false,"usgs":true,"family":"Levin","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":628684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baco, Amy","contributorId":120023,"corporation":false,"usgs":true,"family":"Baco","given":"Amy","email":"","affiliations":[],"preferred":false,"id":628685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowden, David","contributorId":10864,"corporation":false,"usgs":true,"family":"Bowden","given":"David","email":"","affiliations":[],"preferred":false,"id":628686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colaco, Ana","contributorId":169152,"corporation":false,"usgs":false,"family":"Colaco","given":"Ana","email":"","affiliations":[{"id":25423,"text":"Univ. of the Azores","active":true,"usgs":false}],"preferred":false,"id":628687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":628688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cunha, Marina","contributorId":169153,"corporation":false,"usgs":false,"family":"Cunha","given":"Marina","email":"","affiliations":[{"id":25424,"text":"Univ. de Aveiro","active":true,"usgs":false}],"preferred":false,"id":628689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":628683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gobin, Judith","contributorId":169154,"corporation":false,"usgs":false,"family":"Gobin","given":"Judith","email":"","affiliations":[{"id":25425,"text":"Univ. West Indies","active":true,"usgs":false}],"preferred":false,"id":628690,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grupe, Ben","contributorId":169155,"corporation":false,"usgs":false,"family":"Grupe","given":"Ben","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628691,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Le, Jennifer","contributorId":169163,"corporation":false,"usgs":false,"family":"Le","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":628692,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Metaxas, Anna","contributorId":169156,"corporation":false,"usgs":false,"family":"Metaxas","given":"Anna","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":628693,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Netburn, Amanda","contributorId":169157,"corporation":false,"usgs":false,"family":"Netburn","given":"Amanda","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628694,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rouse, Greg","contributorId":169158,"corporation":false,"usgs":false,"family":"Rouse","given":"Greg","email":"","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628695,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thurber, Andrew","contributorId":169159,"corporation":false,"usgs":false,"family":"Thurber","given":"Andrew","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":628696,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tunnicliffe, Verena","contributorId":169160,"corporation":false,"usgs":false,"family":"Tunnicliffe","given":"Verena","email":"","affiliations":[{"id":25427,"text":"Univ. of Victoria","active":true,"usgs":false}],"preferred":false,"id":628697,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Van Dover, Cindy L.","contributorId":95341,"corporation":false,"usgs":true,"family":"Van Dover","given":"Cindy L.","affiliations":[],"preferred":false,"id":628698,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vanreusel, Ann","contributorId":169161,"corporation":false,"usgs":false,"family":"Vanreusel","given":"Ann","email":"","affiliations":[{"id":25428,"text":"Ghent Univ.","active":true,"usgs":false}],"preferred":false,"id":628699,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Watling, Les","contributorId":54755,"corporation":false,"usgs":false,"family":"Watling","given":"Les","email":"","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":628714,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70170821,"text":"70170821 - 2016 - Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","interactions":[],"lastModifiedDate":"2016-07-28T10:53:13","indexId":"70170821","displayToPublicDate":"2016-05-04T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":904,"text":"Arid Land Research and Management","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","docAbstract":"Dune destabilization and increased mobility is a worldwide issue causing ecological, economic, and health problems for the inhabitants of areas with extensive dune fields. Dunes cover nearly a third of the Navajo Nation within the Colorado Plateau of southwestern USA. There, higher temperatures and prolonged drought beginning in 1996 have produced significant increases in dune mobility. Vegetation plays an important role in dune stabilization, but there are few studies of the plants of the aeolian surfaces of this region. We examined plant species and their attributes within a moderately vegetated dune field of the Navajo Nation to understand the types and characteristics of plants that stabilize rangeland dunes. These dunes supported a low cover of mixed grass-scrubland with fifty-two perennial and annual species including extensive occurrence of non-native annual Salsola spp. Perennial grass richness and shrub cover were positively associated with increased soil sand composition. Taprooted shrubs were more common on sandier substrates. Most dominant grasses had C4 photosynthesis, suggestive of higher water-use efficiencies and growth advantage in warm arid environments. Plant cover was commonly below the threshold of dune stabilization. Increasing sand movement with continued aridity will select for plants adapted to burial, deflation, and abrasion. The study indicates plants tolerant of increased sand mobility and burial but more investigation is needed to identify the plants adapted to establish and regenerate under these conditions. In addition, the role of Salsola spp. in promoting decline of perennial grasses and shrubs needs clarification.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2016.1138157","usgsCitation":"Thomas, K.A., and Redsteer, M.H., 2016, Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA: Arid Land Research and Management, v. 30, no. 4, p. 400-411, https://doi.org/10.1080/15324982.2016.1138157.","productDescription":"12 p.","startPage":"400","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063167","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":502595,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":320950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Navajo Nation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.3134765625,\n 34.56085936708387\n ],\n [\n -111.3134765625,\n 38.22091976683121\n ],\n [\n -107.29248046875,\n 38.22091976683121\n ],\n [\n -107.29248046875,\n 34.56085936708387\n ],\n [\n -111.3134765625,\n 34.56085936708387\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"572b0f1ce4b0b13d391a8407","contributors":{"authors":[{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Redsteer, Margaret H.","contributorId":9123,"corporation":false,"usgs":true,"family":"Redsteer","given":"Margaret","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":628555,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170814,"text":"70170814 - 2016 - Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","interactions":[],"lastModifiedDate":"2016-05-04T10:03:24","indexId":"70170814","displayToPublicDate":"2016-05-04T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","docAbstract":"Estuarine navigation channels have long been recognized as conduits for saltwater intrusion into coastal wetlands. Salt flux decomposition and time series measurements of velocity and salinity were used to examine salt flux components and drivers of baroclinic and barotropic exchange in the Houma Navigation Channel, an estuarine channel located in the Mississippi River delta plain that receives substantial freshwater inputs from the Mississippi-Atchafalaya River system at its inland extent. Two modes of vertical current structure were identified from the time series data. The first mode, accounting for 90% of the total flow field variability, strongly resembled a barotropic current structure and was coherent with alongshelf wind stress over the coastal Gulf of Mexico. The second mode was indicative of gravitational circulation and was linked to variability in tidal stirring and the horizontal salinity gradient along the channel’s length. Tidal oscillatory salt flux was more important than gravitational circulation in transporting salt upestuary, except over equatorial phases of the fortnightly tidal cycle during times when river inflows were minimal. During all tidal cycles sampled, the advective flux, driven by a combination of freshwater discharge and wind-driven changes in storage, was the dominant transport term, and net flux of salt was always out of the estuary. These findings indicate that although human-made channels can effectively facilitate inland intrusion of saline water, this intrusion can be minimized or even reversed when they are subject to significant freshwater inputs.
","language":"English","publisher":"MDPI","doi":"10.3390/w8050184","usgsCitation":"Snedden, G., 2016, Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain: Water, v. 8, no. 5, Article 184: 15 p., https://doi.org/10.3390/w8050184.","productDescription":"Article 184: 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069649","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8050184","text":"Publisher Index Page"},{"id":320948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Houma Navigation Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.74844360351562,\n 29.216904948184734\n ],\n [\n -90.74844360351562,\n 29.58898286696141\n ],\n [\n -90.604248046875,\n 29.58898286696141\n ],\n [\n -90.604248046875,\n 29.216904948184734\n ],\n [\n -90.74844360351562,\n 29.216904948184734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-30","publicationStatus":"PW","scienceBaseUri":"572b0f19e4b0b13d391a83ec","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":140235,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":628526,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170954,"text":"70170954 - 2016 - Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","interactions":[],"lastModifiedDate":"2016-05-13T09:18:39","indexId":"70170954","displayToPublicDate":"2016-05-04T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","docAbstract":"Most research on the effects of wildfires on stream water quality has focused on suspended sediment and nutrients in streams and water bodies, and relatively little research has examined the effects of wildfires on trace elements. The purpose of this study was two-fold: 1) to determine the effect of the 2009 Station Fire in the Angeles National Forest northeast of Los Angeles, CA on trace element concentrations in streams, and 2) compare trace elements in post-fire stormflow water quality to criteria for aquatic life to determine if trace elements reached concentrations that can harm aquatic life. Pre-storm and stormflow water-quality samples were collected in streams located inside and outside of the burn area of the Station Fire. Ash and burned soil samples were collected from several locations within the perimeter of the Station Fire. Filtered concentrations of Fe, Mn, and Hg and total concentrations of most trace elements in storm samples were elevated as a result of the Station Fire. In contrast, filtered concentrations of Cu, Pb, Ni, and Se and total concentrations of Cu were elevated primarily due to storms and not the Station Fire. Total concentrations of Se and Zn were elevated as a result of both storms and the Station Fire. Suspended sediment in stormflows following the Station Fire was an important transport mechanism for trace elements. Cu, Pb, and Zn primarily originate from ash in the suspended sediment. Fe primarily originates from burned soil in the suspended sediment. As, Mn, and Ni originate from both ash and burned soil. Filtered concentrations of trace elements in stormwater samples affected by the Station Fire did not reach levels that were greater than criteria established for aquatic life. Total concentrations for Fe, Pb, Ni, and Zn were detected at concentrations above criteria established for aquatic life.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0153372","collaboration":"Amphibian Research and Monitoring Initiative (BRD) Mineral Resources Program (USGS)","usgsCitation":"Burton, C.A., Hoefen, T.M., Plumlee, G.S., Baumberger, K., Backlin, A.R., Gallegos, E., and Fisher, R.N., 2016, Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California: PLoS ONE, v. 11, no. 5, https://doi.org/10.1371/journal.pone.0153372.","productDescription":"26 p.","startPage":"e0153372","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0153372","text":"Publisher Index Page"},{"id":321203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321176,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1371/journal.pone.0153372."}],"country":"United States","state":"California","otherGeospatial":"Angeles National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.466667,\n 34.625\n ],\n [\n -118.466667,\n 34.125\n ],\n [\n -117.6875,\n 34.125\n ],\n [\n -117.6875,\n 34.625\n ],\n [\n -118.466667,\n 34.625\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"5736fae1e4b0dae0d5e03ebb","contributors":{"authors":[{"text":"Burton, Carmen A. 0000-0002-6381-8833 caburton@usgs.gov","orcid":"https://orcid.org/0000-0002-6381-8833","contributorId":444,"corporation":false,"usgs":true,"family":"Burton","given":"Carmen","email":"caburton@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626 gplumlee@usgs.gov","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":960,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"gplumlee@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":629207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baumberger, Katherine L. kbaumberger@usgs.gov","contributorId":5870,"corporation":false,"usgs":true,"family":"Baumberger","given":"Katherine L.","email":"kbaumberger@usgs.gov","affiliations":[],"preferred":true,"id":629208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gallegos, Elizabeth 0000-0002-8402-2631 egallegos@usgs.gov","orcid":"https://orcid.org/0000-0002-8402-2631","contributorId":1528,"corporation":false,"usgs":true,"family":"Gallegos","given":"Elizabeth","email":"egallegos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629210,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629211,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170139,"text":"sir20165046 - 2016 - Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","interactions":[],"lastModifiedDate":"2021-10-12T17:00:16.258141","indexId":"sir20165046","displayToPublicDate":"2016-05-04T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5046","title":"Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","docAbstract":"The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.
The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.
The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165046","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Wood, T.M., Wherry, S.A., Piccolroaz, S., and Girdner, S.F., 2016, Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099: U.S. Geological Survey Scientific Investigations Report 2016–5046, 43 p. https://doi.org/10.3133/sir20165046","productDescription":"vii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066051","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":320860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5046/sir20165046.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-5046 Report PDF"},{"id":320859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5046/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.18616485595703,\n 42.892567248047285\n ],\n [\n -122.18616485595703,\n 42.986065036562955\n ],\n [\n -122.03922271728514,\n 42.986065036562955\n ],\n [\n -122.03922271728514,\n 42.892567248047285\n ],\n [\n -122.18616485595703,\n 42.892567248047285\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: February 2020; Version 1.0: October 2016","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
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http://or.water.usgs.gov
During July 2015, water samples were collected from 18 wetlands on the Lake Traverse Indian Reservation in northeastern South Dakota and southeastern North Dakota and analyzed for physical properties and 54 pesticides. This study by the U.S. Geological Survey in cooperation with the Sisseton-Wahpeton Oyate was designed to provide an update on pesticide concentrations of the same 18 wetlands that were sampled for a reconnaissance-level assessment during July 2006. The purpose of this report is to present the results of the assessment of pesticide concentrations in selected Lake Traverse Indian Reservation wetlands during July 2015 and provide a comparison of pesticide concentrations between 2006 and 2015.
Of the 54 pesticides that were analyzed for in the samples collected during July 2015, 47 pesticides were not detected in any samples. Seven pesticides—2-chloro-4-isopropylamino-6-amino-s-triazine (CIAT); 2,4–D; acetachlor; atrazine; glyphosate; metolachlor; and prometon—were detected in the 2015 samples with estimated concentrations or concentrations greater than the laboratory reporting level, and most pesticides were detected at low concentrations in only a few samples. Samples from all wetlands contained at least one detected pesticide. The maximum number of pesticides detected in a wetland sample was six, and the median number of pesticides detected was three.
The most commonly detected pesticides in the 2015 samples were atrazine and the atrazine degradate CIAT (also known as deethylatrazine), which were detected in 14 and 13 of the wetlands sampled, respectively. Glyphosate was detected in samples from 11 wetlands, and metolachlor was detected in samples from 10 wetlands. The other detected pesticides were 2,4–D (4 wetlands), acetochlor (3 wetlands), and prometon (1 wetland).
The same pesticides that were detected in the 2006 samples were detected in the 2015 samples, with the exception of simazine, which was detected only in one sample in 2006. Atrazine and CIAT were the most commonly detected pesticides in both sampling years; however, atrazine and CIAT were detected in fewer wetlands in 2015 (14 and 13 wetlands, respectively) than in 2006 (17 wetlands for both pesticides). The pesticides 2,4–D and prometon also were detected in fewer wetlands in 2015 than 2006, and simazine was only detected in 2006. In contrast, acetochlor, glyphosate, and metolachlor were detected in samples from more wetlands in 2015 than in 2006. In samples from individual wetlands, the number of pesticides detected was similar between 2006 and 2015. At least one pesticide was detected in all wetlands in 2015, and all but one wetland had pesticide detections in 2006.
Concentrations of pesticides detected in samples from wetlands were compared to selected water-quality (human-health and aquatic-life) benchmarks. None of the concentrations in either 2006 or 2015 were greater than water-quality benchmarks, with the exception of atrazine. All detections of atrazine in the 2006 and 2015 samples were greater than the acute benchmark of 0.001 microgram per liter (μg/L) for vascular plants. In addition, some concentrations of 2,4–D and atrazine were within an order of magnitude of a water-quality benchmark. The 2,4–D concentrations in the 2015 samples from three wetlands were within an order of magnitude of the U.S. Environmental Protection Agency’s Maximum Contaminant Level of 70 μg/L (that is, sample concentrations were greater than 7.0 μg/L). The maximum dissolved atrazine concentration of 0.185 μg/L in the 2015 samples along with the concentrations in 2006 samples from two wetlands were within an order of magnitude of the acute benchmark of less than 1 μg/L for nonvascular plants (that is, concentrations were greater than 0.1 μg/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds984","collaboration":"Prepared in cooperation with the Sisseton-Wahpeton Oyate","usgsCitation":"Carter, J.M., and Thompson, R.F., 2016, Pesticide concentrations in wetlands on the Lake Traverse Indian Reservation, South and North Dakota, July 2015: U.S. Geological Survey Data Series Report 984, 32 p., https://dx.doi.org/10.3133/ds984.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072207","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":320926,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0984/coverthb.jpg"},{"id":320927,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0984/ds984.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 984"}],"country":"United States","state":"North Dakota, South Dakota","otherGeospatial":"Lake Traverse Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.56021118164062,\n 45.93778073466329\n ],\n [\n -97.5146484375,\n 46.02462129598765\n ],\n [\n -97.18505859374999,\n 44.97645666320777\n ],\n [\n -96.85272216796875,\n 45.60058738537025\n ],\n [\n -96.85684204101562,\n 45.622682153628226\n ],\n [\n -96.84173583984374,\n 45.64188792039229\n ],\n [\n -96.78543090820312,\n 45.68123916702059\n ],\n [\n -96.70989990234374,\n 45.71864517367924\n ],\n [\n -96.66320800781249,\n 45.74261022090537\n ],\n [\n -96.61102294921875,\n 45.79625461321962\n ],\n [\n -96.5753173828125,\n 45.84602106744846\n ],\n [\n -96.56021118164062,\n 45.93778073466329\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
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1608 Mountain View Road
Rapid City, South Dakota 57702
The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (kharif) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second (rabi) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.
","language":"English","doi":"10.1080/17538947.2016.1168489","usgsCitation":"Gumma, M., Thenkabail, P.S., Teluguntla, P.G., Rao, M.N., Mohammed, I., and Whitbread, A.M., 2016, Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data: International Journal of Digital Earth, v. 9, no. 10, p. 981-1003, https://doi.org/10.1080/17538947.2016.1168489.","productDescription":"23 p.","startPage":"981","endPage":"1003","ipdsId":"IP-070335","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2016.1168489","text":"Publisher Index Page"},{"id":330906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bangladesh, Bhutan, India, Nepal, Pakistan, Sri Lanka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 83.97949218750001,\n 15.284185114076433\n ],\n [\n 82.3095703125,\n 11.996338401936226\n ],\n [\n 83.32031250000001,\n 7.754537346539373\n ],\n [\n 81.78222656250001,\n 5.266007882805485\n ],\n [\n 79.365234375,\n 5.747174076651375\n ],\n [\n 76.81640625,\n 7.406047717076271\n ],\n [\n 72.59765625,\n 12.382928338487396\n ],\n [\n 66.4013671875,\n 25.64152637306577\n ],\n [\n 80.4638671875,\n 29.11377539511439\n ],\n [\n 95.61523437500003,\n 30.34192736497245\n ],\n [\n 91.62597656250001,\n 20.67390526467282\n ],\n [\n 83.97949218750001,\n 15.284185114076433\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"582443f5e4b09065cdf30528","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":653404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":653407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Irshad A.","contributorId":176755,"corporation":false,"usgs":false,"family":"Mohammed","given":"Irshad A.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitbread, Anthony M.","contributorId":176756,"corporation":false,"usgs":false,"family":"Whitbread","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653409,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70173933,"text":"70173933 - 2016 - Long-term trends in a Dimictic Lake","interactions":[],"lastModifiedDate":"2016-06-22T13:17:08","indexId":"70173933","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in a Dimictic Lake","docAbstract":"The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.
","language":"English","publisher":"Copernicus Publications","publisherLocation":"Göttingen, Germany","doi":"10.5194/hess-20-1681-2016","usgsCitation":"Robertson, D.M., Hsieh, Y., Lathrop, R.C., Wu, C.H., Magee, M., and Hamilton, D., 2016, Long-term trends in a Dimictic Lake: Hydrology and Earth System Sciences, v. 20, p. 1681-1702, https://doi.org/10.5194/hess-20-1681-2016.","productDescription":"22 p.","startPage":"1681","endPage":"1702","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065196","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471027,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-1681-2016","text":"Publisher Index Page"},{"id":324224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane","otherGeospatial":"Lake 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