This report presents electron microprobe data on glasses and selected crystalline phases from Kīlauea Iki lava lake and glasses from the 1959 summit eruption of Kīlauea Volcano, Hawaii. Some of these data have been published previously, but the complete set has not been published before. In addition, this report includes electron microprobe data for phases in melting experiments reported earlier, which form the basis for using many of the glass compositions reported here to estimate quenching temperatures of the samples. Finally, because of the latter application, this report includes all useful field determinations of temperature taken in Kīlauea Iki boreholes from 1967 to 1988. These field measurements have been merged with geothermometry based on glass and Fe-Ti oxide compositions to produce a comprehensive review of all available thermal information for Kīlauea Iki. Making these datasets available completes documentation of field and chemical information on Kīlauea Iki lava lake, supplementing six previous U.S. Geological Survey Open-File Reports listed in the References Cited.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201012","usgsCitation":"Helz, R.T., 2020, Major-element compositional data and thermal data for drill core from Kīlauea Iki lava lake, plus analyses of glasses from scoria of the 1959 summit eruption of Kīlauea Volcano, Hawaii (ver 1.1, December 2021): U.S. Geological Survey Open-File Report 2020–1012, 48 p., https://doi.org/10.3133/ofr20201012.","productDescription":"Report: v, 48 p.; Appendix 1-2","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109981","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":374174,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012_appendix1.xlsx","text":"Appendix 1","size":"206 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Tables 1.1–1.13 as an Excel file"},{"id":374175,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012_appendix2.xlsx","text":"Appendix 2","size":"48.5 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Tables 2.1–2.4 as an Excel file"},{"id":374172,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1012/coverthb2.jpg"},{"id":374177,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201021_appendix2_csv.zip","text":"Appendix 2","size":"5.50 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 2.1–2.4 as CSV files in a zipped folder"},{"id":374205,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012.pdf","text":"Report","size":"3.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1012"},{"id":392665,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1012/versionHist.txt","size":"691 B","linkFileType":{"id":2,"text":"txt"}},{"id":374176,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201021_appendix1_csv.zip","text":"Appendix 1","size":"41.5 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 1.1–1.13 as CSV files in a zipped folder"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30410766601562,\n 19.38759093442151\n ],\n [\n -155.2306365966797,\n 19.38759093442151\n ],\n [\n -155.2306365966797,\n 19.44846418467642\n ],\n [\n -155.30410766601562,\n 19.44846418467642\n ],\n [\n -155.30410766601562,\n 19.38759093442151\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 23, 2020; Version 1.1: December 15, 2021","contact":"Director, Florence Bascom Geoscience Center
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To define and prioritize focus areas across the United States with resource potential for 35 critical minerals in a few years’ time, the U.S Geological Survey Earth Mapping Resources Initiative (Earth MRI) required an efficient approach to streamline workflow. A mineral systems approach based on current understanding of how ore deposits that contain critical minerals form and relate to broader geologic frameworks and the tectonic history of the Earth was used to satisfy this Earth MRI need. This report describes the rationale for, and structure of, a table developed for Earth MRI that relates critical minerals and principal commodities to the deposit types and mineral systems in which they are concentrated. The hierarchical relationship between systems, deposits, commodities, and critical minerals makes it possible to define and prioritize each system-based focus area once for all of the critical minerals that it may contain. This approach is advantageous because mineral systems are much larger than individual ore deposits and they generally have geologic features that can be “imaged” by the topographic, geologic, geochemical, and geophysical mapping techniques deployed by Earth MRI.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201042","usgsCitation":"Hofstra, A.H., and Kreiner, D.C., 2020, Systems-Deposits-Commodities-Critical Minerals Table for the Earth Mapping Resources Initiative (ver. 1.1, May 2021): U.S. Geological Survey Open-File Report 2020–1042, 26 p., \nhttps://doi.org/10.3133/ofr20201042.","productDescription":"Report: vii, 24 p.; Table","onlineOnly":"Y","ipdsId":"IP-115500","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":374652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1042/coverthb2.jpg"},{"id":374653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1042/ofr20201042.pdf","text":"Report","size":"3.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1042"},{"id":374654,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1042/ofr20201042_table1.pdf","text":"Table 1. Systems-Deposits-Commodities-Critical Minerals Table for the Earth Mapping Resources Initiative","size":"196 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1042 Table 1"},{"id":385684,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1042/versionHist.txt","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020-1042 version history"}],"edition":"Version 1.0: May 28, 2020; Version 1.1: May 19, 2021","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
MS 973, Box 25046
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Below average and infrequent rainfall from May through September 2020 led to an extreme hydrologic drought across much of New England, with some areas experiencing a flash drought, reflecting its quick onset. The U.S. Geological Survey (USGS) recorded record-low streamflow and groundwater levels throughout the region. In September, the U.S. Department of Agriculture (2020) declared Aroostook County in Maine and Hillsborough and Merrimack Counties in New Hampshire as crop disaster areas. By the beginning of October, 166 community water systems and 5 municipalities in New Hampshire, more than 100 municipalities in Massachusetts, and several community water supplies in Connecticut, Maine, and Rhode Island had mandatory water restrictions in place.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201148","usgsCitation":"Lombard, P.J., Barclay, J.R., and McCarthy, D.E., 2020, 2020 drought in New England (ver. 1.1, February 2021): U.S. Geological Survey Open-File Report 2020–1148, 12 p., https://doi.org/10.3133/ofr20201148.","productDescription":"Report: 12 p.; 3 Figures; 2 Tables","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-124096","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":383216,"rank":9,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1148/ofr20201148.pdf","text":"Report","size":"21.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1148"},{"id":383215,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1148/ofr20201148_versionHist.txt","size":"2.33 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In response to a co-occurring non-native scale infestation and Phragmites australis dieback in southeast Louisiana, normalized difference vegetation index (NDVI) satellite mapping was implemented to track P. australis condition in the lower Mississippi River Delta. While the NDVI mapping successfully documented relative condition changes, identification of cause required a quantitative-biophysical metric directly related to P. australis marsh live vegetation proportion. During this study, a satellite mapping tool that quantified P. australis live fraction cover (LFC) magnitude was designed and implemented. The key to development of the quantitative LFC mapping was the field to satellite calibration design. The calibration of P. australis marsh LFC to optical satellite image data combined field and near-in-time satellite data collections in the fall of 2018 and summer of 2019. Basing the field-NDVI to field-LFC calibrations and the satellite-NDVI to field-NDVI calibrations on combined pre-senescence and peak-growth period data offers nearly year-round LFC mapping. The utility of the developed P. australis marsh LFC mapping tool was demonstrated by the creation of a yearly suite of Mississippi River Delta LFC status and change maps extending from 2009 to 2019. P. australis marsh LFC mapping relies on Sentinel-2 for current to future mapping and relies on Landsat for historical mapping.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201131","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Rangoonwala, A., Howard, R.J., and Ramsey, E.W., III, 2020, Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana (ver. 1.1, January 2021): U.S. Geological Survey Open-File Report 2020–1131, 24 p., https://doi.org/10.3133/ofr20201131.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-119555","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":381145,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ASPB4E","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phragmites australis live fractional cover yearly map from 2009 to 2019 of the lower Mississippi River Delta using Landsat and Sentinel-2 satellite data"},{"id":381143,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1131/coverthb2.jpg"},{"id":381144,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1131/ofr20201131.pdf","text":"Report","size":"6.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1131"},{"id":382663,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1131/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020–1131 version history"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.54544067382812,\n 28.930045059458923\n ],\n [\n -89.000244140625,\n 28.930045059458923\n ],\n [\n -89.000244140625,\n 29.40371231103247\n ],\n [\n -89.54544067382812,\n 29.40371231103247\n ],\n [\n -89.54544067382812,\n 28.930045059458923\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 14, 2020; Version 1.1: January 27, 2021","contact":"Director, Wetland and Aquatic Research Center
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Lafayette, Louisiana 70506
Bathymetric geoprocessing analyses of the Florida Reef Tract have provided insights into trends of seafloor accretion and seafloor erosion over time and following major storm events. However, bathymetric surveys sometimes capture manmade structures and vegetation, which do not represent the desired bare-earth data. Therefore, ground truthing is essential to maintain the most accurate bathymetric data possible. Field procedures were developed in the Florida Reef Tract in order to quickly and accurately collect consistent imagery and habitat data across variable sites. Areas of significant elevation change were determined through elevation change analyses; these areas were targeted for ground truthing in order to check the reliability of the surveys. This report outlines the standard operating procedures for underwater photographic imagery and habitat data collection, as well as procedures for the storage of these photographs and associated metadata. These standard operating procedures ensure the reproducibility of photographic operations and habitat data collection in future field excursions, enable longitudinal visual comparisons alongside seafloor elevation change analyses, and also have the potential to be applied to similar studies in different coastal environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201118","usgsCitation":"Fehr, Z.W., and Yates, K.K., 2020, Underwater photographic reconnaissance and habitat data collection in the Florida Keys—A procedure for ground truthing remotely sensed bathymetric data: U.S. Geological Survey Open-File Report 2020–1118, 13 p., https://doi.org/10.3133/ofr20201118.","productDescription":"vii, 13 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114891","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":381619,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1118/ofr20201118.pdf","text":"Report","size":"5.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1118"},{"id":381618,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1118/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.53665161132812,\n 25.022150920405707\n ],\n [\n -80.1177978515625,\n 25.022150920405707\n ],\n [\n -80.1177978515625,\n 25.336579097268118\n ],\n [\n -80.53665161132812,\n 25.336579097268118\n ],\n [\n -80.53665161132812,\n 25.022150920405707\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
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This report presents potentiometric-surface maps of the Aquia and Magothy aquifers and the Upper Patapsco, Lower Patapsco, and Patuxent aquifer systems using water levels measured during the fall season of 2019. The potentiometric surface maps show water levels ranging from 56 feet above sea level to 163 feet below sea level in the Aquia aquifer, from 87 feet above sea level to 119 feet below sea level in the Magothy aquifer, from 114 feet above sea level to 120 feet below sea level in the Upper Patapsco aquifer system, from 136 feet above sea level to 174 feet below sea level in the Lower Patapsco aquifer system, and from 168 feet above sea level to 184 feet below sea level in the Patuxent aquifer system.
Cones of depression have formed around locations with significant aquifer withdrawals. The Aquia aquifer has depressed water levels around well fields at Lexington Park, Solomons Island, and central Talbot County. Cones of depression have formed in the Magothy aquifer around well fields at Waldorf, Arnold, and Easton. The Upper Patapsco aquifer system has depressed water levels around well fields in the Annapolis-Arnold area, Waldorf, the Lexington Park-Leonardtown area, and at Easton. The Lower Patapsco aquifer system has depressed water levels around well fields at Severndale, Broad Creek, Arnold, and Crofton Meadows as well as in central and western Charles County. Cones of depression have formed in the Patuxent aquifer system around well fields at Dorsey Road, Crofton, Arnold, northwestern Charles County, and at the Chalk Point power plant.
","language":"English","publisher":"Maryland Department of Natural Resources","usgsCitation":"Staley, A.W., Andreasen, D.C., and Marchand, E.H., 2020, Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019: Open-File Report 20-02-01, iii, 37 p.","productDescription":"iii, 37 p.","ipdsId":"IP-120572","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":390041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390040,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.mgs.md.gov/reports/OFR_20-02-01.pdf"}],"country":"United 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Center","active":true,"usgs":true}],"preferred":true,"id":808013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217046,"text":"ofr20201142 - 2020 - Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska","interactions":[],"lastModifiedDate":"2020-12-30T12:49:16.90443","indexId":"ofr20201142","displayToPublicDate":"2020-12-29T16:50:00","publicationYear":"2020","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":"2020-1142","displayTitle":"Changing Storm Conditions in Response to Projected 21st Century Climate Change and the Potential Impact on an Arctic Barrier Island–Lagoon System—A Pilot Study for Arey Island and Lagoon, Eastern Arctic Alaska","title":"Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska","docAbstract":"Arey Lagoon, located in eastern Arctic Alaska, supports a highly productive ecosystem, where soft substrate and coastal wet sedge fringing the shores are feeding grounds and nurseries for a variety of marine fish and waterfowl. The lagoon is partially protected from the direct onslaught of Arctic Ocean waves by a barrier island chain (Arey Island) which in itself provides important habitat for migratory shorebirds and waterfowl. In this work, numerically modeled waves and water levels are computed under the provision of sea-level rise and changing conditions brought about by 21st century climate variability. Model results, supported by observations, are used to assess the stability of the barrier chain and spatiotemporal changes in flood patterns across fringing coastal wet sedge areas. The results aim to support studies that investigate the possibility of new biological succession trajectories and loss or increase of habitat areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201142","collaboration":"Prepared in cooperation with and funded in part by the Arctic Landscape Conservation Cooperation (ALCC)","usgsCitation":"Erikson, L.H., Gibbs, A.E., Richmond, B.M., Storlazzi, C.D., Jones, B.M., and Ohman, K.A., 2020, Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska: U.S. Geological Survey Open-File Report 2020–1142, 68, p., https://doi.org/10.3133/ofr20201142.","productDescription":"Report: x, 68 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-079323","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":381735,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LGYO2Q","text":"USGS data release","linkHelpText":"Modeled 21st century storm surge, waves, and coastal flood hazards and supporting oceanographic and geological field data (2010 and 2011) for Arey and Barter Islands, Alaska and vicinity"},{"id":381739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1142/coverthb.jpg"},{"id":381740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1142/ofr20201142.pdf","text":"Report","size":"8.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1142"}],"country":"United States","state":"Alaska","otherGeospatial":"Arey Island and Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -144.09805297851562,\n 70.03559723423488\n ],\n [\n -143.6407470703125,\n 70.03559723423488\n ],\n [\n -143.6407470703125,\n 70.13476515043729\n ],\n [\n -144.09805297851562,\n 70.13476515043729\n ],\n [\n -144.09805297851562,\n 70.03559723423488\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Stewart B. McKinney National Wildlife Refuge in Connecticut. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $1,190,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $1,190,000 included controlling avian predators in both management units, managing stormwater on lands adjacent to one marsh management unit, and removing a tide gate and breaching a dike to improve tidal flow in the other marsh management unit. The management benefits were derived from expected increases in the numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and an expected decrease in the use of herbicides to control invasive vegetation. The prototype presented here provides a framework for decision making at the Stewart B. McKinney National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201139","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Low, L.E. , Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Vagos, K., and Potvin, R., 2020, Optimization of salt marsh management at the Stewart B. McKinney National Wildlife Refuge, Connecticut, through use of structured decision making: U.S. Geological Survey Open-File Report 2020–1139, 28 p., https://doi.org/10.3133/ofr20201139.","productDescription":"vi, 28 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120812","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381645,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1139/ofr20201139.pdf","text":"Report","size":"2.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1139"},{"id":381644,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1139/coverthb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Stewart B. McKinney National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.17169189453125,\n 41.15022321163024\n ],\n [\n -73.13186645507812,\n 41.13677892209895\n ],\n [\n -73.10028076171875,\n 41.14867208811923\n ],\n [\n -73.15177917480469,\n 41.18537216794189\n ],\n [\n -73.18113327026366,\n 41.17090135180691\n ],\n [\n -73.17169189453125,\n 41.15022321163024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708–4039
Hanford, Washington (USA) is the construction site of a multi-billion-dollar high-level nuclear waste treatment facility. This site lies 200 kilometers (km) east of Mount St. Helens (MSH), the most active volcano in the contiguous United States. Tephra from a future MSH eruption could pose a hazard to the air intake and filtration systems at this plant. In this report, we present a probabilistic estimate of the amount of tephra that could fall, and the concentrations of airborne ash that could occur at the Hanford Site during a future eruption. Mount St. Helens has produced four large explosive eruptions in approximately the past 500 years, suggesting that its annual probability of eruption (P1) is roughly 4/500=0.008. Assuming that a large eruption occurs, we calculate the probability (P3|1) of a given fall deposit thickness or airborne concentration at Hanford by running about 10,000 simulations of ash-producing eruptions using the atmospheric transport model Ash3d. In each simulation, we calculate the pattern of tephra dispersal, deposit thickness at Hanford, and airborne ash concentration at ground level. As input for each simulation, we choose meteorological conditions from a randomly chosen time in the historical record between 1980 and 2010, using data from the European Centre for Medium-Range Weather Forecasting (ECMWF) Reanalysis (ERA) Interim model. The volume (dense-rock equivalent) of each simulated eruption is randomly chosen from a uniform probability distribution on a log scale from the range of magma volumes (0.008–2.3 cubic kilometers [km3]) estimated for late Holocene eruptions at MSH. Plume heights and durations of each eruption are chosen using empirical correlations between volume, height, and eruption rate, which account for the fact that larger eruptions have higher plumes and last longer. We construct summary tables of final deposit thickness (T), maximum ground-level airborne concentration (Cmax), and average ground-level airborne concentration (Cavg) during tephra-fall for each run. Each table is sorted and ranked by decreasing value of T, Cmax, or Cavg. Conditional probabilities (P3|1) are derived by dividing rank by n+1, where n is the total number of successful runs. For example, a deposit thickness of 5.10 centimeters (cm) from run 446 is ranked 123 of 9,785 successful runs, yielding P3|1=123/9,786=0.01257. Its annual probability is P=P1·P3|1=0.008×0.01257=0.000101. By interpolation, the deposit thickness (T10k) having an annual probability of 1 in 10,000 (P= 0.0001) is 5.11 cm. Analogous concentration values are Cmax,10k=3,819 and Cavg,10k=1,513 milligrams per cubic meter (mg/m3), respectively. Independent calculations using the known mass accumulation rate of the deposit (=0.001–0.006 kilograms per square meter per second [kg/m2/s]), aggregate fall velocities (u=0.3–0.8 meters per second [m/s]), and the simple formula , yield similar results, although highly variable fall velocities add significant uncertainty. This formula implies that deposit accumulation rates of millimeters (mm) to greater than 1 cm per hour, which are not uncommon during heavy ash fall, are associated with airborne concentrations of 102–103 milligrams per cubic meter (mg/m3). These concentrations are much higher than published measurements (10-3–101 mg/m3), which record only suspended particles sampled in sheltered areas. During heavy ashfall, most fine ash falls as aggregates. Whether such aggregates will be ingested into air ducts will depend on the aggregate size and fall rate, the fragility of the aggregates, the air duct geometry, intake velocity, and other factors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201133","collaboration":"Prepared in cooperation with the U.S. Department of Energy, Office of River Protection","usgsCitation":"Mastin, L.G., Van Eaton, A., and Schwaiger, H.F., 2020, A probabilistic assessment of tephra-fall hazards at Hanford, Washington, from a future eruption of Mount St. Helens: U.S. Geological Survey Open-File Report 2020–1133, 54 p., https://doi.org/10.3133/ofr20201133.","productDescription":"Report: ix, 54 p.; Data Release","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-112179","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":381546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1133/covrthb.jpg"},{"id":381547,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1133/ofr20201133.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381548,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VPFXQR","linkHelpText":"Data Used to Develop A Probabilistic Assessment of Tephra-Fall Hazards at Hanford, Washington"}],"country":"United States","state":"Washington","otherGeospatial":"Hanford","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.88281249999999,\n 46.33175800051563\n ],\n [\n -119.2950439453125,\n 46.33175800051563\n ],\n [\n -119.2950439453125,\n 46.81509864599243\n ],\n [\n -119.88281249999999,\n 46.81509864599243\n ],\n [\n -119.88281249999999,\n 46.33175800051563\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683
About one-quarter of the water supply for the Village of Ruidoso, New Mexico, is from groundwater pumped from wells located along North Fork Eagle Creek in the National Forest System lands of the Lincoln National Forest near Alto, New Mexico. Because of concerns regarding the effects of groundwater pumping on surface-water hydrology in the North Fork Eagle Creek Basin and the effects of the 2012 Little Bear Fire, which resulted in substantial loss of vegetation in the basin, the U.S. Department of Agriculture Forest Service, Lincoln National Forest, has required monitoring of a portion of North Fork Eagle Creek for short-term geomorphic change as part of the permitting decision that allows for the continued pumping of the production wells. The objective of this study is to address the geomorphic monitoring requirements of the permitting decision by conducting annual geomorphic surveys of North Fork Eagle Creek along the stream reach between the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station (U.S. Geological Survey [USGS] site 08387550) and the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station (USGS site 08387600). The monitoring of short-term geomorphic change in the stream reach began in June 2017 with surveys of select cross sections and surveys of all woody debris accumulations and pools found in the channel. In June 2018, the monitoring of short-term geomorphic change continued with another geomorphic survey of the stream reach (with some modification to the monitoring methods).
The 2017 and 2018 surveys were conducted by the USGS, in cooperation with the Village of Ruidoso, and were the first two in a planned series of five annual geomorphic surveys. The results of the 2017 geomorphic survey were summarized and interpreted in a previous USGS Open-File Report, and the data were published in the companion data release of that report. In this report, the results of the 2018 geomorphic survey are summarized, interpreted, and compared to the results of the 2017 survey. The data from the 2018 geomorphic survey are published in the companion data release of this report.
The study reach surveyed in June 2018 is 1.89 miles long, beginning about 260 feet upstream from the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station and ending at the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station. Large sections of the study reach are characterized by intermittent streamflow, and where streamflow is normally continuous (including at the upper and lower portions of the study reach, near the streamflow-gaging stations), the streamflow typically remains less than 2 cubic feet per second throughout the year except during seasonal high flows, which most often result from rainfall during the North American monsoon months of July, August, and September or from snowmelt runoff in March, April, and May. Between the 2017 and 2018 surveys, high-flow events resulting from both rainfall (during the North American monsoon season) and snowmelt runoff (during the winter) occurred in the study reach, and those high-flow events appeared to have caused some minor and localized geomorphic changes in the study reach, which were evaluated through comparison of the 2017 and 2018 survey results.
For the 2017 geomorphic survey of North Fork Eagle Creek, cross sections were established and surveyed at 14 locations along the study reach, and in 2018, those same 14 cross sections were resurveyed. Comparisons of the cross-section survey results indicated that minor observable geomorphic changes had occurred in 3 of the 14 cross sections. These minor observable geomorphic changes included aggradation or degradation of surface materials by about 1–2 feet in some parts of the affected cross sections.
To further assess geomorphic changes within the study reach, other features, including woody debris accumulations and pools, were surveyed in both 2017 and 2018. During the 2018 geomorphic survey, 112 distinct accumulations of woody debris and 71 pools were identified in the study reach. Charred wood or burn-marked wood was present in at least 17 of the identified woody debris accumulations (and was present in some of the woody debris accumulations identified during the 2017 survey), indicating that some of the woody debris in the channel may have been sourced from trees or forest litter that had burned during 2012 Little Bear Fire. Only 22 of the 112 woody debris accumulations identified during the 2018 survey were certain to have also been present during the 2017 survey (when 58 woody debris accumulations were identified), indicating that most of the woody debris accumulations surveyed in 2017 were likely transported during the high-flow events between the 2017 and 2018 surveys but also indicating that the flows during those events were not high enough to remove some of the more firmly anchored woody debris accumulations. Most woody debris accumulations identified in 2018 did not appear to have substantially influenced geomorphic change in the locations where they were found. However, the formation of 10 of the 71 pools identified in the study reach in 2018 appeared to have been influenced by the presence of woody debris, indicating that some woody debris accumulations may have driven local geomorphic changes. Notably, pool totals from the 2017 survey could not be accurately compared to the pool totals from the 2018 survey because of differences between the two surveys in the methods used to identify pools.
Because the study began 5 years after the 2012 Little Bear Fire, and because the period and geomorphic scope of the study have so far been limited, it cannot be said that the geomorphic changes observed between the 2017 and 2018 surveys are representative of a pattern of geomorphic change following the 2012 Little Bear Fire. Though, once geomorphic changes between the 2017 and 2018 surveys can be compared with results from geomorphic surveys planned for 2019, 2020, and 2021, it may be possible to develop an understanding of the patterns in geomorphic change following the 2012 Little Bear Fire.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201121","collaboration":"Prepared in cooperation with the Village of Ruidoso, New Mexico","usgsCitation":"Graziano, A.P., 2020, Geomorphic survey of North Fork Eagle Creek, New Mexico, 2018: U.S. Geological Survey Open-File Report 2020–1121, 37 p., https://doi.org/10.3133/ofr20201121.","productDescription":"Report: v, 37 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-112737","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":381235,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1121/ofr20201121.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1121"},{"id":381236,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94ZQHKU","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data supporting the 2018 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":381234,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1121/coverthb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"North Fork Eagle Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.5621337890625,\n 32.99023555965106\n ],\n [\n -104.7930908203125,\n 32.99023555965106\n ],\n [\n -104.7930908203125,\n 33.770015152780125\n ],\n [\n -105.5621337890625,\n 33.770015152780125\n ],\n [\n -105.5621337890625,\n 32.99023555965106\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the fourth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. The report contains information pertinent to data collection during the 2019 water year, from October 2018 to September 2019. No changes to the previously installed data collection network were made during this period.
Discharge and salinity varied widely during the data collection period, which included above-average rainfall for all counties in the study area over the 3-month period from November to January, below-average annual rainfall for all counties, and effects from Hurricane Dorian in September 2019. Total annual rainfall for all counties ranked third among the annual totals computed for the 4 years considered for this study. Annual mean discharge at Durbin Creek was highest among the tributaries, followed by Trout River, Ortega River, Julington Creek, Pottsburg Creek, Broward River, Cedar River, Clapboard Creek, and Dunn Creek. The annual mean discharge for each of the main-stem sites was lower for the 2019 water year than for the 2018 water year. Since the beginning of the study in 2016, the St. Johns River at Astor station computed its lowest annual mean discharge, the Jacksonville station recorded its second lowest, and the Buffalo Bluff station recorded its second highest in 2019.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which was expected. Relative to annual mean salinity calculated for the 2018 water year, annual mean salinity at all monitoring locations was higher for the 2019 water year except at the main-stem site below Shands Bridge and at the tributary sites of Durbin Creek and Julington Creek, which remained the same. The 2019 annual mean salinity at Dunn Creek was the highest on record for that site, and Clapboard Creek and Trout River were the second highest on record for those sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201140","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2020, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019: U.S. Geological Survey Open-File Report 2020–1140, 48 p., https://doi.org/10.3133/ofr20201140.","productDescription":"ix, 48 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-118214","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":381275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1140/coverthb.jpg"},{"id":381276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1140/ofr20201140.pdf","text":"Report","size":"7.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1140"}],"country":"United States","state":"Florida","otherGeospatial":"St John's River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93878173828125,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 29.1161749329972\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Biological conservation is a fundamental purpose of the National Park system, and Catoctin Mountain Park (CATO) supports high-quality habitat for native fishes in the headwaters of the Chesapeake Bay watershed in eastern North America. However, native Blue Ridge sculpin (Cottus caeruleomentum) have been extirpated in Big Hunting Creek above Cunningham Falls in CATO. Prior research indicates that infection by the fungal-like protist Dermocystidium is a likely cause for the extirpation, but elevated stream temperatures also have been observed in the study area, and it remains unknown whether thermal stress may exacerbate infections or otherwise limit habitat suitability for fishes in CATO.
The purpose of this study was to quantify spatial variation in summer stream temperatures and to evaluate the effects of temperature on sculpin growth rates and susceptibility to Dermocystidium infection. We used observational and experimental methods to address these objectives. First, we deployed stream temperature gages at 10 sites throughout the study area to assess hourly and daily temperatures during the summer of 2019. Second, we conducted an in situ fish enclosure experiment at five of the temperature sites to assess fish growth and susceptibility to Dermocystidium infection over a 45-day exposure period. For this experiment we collected sculpin from a stream in CATO that supports a robust population of Blue Ridge sculpin (Owens Creek) and held them in quarantine for 50 days in the Experimental Stream Laboratory at the U.S. Geological Survey (USGS) Leetown Science Center. Pre-exposure histopathology confirmed the absence of Dermocystidium infection prior to the introduction of fish into experimental enclosures.
We found that stream temperatures were warmer where sculpin have been extirpated than elsewhere in CATO where sculpin persist. However, the fish enclosure experiment revealed a positive effect of temperature on fish growth, suggesting that increased food availability and foraging rates compensated for increased metabolic demands in the warmest sites. Moreover, fish held in enclosures did not develop Dermocystidium infection. Our results therefore suggest that current environmental conditions in upper Big Hunting Creek may be suitable for Blue Ridge sculpin reintroduction, and this could ultimately lead to sportfishing opportunities by increasing the forage base for native brook trout (Salvelinus fontinalis).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201137","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Hitt, N.P., Kessler, K.G., Kelly, Z.A., Rogers, K.M., Macmillan, H.E., and Walsh, H.L., 2020, Assessing native fish restoration potential in Catoctin Mountain Park: U.S. Geological Survey Open-File Report 2020–1137, 17 p., https://doi.org/10.3133/ofr20201137.","productDescription":"Report: vii, 17 p.; Data Release","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122955","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381222,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P950A13P","text":"USGS data release","linkHelpText":"Stream temperature and sculpin growth data collected from Catoctin Mountain Park in 2019"},{"id":381221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1137/ofr20201137.pdf","text":"Report","size":"4.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1137"},{"id":381220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1137/coverthb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Catoctin Mountain Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51781463623047,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.60621720230201\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
White-nose syndrome (WNS) is an emerging infectious disease of hibernating bats caused by a fungus previously known as Geomyces destructans and reclassified as Pseudogymnoascus destructans. The disease was first documented in 2006 in New York, has since spread across much of eastern North America, and as of January 2012, had caused the death of at least 5.7 to 6.7 million bats. Previous studies have suggested that environmental conditions play a strong role in WNS mortality. However, to predict where and when the disease will spread to new sites is difficult because detailed site information and associated environmental data are notably sparse. This paper presents a chronology of where and when WNS was detected in North America before October 2011 and indicates who reported the infections. This paper also presents available data on WNS-infected site elevation, geology, sediment chemistry and biota, air temperature, and relative humidity.
By the end of September 2011, at least 241 known WNS-infected sites were in North America and the number of infected sites per winter season had increased each year since 2006. The progressive increase in the number of infected sites per winter season suggests that the number of WNS infections had not peaked as of the 2010–11 winter season. WNS-infected sites include caves and mines, but the sites are not restricted by elevation, lithology, or strata age. Available data on site sediment chemistry are sparse but present a wide range of values, suggesting that caves and mines may contain a great range of microenvironments that are still poorly understood. The distribution of WNS may be restricted by air temperature and relative humidity. Published air temperature values from WNS-infected sites range from −15 to 33 degrees Celsius (but most temperature values are less than 20 degrees Celsius), and relative humidity values range from 50 to 100 percent. The spread of WNS may be restricted by a cave or mine temperature threshold of 20 degrees Celsius (which is likely to be south of most of the continental United States) and by some yet to be determined threshold of low relative humidity. These results indicate that WNS may not spread south into Mexico or to Puerto Rico.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201117","usgsCitation":"Swezey, C.S., and Garrity, C.P., 2020, Environmental data associated with sites infected with white-nose syndrome (WNS) before October 2011 in North America: U.S. Geological Survey Open-File Report 2020–1117, 67 p., https://doi.org/10.3133/ofr20201117.","productDescription":"x, 67 p.","numberOfPages":"67","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-117667","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":381184,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1117/coverthb.jpg"},{"id":381185,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1117/ofr20201117.pdf","text":"Report","size":"19.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1117"}],"country":"Canada, United States","state":"Connecticut, Delaware, Indiana, Kentucky, Maine, Maryland, Massachsetts, Missouri, New Brunswick, New Hampshire, New Jersey, New York, North Carolina, Nova Scotia, Ohio, Oklahoma, Ontario, Pennsylvania, Quebec, Tennessee, Vermont, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.95898437499999,\n 33.797408767572485\n ],\n [\n -75.673828125,\n 35.88905007936091\n ],\n [\n -74.53125,\n 39.436192999314095\n ],\n [\n -73.65234375,\n 40.78054143186033\n ],\n [\n -70.13671875,\n 42.16340342422401\n ],\n [\n -64.775390625,\n 43.389081939117496\n ],\n [\n -59.4140625,\n 46.31658418182218\n ],\n [\n -65.390625,\n 49.724479188712984\n ],\n [\n -66.0498046875,\n 54.521081495443596\n ],\n [\n -79.4970703125,\n 54.62297813269033\n ],\n [\n -89.296875,\n 56.77680831656842\n ],\n [\n -95.44921875,\n 52.669720383688166\n ],\n [\n -95.2294921875,\n 49.03786794532644\n ],\n [\n -89.7802734375,\n 48.37084770238366\n ],\n [\n -83.935546875,\n 46.9502622421856\n ],\n [\n -81.9580078125,\n 43.70759350405294\n ],\n [\n -83.5400390625,\n 41.64007838467894\n ],\n [\n -86.8798828125,\n 41.83682786072714\n ],\n [\n -87.451171875,\n 41.57436130598913\n ],\n [\n -88.24218749999999,\n 37.47485808497102\n ],\n [\n -89.2529296875,\n 36.56260003738545\n ],\n [\n -90.04394531249999,\n 35.24561909420681\n ],\n [\n -85.5615234375,\n 34.95799531086792\n ],\n [\n -82.880859375,\n 34.994003757575776\n ],\n [\n -82.265625,\n 35.15584570226544\n ],\n [\n -81.01318359375,\n 35.08395557927643\n ],\n [\n -79.716796875,\n 34.77771580360469\n ],\n [\n -78.486328125,\n 33.815666308702774\n ],\n [\n -77.95898437499999,\n 33.797408767572485\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The Upper Floridan aquifer is the uppermost, reliable aquifer in southwest Georgia. The aquifer lies on top of the Claiborne, Clayton, and Cretaceous aquifers, all of which exhibited water level declines in the 1960s and 1970s. The U.S. Geological Survey has been working cooperatively with Albany Utilities to monitor groundwater quality and availability in these aquifers since 1977.
During January 2020, nine wells were sampled—six for anions, metals, and nitrate plus nitrite as nitrogen, and three for anions, metals, and pesticides. Nitrate plus nitrite as nitrogen concentrations ranged from 2.4 milligrams per liter (mg/L) to 10.4 mg/L, and no pesticides were detected. Nitrate plus nitrite as nitrogen concentrations in well 12L277, open to the Upper Floridan aquifer, have been above the U.S. Environmental Protection Agency Maximum Contaminant Level of 10 mg/L for nitrates in drinking water since 2014.
Flow direction in the Upper Floridan aquifer is to the south and toward the Flint River. Water levels varied during the past year above and below period of record median values. Water levels in the Upper Floridan aquifer were primarily above median levels. Water levels in the Claiborne aquifer were above median levels, whereas water levels in the Clayton and Cretaceous aquifers were below median levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201120","collaboration":"Prepared in cooperation with Albany Utilities","usgsCitation":"Gordon, D.W., 2020, Groundwater quality and groundwater levels in Dougherty County, Georgia, April 2019 through March 2020: U.S. Geological Survey Open-File Report 2020–1120, 12 p., https://doi.org/10.3133/ofr20201120.","productDescription":"vi, 12 p.","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118275","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":380954,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1120/coverthb.jpg"},{"id":380955,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1120/ofr20201120.pdf","text":"Report","size":"1.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1120"}],"country":"United 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South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
Over the past few decades (1990–2019), the United States has become reliant on foreign sources to meet domestic demand for a large and growing number of mineral commodities. In combination with recent trends towards progressively concentrated supply of mineral commodities from a limited number of countries, this heightened import reliance may increase the risk to the United States economy and national security. Several factors obscure the true net import reliance of mineral commodities essential to the United States, including indirect trade reliance, embedded trade reliance, and foreign ownership. This report provides a detailed overview of contributions to and trends of these mineral commodity supply risks and provides an outline of the salient factors pertaining to each mineral commodity’s supply chain. It also describes some additional considerations and provides a general framework for evaluating different strategies aimed at reducing net import reliance and supply risk.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201127","usgsCitation":"Nassar, N.T., Alonso, E., and Brainard, J.L., 2020, Investigation of U.S. Foreign Reliance on Critical Minerals—U.S. Geological Survey Technical Input Document in Response to Executive Order No. 13953 Signed September 30, 2020 (Ver. 1.1, December 7, 2020): U.S. Geological Survey Open-File Report 2020–1127, 37 p., https://doi.org/10.3133/ofr20201127.","productDescription":"vii, 37 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123693","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":381043,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1127/ofr20201127.pdf","text":"Report","size":"4.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1127"},{"id":381064,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1127/versionHist.txt","size":"1.4 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1127/coverthb3.jpg"}],"edition":"Version 1.0: December 4, 2020; Version 1.1: December 7, 2020","contact":"National Minerals Information Center
U.S. Geological Survey
988 National Center
12201 Sunrise Valley Drive
Reston, VA 20191
The western subspecies of the purple martin (Progne subis arboricola) is currently listed as a “critically” sensitive species in four ecoregions of western Oregon: Coast Range, Klamath Mountains, West Cascades, and Willamette Valley (Oregon Department of Fish and Wildlife, 2019). Importantly distinct from the abundant and widespread eastern subspecies (Progne subis subis), the western subspecies is of particular concern to Federal forest managers. Whereas the eastern subspecies is almost entirely dependent on artificial human-provided housing, the western subspecies continues to rely on natural cavities for nesting habitat (Bettinger, 2003). Accurate estimates of the regional abundance of the western purple martin are difficult to obtain; the most recent statewide census for Oregon, conducted in 2005, estimated the population at 1,100 pairs (Western Purple Martin Working Group, 2010). Several factors, including a small population size, loss of breeding habitat, and reductions in the number of suitable nesting sites have put populations of the western purple martin at risk throughout much of the Pacific Northwest region (Rockwell, 2019).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201130","usgsCitation":"Hagar, J.C., and Branch, E.C., 2020, Western purple martin (Progne subis arboricola) occurrence on the Siuslaw National Forest, summer 2019: U.S. Geological Survey Open-File Report 2020-1130, 25 p., https://doi.org/10.3133/ofr20201130.","productDescription":"iv, 25 p.","onlineOnly":"Y","ipdsId":"IP-117452","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":380937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1130/coverthb.jpg"},{"id":380938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1130/ofr20201130.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1130"}],"country":"United States","state":"Oregon","otherGeospatial":"Siuslaw National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.14001464843749,\n 43.691707903073805\n ],\n [\n -123.42041015624999,\n 43.691707903073805\n ],\n [\n -123.42041015624999,\n 44.66865287227321\n ],\n [\n -124.14001464843749,\n 44.66865287227321\n ],\n [\n -124.14001464843749,\n 43.691707903073805\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Mercury is an environmentally ubiquitous neurotoxin, and its methylated form presents health risks to humans and other biota, primarily through dietary intake. Because methylmercury bioaccumulates and biomagnifies in living tissue, concentrations progressively increase at higher trophic positions in ecosystem food webs. Therefore, the greatest health risks are for organisms at the highest trophic positions and for humans who consume organisms such as fish from these high trophic positions. Data on environmental mercury concentrations in various media and biota provide a basis for comparison among sites and regions and for evaluating ecosystem health risks. The U.S. Geological Survey, in cooperation with the Natural Resources Department, Bad River Band of Lake Superior Chippewa, have compiled a dataset from analyses of mercury concentrations in surface water, bed sediment, fish tissue, Rana clamitans (green frog) tissue, Haliaeetus leucocephalus (bald eagle) feathers, Lontra canadensis (North American river otter) hair, Zizania palustris (northern wild rice), and litterfall from samples collected in the Bad River watershed, Wisconsin during 2004–18. These data originated from either the Natural Resources Department or another agency based on samples collected within or near to Bad River Tribal lands before transfer to the U.S. Geological Survey for compilation and analysis at the onset of the project. This report describes the compiled mercury dataset, provides comparisons to similar measurements in the region and elsewhere, and evaluates health risks to humans and to the sampled biota. Except for litterfall, data were not collected on a consistent, regular basis over a sufficient period to evaluate temporal patterns. The reported mercury concentrations are generally similar to those reported elsewhere in the upper Great Lakes region. Reported values are consistent with atmospheric deposition as the principal source and reflect a favorable environment for mercury methylation. Fish mercury concentrations increased at higher food web positions and generally increased with length in most species measured. Sander vitreus (walleye) present the greatest risk to humans among fishes considered here because of their high trophic position and associated elevated mercury concentrations in combination with relatively high walleye consumption rates by the Native American community. Methylmercury concentrations in wild rice are generally low and likely pose little health risk. Despite reports of declining atmospheric mercury deposition across eastern North America during the past decade, a downward trend in litterfall mercury deposition was not evident in samples collected during 2012–18. Limitations in this data compilation and analysis were noted due to missing information such as collection dates and site locations for some samples. Regular monitoring of mercury in litterfall and surface waters along with periodic collection of fish would enable evaluation of temporal change in the mercury cycle that might affect future risk to humans and aquatic ecosystem inhabitants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201095","collaboration":"Prepared in cooperation with the Natural Resources Department, Bad River Band of Lake Superior Chippewa","usgsCitation":"Burns, D.A., 2020, Compilation of mercury data and associated risk to human and ecosystem health, Bad River Band of Lake Superior Chippewa, Wisconsin (ver 1.1, December 2020): U.S. Geological Survey Open-File Report 2020–1095, 19 p., https://doi.org/10.3133/ofr20201095.","productDescription":"Report: vii, 19 p.; Database; Data Release","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-110861","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":377882,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- USGS water data for the Nation"},{"id":377880,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1095/ofr20201095.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1095"},{"id":377879,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1095/coverthb2.jpg"},{"id":377881,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HRS2C3","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Mercury data from the Bad River Watershed, Wisconsin, 2004–2018"},{"id":380931,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1095/versionHist.txt","size":"448 B","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bad River Tribal Lands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.48751831054686,\n 46.54658317951774\n ],\n [\n -90.4779052734375,\n 46.57868671298067\n ],\n [\n -90.51223754882812,\n 46.599449464868584\n ],\n [\n -90.59600830078125,\n 46.63057868059483\n ],\n [\n -90.69488525390625,\n 46.69184147024343\n ],\n [\n -90.78140258789062,\n 46.71632714994794\n ],\n [\n -90.7855224609375,\n 46.66734468444288\n ],\n [\n -90.83221435546875,\n 46.62020426357956\n ],\n [\n -90.8294677734375,\n 46.57774276255591\n ],\n [\n -90.83770751953125,\n 46.39619977845332\n ],\n [\n -90.55343627929688,\n 46.409457767475764\n ],\n [\n -90.54931640625,\n 46.54280504427768\n ],\n [\n -90.48751831054686,\n 46.54658317951774\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: August 2020; Version 1.1: December 2020","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
This report describes considerations for incorporating routine quality-assessment and quality-control evaluations into U.S. Geological Survey discrete water-sampling programs and projects. U.S. Geological Survey water-data science in 2020 is characterized by robustness, external reproducibility, collaborative large-volume data analysis, and efficient delivery of water-quality data. Confidence in data, or robustness, can be increased by supplementing traditional field-based quality-control data with laboratory quality control (QC) data, such as third-party blind spikes and blind blanks, laboratory blanks, and laboratory-reagent spikes. Laboratory quality-control data can provide additional information about bias and variability, method performance, and false-positive and false-negative rates that are not available from field QC data alone. Reproducibility is supported by means of standardizing metadata and documentation. Collaborative analysis brings together disparate elements of various types of quality-control review and communicates persistent data quality issues for compounds to data users internal and external to the U.S. Geological Survey. Efficient delivery of water-quality data is achieved when quality-control review is accomplished in the same expedited (near real-time) time frame as distribution of environmental results to the public and might be improved with consideration given to data versioning or to a system of alerting data users to data interpretation that might differ from originally published data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201109","usgsCitation":"Medalie, L., 2020, Considerations for incorporating quality control into water quality sampling strategies for the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2020–1109, 5 p., https://doi.org/10.3133/ofr20201109.","productDescription":"iii, 5 p.","numberOfPages":"5","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120022","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":380650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1109/coverthb.jpg"},{"id":380651,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1109/ofr20201109.pdf","text":"Report","size":"935 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1109"}],"contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The U.S. Geological Survey (USGS), in cooperation with the California State Water Resources Control Board, is evaluating several questions about oil and gas development and groundwater resources in California, including (1) the location of groundwater resources; (2) the proximity of oil and gas operations to groundwater and the geologic materials between them; (3) evidence (or no evidence) of fluids from oil and gas sources in groundwater; and (4) the pathways or processes responsible when fluids from oil and gas sources are present in groundwater (U.S. Geological Survey, 2017). As part of this evaluation, the USGS installed a multiple-well monitoring site in the southern San Joaquin Valley groundwater basin adjacent to the North and South Belridge oil fields, about 7 miles southwest of Lost Hills, California. Data collected at the Belridge multiple-well monitoring site (BWSD) provide information about the geology, hydrology, geophysical properties, and geochemistry of the aquifer system, thus enhancing understanding of relations between adjacent groundwater and the North and South Belridge oil fields in an area where there are few groundwater data. This report presents construction information for the BWSD and initial hydrogeologic data collected from the site. A similar site installed to the east of the Lost Hills oil field, 11.5 miles to the north of the BWSD site, was described by Everett and others (2020a).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201116","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Everett, R.R., Brown, A.A., Gillespie, J.M., Kjos, A., and Fenton, N.C., 2020, Multiple-well monitoring site adjacent to the North and South Belridge Oil Fields, Kern County, California: U.S. Geological Survey Open-File Report 2020-1116, 10 p., https://doi.org/10.3133/ofr20201116.","productDescription":"Report: 10 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-112077","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":380658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1116/ofr20201116.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1116"},{"id":380659,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96WITX5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Aquifer test data for the Belridge multiple-well monitoring site (BWSD), Kern County, California"},{"id":380657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1116/coverthb.jpg"}],"country":"United States","state":"California","county":"Kern County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-120.1945,35.788],[-120.1842,35.789],[-120.1655,35.7891],[-120.1474,35.7887],[-120.0816,35.7886],[-119.9688,35.7896],[-119.852,35.7891],[-119.7618,35.7906],[-119.6472,35.7895],[-119.5395,35.79],[-119.4301,35.7905],[-119.3308,35.7899],[-119.2169,35.7906],[-119.1182,35.7903],[-118.9027,35.789],[-118.6504,35.7897],[-118.6441,35.7896],[-118.5885,35.7897],[-118.5233,35.7892],[-118.4785,35.7915],[-118.4706,35.7919],[-118.4502,35.7908],[-118.2716,35.7896],[-118.2562,35.7894],[-118.2387,35.7897],[-118.2137,35.7894],[-118.1956,35.7896],[-118.1632,35.7893],[-118.0839,35.7865],[-118.0697,35.7859],[-118.009,35.7861],[-117.9234,35.7863],[-117.9249,35.7986],[-117.9005,35.7983],[-117.8738,35.7988],[-117.8523,35.7985],[-117.6362,35.7958],[-117.6355,35.7086],[-117.6537,35.7085],[-117.6527,35.6776],[-117.6176,35.6775],[-117.6166,35.6493],[-117.6353,35.6487],[-117.6354,35.6233],[-117.6352,35.5807],[-117.6356,35.5666],[-117.6351,35.5639],[-117.6346,35.4472],[-117.6352,35.3755],[-117.6353,35.3464],[-117.6351,35.3319],[-117.6343,35.3174],[-117.6341,35.3028],[-117.6345,35.2874],[-117.6343,35.2742],[-117.6341,35.2588],[-117.6339,35.2447],[-117.6342,35.2302],[-117.634,35.2157],[-117.6338,35.2011],[-117.6336,35.1861],[-117.6334,35.1707],[-117.6338,35.1562],[-117.6336,35.1417],[-117.6333,35.1271],[-117.6331,35.1126],[-117.6329,35.098],[-117.6352,35.0981],[-117.636,35.0872],[-117.6358,35.0727],[-117.6356,35.0581],[-117.6357,35.0295],[-117.6361,35.015],[-117.6357,34.985],[-117.6351,34.8233],[-117.6519,34.8227],[-117.6704,34.8221],[-117.7757,34.8229],[-118.1408,34.8195],[-118.1493,34.8195],[-118.5995,34.8175],[-118.8946,34.8181],[-118.8945,34.818],[-118.8825,34.791],[-118.9772,34.7902],[-118.9771,34.8126],[-119.2462,34.8147],[-119.2461,34.857],[-119.2797,34.858],[-119.2779,34.8793],[-119.3844,34.8794],[-119.385,34.884],[-119.3849,34.899],[-119.4382,34.8999],[-119.4438,34.8999],[-119.4544,34.8999],[-119.4571,34.9],[-119.4746,34.9004],[-119.4746,34.9005],[-119.4746,34.9136],[-119.474,34.9367],[-119.474,34.9499],[-119.474,34.9576],[-119.474,34.9721],[-119.4746,35.0184],[-119.4746,35.0325],[-119.4745,35.077],[-119.4908,35.077],[-119.4914,35.092],[-119.5004,35.0915],[-119.5088,35.0906],[-119.5628,35.0883],[-119.5583,35.1369],[-119.5566,35.1601],[-119.5549,35.1791],[-119.5769,35.1787],[-119.6095,35.1773],[-119.6675,35.1749],[-119.6675,35.1908],[-119.6675,35.2049],[-119.6688,35.2617],[-119.7397,35.2629],[-119.7572,35.2633],[-119.7746,35.2633],[-119.8113,35.2641],[-119.8122,35.3508],[-119.8815,35.3501],[-119.8824,35.41],[-119.8824,35.4246],[-119.8831,35.4377],[-119.9999,35.4396],[-120.0007,35.4695],[-120.0171,35.469],[-120.0194,35.4835],[-120.0358,35.4834],[-120.0359,35.497],[-120.0523,35.4974],[-120.053,35.5124],[-120.0699,35.5128],[-120.0711,35.5268],[-120.0875,35.5276],[-120.0876,35.6139],[-120.1951,35.6151],[-120.1947,35.7481],[-120.1942,35.7626],[-120.1945,35.788]]]},\"properties\":{\"name\":\"Kern\",\"state\":\"CA\"}}]}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Five commercially available turbidity sensors were field tested by the U.S. Geological Survey Hydrologic Instrumentation Facility for accuracy and data comparability. The tested sensors were the Xylem EXO (EXO), the Hach Solitax sc (Solitax), the In Situ Aqua TROLL sensor installed onto a TROLL 600 sonde (TROLL 600), the Campbell Scientific OBS501 (OBS501), and the Observator ANALITE NEP–5000 (NEP–5000). The sensors were deployed at Pearl River at National Space Technology Laboratories Station, Mississippi (U.S. Geological Survey site 02492620), and were serviced weekly. In addition to the five in situ turbidity sensors, corresponding discrete samples were collected and analyzed during the evaluation on a calibrated Hach 2100N benchtop turbidimeter. The OBS501 malfunctioned early in the evaluation and eventually failed, resulting in few data from the sensor.
During this study, the four remaining sensors (minus the OBS501) changed similarly throughout the field test; however, sensor data from the EXO consistently demonstrated lower results than the Solitax, TROLL 600, and NEP–5000, possibly because of the variation in raw signal processing among manufacturers. Results from a single factor analysis of variance test and a Tukey Honestly Significant Difference test verified the low bias observed in the EXO data and indicated there was a significant difference between the EXO data and data from the Solitax, TROLL 600, and NEP–5000 but an insignificant difference among the data when the Solitax, TROLL 600, and NEP–5000 were compared to each other.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201123","usgsCitation":"Snazelle, T.T., 2020, Field comparison of five in situ turbidity sensors: U.S. Geological Survey Open-File Report 2020–1123, 15 p., https://doi.org/10.3133/ofr20201123.","productDescription":"Report: iv, 15 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-103944","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":380549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1123/ofr20201123.pdf","text":"Report","size":"3.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1123"},{"id":380548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1123/coverthb.jpg"},{"id":380550,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KDERG6","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Turbidity data collected by five in situ sensors at USGS site 02492620 Pearl River at NSTL station, Mississippi, from November 2017 to January 2018"},{"id":380551,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Mississippi","otherGeospatial":"National Space Technology Laboratories Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.0274658203125,\n 30.211608223816906\n ],\n [\n -89.28314208984375,\n 30.211608223816906\n ],\n [\n -89.28314208984375,\n 30.41078179084589\n ],\n [\n -90.0274658203125,\n 30.41078179084589\n ],\n [\n -90.0274658203125,\n 30.211608223816906\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"U.S. Geological Survey
Water Mission Area
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey monitored dissolved nitrate plus nitrite as nitrogen (N) and dissolved organic carbon (DOC) concentrations and calculated loads of these constituents at the W.P. Franklin Lock and Dam (S-79) from April 2014 to December 2017. Flows from Lake Okeechobee controlled by S-77, S-78 and S-79 affect water quality in the downstream Caloosahatchee River Estuary, where increased nutrients and dissolved organic matter are of concern. Numerous algal blooms have occurred in the Caloosahatchee River and downstream estuaries in recent years (2005–18) and are often attributed to eutrophication. Dissolved nitrate plus nitrite as N (hereafter, referred to as nitrate) data were collected at 15-minute intervals using a submersible ultraviolet optical nitrate sensor. The instrument data were corrected for interferences, as determined by the relation between instrument measurements and 20 concurrent laboratory values. A surrogate model, based on 36 concurrent measurements of DOC, fluorescence of chromophoric dissolved organic matter, and specific conductance, was developed to calculate DOC at 15-minute intervals.
Mean and median calculated nitrate concentrations for the study period (2014–17) were both 0.21 milligram per liter (mg/L). Monthly mean nitrate concentrations ranged from 0.04 mg/L in April 2017 to 0.48 mg/L in November 2015. Monthly mean nitrate concentrations and the proportion of water that was attributed to Lake Okeechobee discharge, released through S-79, were weakly correlated and indicate that the nitrate concentrations typically decreased as the percentage of water released from the lake increased. Annual nitrate loads were 278 metric tons in 2015, 782 metric tons in 2016, and 525 metric tons in 2017. Monthly mean nitrate loads ranged from 1.2 metric tons in April 2017 to 171.3 metric tons in February 2016. Nitrate loads increased linearly with an increase in flow and typically increased during the wet season, May to October. Monthly loads of nitrate were strongly correlated with flow at S-77 and S-79.
Mean and median calculated DOC concentrations for the study period were 18.3 mg/L and 18.9 mg/L, respectively. Monthly mean DOC concentrations ranged from 12.6 mg/L in May 2017 to 21.5 mg/L in September 2015. Generally, DOC concentrations were lower during the dry season months (November to April) and higher during the wet season months. Monthly mean DOC concentrations were moderately correlated with monthly mean flow volumes at S-79. There was a strong correlation between monthly mean DOC concentrations and the proportion of water released at S-79 that can be attributed directly to Lake Okeechobee, indicating that contributions between Moore Haven Lock and Dam (S-77) and S-79 have a higher DOC concentration than water released from Lake Okeechobee. Monthly mean nitrate concentrations and monthly mean DOC concentrations were strongly correlated. Annual loads of DOC were 23,960 metric tons in 2015 and 65,610 metric tons in 2016 (2014 and 2017 data were incomplete). Monthly loads of DOC ranged from 284 metric tons in May 2017 to 15,122 metric tons in September 2017, the latter corresponding to the effects from Hurricane Irma. Monthly loads of DOC were strongly correlated with flow at S-77 and S-79.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201094","collaboration":"USGS Greater Everglades Priority Ecosystem Science Program","usgsCitation":"Booth, A., 2020, Measured and calculated nitrate and dissolved organic carbon concentrations and loads at the W.P. Franklin Lock and Dam, S-79, south Florida, 2014-17: U.S. Geological Survey Open-File Report 2020-1094, 37 p., https://doi.org/10.3133/ofr20201094.","productDescription":"Report: vi, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091619","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":380478,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1094/coverthb.jpg"},{"id":380479,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1094/ofr20201094.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1094"},{"id":380480,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V4ZGWU","text":"USGS data release","linkHelpText":"Calculated carbon concentrations, Franklin Lock and Dam (S-79) southern Florida, 2014-2017"}],"country":"United States","state":"Florida","otherGeospatial":"W.P. Franklin Lock and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.7437744140625,\n 26.701452590314368\n ],\n [\n -81.47735595703125,\n 26.701452590314368\n ],\n [\n -81.47735595703125,\n 26.74683674289727\n ],\n [\n -81.7437744140625,\n 26.74683674289727\n ],\n [\n -81.7437744140625,\n 26.701452590314368\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The U.S. Geological Survey, in cooperation with the Connecticut Department of Public Health, conducted a study to determine the presence of arsenic and uranium in private drinking water wells in Connecticut. Samples were collected during 2013–18 from wells completed in 115 geologic units, with 2,433 samples analyzed for arsenic and 2,191 samples analyzed for uranium. The study concluded four major findings.
Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
This report is an instructional reference document that describes methods developed and used by the U.S. Geological Survey (USGS) New Jersey Water Science Center (NJWSC) to assure the quality and completeness of water-use data as provided by the New Jersey Department of Environmental Protection (NJDEP) Bureau of Water Allocation. These data are owned wholly by the State of New Jersey. The role of the USGS NJWSC is to assure the quality of these data by compiling, reviewing, and checking the datasets before uploading them into the New Jersey Water Transfer Data System (NJWaTr) database on an annual basis. The complete uploaded version of the NJWaTr database serves as the repository for New Jersey’s approved and published water-use data. The State of New Jersey maintains a public-facing version of the NJWaTr database (available online at https://www.nj.gov/dep/njgs/geodata/dgs10-3.htm) that contains monthly water-use data at the municipality and 14-digit Hydrologic Unit Code subwatershed level. The protected version of the NJWaTr database that contains monthly site-specific water-use data is available from the NJDEP upon request.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201085","collaboration":"Prepared in cooperation with New Jersey Department of Environmental Protection","usgsCitation":"Shourds, J.L., 2020, Quality assurance/quality control procedure for New Jersey’s water-use data for the New Jersey Water Transfer Data System (NJWaTr): U.S. Geological Survey Open-File Report 2020–1085, 26 p., https://doi.org/10.3133/ofr20201085.","productDescription":"viii, 26 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112307","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":380203,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1085/coverthb.jpg"},{"id":380204,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1085/ofr20201085.pdf","text":"Report","size":"2.09 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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
This report provides the best estimates of riparian area evapotranspiration (ET) on the rivers and streams of the Navajo Nation by (1) quantifying the natural riparian vegetation water use within the Little Colorado River watershed using a literature search for comparable riparian ET estimates, and (2) in conjunction with the given area of stream-side plant cover on the Navajo Nation, provides the best estimate of consumptive use, the total water requirement (in acre-feet). This report includes riparian water use information only from the literature for riparian areas that are in similar dryland ecosystems in the Southwest, and not specific to the perennial tributaries and springs on the Navajo Nation within the Little Colorado River watershed. The report also includes any information found regarding the location of Navajo Nation weather station variables, such as where we can derive required data inputs from the Navajo Nation to estimate actual ET rates (in millimeters per day or millimeters per year). We provide estimates of annual riparian plant water use and calculations that include reference ET (potential ET or ETo), precipitation (in millimeters), and the calculations of consumptive water requirements of riparian vegetation. We cite our data sources and provide references used to determine the consumptive water requirement (acre-feet).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201129","collaboration":"Prepared in cooperation with Fred Phillips Consulting","usgsCitation":"Nagler, P.L., 2020, Literature reviewed estimates of riparian consumptive water use in the drylands of Northeast Arizona, USA: U.S. Geological Survey Open-File Report 2020–1129, 9 p., https://doi.org/10.3133/ofr20201129.","productDescription":"v, 9 p.","onlineOnly":"Y","ipdsId":"IP-122975","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":380268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1129/coverthb.jpg"},{"id":380269,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1129/ofr20201129.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1129"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.26855468749999,\n 32.30570601389429\n ],\n [\n -113.51074218749999,\n 32.30570601389429\n ],\n [\n -113.51074218749999,\n 35.71083783530009\n ],\n [\n -115.26855468749999,\n 35.71083783530009\n ],\n [\n -115.26855468749999,\n 32.30570601389429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.90673828125,\n 34.45221847282654\n ],\n [\n -108.984375,\n 34.45221847282654\n ],\n [\n -108.984375,\n 36.96744946416934\n ],\n [\n -111.90673828125,\n 36.96744946416934\n ],\n [\n -111.90673828125,\n 34.45221847282654\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001