In 2010, in cooperation with the Mining and Minerals Division (MMD) of the State of New Mexico Energy, Minerals and Natural Resources Department, the U.S. Geological Survey (USGS) initiated a 4-year assessment of hydrologic conditions at the San Juan coal mine (SJCM), located about 14 miles west-northwest of the city of Farmington, San Juan County, New Mexico. The mine produces coal for power generation at the adjacent San Juan Generating Station (SJGS) and stores coal-combustion byproducts from the SJGS in mined-out surface-mining pits. The purpose of the hydrologic assessment is to identify groundwater flow paths away from SJCM coal-combustion-byproduct storage sites that might allow metals that may be leached from coal-combustion byproducts to eventually reach wells or streams after regional dewatering ceases and groundwater recovers to predevelopment levels. The hydrologic assessment, undertaken between 2010 and 2013, included compilation of existing data. The purpose of this report is to present data that were acquired and compiled by the USGS for the SJCM hydrologic assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds933","collaboration":"Prepared in cooperation with the Mining and Minerals Division of the State of New Mexico Energy, Minerals and Natural Resources Department","usgsCitation":"Stewart, A.M., and Thomas, N., 2015, Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico: U.S. Geological Survey Data Series 933, HTML Document, https://doi.org/10.3133/ds933.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059091","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":301053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds933.jpg"},{"id":301051,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0933/"},{"id":301052,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0933/ds933.html","text":"Report","size":"19 KB","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"New Mexico","county":"San Juan County","otherGeospatial":"San Juan coal mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.24623107910156,\n 36.72402574695313\n ],\n [\n -108.19747924804688,\n 36.76584198280488\n ],\n [\n -108.18168640136719,\n 36.791140738852704\n ],\n [\n -108.18168640136719,\n 36.8037869853087\n ],\n [\n -108.15284729003906,\n 36.86039455866718\n ],\n [\n -108.1391143798828,\n 36.88401445049676\n ],\n [\n -108.13156127929686,\n 36.90762703795211\n ],\n [\n -108.13499450683594,\n 36.929036787414525\n ],\n [\n -108.16932678222656,\n 36.93836736111466\n ],\n [\n -108.20091247558592,\n 36.94001381436853\n ],\n [\n -108.22288513183594,\n 36.92848789456677\n ],\n [\n -108.24829101562499,\n 36.89499795802219\n ],\n [\n -108.26133728027344,\n 36.8631414329529\n ],\n [\n -108.28125,\n 36.83346996591306\n ],\n [\n -108.3306884765625,\n 36.82797398619907\n ],\n [\n -108.39317321777344,\n 36.832370801556834\n ],\n [\n -108.48518371582031,\n 36.79718920417815\n ],\n [\n -108.49067687988281,\n 36.74328605437939\n ],\n [\n -108.29498291015624,\n 36.72017310567465\n ],\n [\n -108.24623107910156,\n 36.72402574695313\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5572ba25e4b077dba76c1b90","contributors":{"authors":[{"text":"Stewart, Anne M. astewart@usgs.gov","contributorId":3938,"corporation":false,"usgs":true,"family":"Stewart","given":"Anne","email":"astewart@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Nicole nithomas@usgs.gov","contributorId":5649,"corporation":false,"usgs":true,"family":"Thomas","given":"Nicole","email":"nithomas@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548226,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70147914,"text":"sir20155056 - 2015 - Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014","interactions":[],"lastModifiedDate":"2015-06-03T14:00:29","indexId":"sir20155056","displayToPublicDate":"2015-06-03T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5056","title":"Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014","docAbstract":"From August 28 to 29, 2011, Tropical Storm Irene delivered rainfall ranging from about 4 inches to more than 7 inches in the White River Basin. The rainfall resulted in severe flooding throughout the basin and significant damage along the White River and Tweed River. In response to the flooding, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, conducted a new flood study to aid in the flood recovery and restoration. This flood study includes a 20.7-mile reach of the White River from the downstream end at about 2,000 feet downstream from the State Route 107 bridge in the Village of Bethel, Vermont, to the upstream end at about 1,000 feet upstream from the River Brook Drive bridge in the Village of Rochester, Vt., and a 7.9-mile reach of the Tweed River from its mouth in Stockbridge, Vt., to the confluence of the West and South Branches of the Tweed River and continuing upstream on the South Branch Tweed River to the Pittsfield, Vt., town line.
\nThis report presents water-surface elevations determined for the study reaches using the U.S. Army Corps of Engineers one-dimensional step-backwater Hydrologic Engineering Center River Analysis System model, also known as HEC– RAS. The water-surface elevations were determined for floods having a 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability (AEP) and for the floodway.
\nEighteen high-water marks from Tropical Storm Irene were available along the studied reaches. The discharges in the Tropical Storm Irene HEC–RAS model were adjusted so that the resulting water-surface elevations matched the high-water mark elevations along the study reaches. This allowed for an estimation of the water-surface profile throughout the study area resulting from Tropical Storm Irene. From a comparison of the estimated water-surface profile of Tropical Storm Irene to the water-surface profiles of the 1- and 0.2-percent AEP floods, it was determined that the high-water elevations resulting from Tropical Storm Irene exceeded the estimated 1-percent AEP flood throughout the White River and Tweed River study reaches and exceeded the estimated 0.2-percent AEP flood in 16.7 of the 28.6 study reach miles. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 18.2-centimeter vertical accuracy at the 95-percent confidence level and 1-meter horizontal resolution to delineate the area flooded for each water-surface profile.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155056","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2015, Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014: U.S. Geological Survey Scientific Investigations Report 2015-5056, Report: vi, 32 p.; Readme; Map file and datasets; Metadata, https://doi.org/10.3133/sir20155056.","productDescription":"Report: vi, 32 p.; Readme; Map file and datasets; Metadata","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-057993","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":301023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155056.jpg"},{"id":301018,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5056/"},{"id":301019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5056/pdf/sir2015-5056.pdf","text":"Report","size":"2.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301020,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_readme.txt","text":"Readme","size":"1.09 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Readme"},{"id":301021,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_map.zip","text":"Map file and datasets","size":"2.11 GB","linkFileType":{"id":6,"text":"zip"},"description":"Map file and datasets","linkHelpText":"Contains the published map file and the map dataset. For use with ArcReader, which is free and available at http://www.esri.com/software/argis/arcreader"},{"id":301022,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_metadata.zip","text":"Metadata","size":"162 KB","linkFileType":{"id":6,"text":"zip"},"description":"Metadata","linkHelpText":"The metadata for the map contents"}],"country":"United States","state":"Vermont","city":"Bethel, Pittsfield, Rochester, Stockbridge","otherGeospatial":"Tweed River, White River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.8122329711914,\n 43.88205730390537\n ],\n [\n -72.80502319335938,\n 43.88279966767229\n ],\n [\n -72.80261993408203,\n 43.877355451898595\n ],\n [\n -72.806396484375,\n 43.87017822557581\n ],\n [\n -72.80296325683594,\n 43.86151490472453\n ],\n [\n -72.79747009277344,\n 43.84938414031938\n ],\n [\n -72.78820037841797,\n 43.83650797709095\n ],\n [\n -72.7840805053711,\n 43.81991343882605\n ],\n [\n -72.77961730957031,\n 43.806287608590075\n ],\n [\n -72.76485443115234,\n 43.79984522482957\n ],\n [\n -72.74253845214844,\n 43.7715896488274\n ],\n [\n -72.73017883300781,\n 43.761672246385025\n ],\n [\n -72.71781921386719,\n 43.7715896488274\n ],\n [\n -72.70511627197266,\n 43.78398408962279\n ],\n [\n -72.68383026123047,\n 43.79612814894592\n ],\n [\n -72.66975402832031,\n 43.79959742696462\n ],\n [\n -72.67284393310547,\n 43.80901302334783\n ],\n [\n -72.65876770019531,\n 43.81718852149039\n ],\n [\n -72.64572143554688,\n 43.81842713569542\n ],\n [\n -72.63988494873047,\n 43.82536290042666\n ],\n [\n -72.63988494873047,\n 43.83180253191123\n ],\n [\n -72.62889862060547,\n 43.83205019617054\n ],\n [\n -72.62306213378906,\n 43.82734439949711\n ],\n [\n -72.62237548828125,\n 43.82164741238288\n ],\n [\n -72.62992858886719,\n 43.81966572420698\n ],\n [\n -72.63404846191406,\n 43.81099506506452\n ],\n [\n -72.65464782714844,\n 43.808269740746574\n ],\n [\n -72.66082763671875,\n 43.8033142870288\n ],\n [\n -72.65808105468749,\n 43.79191518340848\n ],\n [\n -72.66735076904297,\n 43.78943682964683\n ],\n [\n -72.67387390136719,\n 43.78993250862075\n ],\n [\n -72.69893646240234,\n 43.773325025204\n ],\n [\n -72.72056579589842,\n 43.755968995444164\n ],\n [\n -72.7408218383789,\n 43.75646495188919\n ],\n [\n -72.7573013305664,\n 43.77134173380578\n ],\n [\n -72.76966094970703,\n 43.77109381775651\n ],\n [\n -72.79163360595703,\n 43.774812450590474\n ],\n [\n -72.806396484375,\n 43.77233338772627\n ],\n [\n -72.81017303466797,\n 43.76315996157264\n ],\n [\n -72.81566619873047,\n 43.74530493763506\n ],\n [\n -72.81669616699219,\n 43.72769268338755\n ],\n [\n -72.8177261352539,\n 43.725707879311514\n ],\n [\n -72.83042907714844,\n 43.725707879311514\n ],\n [\n -72.82527923583984,\n 43.763903805293104\n ],\n [\n -72.81909942626953,\n 43.776547733448844\n ],\n [\n -72.80158996582031,\n 43.782496892381175\n ],\n [\n -72.78579711914062,\n 43.78398408962279\n ],\n [\n -72.77069091796875,\n 43.78076178217298\n ],\n [\n -72.7621078491211,\n 43.77877873741692\n ],\n [\n -72.77824401855469,\n 43.79612814894592\n ],\n [\n -72.7950668334961,\n 43.80504874259129\n ],\n [\n -72.79884338378906,\n 43.82164741238288\n ],\n [\n -72.80570983886717,\n 43.83848910616803\n ],\n [\n -72.81257629394531,\n 43.85557361417025\n ],\n [\n -72.81669616699219,\n 43.862257524417934\n ],\n [\n -72.8122329711914,\n 43.88205730390537\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5570171ae4b0d9246a9fd14b","contributors":{"authors":[{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546370,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203357,"text":"70203357 - 2015 - Modeling and management of pit lake water chemistry 1: Theory","interactions":[],"lastModifiedDate":"2019-05-07T13:27:13","indexId":"70203357","displayToPublicDate":"2015-06-01T13:22:41","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Modeling and management of pit lake water chemistry 1: Theory","docAbstract":"Pit lakes are permanent hydrologic/landscape features that can result from open pit mining for metals, coal, uranium, diamonds, oil sands, and aggregates. Risks associated with pit lakes include local and regional impacts to water quality and related impacts to aquatic and terrestrial ecosystems. Stakeholders rely on predictive models of water chemistry to prepare for and manage these risks. This paper is the first of a two part series on the modeling and management of pit lakes. Herein, we review approaches that have been used to quantify wall-rock runoff geochemistry, wall-rock leachate geochemistry, pit lake water balance, pit lake limnology (i.e. extent of vertical mixing), and pit lake water quality, and conclude with guidance on the application of models within the mine life cycle. The purpose of this paper is to better prepare stakeholders, including future modelers, mine managers, consultants, permitting agencies, land management agencies, regulators, research scientists, academics, and other interested parties, for the challenges of predicting and managing future pit lakes in un-mined areas.
Copper oxide (CuO) nanoparticles (NPs) are widely used, and likely released into the aquatic environment. Both aqueous (i.e., dissolved Cu) and particulate Cu can be taken up by organisms. However, how exposure routes influence the bioavailability and subsequent toxicity of Cu remains largely unknown. Here, we assess the importance of exposure routes (water and sediment) and Cu forms (aqueous and nanoparticulate) on Cu bioavailability and toxicity to the freshwater oligochaete, Lumbriculus variegatus, a head-down deposit-feeder. We characterize the bioaccumulation dynamics of Cu in L. variegatus across a range of exposure concentrations, covering both realistic and worst-case levels of Cu contamination in the environment. Both aqueous Cu (Cu-Aq; administered as Cu(NO3)2) and nanoparticulate Cu (CuO NPs), whether dispersed in artificial moderately hard freshwater or mixed into sediment, were weakly accumulated by L. variegatus. Once incorporated into tissues, Cu elimination was negligible, i.e., elimination rate constants were in general not different from zero for either exposure route or either Cu form. Toxicity was only observed after waterborne exposure to Cu-Aq at very high concentration (305 µgL-1), where all worms died. There was no relationship between exposure route, Cu form or Cu exposure concentration on either worm survival or growth. Slow feeding rates and low Cu assimilation efficiency (approximately 30%) characterized the uptake of Cu from the sediment for both Cu forms. In nature, L. variegatus is potentially exposed to Cu via both water and sediment. However, sediment progressively becomes the predominant exposure route for Cu in L. variegatus as Cu partitioning to sediment increases.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.aquatox.2015.04.022","usgsCitation":"Ramskov, T., Thit, A., Croteau, M.N., and Selck, H., 2015, Biodynamics of copper oxide nanoparticles and copper ions in an oligochaete: Part I: relative importance of water and sediment as exposure routes: Aquatic Toxicology, v. 164, p. 81-91, https://doi.org/10.1016/j.aquatox.2015.04.022.","productDescription":"11 p.","startPage":"81","endPage":"91","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061794","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":300967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"164","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"556ed3b7e4b0d9246a9fa7c7","contributors":{"authors":[{"text":"Ramskov, Tina","contributorId":140202,"corporation":false,"usgs":false,"family":"Ramskov","given":"Tina","email":"","affiliations":[{"id":13410,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, PO Box 260, Universitetsvej 1, DK-4000 Roskilde, Denmark","active":true,"usgs":false}],"preferred":false,"id":547998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thit, Amalie","contributorId":141022,"corporation":false,"usgs":false,"family":"Thit","given":"Amalie","email":"","affiliations":[{"id":13657,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, Denmark","active":true,"usgs":false}],"preferred":false,"id":547999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":547997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Selck, Henriette","contributorId":28475,"corporation":false,"usgs":false,"family":"Selck","given":"Henriette","affiliations":[{"id":13410,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, PO Box 260, Universitetsvej 1, DK-4000 Roskilde, Denmark","active":true,"usgs":false}],"preferred":false,"id":548000,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156306,"text":"70156306 - 2015 - Plant-plant interactions in a subtropical mangrove-to-marsh transition zone: effects of environmental drivers","interactions":[],"lastModifiedDate":"2015-10-19T12:17:40","indexId":"70156306","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Plant-plant interactions in a subtropical mangrove-to-marsh transition zone: effects of environmental drivers","docAbstract":"Does the presence of herbaceous vegetation affect the establishment success of mangrove tree species in the transition zone between subtropical coastal mangrove forests and marshes? How do plant–plant interactions in this transition zone respond to variation in two primary coastal environmental drivers?
\nSubtropical coastal region of the southern United States.
\nWe conducted a greenhouse study to better understand how abiotic factors affect plant species interactions in the mangrove-to-marsh transition zone, or ecotone. We manipulated salinity (fresh, brackish or salt water) and hydrologic conditions (continuously saturated or 20-cm tidal range) to simulate ecotonal environments. Propagules of the mangroves Avicennia germinans and Laguncularia racemosa were introduced to mesocosms containing an established marsh community. Both mangrove species were also introduced to containers lacking other vegetation. We monitored mangrove establishment success and survival over 22 mo. Mangrove growth was measured as stem height and above-ground biomass. Stem height, stem density and above-ground biomass of the dominant marsh species were documented.
\nEstablishment success of A. germinans was reduced under saturated saltwater conditions, but establishment of L. racemosa was not affected by experimental treatments. There was complete mortality of A. germinans in mesocosms under freshwater conditions, and very low survival of L. racemosa. In contrast, survival of both species in monoculture under freshwater conditions exceeded 62%. The marsh species Distichlis spicata and Eleocharis cellulosa suppressed growth of both mangroves throughout the experiment, whereas the mangroves did not affect herbaceous species growth. The magnitude of growth suppression by marsh species varied with environmental conditions; suppression was often higher in saturated compared to tidal conditions, and higher in fresh and salt water compared to brackish water.
\nOur results indicate that herbaceous marsh species can suppress mangrove early seedling growth. Depending on species composition and density, marsh plants can slow mangrove landward migration under predicted climate change scenarios as salinity in freshwater and oligohaline wetlands increases with rising sea levels. Change in the relative coverage of mangrove forests and marshes will depend on both the ability of marsh species to migrate further inland as mangroves advance, and the ability of shoreline mangroves to adjust to rising sea level through accretionary processes.
\nNatural uranium (U) occurs as a mixture of three radioactive isotopes: 238U, 235U, and 234U. Only 235U is fissionable and makes up about 0.7% of natural U, while 238U is overwhelmingly the most abundant at greater than 99% of the total mass of U. Prior to the 1940s, U was predominantly used as a coloring agent, and U-bearing ores were mined mainly for their radium (Ra) and/or vanadium (V) content; the bulk of the U was discarded with the tailings (Finch et al., 1972). Once nuclear fission was discovered, the economic importance of U increased greatly. The mining and milling of U-bearing ores is the first step in the nuclear fuel cycle, and the contact of residual waste with natural water is a potential source of contamination of U and associated elements to the environment. Uranium is mined by three basic methods: surface (open pit), underground, and solution mining (in situ leaching or in situ recovery), depending on the deposit grade, size, location, geology and economic considerations (Abdelouas, 2006). Solid wastes at U mill tailings (UMT) sites can include both standard tailings (i.e., leached ore rock residues) and solids generated on site by waste treatment processes. The latter can include sludge or “mud” from neutralization of acidic mine/mill effluents, containing Fe and a range of coprecipitated constituents, or barium sulfate precipitates that selectively remove Ra (e.g., Carvalho et al., 2007). In this chapter, we review the hydrometallurgical processes by which U is extracted from ore, the biogeochemical processes that can affect the fate and transport of U and associated elements in the environment, and possible remediation strategies for site closure and aquifer restoration.
This paper represents the fourth in a series of review papers from the U.S. Geological Survey (USGS) on geochemical aspects of UMT management that span more than three decades. The first paper (Landa, 1980) in this series is a primer on the nature of tailings and radionuclide mobilization from them. The second paper (Landa, 1999) includes coverage of research carried out under the U.S. Department of Energy’s Uranium Mill Tailings Remedial Action Program (UMTRA). The third paper (Landa, 2004) reflects the increased focus of researchers on biotic effects in UMT environs. This paper expands the focus to U mining, milling, and remedial actions, and includes extensive coverage of the increasingly important alkaline in situ recovery and groundwater restoration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.07.022","usgsCitation":"Campbell, K.M., Gallegos, T.J., and Landa, E.R., 2015, Biogeochemical aspects of uranium mineralization, mining, milling, and remediation: Applied Geochemistry, v. 57, p. 206-235, https://doi.org/10.1016/j.apgeochem.2014.07.022.","productDescription":"30 p.","startPage":"206","endPage":"235","ipdsId":"IP-053469","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":331114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582ecff0e4b04d580bd43534","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":653459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallegos, Tanya J. 0000-0003-3350-6473 tgallegos@usgs.gov","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":2206,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya","email":"tgallegos@usgs.gov","middleInitial":"J.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":654048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landa, Edward R. erlanda@usgs.gov","contributorId":2112,"corporation":false,"usgs":true,"family":"Landa","given":"Edward","email":"erlanda@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":654049,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191256,"text":"70191256 - 2015 - Applied Geochemistry Special Issue on Environmental geochemistry of modern mining","interactions":[],"lastModifiedDate":"2020-03-10T14:38:56","indexId":"70191256","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Applied Geochemistry Special Issue on Environmental geochemistry of modern mining","docAbstract":"Environmental geochemistry is an integral part of the mine-life cycle, particularly for modern mining. The critical importance of environmental geochemistry begins with pre-mining baseline characterization and the assessment of environmental risks related to mining, continues through active mining especially in water and waste management practices, and culminates in mine closure. The enhanced significance of environmental geochemistry to modern mining has arisen from an increased knowledge of the impacts that historical and active mining can have on the environment, and from new regulations meant to guard against these impacts. New regulations are commonly motivated by advances in the scientific understanding of the environmental impacts of past mining. The impacts can be physical, chemical, and biological in nature. The physical challenges typically fall within the purview of engineers, whereas the chemical and biological challenges typically require a multidisciplinary array of expertise including geologists, geochemists, hydrologists, microbiologists, and biologists. The modern mine-permitting process throughout most of the world now requires that potential risks be assessed prior to the start of mining. The strategies for this risk assessment include a thorough characterization of pre-mining baseline conditions and the identification of risks specifically related to the manner in which the ore will be mined and processed, how water and waste products will be managed, and what the final configuration of the post-mining landscape will be.
In the Fall 2010, the Society of Economic Geologists held a short course in conjunction with the annual meeting of the Geological Society of America in Denver, Colorado (USA) to examine the environmental geochemistry of modern mining. The intent was to focus on issues that are pertinent to current and future mines, as opposed to abandoned mines, which have been the focus of numerous previous short courses. The geochemical challenges of current and future mines share similarities with abandoned mines, but differences also exist. Mining and ore processing techniques have changed; the environmental footprint of waste materials has changed; environmental protection has become a more integral part of the mine planning process; and most historical mining was done with limited regard for the environment. The 17 papers in this special issue evolved from the Society of Economic Geologists’ short course.
The relevant geochemical processes encompass the source, transport, and fate of contaminants related to the life cycle of a mine. Contaminants include metals and other inorganic species derived from geologic sources such as ore and solid mine waste, and substances brought to the site for ore processing, such as cyanide to leach gold. Factors, such as mine-waste mineralogy, hydrologic setting, mine-drainage chemistry, and microbial activity, that affect the hydrochemical risks from mining are reviewed by Nordstrom et al. In another paper, Nordstrom discusses baseline characterization at mine sites in a regulatory framework, and emphasizes the influence of mineral deposits in producing naturally elevated concentrations of many trace elements in surface water and groundwater. Surface water quality in mineralized watersheds is influenced by a number of processes that act on daily (diel) cycles and can produce dramatic variations in trace element concentrations as described by Gammons et al. Pre-mining baseline characterization studies should strive to capture the magnitude of these diel variations. Desbarats et al., using a case study of mine drainage from a gold mine, illustrate how elements that commonly occur as negatively charged species (anions) in solution, such as arsenic as arsenate, behave in an opposite fashion than most metals, which occur as positively charged species (cations). Significant improvement in the understanding of factors that influence the toxicity of metals to aquatic organisms in surface water has highlighted the importance of aqueous chemistry, particularly dissolved organic carbon, as described by Smith et al. Stream sediment contamination is another important pathway for affecting aquatic organisms, as reviewed by Besser et al. Understanding and predicting environmental consequences from mining begins with knowing the mineralogy and mineral reactivity of the ore, the wastes, and of secondary minerals formed later. Jamieson et al. review the importance of mineralogical studies in mine planning and remediation. A number of types of site-specific studies are needed to identify environmental risks related to individual mines. Lapakko reviews the general framework of mine waste characterization studies that are integral to the mine planning process. Hageman et al. present a comparative study of several static tests commonly used to characterize mine waste.
The mining and ore processing practices employed at a specific mine site will vary on the basis of the commodities being targeted, the geology of the deposit, the geometry of the deposit, and the mining and ore processing methods used. Thus, these factors, in addition to the waste management practices used, can result in a variety of end-member mine waste features, each of which has its own set of challenges. Open pit mines and underground mines require waste rock to be removed to access ore. Waste rock presents unique problems because the rock is commonly mineralized at sub-economic grades and has not been processed to remove potentially problematic minerals, such as pyrite. Amos et al. examine the salient aspects of the geochemistry of waste rock. Mill tailings – the waste material after ore minerals have been removed – are a volumetrically important solid waste at many mine sites. Their fine grain size and the options for their management make their behavior in the environment distinct from that of waste rock. Lindsay et al. describe some of these differences through three case-study examples. Subaqueous disposal of tailings is another option described by Moncur et al. Cyanide leaching for gold extraction is a common method throughout the world. Johnson describes environmental aspects of cyanidation. Uranium mining presents unique environmental challenges, particularly since in-situ recovery has seen widespread use. Campbell et al. review the environmental geochemistry of uranium mining and current research on bioremediation. Ore concentrates from many types of metal mining undergo a pyrometallurgical technique known as smelting to extract the metal. Slag is the result of smelting, and it may be an environmental liability or a valuable byproduct, as described by Piatak et al. Finally, the open pits that result from surface mining commonly reach below the water table. At the end of mining, these pits may fill to form lakes that become part of the legacy of the mine. Castendyk et al., in two papers, review theoretical aspects of the environmental limnology of pit lakes. They also describe approaches that have been used to model pit lake water balance, wall-rock contributions to pit lake chemistry, pit lake water quality, and limnological processes, such as vertical mixing, through the use of three case studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.04.019","usgsCitation":"Seal, R., and Nordstrom, D.K., 2015, Applied Geochemistry Special Issue on Environmental geochemistry of modern mining: Applied Geochemistry, v. 57, p. 1-2, https://doi.org/10.1016/j.apgeochem.2015.04.019.","productDescription":"2 p.","startPage":"1","endPage":"2","ipdsId":"IP-063499","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":346319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d3502ae4b05fe04cc34d6f","contributors":{"authors":[{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":711701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","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":false,"id":711702,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182182,"text":"70182182 - 2015 - Aspect-dependent soil saturation and insight into debris-flow initiation during extreme rainfall in the Colorado Front Range","interactions":[],"lastModifiedDate":"2017-02-20T11:35:54","indexId":"70182182","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Aspect-dependent soil saturation and insight into debris-flow initiation during extreme rainfall in the Colorado Front Range","docAbstract":"Hydrologic processes during extreme rainfall events are poorly characterized because of the rarity of measurements. Improved understanding of hydrologic controls on natural hazards is needed because of the potential for substantial risk during extreme precipitation events. We present field measurements of the degree of soil saturation and estimates of available soil-water storage during the September 2013 Colorado extreme rainfall event at burned (wildfire in 2010) and unburned hillslopes with north- and south-facing slope aspects. Soil saturation was more strongly correlated with slope aspect than with recent fire history; south-facing hillslopes became fully saturated while north-facing hillslopes did not. Our results suggest multiple explanations for why aspect-dependent hydrologic controls favor saturation development on south-facing slopes, causing reductions in effective stress and triggering of slope failures during extreme rainfall. Aspect-dependent hydrologic behavior may result from (1) a larger gravel and stone fraction, and hence lower soil-water storage capacity, on south-facing slopes, and (2) lower weathered-bedrock permeability on south-facing slopes, because of lower tree density and associated deep roots penetrating bedrock as well as less intense weathering, inhibiting soil drainage.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G36741.1","usgsCitation":"Ebel, B.A., Rengers, F., and Tucker, G.E., 2015, Aspect-dependent soil saturation and insight into debris-flow initiation during extreme rainfall in the Colorado Front Range: Geology, v. 43, no. 8, p. 659-662, https://doi.org/10.1130/G36741.1.","productDescription":"4 p.","startPage":"659","endPage":"662","ipdsId":"IP-065569","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":335827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-23","publicationStatus":"PW","scienceBaseUri":"58ac0e2fe4b0ce4410e7d5fc","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":669910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengers, Francis K.","contributorId":181893,"corporation":false,"usgs":false,"family":"Rengers","given":"Francis K.","affiliations":[],"preferred":false,"id":669911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Gregory E.","contributorId":177811,"corporation":false,"usgs":false,"family":"Tucker","given":"Gregory","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":669912,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182185,"text":"70182185 - 2015 - Suburbanization, estrogen contamination, and sex ratio in wild amphibian populations","interactions":[],"lastModifiedDate":"2018-09-04T15:47:41","indexId":"70182185","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Suburbanization, estrogen contamination, and sex ratio in wild amphibian populations","docAbstract":"Research on endocrine disruption in frog populations, such as shifts in sex ratios and feminization of males, has predominantly focused on agricultural pesticides. Recent evidence suggests that suburban landscapes harbor amphibian populations exhibiting similar levels of endocrine disruption; however the endocrine disrupting chemical (EDC) sources are unknown. Here, we show that sex ratios of metamorphosing frogs become increasingly female-dominated along a suburbanization gradient. We further show that suburban ponds are frequently contaminated by the classical estrogen estrone and a variety of EDCs produced by plants (phytoestrogens), and that the diversity of organic EDCs is correlated with the extent of developed land use and cultivated lawn and gardens around a pond. Our work also raises the possibility that trace-element contamination associated with human land use around suburban ponds may be contributing to the estrogenic load within suburban freshwaters and constitutes another source of estrogenic exposure for wildlife. These data suggest novel, unexplored pathways of EDC contamination in human-altered environments. In particular, we propose that vegetation changes associated with suburban neighborhoods (e.g., from forests to lawns and ornamental plants) increase the distribution of phytoestrogens in surface waters. The result of frog sex ratios varying as a function of human land use implicates a role for environmental modulation of sexual differentiation in amphibians, which are assumed to only have genetic sex determination. Overall, we show that endocrine disruption is widespread in suburban frog populations and that the causes are likely diverse.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1501065112","usgsCitation":"Lambert, M.R., Giller, G.S., Barber, L.B., Fitzgerald, K.C., and Skelly, D.K., 2015, Suburbanization, estrogen contamination, and sex ratio in wild amphibian populations: Proceedings of the National Academy of Sciences of the United States of America, v. 112, no. 38, p. 11881-11886, https://doi.org/10.1073/pnas.1501065112.","productDescription":"6 p.","startPage":"11881","endPage":"11886","ipdsId":"IP-062730","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":472068,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1501065112","text":"External Repository"},{"id":335838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"38","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-08","publicationStatus":"PW","scienceBaseUri":"58ac0e2ee4b0ce4410e7d5fa","contributors":{"authors":[{"text":"Lambert, Max R.","contributorId":181897,"corporation":false,"usgs":false,"family":"Lambert","given":"Max","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":669920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giller, Geoffrey S. J.","contributorId":181898,"corporation":false,"usgs":false,"family":"Giller","given":"Geoffrey","email":"","middleInitial":"S. J.","affiliations":[],"preferred":false,"id":669921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":669919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzgerald, Kevin C. kcfitzgerald@usgs.gov","contributorId":5534,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Kevin","email":"kcfitzgerald@usgs.gov","middleInitial":"C.","affiliations":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"preferred":true,"id":669922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skelly, David K.","contributorId":181900,"corporation":false,"usgs":false,"family":"Skelly","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":669923,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159048,"text":"70159048 - 2015 - Hydrology: The interdisciplinary science of water","interactions":[],"lastModifiedDate":"2015-10-15T09:08:54","indexId":"70159048","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hydrology: The interdisciplinary science of water","docAbstract":"We live in a world where biophysical and social processes are tightly coupled. Hydrologic systems change in response to a variety of natural and human forces such as climate variability and change, water use and water infrastructure, and land cover change. In turn, changes in hydrologic systems impact socioeconomic, ecological, and climate systems at a number of scales, leading to a coevolution of these interlinked systems. The Harvard Water Program, Hydrosociology, Integrated Water Resources Management, Ecohydrology, Hydromorphology, and Sociohydrology were all introduced to provide distinct, interdisciplinary perspectives on water problems to address the contemporary dynamics of human interaction with the hydrosphere and the evolution of the Earth’s hydrologic systems. Each of them addresses scientific, social, and engineering challenges related to how humans influence water systems and vice versa. There are now numerous examples in the literature of how holistic approaches can provide a structure and vision of the future of hydrology. We review selected examples, which taken together, describe the type of theoretical and applied integrated hydrologic analyses and associated curricular content required to address the societal issue of water resources sustainability. We describe a modern interdisciplinary science of hydrology needed to develop an in-depth understanding of the dynamics of the connectedness between human and natural systems and to determine effective solutions to resolve the complex water problems that the world faces today. Nearly, every theoretical hydrologic model introduced previously is in need of revision to accommodate how climate, land, vegetation, and socioeconomic factors interact, change, and evolve over time.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR017049","usgsCitation":"Vogel, R.M., Lall, U., Cai, X., Rajagopalan, B., Weiskel, P.K., Hooper, R.P., and Matalas, N.C., 2015, Hydrology: The interdisciplinary science of water: Water Resources Research, v. 51, no. 6, p. 4409-4430, https://doi.org/10.1002/2015WR017049.","productDescription":"22 p.","startPage":"4409","endPage":"4430","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065855","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":472065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017049","text":"Publisher Index Page"},{"id":309897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-21","publicationStatus":"PW","scienceBaseUri":"5620ce77e4b06217fc478aee","contributors":{"authors":[{"text":"Vogel, Richard M.","contributorId":66811,"corporation":false,"usgs":true,"family":"Vogel","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":577535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lall, Upmanu","contributorId":101172,"corporation":false,"usgs":true,"family":"Lall","given":"Upmanu","affiliations":[],"preferred":false,"id":577536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cai, Ximing","contributorId":149230,"corporation":false,"usgs":false,"family":"Cai","given":"Ximing","email":"","affiliations":[{"id":17685,"text":"University of Illinois, Champagne-Urbana","active":true,"usgs":false}],"preferred":false,"id":577537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rajagopalan, Balaji","contributorId":145813,"corporation":false,"usgs":false,"family":"Rajagopalan","given":"Balaji","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":577538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weiskel, Peter K. pweiskel@usgs.gov","contributorId":1099,"corporation":false,"usgs":true,"family":"Weiskel","given":"Peter","email":"pweiskel@usgs.gov","middleInitial":"K.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":577534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooper, Richard P.","contributorId":19144,"corporation":false,"usgs":true,"family":"Hooper","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":577539,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matalas, Nicholas C.","contributorId":34535,"corporation":false,"usgs":true,"family":"Matalas","given":"Nicholas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":577540,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189467,"text":"70189467 - 2015 - Sediment source apportionment in Laurel Hill Creek, PA, using Bayesian chemical mass balance and isotope fingerprinting","interactions":[],"lastModifiedDate":"2017-07-13T13:29:57","indexId":"70189467","displayToPublicDate":"2015-05-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Sediment source apportionment in Laurel Hill Creek, PA, using Bayesian chemical mass balance and isotope fingerprinting","docAbstract":"A Bayesian chemical mass balance (CMB) approach was used to assess the contribution of potential sources for fluvial samples from Laurel Hill Creek in southwest Pennsylvania. The Bayesian approach provides joint probability density functions of the sources' contributions considering the uncertainties due to source and fluvial sample heterogeneity and measurement error. Both elemental profiles of sources and fluvial samples and 13C and 15N isotopes were used for source apportionment. The sources considered include stream bank erosion, forest, roads and agriculture (pasture and cropland). Agriculture was found to have the largest contribution, followed by stream bank erosion. Also, road erosion was found to have a significant contribution in three of the samples collected during lower-intensity rain events. The source apportionment was performed with and without isotopes. The results were largely consistent; however, the use of isotopes was found to slightly increase the uncertainty in most of the cases. The correlation analysis between the contributions of sources shows strong correlations between stream bank and agriculture, whereas roads and forest seem to be less correlated to other sources. Thus, the method was better able to estimate road and forest contributions independently. The hypothesis that the contributions of sources are not seasonally changing was tested by assuming that all ten fluvial samples had the same source contributions. This hypothesis was rejected, demonstrating a significant seasonal variation in the sources of sediments in the stream.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10364","usgsCitation":"Stewart, H., Massoudieh, A., and Gellis, A.C., 2015, Sediment source apportionment in Laurel Hill Creek, PA, using Bayesian chemical mass balance and isotope fingerprinting: Hydrological Processes, v. 29, no. 11, p. 2545-2560, https://doi.org/10.1002/hyp.10364.","productDescription":"16 p.","startPage":"2545","endPage":"2560","ipdsId":"IP-060412","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":343802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Laurel Hill Creek","volume":"29","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-12-03","publicationStatus":"PW","scienceBaseUri":"596886a2e4b0d1f9f05f59c1","contributors":{"authors":[{"text":"Stewart, Heather","contributorId":173199,"corporation":false,"usgs":false,"family":"Stewart","given":"Heather","affiliations":[{"id":27188,"text":"Alaska Department of Natural Resources Division of Agriculture","active":true,"usgs":false}],"preferred":false,"id":704793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massoudieh, Arash","contributorId":194625,"corporation":false,"usgs":false,"family":"Massoudieh","given":"Arash","email":"","affiliations":[],"preferred":false,"id":704794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":172245,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":704795,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70136357,"text":"sir20145236 - 2015 - Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","interactions":[],"lastModifiedDate":"2015-11-04T12:07:21","indexId":"sir20145236","displayToPublicDate":"2015-05-27T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5236","title":"Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","docAbstract":"A series of nine digital flood-inundation maps were developed for an 8-mile reach of the Hoosic River in North Adams and Williamstown, Massachusetts, by the U.S. Geological Survey (USGS) in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence with the North Branch Hoosic River to the Vermont State line. Peak flows with 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations, and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using the current (2014) stage-discharge relation at the USGS streamgage Hoosic River near Williamstown, Massachusetts (01332500), and from documented high-water marks from the tropical storm Irene flood, which had approximately a 1-percent annual exceedance probability.
\nThe hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from 9 feet (ft; 624.45 ft North American Vertical Datum of 1988 [NAVD 1988]), which is near bankfull, to 16.1 ft (631.59 ft NAVD 1988), which exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft. The mapped stages, 10.9 to 16.1 ft, were selected to match the stages of flows with annual exceedance probabilities between 20 and 0.2 percent, and thus do not fall at exact 1-ft increments. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps.
\nThe availability of the flood-inundation maps, combined with information regarding current (near real-time) stage from USGS streamgage Hoosic River near Williamstown, and forecasted flood stages from the National Weather Service Advanced Hydrologic Prediction Service will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and post-flood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145236","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Lombard, P., and Bent, G.C., 2015, Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line: U.S. Geological Survey Scientific Investigations Report 2014-5236, Report: vi, 15 p.; Downloads Directory, https://doi.org/10.3133/sir20145236.","productDescription":"Report: vi, 15 p.; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059673","costCenters":[{"id":371,"text":"Maine Water Science 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Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa.
\nTwenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart.
\nFor the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013).
\nFor drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias.
\nAn examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1-4 from the 1987 single-variable RREs and for flood regions 1-3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155055","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR-678)","usgsCitation":"Eash, D.A., 2015, Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013: U.S. Geological Survey Scientific Investigations Report 2015-5055, viii, 37 p., https://doi.org/10.3133/sir20155055.","productDescription":"viii, 37 p.","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058580","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":300734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155055.jpg"},{"id":300732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5055/pdf/sir2015-5055.pdf","text":"Report","size":"2.06 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5055"},{"id":300731,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5055/"},{"id":300733,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5055/downloads/","text":"Downloads Directory","linkFileType":{"id":3,"text":"xlsx"},"description":"Contains: Table 3, 4, 8, 9, and 10 in XLSX format","linkHelpText":"SIR 2015-5055 Downloads Directory"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.7236328125,\n 43.51668853502906\n ],\n [\n -91.2744140625,\n 43.51668853502906\n ],\n [\n -91.01074218749999,\n 43.29320031385282\n ],\n [\n -91.20849609375,\n 43.11702412135048\n ],\n [\n -91.01074218749999,\n 42.79540065303723\n ],\n [\n -90.703125,\n 42.65012181368022\n ],\n [\n -90.06591796875,\n 42.08191667830631\n ],\n [\n -90.32958984375,\n 41.508577297439324\n ],\n [\n -91.01074218749999,\n 41.37680856570233\n ],\n [\n -90.85693359375,\n 40.896905775860006\n ],\n [\n -91.47216796875,\n 40.29628651711716\n ],\n [\n -91.8017578125,\n 40.58058466412761\n ],\n [\n -95.73486328124999,\n 40.54720023441049\n ],\n [\n -95.97656249999999,\n 40.713955826286046\n ],\n [\n -96.70166015624999,\n 42.73087427928485\n ],\n [\n -96.70166015624999,\n 43.14909399920127\n ],\n [\n -96.7236328125,\n 43.51668853502906\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560451be4b0afeb70724141","contributors":{"authors":[{"text":"Eash, David A. 0000-0002-2749-8959 daeash@usgs.gov","orcid":"https://orcid.org/0000-0002-2749-8959","contributorId":1887,"corporation":false,"usgs":true,"family":"Eash","given":"David","email":"daeash@usgs.gov","middleInitial":"A.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544976,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141461,"text":"sir20155015 - 2015 - Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","interactions":[],"lastModifiedDate":"2015-05-28T09:27:59","indexId":"sir20155015","displayToPublicDate":"2015-05-22T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5015","title":"Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","docAbstract":"The South Platte River and underlying alluvial aquifer form an important hydrologic resource in northeastern Colorado that provides water to population centers along the Front Range and to agricultural communities across the rural plains. Water is regulated based on seniority of water rights and delivered using a network of administration structures that includes ditches, reservoirs, wells, impacted river sections, and engineered recharge areas. A recent addendum to Colorado water law enacted during 2002-2003 curtailed pumping from thousands of wells that lacked authorized augmentation plans. The restrictions in pumping were hypothesized to increase water storage in the aquifer, causing groundwater to rise near the land surface at some locations. The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board and the Colorado Water Institute, completed an assessment of 60 years (yr) of historical groundwater-level records collected from 1953 to 2012 from 1,669 wells. Relations of \"high\" groundwater levels, defined as depth to water from 0 to 10 feet (ft) below land surface, were compared to precipitation, river discharge, and 36 geographic and administrative attributes to identify natural and human controls in areas with shallow groundwater.
\nAveraged per decade and over the entire aquifer, depths to groundwater varied between 24 and 32 ft over the 60-yr record. The shallowest average depth to water was identified during 1983-1992, which also recorded the highest levels of decadal precipitation. Average depth to water was greatest (32 ft) during 1953-1962 and intermediate (30 ft) in the recent decade (2003-2012) following curtailment of pumping. Between the decades 1993-2002 and 2003-2012, groundwater levels declined about 2 ft across the aquifer. In comparison, in areas where groundwater levels were within 20 ft of the land surface, observed groundwater levels rose about 0.6 ft, on average, during the same period, which demonstrated preferential rise in areas with shallow groundwater.
\nApproximately 29 percent of water-level observations were identified as high groundwater in the South Platte River alluvial aquifer over the 60-yr record. High groundwater levels were found in 17 to 33 percent of wells examined by decade, with the largest percentages occurring over three decades from 1963 to 1992. The recent decade (2003-2012) exhibited an intermediate percentage (25 percent) of wells with high groundwater levels but also had the highest percentage (30 percent) of high groundwater observations, although results by observations were similar (26-29 percent) over three decades prior, from 1963 to 1992. Major sections of the aquifer from north of Sterling to Julesburg and areas near Greeley, La Salle, and Gilcrest were identified with the highest frequencies of high groundwater levels.
\nChanges in groundwater levels were evaluated using Kendal line and least trimmed squares regression methods using a significance level of 0.01 and statistical power of 0.8. During 2003-2012, following curtailment of pumping, 88 percent of wells and 81 percent of subwatershed areas with significant trends in groundwater levels exhibited rising water levels. Over the complete 60-yr record, however, 66 percent of wells and 57 percent of subwatersheds with significant groundwater-level trends still showed declining water levels; rates of groundwater-level change were typically less than 0.125 ft/yr in areas near the South Platte River, with greater declines along the southern tributaries. In agreement, 58 percent of subwatersheds evaluated between 1963-1972 and 2003-2012 showed net declines in average decadal groundwater levels. More areas had groundwater decline in upgradient sections to the west and rise in downgradient sections to the east, implying a redistribution of water has occurred in some areas of the aquifer.
\nPrecipitation was identified as having the strongest statistically significant correlations to river discharge over annual and decadal periods (Pearson correlation coefficients of 0.5 and 0.8, respectively, and statistical significance defined by p-values less than 0.05). Correlation coefficients between river discharge and frequency of high groundwater levels were statistically significant at 0.4 annually and 0.6 over decadal periods, indicating that periods of high river flow were often coincident with high groundwater conditions. Over seasonal periods in five of the six decades examined, peak high groundwater levels occurred after spring runoff from July to September when administrative structures were most active. Between 1993-2002 and 2003-2012, groundwater levels rose while river discharge decreased, in part from greater reliance on surface water and curtailed pumping from wells without augmentation plans.
\nGeographic attributes of elevation and proximity to streams and rivers showed moderate correlations to high groundwater levels in wells used for observing groundwater levels (correlation coefficients of 0.3 to 0.4). Local depressions and regional lows within the aquifer were identified as areas of potential shallow groundwater. Wells close to the river regularly indicated high groundwater levels, while those within depleted tributaries tended to have low frequencies of high groundwater levels. Some attributes of administrative structures were spatially correlated to high groundwater levels at moderate to high magnitudes (correlation coefficients of 0.3 to 0.7). The number of affected river reaches or recharge areas that surround a well where groundwater levels were observed and its distance from the nearest well field showed the strongest controls on high groundwater levels. Influences of administrative structures on groundwater levels were in some cases local over a mile or less but could extend to several miles, often manifesting as diffuse effects from multiple surrounding structures.
\nA network of candidate monitoring wells was proposed to initiate a regional monitoring program. Consistent monitoring and analysis of groundwater levels will be needed for informed decisions to optimize beneficial use of water and to limit high groundwater levels in susceptible areas. Finalization of the network will require future field reconnaissance to assess local site conditions and discussions with State authorities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155015","collaboration":"Prepared in cooperation with the Colorado Water Institute and Colorado Water Conservation Board","usgsCitation":"Wellman, T., 2015, Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels: U.S. Geological Survey Scientific Investigations Report 2015-5015, viii, 68 p., https://doi.org/10.3133/sir20155015.","productDescription":"viii, 68 p.","numberOfPages":"79","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1953-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-057966","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":300710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155015.jpg"},{"id":300708,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5015/pdf/sir2015-5015.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5015 Report"},{"id":300709,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5015/"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.13818359375,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 36.98500309285596\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55604523e4b0afeb70724143","contributors":{"authors":[{"text":"Wellman, Tristan 0000-0003-3049-6214 twellman@usgs.gov","orcid":"https://orcid.org/0000-0003-3049-6214","contributorId":2166,"corporation":false,"usgs":true,"family":"Wellman","given":"Tristan","email":"twellman@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547513,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70156183,"text":"70156183 - 2015 - Modeling apple snail population dynamics on the Everglades landscape","interactions":[],"lastModifiedDate":"2019-07-25T15:01:35","indexId":"70156183","displayToPublicDate":"2015-05-22T01:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling apple snail population dynamics on the Everglades landscape","docAbstract":"Context
\nThe Florida Everglades has diminished in size and its existing wetland hydrology has been altered. The endangered snail kite (Rostrhamus sociabilis) has nearly abandoned the Everglades, and its prey, the apple snail (Pomacea paludosa), has declined.
\nObjective
\nWe developed a population model (EverSnail) to understand apple snail response to inter- and intra-annual fluctuations in water depths over the Everglades landscape. EverSnail was developed as a tool to understand how apple snails respond to different hydrologic scenarios.
\nMethods
\nEverSnail is an age- and size-structured, spatially-explicit landscape model of P. paludosa in the Everglades. Landscape-level inputs are water depth and air temperature. We conducted sensitivity analyses by running EverSnail with ± 20 % the baseline value of eight parameters.
\nResults
\nEverSnail was sensitive to changes in survival and water depth associated with reproduction. The EverSnail population varied with changes and/or differences in depth generally consistent with empirical data; site-specific comparisons to field data proved less reliable. A simulated 3-year wet period resulted in a shift in apple snail distribution, but little change in total abundance over the landscape. In contrast, a simulated 3-year succession of relatively dry years resulted in overall lower snail abundances.
\nConclusions
\nComparisons of model output to empirical data indicate the need for more data to better understand, and eventually parameterize, several aspects of snail ecology in support of EverSnail. A primary value of EverSnail is its capacity to describe the relative response of snail abundance to alternative hydrologic scenarios considered for Everglades water management and restoration.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s10980-015-0205-5","usgsCitation":"Darby, P., DeAngelis, D., Romanach, S.S., Suir, K.J., and Bridevaux, J.L., 2015, Modeling apple snail population dynamics on the Everglades landscape: Landscape Ecology, v. 30, no. 8, p. 1497-1510, https://doi.org/10.1007/s10980-015-0205-5.","productDescription":"14 p.","startPage":"1497","endPage":"1510","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056099","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":306812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.1060791015625,\n 25.199970890386023\n ],\n [\n -83.1060791015625,\n 28.338230147025865\n ],\n [\n -79.8486328125,\n 28.338230147025865\n ],\n [\n -79.8486328125,\n 25.199970890386023\n ],\n [\n -83.1060791015625,\n 25.199970890386023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"8","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-22","publicationStatus":"PW","scienceBaseUri":"560bb6d5e4b058f706e53d8b","contributors":{"authors":[{"text":"Darby, Phil","contributorId":146459,"corporation":false,"usgs":false,"family":"Darby","given":"Phil","email":"","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":567951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":138934,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":567949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"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":567950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suir, Kevin J. 0000-0003-1570-9648 suirk@usgs.gov","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":4894,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","email":"suirk@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":567952,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bridevaux, Joshua L.","contributorId":103567,"corporation":false,"usgs":true,"family":"Bridevaux","given":"Joshua","email":"","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":567953,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70144908,"text":"pp1813 - 2015 - Mercury and methylmercury in reservoirs in Indiana","interactions":[],"lastModifiedDate":"2015-05-20T15:39:27","indexId":"pp1813","displayToPublicDate":"2015-05-20T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1813","title":"Mercury and methylmercury in reservoirs in Indiana","docAbstract":"Mercury (Hg) is an element that occurs naturally, but evidence suggests that human activities have resulted in increased amounts being released to the atmosphere and land surface. When Hg is converted to methylmercury (MeHg) in aquatic ecosystems, MeHg accumulates and increases in the food web so that some fish contain levels which pose a health risk to humans and wildlife that consume these fish. Reservoirs unlike natural lakes, are a part of river systems that are managed for flood control. Data compiled and interpreted for six flood-control reservoirs in Indiana showed a relation between Hg transport, MeHg formation in water, and MeHg in fish that was influenced by physical, chemical, and biological differences among the reservoirs. Existing information precludes a uniform comparison of Hg and MeHg in all reservoirs in the State, but factors and conditions were identified that can indicate where and when Hg and MeHg levels in reservoirs could be highest.
\nAs part of a statewide monitoring network for Hg and MeHg in Indiana streams, 66 water samples were collected from four reservoir tailwater sites (downstream near the dams) on a quarterly schedule for 5 years. The reservoirs were Brookville Lake, Cagles Mill Lake, J. Edward Roush Lake, and Mississinewa Lake. Particulate-bound Hg concentrations were significantly lower in tailwater samples than in samples from free-flowing streams in the statewide network. (Free-flowing streams were not affected by dams and were not upstream from these reservoirs.) These data indicated the reduced flow velocity of water upstream from dams was allowing particulate-bound Hg to settle out of the water in the reservoir pools. The concentration ratios of MeHg to Hg were significantly higher in the tailwater samples than in samples from free-flowing streams, and the MeHg to Hg ratios were significantly higher in summer than in other seasons.
\nTo evaluate the conditions related to MeHg formation, pools of three reservoirs (Brookville Lake, Monroe Lake, and Patoka Lake) were investigated during summer hydrologic conditions. Water temperature and dissolved oxygen were measured from the water surface to the lake bottom at 10 to 17 transects across each reservoir to identify three thermal strata, defined by water temperature, dissolved oxygen concentration, and depth. Depth-specific water samples were collected from these thermal strata throughout each reservoir, from the headwaters to the dam and from the tailwater. Mercury concentrations higher than 0.04 nanogram per liter (ng/L) were detected in all 53 samples, and MeHg concentrations higher than 0.04 ng/L were detected in 53 percent of the samples.
\nThe investigation found a zone of water below 8 or 9 meters, with temperatures less than 18 degrees Celsius and dissolved oxygen less than 3.5 milligrams per liter, extending through nearly half the reservoir area in Monroe Lake and Patoka Lake. This zone had abundant dissolved MeHg and concentration ratios of dissolved MeHg to Hg that ranged from 25 to 82 percent. This zone also had water with pH less than 7 and decreased dissolved sulfate, conditions indicating sulfate reduction by microorganisms that promoted a high potential for the conversion of Hg to MeHg. Reservoir outflow came from this zone at Monroe Lake and contributed to a tailwater concentration ratio for dissolved MeHg to Hg of 56 percent. Reservoir outflow at Patoka Lake was not from this zone, and dissolved MeHg was not detected in the tailwater. In contrast, samples from the summer pool at Brookville Lake had no MeHg detections even though Hg was detected, probably because the water pH higher than 7 inhibited sulfate reduction and did not promote the conversion of Hg to MeHg.
\nMercury and MeHg concentrations and the concentration ratios of MeHg to Hg in water varied among the six reservoirs in Indiana, and the differences were related to a combination of factors that could apply to other reservoirs. In areas with moderate to high rates of atmospheric Hg wet and dry deposition, Hg runoff and transport to streams and reservoirs was potentially highest for reservoirs with heavily forested watersheds in steep terrains of near-surface bedrock. Methylmercury concentrations and concentration ratios of MeHg to Hg were highest for reservoirs with the longest summer pools and highest inflow-to-outflow retention times, where water-chemistry conditions favoring sulfate reduction promoted conversion of Hg to MeHg.
\nMethylmercury (reported as Hg) in fish-tissue samples collected for the State fish consumption advisory program was used to describe MeHg food-web accumulation and magnification in the reservoirs. The highest percentages of fish-tissue samples with Hg concentrations that exceeded the criterion of 0.30 milligram per kilogram for protection of human health were from Monroe Lake (38 percent) and Patoka Lake (33 percent). A review of the number and size of fish species caught from these two reservoirs resulted in two implications for fish consumption by humans. First, the highest numbers of fish harvested for potential human consumption were species more likely to have MeHg concentrations lower than the human-health criterion (crappie, bluegill, and catfish). Second, although largemouth bass were likely to have MeHg concentrations higher than the human-health criterion, they were caught and released more often than they were harvested. However, the average size largemouth bass (in both reservoirs) and above-average size walleye (in Monroe Lake) that were harvested for potential human consumption were likely to have MeHg concentrations higher than the human-health criterion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1813","usgsCitation":"Risch, M.R., and Fredericksen, A.L., 2015, Mercury and methylmercury in reservoirs in Indiana: U.S. Geological Survey Professional Paper 1813, vii, 57 p., https://doi.org/10.3133/pp1813.","productDescription":"vii, 57 p.","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-032724","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":300626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1813.jpg"},{"id":300624,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1813/pdf/pp1813.pdf","text":"Report","size":"6.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300623,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1813/"}],"country":"United States","state":"Indiana","otherGeospatial":"Brookville Lake, Cagles Mill Lake, J. 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Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fredericksen, Amanda L. afredericksen@usgs.gov","contributorId":2440,"corporation":false,"usgs":true,"family":"Fredericksen","given":"Amanda","email":"afredericksen@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":543841,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70146632,"text":"sim3326 - 2015 - Water-table and potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers of Long Island, New York, April-May 2013","interactions":[],"lastModifiedDate":"2016-06-23T16:08:43","indexId":"sim3326","displayToPublicDate":"2015-05-18T23:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3326","title":"Water-table and potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers of Long Island, New York, April-May 2013","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with State and local agencies, systematically collects groundwater data at varying measurement frequencies to monitor the hydrologic conditions on Long Island, New York. Each year during April and May, the USGS conducts a synoptic survey of water levels to define the spatial distribution of the water table and potentiometric surfaces within the three main water-bearing units underlying Long Island—the upper glacial, Magothy, and Lloyd aquifers (Smolensky and others, 1989)—and the hydraulically connected Jameco (Soren, 1971) and North Shore aquifers (Stumm, 2001). These data and the maps constructed from them are commonly used in studies of Long Island's hydrology and are utilized by water managers and suppliers for aquifer management and planning purposes.
\nWater-level measurements made in 502 monitoring wells (observation and supply wells) and 16 streamgage locations across Long Island during April–May 2013 were used to prepare the maps in this report. Groundwater measurements were made by the wetted-tape method to the nearest hundredth of a foot. Contours of water-table and potentiometric-surface altitudes were created by using the groundwater measurements. The water-table contours were interpreted by using water-level data collected from 16 streamgages, 334 observation wells, and 1 supply well screened in the upper glacial aquifer or the shallow Magothy aquifer; the Magothy aquifer's potentiometric-surface contours were interpreted from measurements at 70 observation wells and 31 supply wells screened in the middle to deep Magothy aquifer and the contiguous and hydraulically connected Jameco aquifer. The Lloyd aquifer's potentiometric-surface contours were interpreted from measurements at 58 observation wells and 8 supply wells screened in the Lloyd aquifer and the contiguous and hydraulically connected North Shore aquifer. Many of the supply wells are in continuous operation and therefore, were turned off for a minimum of 24 hours before measurements were made to allow the water levels in the wells to recover to ambient (non-pumping) conditions. Full recovery time at some of these supply wells can exceed 24 hours; therefore, water levels measured at these wells are assumed to be less accurate than those measured at observation wells, which are not pumped (Busciolano, 2002). In addition to pumping stresses, elevated chloride concentrations (saline water) also lower the water levels measured in certain wells. This reduction in water level is the result of saline water being denser than freshwater (Lusczynski, 1961). In this report, all water-level altitudes are referenced to the National Geodetic Vertical Datum of 1929 (NGVD 29).
\nThe land surface or topography was downloaded from the National Map portal (http://nationalmap.gov), which represents the most currently available terrain representation as a 10-meter digital elevation model (DEM). The National Map terrain representation was combined with additional land surface terrain models of Suffolk County and New York City, which were collected using lidar to produce a high accuracy three-dimensional land surface altitude model based on the geospatial product for coastal flood mapping. The datum for land surface altitude is North American Vertical Datum of 1988 (NAVD 88). On Long Island NAVD 88 is approximately 1-foot lower than NGVD 29.
\nHydrographs are included on these maps for selected wells that have digital recording equipment. These hydrographs are representative of the 2013 water year to show the changes that have occurred throughout that period. The synoptic survey water level measured at the well is included on each hydrograph.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3326","collaboration":"Prepared in cooperation with the Long Island Water Conference, Nassau County Department of Public Works, New York City Department of Environmental Protection, Port Washington Water District, Suffolk County Department of Health Services, Towns of North Hempstead and Shelter Island, Manhasset-Lakeville Water District, Nassau Suffolk Water Commissioners Association, New York State Department of Environmental Conservation, Sands Point Water Department, Suffolk County Water Authority, Water Authority of Great Neck North","usgsCitation":"Como, M.D., Noll, M.L., Finkelstein, J.S., Monti, J., and Busciolano, R., 2015, Water-table and potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers of Long Island, New York, April-May 2013: U.S. Geological Survey Scientific Investigations Map 3326, Pamphlet: 8 p.; 4 Plates: 72.0 x 34.0 inches, https://doi.org/10.3133/sim3326.","productDescription":"Pamphlet: 8 p.; 4 Plates: 72.0 x 34.0 inches","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2013-04-01","temporalEnd":"2013-05-31","ipdsId":"IP-060337","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":300539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3326.JPG"},{"id":300535,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s1p.pdf","text":"Sheet 1 (Water table)","size":"11.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (11.3 MB)","linkHelpText":"SIM 3326 Sheet 1"},{"id":300533,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3326/"},{"id":300538,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s4p.pdf","text":"Sheet 4 (Depth to water table)","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (11.1 MB)","linkHelpText":"SIM 3326 Sheet 4"},{"id":300534,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326.pdf","text":"Text Pamphlet","size":"78 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIM 3326 Text"},{"id":300536,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s2p.pdf","text":"Sheet 2 (Potentiometric surface in the Magothy and Jameco aquifers)","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (11.2 MB)","linkHelpText":"SIM 3326 Sheet 2"},{"id":300537,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s3p.pdf","text":"Sheet 3 (Potentiometric surface in the Lloyd and North Shore aquifers)","size":"17.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (17.8 MB)","linkHelpText":"SIM 3326 Sheet 3"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.80615234375,\n 40.80965166748856\n ],\n [\n -73.9434814453125,\n 40.78054143186031\n ],\n [\n -74.014892578125,\n 40.730608477796636\n ],\n [\n -74.0643310546875,\n 40.61812224225511\n ],\n [\n -74.0093994140625,\n 40.56389453066509\n ],\n [\n -73.9324951171875,\n 40.53050177574321\n ],\n [\n -73.2843017578125,\n 40.60561205826018\n ],\n [\n -72.8668212890625,\n 40.72644570551446\n ],\n [\n -71.8011474609375,\n 41.075210270566636\n ],\n [\n -71.949462890625,\n 41.08763212467916\n ],\n [\n -72.125244140625,\n 41.13729606112276\n ],\n [\n -72.257080078125,\n 41.15797827873605\n ],\n [\n -72.333984375,\n 41.166249339091976\n ],\n [\n -72.6251220703125,\n 41.0130657870063\n ],\n [\n -73.1524658203125,\n 40.98819156349393\n ],\n [\n -73.4051513671875,\n 40.95915977213492\n ],\n [\n -73.7127685546875,\n 40.89275342420696\n ],\n [\n -73.80615234375,\n 40.80965166748856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180
(518) 285-5600
http://ny.water.usgs.gov
The Pressure Water Level Data Logger manufactured by Infinities USA, Inc., was evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility for conformance with the manufacturer’s stated accuracy specifications for measuring pressure throughout the device’s operating temperature range and with the USGS accuracy requirements for water-level measurements. The Pressure Water Level Data Logger (Infinities Logger) is a submersible, sealed, water-level sensing device with an operating pressure range of 0 to 11.5 feet of water over a temperature range of −18 to 49 degrees Celsius. For the pressure range tested, the manufacturer’s accuracy specification of 0.1 percent of full scale pressure equals an accuracy of ±0.138 inch of water. Three Infinities Loggers were evaluated, and the testing procedures followed and results obtained are described in this report. On the basis of the test results, the device is poorly compensated for temperature. For the three Infinities Loggers, the mean pressure differences varied from –4.04 to 5.32 inches of water and were not within the manufacturer’s accuracy specification for pressure measurements made within the temperature-compensated range. The device did not meet the manufacturer’s stated accuracy specifications for pressure within its temperature-compensated operating range of –18 to 49 degrees Celsius or the USGS accuracy requirements of no more than 0.12 inch of water (0.01 foot of water) or 0.10 percent of reading, whichever is larger. The USGS accuracy requirements are routinely examined and reported when instruments are evaluated at the Hydrologic Instrumentation Facility. The estimated combined measurement uncertainty for the pressure cycling test was ±0.139 inch of water, and for temperature, the cycling test was ±0.127 inch of water for the three Infinities Loggers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151049","usgsCitation":"Carnley, M.V., 2015, Laboratory evaluation of the pressure water level data logger manufactured by Infinities USA, Inc.: results of pressure and temperature tests: U.S. Geological Survey Open-File Report 2015-1049, iv, 14 p., https://doi.org/10.3133/ofr20151049.","productDescription":"iv, 14 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059926","costCenters":[{"id":339,"text":"Hydrologic Instrumentation Facility","active":false,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":300469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151049.jpg"},{"id":300467,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1049/"},{"id":300468,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1049/pdf/ofr2015-1049.pdf","text":"Report","size":"974 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555aff21e4b0a92fa7eac5ce","contributors":{"authors":[{"text":"Carnley, Mark V. mcarnley@usgs.gov","contributorId":2723,"corporation":false,"usgs":true,"family":"Carnley","given":"Mark","email":"mcarnley@usgs.gov","middleInitial":"V.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":542490,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148060,"text":"70148060 - 2015 - Diel cycling of trace elements in streams draining mineralized areas: a review","interactions":[],"lastModifiedDate":"2018-08-09T12:41:06","indexId":"70148060","displayToPublicDate":"2015-05-18T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Diel cycling of trace elements in streams draining mineralized areas: a review","docAbstract":"Many trace elements exhibit persistent diel, or 24-h, concentration cycles in streams draining mineralized areas. These cycles can be caused by various physical and biogeochemical mechanisms including streamflow variation, photosynthesis and respiration, as well as reactions involving photochemistry, adsorption and desorption, mineral precipitation and dissolution, and plant assimilation. Iron is the primary trace element that exhibits diel cycling in acidic streams. In contrast, many cationic and anionic trace elements exhibit diel cycling in near-neutral and alkaline streams. Maximum reported changes in concentration for these diel cycles have been as much as a factor of 10 (988% change in Zn concentration over a 24-h period). Thus, monitoring and scientific studies must account for diel trace-element cycling to ensure that water-quality data collected in streams appropriately represent the conditions intended to be studied.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.05.008","usgsCitation":"Gammons, C.H., Nimick, D.A., and Parker, S.R., 2015, Diel cycling of trace elements in streams draining mineralized areas: a review: Applied Geochemistry, v. 57, p. 35-44, https://doi.org/10.1016/j.apgeochem.2014.05.008.","productDescription":"10 p.","startPage":"35","endPage":"44","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041373","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":300462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555aff1fe4b0a92fa7eac5c6","contributors":{"authors":[{"text":"Gammons, Chris","contributorId":140801,"corporation":false,"usgs":false,"family":"Gammons","given":"Chris","affiliations":[{"id":13574,"text":"Montana Tech of the University of Montana, Butte, MT","active":true,"usgs":false}],"preferred":false,"id":547019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nimick, David A. dnimick@usgs.gov","contributorId":421,"corporation":false,"usgs":true,"family":"Nimick","given":"David","email":"dnimick@usgs.gov","middleInitial":"A.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"preferred":true,"id":547018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, Stephen R.","contributorId":140802,"corporation":false,"usgs":false,"family":"Parker","given":"Stephen","email":"","middleInitial":"R.","affiliations":[{"id":13574,"text":"Montana Tech of the University of Montana, Butte, MT","active":true,"usgs":false}],"preferred":false,"id":547020,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70138888,"text":"sir20145238 - 2015 - Status and understanding of groundwater quality in the Cascade Range and Modoc Plateau study unit, 2010: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2015-05-18T09:11:07","indexId":"sir20145238","displayToPublicDate":"2015-05-18T08:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5238","title":"Status and understanding of groundwater quality in the Cascade Range and Modoc Plateau study unit, 2010: California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the Cascade Range and Modoc Plateau study unit was investigated as part of the California State Water Resources Control Board’s Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. The study was designed to provide a statistically unbiased assessment of untreated groundwater quality in the primary aquifer system. The depth of the primary aquifer system for the Cascade Range and Modoc Plateau study unit was delineated by the depths of the screened or open intervals of wells in the State of California’s database of public-supply wells. Two types of assessments were made: a status assessment that described the current quality of the groundwater resource, and an understanding assessment that made evaluations of relations between groundwater quality and potential explanatory factors representing characteristics of the primary aquifer system. The assessments characterize the quality of untreated groundwater, not the quality of treated drinking water delivered to consumers by water distributors.
\nThe status assessment was based on water-quality data collected in 2010 by the U.S. Geological Survey from 90 wells and springs (USGS-grid wells) and on water-quality data compiled from the State of California’s regulatory compliance database for samples collected from 240 public-supply wells between September 2007 and September 2010. To provide context, the water-quality data discussed in this report were compared to California and Federal drinking-water regulatory and non-regulatory benchmarks for treated drinking water. Groundwater quality is defined in terms of relative concentrations (RCs), which are calculated by dividing the concentration of a constituent in groundwater by the concentration of the benchmark for that constituent. The RCs for inorganic constituents (major ions, trace elements, nutrients, and radioactive constituents) were classified as “high” (the RC is greater than 1.0, indicating that the concentration is above the benchmark), “moderate” (the RC is from 1.0 to greater than 0.5), or “low” (the RC is less than or equal to 0.5). For organic constituents (volatile organic compounds and pesticides) and special-interest constituents (perchlorate), the boundary between moderate and low RCs was set at 0.1. All benchmarks used for organic constituents were health-based. For inorganic constituents, health-based and aesthetic-based benchmarks were used. Constituents without benchmarks were not considered in the status assessment.
\nThe primary metric used for quantifying regional-scale groundwater quality was the aquifer-scale proportion—the areal percentages of the primary aquifer system with high, moderate, and low RCs for a given constituent or class of constituents. The study unit was divided into six study areas on the basis of geologic differences (Eastside Sacramento Valley, Honey Lake Valley groundwater basin, Cascade Range and Modoc Plateau Low Use Basins, Quaternary Volcanic Areas, Shasta Valley and Mount Shasta Volcanic Area, and Tertiary Volcanic Areas), and each study area was divided into equal-area grid cells. Aquifer-scale proportions were calculated for individual constituents and constituent classes for each of the six study areas and for the study unit as a whole by using grid-based (one well per cell) and spatially weighted (many wells per cell) statistical methods.
\nThe status assessment showed that inorganic constituents were present at high and moderate RCs in greater proportions of the Cascade Range and Modoc Plateau study unit than were organic constituents. One or more inorganic constituents with health-based benchmarks were present at high RCs in 9.4 percent, and at moderate RCs in 14.7 percent of the primary aquifer system. Arsenic was present at high RCs in approximately 3 percent of the primary aquifer system; boron, molybdenum, uranium, and vanadium each were present at high RCs in approximately 2 percent of the primary aquifer system. One or more inorganic constituents with aesthetic-based benchmarks were present at high RCs in 15.1 percent of the primary aquifer system and at moderate RCs in 4.9 percent. Manganese, iron, and total dissolved solids were present at high RCs in approximately 12 percent, 5 percent, and 2 percent, respectively, of the primary aquifer system.
\nOrganic constituents were not detected at high or moderate RCs in the primary aquifer system, and one or more organic constituents were detected at low RCs in approximately 40 percent of the primary aquifer system.
\nTwo classes of organic constituents were detected in more than 10 percent of the primary aquifer system: trihalomethanes (chloroform only) and herbicides. The special interest constituent perchlorate was not detected at high RCs, but was detected at moderate RCs in approximately 2 percent of the primary aquifer system.
\nThe understanding assessment relied on statistical tests to evaluate relations between concentrations of constituents and values of potential explanatory factors representing geology, land use, well construction, hydrologic conditions, groundwater age, and geochemical conditions.
\nThe majority of the high and moderate RCs of arsenic, boron, molybdenum, uranium, and total dissolved solids were in samples from the Honey Lake Valley groundwater basin study area. Groundwater mixing with hydrothermal fluids present in the study area, evaporative concentration of groundwater in the Honey Lake playa, presence of uranium-bearing sediment derived from the adjacent Sierra Nevada, and release of arsenic and other trace elements from sediments under high pH and low dissolved oxygen conditions all appeared to contribute to these elevated concentrations. Thermal springs are in many parts of the Cascade Range and Modoc Plateau study unit and could account for locally elevated concentrations of arsenic, boron, molybdenum, and total dissolved solids in samples from the other study areas. Vanadium concentrations were greater in oxic samples than in anoxic samples, but were not correlated with pH, contrary to expectations from previous studies.
\nOrganic constituents were not detected at high or moderate RCs, and the occurrence of low organic constituents at low RCs ranged from 27 percent to 73 percent of the primary aquifers system in the six study areas. The Shasta Valley and Mount Shasta Volcanic study area had significantly greater occurrence of low RCs of herbicides compared to all of the other study areas, which could reflect the greater prevalence of modern groundwater in the Shasta Valley and Mount Shasta Volcanic study area and the presence of potential sources of herbicides, including applications to timberlands and roadside rights-of-way. The Eastside Sacramento Valley study area had the greatest occurrence of low concentrations of chloroform, and chloroform occurrence was most strongly associated with the combination of septic-tank density greater than two tanks per square kilometer and urban land use greater than 10 percent within a radius of 500 meters of the well. These conditions were most prevalent in the Eastside Sacramento Valley study area. The detection frequency of low concentrations of perchlorate was consistent with the probability of occurrence expected under natural conditions, except in the Eastside Sacramento Valley study area, where detection frequencies were much higher than expected and could not be explained by known anthropogenic sources of perchlorate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145238","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S., and Shelton, J.L., 2015, Status and understanding of groundwater quality in the Cascade Range and Modoc Plateau study unit, 2010: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5238, xii, 131 p., https://doi.org/10.3133/sir20145238.","productDescription":"xii, 131 p.","numberOfPages":"147","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-033356","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":300460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145238.jpg"},{"id":300457,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5238/pdf/sir2014-5238.pdf","text":"Report","size":"28.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300444,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5238/"}],"projection":"Albers Equal Area Projection","datum":"North American Datum of 1983","country":"United States","state":"California","otherGeospatial":"Cascade Range, Modoc Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.99954223632812,\n 41.99522219923445\n ],\n [\n -122.57720947265624,\n 42.00695837037897\n ],\n [\n -122.50236511230467,\n 41.8322234439287\n ],\n [\n -122.66716003417969,\n 41.75543440328294\n ],\n [\n -122.66166687011719,\n 41.679066225164114\n ],\n [\n -122.55935668945312,\n 41.61492897332632\n ],\n [\n -122.60261535644531,\n 41.53839396783225\n ],\n [\n -122.57377624511719,\n 41.484405435611926\n ],\n [\n -122.48382568359374,\n 41.448902743309674\n ],\n [\n -122.45361328124999,\n 41.32732632036622\n ],\n [\n -122.200927734375,\n 41.244772343082076\n ],\n [\n -122.09381103515624,\n 41.20552261955812\n ],\n [\n -121.80816650390625,\n 41.18278832811288\n ],\n [\n -121.805419921875,\n 41.135227480564936\n ],\n [\n -121.92352294921874,\n 41.11660732012894\n ],\n [\n -122.01141357421875,\n 40.94671366508002\n ],\n [\n -121.9757080078125,\n 40.863679665481676\n ],\n [\n -122.11303710937499,\n 40.72228267283148\n ],\n [\n -122.2174072265625,\n 40.697299008636755\n ],\n [\n -122.12677001953124,\n 40.214538129296336\n ],\n [\n -121.68182373046875,\n 39.67125632523974\n ],\n [\n -121.56921386718751,\n 39.69450749856091\n ],\n [\n -121.0748291015625,\n 40.17467622056341\n ],\n [\n -121.01303100585938,\n 40.287906612507406\n ],\n [\n -120.97183227539061,\n 40.29209669470104\n ],\n [\n -120.904541015625,\n 40.27428705136608\n ],\n [\n -120.96908569335938,\n 40.395718433470364\n ],\n [\n -120.948486328125,\n 40.42499671108253\n ],\n [\n -120.68206787109375,\n 40.408267826445226\n ],\n [\n -120.36621093749999,\n 40.14633904771964\n ],\n [\n -120.24261474609374,\n 40.10538669840983\n ],\n [\n -120.00091552734375,\n 39.902362098539705\n ],\n [\n -119.99954223632812,\n 41.99522219923445\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555aff21e4b0a92fa7eac5d0","contributors":{"authors":[{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148053,"text":"70148053 - 2015 - Evapotranspiration trends over the eastern United States during the 20th century","interactions":[],"lastModifiedDate":"2019-09-04T14:35:57","indexId":"70148053","displayToPublicDate":"2015-05-14T10:45:00","publicationYear":"2015","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":"Evapotranspiration trends over the eastern United States during the 20th century","docAbstract":"Most models evaluated by the Intergovernmental Panel for Climate change estimate projected increases in temperature and precipitation with rising atmospheric CO2 levels. Researchers have suggested that increases in CO2 and associated increases in temperature and precipitation may stimulate vegetation growth and increase evapotranspiration (ET), which acts as a cooling mechanism, and on a global scale, may slow the climate-warming trend. This hypothesis has been modeled under increased CO2 conditions with models of different vegetation-climate dynamics. The significance of this vegetation negative feedback, however, has varied between models. Here we conduct a century-scale observational analysis of the Eastern US water balance to determine historical evapotranspiration trends and whether vegetation greening has affected these trends. We show that precipitation has increased significantly over the twentieth century while runoff has not. We also show that ET has increased and vegetation growth is partially responsible.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"Katlenburg-Lindau, Germany","doi":"10.3390/hydrology2020093","usgsCitation":"Kramer, R.J., Bounoua, L., Zhang, P., Wolfe, R.E., Huntington, T.G., Imhoff, M.L., Thome, K., and Noyce, G.L., 2015, Evapotranspiration trends over the eastern United States during the 20th century: Hydrology and Earth System Sciences, v. 2, no. 2, p. 93-111, https://doi.org/10.3390/hydrology2020093.","productDescription":"19 p.","startPage":"93","endPage":"111","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056810","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":472089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology2020093","text":"Publisher Index Page"},{"id":300464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-14","publicationStatus":"PW","scienceBaseUri":"555b0d43e4b0a92fa7eac61c","contributors":{"authors":[{"text":"Kramer, Ryan J.","contributorId":140788,"corporation":false,"usgs":false,"family":"Kramer","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":546977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bounoua, Lahouari","contributorId":140790,"corporation":false,"usgs":false,"family":"Bounoua","given":"Lahouari","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":546979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Ping","contributorId":140789,"corporation":false,"usgs":false,"family":"Zhang","given":"Ping","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":546978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolfe, Robert E.","contributorId":56560,"corporation":false,"usgs":true,"family":"Wolfe","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":546980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":1884,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Imhoff, Marc L.","contributorId":140791,"corporation":false,"usgs":false,"family":"Imhoff","given":"Marc","email":"","middleInitial":"L.","affiliations":[{"id":13566,"text":"Joint Global Change Research Institute, Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":546981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thome, Kurt","contributorId":140792,"corporation":false,"usgs":false,"family":"Thome","given":"Kurt","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":546982,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Noyce, Genevieve L.","contributorId":140793,"corporation":false,"usgs":false,"family":"Noyce","given":"Genevieve","email":"","middleInitial":"L.","affiliations":[{"id":13567,"text":"Goddard Space Flight Center, 100 St. George Street, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":546983,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70148002,"text":"70148002 - 2015 - Temperature impacts on the water year 2014 drought in California","interactions":[],"lastModifiedDate":"2017-01-18T10:02:44","indexId":"70148002","displayToPublicDate":"2015-05-12T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Temperature impacts on the water year 2014 drought in California","docAbstract":"California is experiencing one of the worst droughts on record. Here we use a hydrological model and risk assessment framework to understand the influence of temperature on the water year (WY) 2014 drought in California and examine the probability that this drought would have been less severe if temperatures resembled the historical climatology. Our results indicate that temperature played an important role in exacerbating the WY 2014 drought severity. We found that if WY 2014 temperatures resembled the 1916–2012 climatology, there would have been at least an 86% chance that winter snow water equivalent and spring-summer soil moisture and runoff deficits would have been less severe than the observed conditions. We also report that the temperature forecast skill in California for the important seasons of winter and spring is negligible, beyond a lead-time of one month, which we postulate might hinder skillful drought prediction in California.
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University","active":true,"usgs":false}],"preferred":false,"id":546724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":546720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145954,"text":"sir20155053 - 2015 - Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling","interactions":[],"lastModifiedDate":"2015-05-12T09:30:22","indexId":"sir20155053","displayToPublicDate":"2015-05-12T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5053","title":"Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling","docAbstract":"The Lake Michigan Diversion Accounting (LMDA) system has been developed by the U.S. Army Corps of Engineers, Chicago District (USACE-Chicago) and the State of Illinois as a part of the interstate Great Lakes water regulatory program. The diverted Lake Michigan watershed is a 673-square-mile watershed that is comprised of the Chicago River and Calumet River watersheds. They originally drained into Lake Michigan, but now flow to the Mississippi River watershed via three canals constructed in the Chicago area in the early twentieth century. Approximately 393 square miles of the diverted watershed is ungaged, and the runoff from the ungaged portion of the diverted watershed has been estimated by the USACE-Chicago using the Hydrological Simulation Program-FORTRAN (HSPF) program. The accuracy of simulated runoff depends on the accuracy of the parameter set used in the HSPF program. Nine parameter sets comprised of the North Branch, Little Calumet, Des Plaines, Hickory Creek, CSSC, NIPC, 1999, CTE, and 2008 have been developed at different time periods and used by the USACE-Chicago. In this study, the U.S. Geological Survey and the USACE-Chicago collaboratively analyzed the parameter sets using nine gaged watersheds in or adjacent to the diverted watershed to assess the predictive accuracies of selected parameter sets. Six of the parameter sets, comprising North Branch, Hickory Creek, NIPC, 1999, CTE, and 2008, were applied to the nine gaged watersheds for evaluating their simulation accuracy from water years 1996 to 2011. The nine gaged watersheds were modeled by using the three LMDA land-cover types (grass, forest, and hydraulically connected imperviousness) based on the 2006 National Land Cover Database, and the latest meteorological and precipitation data consistent with the current (2014) LMDA modeling framework.
\nResults indicate that the North Branch and Hickory Creek parameter sets, which belong to the original calibration group, attained an overall “satisfactory” rating on monthly runoff volumes based on the three performance statistics selected, but the annual and over-the-period runoff volumes were generally underestimated. Parameter sets CTE and 2008 attained a similar satisfactory rating on monthly runoff volumes but the annual and over-the-period runoff volumes were overestimated in general. Although the percent bias was improved, the CTE and 2008 parameter sets also had increased residuals in monthly runoff volumes and decreased quality of the model fit to the measured streamflows relative to the North Branch and Hickory Creek parameter sets. The NIPC and 1999 parameter sets, on the other hand, had larger percent bias and residuals in monthly runoff volumes, and underestimated the annual and over-the-period runoff volumes.
\nRecalibration of the HSPF parameters to the updated inputs and land covers was completed on two representative watershed models selected from the nine by using a manual method (HSPEXP) and an automatic method (PEST). The objective of the recalibration was to develop a regional parameter set that improves the accuracy in runoff volume prediction for the nine study watersheds. Knowledge about flow and watershed characteristics plays a vital role for validating the calibration in both manual and automatic methods. The best performing parameter set was determined by the automatic calibration method on a two-watershed model. Applying this newly determined parameter set to the nine watersheds for runoff volume simulation resulted in “very good” ratings in five watersheds, an improvement as compared to “very good” ratings achieved for three watersheds by the North Branch parameter set.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155053","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Soong, D.T., and Over, T.M., 2015, Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling: U.S. Geological Survey Scientific Investigations Report 2015-5053, vii, 55 p., https://doi.org/10.3133/sir20155053.","productDescription":"vii, 55 p.","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044193","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":300319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155053.jpg"},{"id":300317,"rank":1,"type":{"id":15,"text":"Index 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New Mexico, FY 2015","docAbstract":"The U.S. Geological Survey (USGS) has collected hydrologic information in New Mexico since 1889, beginning with the first USGS streamflow-gaging station in the Nation, located on the Rio Grande near Embudo, New Mexico. Water-resources information provided by the USGS is used by many government agencies for issuing flood warnings to protect lives and reduce property damage,managing water rights and interstate water use, protecting water quality and regulating pollution discharges, designing highways and bridges, planning, designing, and operating reservoirs and watersupply facilities, monitoring the availability of groundwater resources and forecasting aquifer response to human and environmental stressors, and prioritizing areas where emergency erosion mitigation or other protective measures may be necessary after a wildfire. For more than 100 years, the Cooperative Water Program has been a highly successful cost-sharing partnership between the USGS and water-resources agencies at the State, local, and tribal levels. It would be difficult to effectively accomplish the mission of the USGS without the contributions of the Cooperative Water Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153039","usgsCitation":"Mau, D.P., 2015, U.S. Geological Survey water-resources programs in New Mexico, FY 2015: U.S. Geological Survey Fact Sheet 2015-3039, 2 p., https://doi.org/10.3133/fs20153039.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065455","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":300283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153039.jpg"},{"id":300282,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3039/pdf/fs2015-3039.pdf","text":"Report","size":"439 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300281,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3039/"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.072265625,\n 31.31610138349565\n ],\n [\n -108.226318359375,\n 31.3348710339506\n ],\n [\n -108.21533203125,\n 31.77487761850741\n ],\n [\n -106.490478515625,\n 31.77487761850741\n ],\n [\n -106.622314453125,\n 31.98012335736804\n ],\n [\n -103.07373046875,\n 31.99875937194732\n ],\n [\n -102.996826171875,\n 37.00255267215955\n ],\n [\n -109.072265625,\n 37.01132594307015\n ],\n [\n -109.072265625,\n 31.31610138349565\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5551c4abe4b0a92fa7e93b98","contributors":{"authors":[{"text":"Mau, David P. dpmau@usgs.gov","contributorId":457,"corporation":false,"usgs":true,"family":"Mau","given":"David","email":"dpmau@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":546408,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144853,"text":"ofr20151065 - 2015 - Results from laboratory and field testing of nitrate measuring spectrophotometers","interactions":[],"lastModifiedDate":"2015-05-12T13:25:42","indexId":"ofr20151065","displayToPublicDate":"2015-05-11T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1065","title":"Results from laboratory and field testing of nitrate measuring spectrophotometers","docAbstract":"Five ultraviolet (UV) spectrophotometer nitrate analyzers were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) during a two-phase evaluation. In Phase I, the TriOS ProPs (10-millimeter (mm) path length), Hach NITRATAX plus sc (5-mm path length), Satlantic Submersible UV Nitrate Analyzer (SUNA, 10-mm path length), and S::CAN Spectro::lyser (5-mm path length) were evaluated in the HIF Water-Quality Servicing Laboratory to determine the validity of the manufacturer's technical specifications for accuracy, limit of linearity (LOL), drift, and range of operating temperature. Accuracy specifications were met in the TriOS, Hach, and SUNA. The stock calibration of the S::CAN required two offset adjustments before the analyzer met the manufacturer's accuracy specification. Instrument drift was observed only in the S::CAN and was the result of leaching from the optical path insert seals. All tested models, except for the Hach, met their specified LOL in the laboratory testing. The Hach's range was found to be approximately 18 milligrams nitrogen per liter (mg-N/L) and not the manufacturer-specified 25 mg-N/L. Measurements by all of the tested analyzers showed signs of hysteresis in the operating temperature tests. Only the SUNA measurements demonstrated excessive noise and instability in temperatures above 20 degrees Celsius (°C). The SUNA analyzer was returned to the manufacturer at the completion of the Phase II field deployment evaluation for repair and recalibration, and the performance of the sensor improved significantly.
\nIn Phase II, the analyzers were deployed in field conditions at three diferent USGS sites. The measured nitrate concentrations were compared to discrete (reference) samples analyzed by the Direct UV method on a Shimadzu UV1800 bench top spectrophotometer, and by the National Environmental Methods Index (NEMI) method I-2548-11 at the USGS National Water Quality Laboratory. The first deployment at USGS site 0249620 on the East Pearl River in Hancock County, Mississippi, tested the ability of the TriOs ProPs (10-mm path length), Hach NITRATAX (5 mm), Satlantic SUNA (10 mm), and the S::CAN Spectro::lyser (5 mm) to accurately measure low-level (less than 2 mg-N/L) nitrate concentrations while observing the effect turbidity and colored dissolved organic matter (CDOM) would have on the analyzers' measurements. The second deployment at USGS site 01389005 Passaic River below Pompton River at Two Bridges, New Jersey, tested the analyzer's accuracy in mid-level (2-8 mg-N/L) nitrate concentrations. This site provided the means to test the analyzers' performance in two distinct matrices—the Passaic and the Pompton Rivers. In this deployment, three instruments tested in Phase I (TriOS, Hach, and SUNA) were deployed with the S::CAN Spectro::lyser (35 mm) already placed by the New Jersey Water Science Center (WSC). The third deployment at USGS site 05579610 Kickapoo Creek at 2100E Road near Bloomington, Illinois, tested the ability of the analyzers to measure high nitrate concentrations (greater than 8 mg-N/L) in turbid waters. For Kickapoo Creek, the HIF provided the TriOS (10 mm) and S::CAN (5 mm) from Phase I, and a SUNA V2 (5 mm) to be deployed adjacent to the Illinois WSC-owned Hach (2 mm). A total of 40 discrete samples were collected from the three deployment sites and analyzed. The nitrate concentration of the samples ranged from 0.3–22.2 mg-N/L. The average absolute difference between the TriOS measurements and discrete samples was 0.46 mg-N/L. For the combined data from the Hach 5-mm and 2-mm analyzers, the average absolute difference between the Hach samples and the discrete samples was 0.13 mg-N/L. For the SUNA and SUNA V2 combined data, the average absolute difference between the SUNA samples and the discrete samples was 0.66 mg-N/L. The average absolute difference between the S::CAN samples and the discrete samples was 0.63 mg-N/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151065","usgsCitation":"Snazelle, T., 2015, Results from laboratory and field testing of nitrate measuring spectrophotometers: U.S. Geological Survey Open-File Report 2015-1065, v, 15 p., https://doi.org/10.3133/ofr20151065.","productDescription":"v, 15 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057525","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":300295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151065.jpg"},{"id":300294,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1065/pdf/ofr2015-1065.pdf","text":"Report","size":"2.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300293,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1065/"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5551c4aae4b0a92fa7e93b94","contributors":{"authors":[{"text":"Snazelle, Teri T. tsnazelle@usgs.gov","contributorId":5663,"corporation":false,"usgs":true,"family":"Snazelle","given":"Teri T.","email":"tsnazelle@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":543804,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}