Armenia is a landlocked country located in the mountainous Caucasus region between Asia and Europe. It shares borders with the countries of Georgia on the north, Azerbaijan on the east, Iran on the south, and Turkey and Azerbaijan on the west. The Ararat Basin is a transboundary basin in Armenia and Turkey. The Ararat Basin (or Ararat Valley) is an intermountain depression that contains the Aras River and its tributaries, which also form the border between Armenia and Turkey and divide the basin into northern and southern regions. The Ararat Basin also contains Armenia’s largest agricultural and fish farming zone that is supplied by high-quality water from wells completed in the artesian aquifers that underlie the basin. Groundwater constitutes about 40 percent of all water use, and groundwater provides 96 percent of the water used for drinking purposes in Armenia. Since 2000, groundwater withdrawals and consumption in the Ararat Basin of Armenia have increased because of the growth of aquaculture and other uses. Increased groundwater withdrawals caused decreased springflow, reduced well discharges, falling water levels, and a reduction of the number of flowing artesian wells in the southern part of Ararat Basin in Armenia.
In 2016, the U.S. Geological Survey and the U.S. Agency for International Development (USAID) began a cooperative study in Armenia to share science and field techniques to increase the country’s capabilities for groundwater study and modeling. The purpose of this report is to describe the hydrogeologic framework and groundwater conditions of the Ararat Basin in Armenia based on data collected in 2016 and previous hydrogeologic studies. The study area includes the Ararat Basin in Armenia. This report was completed through a partnership with USAID/Armenia in the implementation of its Science, Technology, Innovation, and Partnerships effort through the Advanced Science and Partnerships for Integrated Resource Development program and associated partners, including the Government of Armenia, Armenia’s Hydrogeological Monitoring Center, and the USAID Global Development Lab and its GeoCenter.
The hydrogeologic framework of the Ararat Basin includes several basin-fill stratigraphic units consisting of interbedded dense clays, gravels, sands, volcanic basalts, and andesite deposits. Previously published cross sections and well lithologic logs were used to map nine general hydrogeologic units. Hydrogeologic units were mapped based on lithology and water-bearing potential. Water-level data measured in the water-bearing hydrogeologic units 2, 4, 6, and 8 in 2016 were used to create potentiometric surface maps. In hydrogeologic unit 2, the estimated direction of groundwater flow is from the west to north in the western part of the basin (away from the Aras River) and from north to south (toward the Aras River) in the eastern part of the basin. In hydrogeologic unit 4, the direction of groundwater flow is generally from west to east and north to south (toward the Aras River) except in the western part of the basin where groundwater flow is toward the north or northwest. Hydrogeologic unit 6 has the same general pattern of groundwater flow as unit 4. Hydrogeologic unit 8 is the deepest of the water-bearing units and is confined in the basin. Groundwater flow generally is from the south to north (away from the Aras River) in the western part of the basin and from west to east and north to south (toward the Aras River) elsewhere in the basin.
In addition to water levels, personnel from Armenia’s Hydrogeological Monitoring Center also measured specific conductance at 540 wells and temperature at 2,470 wells in the Ararat Basin using U.S. Geological Survey protocols in 2016. The minimum specific conductance was 377 microsiemens per centimeter (μS/cm), the maximum value was 4,000 μS/cm, and the mean was 998 μS/cm. The maximum water temperature was 24.2 degrees Celsius. An analysis between water temperature and well depth indicated no relation; however, spatially, most wells with cooler water temperatures were within the 2016 pressure boundary or in the western part of the basin. Wells with generally warmer water temperatures were in the eastern part of the basin.
Samples were collected from four groundwater sites and one surface-water site by the U.S. Geological Survey in 2016. The stable-isotope values were similar for all five sites, indicating similar recharge sources for the sampled wells. The Hrazdan River sample was consistent with the groundwater samples, indicating the river could serve as a source of recharge to the Ararat artesian aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175163","usgsCitation":"Valder, J.F., Carter, J.M., Medler, C.J., Thompson, R.F., and Anderson, M.T., 2018, Hydrogeologic framework and groundwater conditions of the Ararat Basin in Armenia: U.S. Geological Survey Scientific Investigations Report 2017–5163, 40 p., https://doi.org/10.3133/sir20175163.","productDescription":"Report: viii, 40 p.; Tables","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-088554","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":350454,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table6.xls","text":"Table 6. Historical water-level and well yield data from various dates ranging from 1981 to 2013 in the Ararat Basin, Armenia","size":"96 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 6"},{"id":350430,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5163/coverthb.jpg"},{"id":350452,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table5.xlsx","text":"Table 5. Historical water-level data from 2007 in the Ararat Basin, Armenia, provided to the U.S. Geological Survey by Armenian partners","size":"200 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 5"},{"id":350451,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table4.xls","text":"Table 4. Hydrologic data provided to the U.S. Geological Survey from the 2016 well inventory conducted in the Ararat Basin, Armenia, by Armenian partners","size":"808 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 4"},{"id":350434,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table1.xlsx","text":"Table 1 Lithologic descriptions, land-surface elevations, geologic layer thicknesses, and hydrogeologic units of the Ararat Basin, Armenia","size":"792 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 1"},{"id":350432,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5163"}],"country":"Armenia","otherGeospatial":"Ararat Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 43.75,\n 39.75\n ],\n [\n 44.8,\n 39.75\n ],\n [\n 44.8,\n 40.25\n ],\n [\n 43.75,\n 40.25\n ],\n [\n 43.75,\n 39.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center, South Dakota Office
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
We apply linear deconvolution methods to derive mineral and glass proportions for eight field sample training sites at seven dune fields: (1) Algodones, California; (2) Big Dune, Nevada; (3) Bruneau, Idaho; (4) Great Kobuk Sand Dunes, Alaska; (5) Great Sand Dunes National Park and Preserve, Colorado; (6) Sunset Crater, Arizona; and (7) White Sands National Monument, New Mexico. These dune fields were chosen because they represent a wide range of mineral grain mixtures and allow us to gauge a better understanding of both compositional and sorting effects within terrestrial and extraterrestrial dune systems. We also use actual ASTER TIR emissivity imagery to map the spatial distribution of these minerals throughout the seven dune fields and evaluate the effects of degraded spectral resolution on the accuracy of mineral abundances retrieved. Our results show that hyperspectral data convolutions of our laboratory emissivity spectra outperformed multispectral data convolutions of the same data with respect to the mineral, glass and lithic abundances derived. Both the number and wavelength position of spectral bands greatly impacts the accuracy of linear deconvolution retrieval of feldspar proportions (e.g. K-feldspar vs. plagioclase) especially, as well as the detection of certain mafic and carbonate minerals. In particular, ASTER mapping results show that several of the dune sites display patterns such that less dense minerals typically have higher abundances near the center of the active and most evolved dunes in the field, while more dense minerals and glasses appear to be more abundant along the margins of the active dune fields.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2017.12.001","usgsCitation":"Hubbard, B.E., Hooper, D.M., Solano, F., and Mars, J., 2018, Determining mineralogical variations of aeolian deposits using thermal infrared emissivity and linear deconvolution methods: Aeolian Research, v. 30, p. 54-96, https://doi.org/10.1016/j.aeolia.2017.12.001.","productDescription":"43 p.","startPage":"54","endPage":"96","ipdsId":"IP-080975","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":461075,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2017.12.001","text":"Publisher Index Page"},{"id":438055,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MS3QWM","text":"USGS data release","linkHelpText":"Visible, Near Infrared, Shortwave Infrared and Thermal Infrared Laboratory Spectra of Samples of Compositionally Variable Dune Fields in the Western United States and Alaska"},{"id":438054,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CC0XTR","text":"USGS data release","linkHelpText":"Linear Deconvolution Mineral Maps of Compositionally Variable Dune Fields in the Western United States and Alaska"},{"id":350459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Arizona, California, Colorado, Idaho, Nevada, New Mexico","otherGeospatial":"Algodones, Big Dune, Bruneau, Great Kobuk Sand Dunes, Great Sand Dunes National Park and Preserve, Sunset Crater, White Sands National Monument","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60e451e4b06e28e9c14067","contributors":{"authors":[{"text":"Hubbard, Bernard E. 0000-0002-9315-2032 bhubbard@usgs.gov","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":2342,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"bhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":725517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooper, Donald M.","contributorId":197205,"corporation":false,"usgs":false,"family":"Hooper","given":"Donald","email":"","middleInitial":"M.","affiliations":[{"id":35998,"text":"WEX Foundation","active":true,"usgs":false},{"id":35997,"text":"Southwest Research Institute, San Antonio, TX","active":true,"usgs":false}],"preferred":false,"id":725518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solano, Federico 0000-0002-0308-5850 fsolanoc@usgs.gov","orcid":"https://orcid.org/0000-0002-0308-5850","contributorId":4302,"corporation":false,"usgs":true,"family":"Solano","given":"Federico","email":"fsolanoc@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":725519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mars, John C. jmars@usgs.gov","contributorId":127493,"corporation":false,"usgs":true,"family":"Mars","given":"John C.","email":"jmars@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":725520,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194509,"text":"sir20175140 - 2018 - Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois","interactions":[],"lastModifiedDate":"2018-07-25T10:40:07","indexId":"sir20175140","displayToPublicDate":"2018-01-16T11:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5140","title":"Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois","docAbstract":"A two-dimensional hydraulic model and digital flood‑inundation maps were developed for a 30-mile reach of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois. The flood-inundation maps, which can be accessed through the U.S. Geological Survey (USGS) Flood Inundation Mapping Science web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Wabash River at Mount Carmel, Ill (USGS station number 03377500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS AHPS site MCRI2). The NWS AHPS forecasts peak stage information that may be used with the maps developed in this study to show predicted areas of flood inundation.
Flood elevations were computed for the Wabash River reach by means of a two-dimensional, finite-volume numerical modeling application for river hydraulics. The hydraulic model was calibrated by using global positioning system measurements of water-surface elevation and the current stage-discharge relation at both USGS streamgage 03377500, Wabash River at Mount Carmel, Ill., and USGS streamgage 03378500, Wabash River at New Harmony, Indiana. The calibrated hydraulic model was then used to compute 27 water-surface elevations for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from less than the action stage (9 ft) to the highest stage (35 ft) of the current stage-discharge rating curve. The simulated water‑surface elevations were then combined with a geographic information system digital elevation model, derived from light detection and ranging data, to delineate the area flooded at each water level.
The availability of these maps, along with information on the internet regarding current stage from the USGS streamgage at Mount Carmel, Ill., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175140","collaboration":"Prepared in cooperation with the Indiana Department of Transportation; Illinois Department of Transportation","usgsCitation":"Boldt, J.A., 2018, Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois: U.S. Geological Survey Scientific Investigations Report 2017–5140, 13 p., https://doi.org/10.3133/sir20175140.","productDescription":"vi, 13 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087699","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":355963,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZCD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets and model for the flood-inundation study of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois"},{"id":350289,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/sir20175117","text":"Scientific Investigations Report 2017–5117","linkHelpText":"- River Meander Modeling of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois"},{"id":350288,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5140/sir20175140.pdf","text":"Report","size":"3.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5140"},{"id":350287,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5140/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Grayville","otherGeospatial":"Wabash River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.01456451416016,\n 38.153727245014004\n ],\n [\n -87.77870178222656,\n 38.153727245014004\n ],\n [\n -87.77870178222656,\n 38.338694087313534\n ],\n [\n -88.01456451416016,\n 38.338694087313534\n ],\n [\n -88.01456451416016,\n 38.153727245014004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
9818 Bluegrass Parkway
Louisville, KY 40299
Groundwater carbon (C) supply to lakes and streams is important to understanding the role of inland waters in global and regional cycles and in the functioning of aquatic ecosystems. We provide new estimates of the size and discharge of the groundwater C pool using data from a broad survey of groundwater C, information on the depth distribution of groundwater, and data on groundwater age. About 0.25 × 106 km3 of the 8 × 106km3 of groundwater resource is within 100 m of the surface and 4.2 × 106 km3 is above 2000 m. Ages show an average groundwater turnover time of 10 yr at 25 m, 350 yr at 100 m, increasing to about 100 000 yr at 600 m. Global groundwater discharge is 16 000 km3 yr−1; >16% of precipitation passes through groundwater. Groundwater dissolved organic C (DOC) can be high in shallow groundwater but stabilizes at ~2–4 mg L−1 at 100 m. Average groundwater dissolved inorganic C (DIC) is ~30–43 mg L−1. Groundwater C content to 2000 m is ~145 Pg, about the same as all marine sediments and about one-sixth that of the surface ocean. Groundwater C discharge to continental waters is 0.68 Pg yr−1, or 3.4 times that estimated from river base-flow and submarine groundwater discharge. This discharge is 68 times previous estimates, implying a total C flux from land of 3.6 Pg yr−1; 80% of discharge occurs from above 40 m and 99% from the upper 100 m.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20442041.2017.1412918","usgsCitation":"Downing, J.A., and Striegl, R.G., 2018, Size, age, renewal, and discharge of groundwater carbon: Inland Waters, v. 8, no. 1, p. 122-127, https://doi.org/10.1080/20442041.2017.1412918.","productDescription":"6 p.","startPage":"122","endPage":"127","ipdsId":"IP-076067","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":469095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/20442041.2017.1412918","text":"Publisher Index Page"},{"id":356201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","scienceBaseUri":"5b6fc4bae4b0f5d57878eac2","contributors":{"authors":[{"text":"Downing, John A.","contributorId":169033,"corporation":false,"usgs":false,"family":"Downing","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":741405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":741404,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195318,"text":"70195318 - 2018 - A guide to calculating habitat-quality metrics to inform conservation of highly mobile species","interactions":[],"lastModifiedDate":"2018-02-08T14:12:45","indexId":"70195318","displayToPublicDate":"2018-01-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2827,"text":"Natural Resource Modeling","active":true,"publicationSubtype":{"id":10}},"title":"A guide to calculating habitat-quality metrics to inform conservation of highly mobile species","docAbstract":"Many metrics exist for quantifying the relative value of habitats and pathways used by highly mobile species. Properly selecting and applying such metrics requires substantial background in mathematics and understanding the relevant management arena. To address this multidimensional challenge, we demonstrate and compare three measurements of habitat quality: graph-, occupancy-, and demographic-based metrics. Each metric provides insights into system dynamics, at the expense of increasing amounts and complexity of data and models. Our descriptions and comparisons of diverse habitat-quality metrics provide means for practitioners to overcome the modeling challenges associated with management or conservation of such highly mobile species. Whereas previous guidance for applying habitat-quality metrics has been scattered in diversified tracks of literature, we have brought this information together into an approachable format including accessible descriptions and a modeling case study for a typical example that conservation professionals can adapt for their own decision contexts and focal populations.
Considerations for Resource Managers
The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171159","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Bera, Maitreyee, and Ortel, T.W., 2018, Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system: \nU.S. Geological Survey Open-File Report 2017–1159, 16 p., https://doi.org/10.3133/ofr20171159.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087229","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":350409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1159/coverthb.jpg"},{"id":350410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1159/ofr20171159.pdf","text":"Report","size":"3.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1159"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.2634,41.9876],[-88.1473,41.9883],[-88.0342,41.9925],[-87.9175,41.9938],[-87.9188,41.9076],[-87.9178,41.8185],[-87.9142,41.7318],[-87.9139,41.7172],[-87.9438,41.7017],[-87.9482,41.694],[-87.9674,41.6879],[-87.9883,41.6877],[-88.0013,41.6874],[-88.0308,41.6868],[-88.0317,41.7295],[-88.1499,41.7272],[-88.2625,41.7251],[-88.2628,41.811],[-88.2632,41.8623],[-88.2631,41.9],[-88.2634,41.9876]]]},\"properties\":{\"name\":\"Dupage\",\"state\":\"IL\"}}]}","contact":"Director, Illinois-Iowa Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Flow-proportional composite water samples were collected in water years 2013 and 2014 by the U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, from the Blackstone River at Millville, Massachusetts (U.S. Geological Survey station 01111230), about 0.5 mile from the border with Rhode Island. Samples were collected in order to better understand the dynamics of selected nutrient and metal constituents, assist with planning, guide activities to meet water-quality goals, and provide real-time water-quality information to the public. An automated system collected the samples at 14-day intervals to determine total and dissolved nitrogen and phosphorus concentrations, to provide accurate monthly nutrient concentration data, and to calculate monthly load estimates. Concentrations of dissolved trace metals and total aluminum were determined from 4-day composite water samples that were collected twice monthly by the automated system. Results from 4-day composites provide stakeholders with information to evaluate trace metals on the basis of chronic 4-day exposure criteria for aquatic life, and the potential to use the biotic ligand model to evaluate copper concentrations. Nutrient, trace metal, suspended sediment, dissolved organic carbon, and chlorophyll a concentrations were determined from discrete samples collected at the Millville station and from across the stream transect at the upstream railroad bridge, and these concentrations served as a means to evaluate the representativeness of the Millville point location.
Analytical results from samples collected with the automated flow-proportional sampling system provided the means to calculate monthly and annual loading data. Total nitrogen and total phosphorus loads in water year (WY) 2013 were about 447,000 and 36,000 kilograms (kg), respectively. In WY 2014, annual loads of total nitrogen and total phosphorus were about 342,000 and 21,000 kg, respectively. Total nitrogen and total phosphorus loads from WYs 2013 and 2014 were about 56 and 65 percent lower than those reported for WYs 2008 and 2009. The higher loads in 2008 and 2009 may be explained by the higher than average flows in WY 2009 and by facility upgrades made by wastewater treatment facilities in the basin.
Median loads were determined from composite samples collected with the automated system between October 2012 and October 2014. Median dissolved cadmium and chromium 4-day loads were 0.55 and 0.84 kg, respectively. Dissolved copper and total lead median 4-day loads were 8.02 and 1.42 kg, respectively. The dissolved nickel median 4-day load was 5.45 kg, and the dissolved zinc median 4-day load was 36 kg. Median total aluminum 4-day loads were about 197 kg.
Spearman’s rank correlation analyses were used with discrete sample concentrations and continuous records of temperature, specific conductance, turbidity, and chlorophyll a to identify correlations between variables that could be used to develop regression equations for estimating real-time concentrations of constituents. Correlation coefficients were generated for flow, precipitation, antecedent precipitation, physical parameters, and chemical constituents. A 95-percent confidence limit for each value of Spearman’s rho was calculated, and multiple linear regression analysis using ordinary least squares regression techniques was used to develop regression equations for concentrations of total phosphorus, total nitrogen, suspended sediment concentration, total copper, and total aluminum. Although the correlations are based on the limited amount of data collected as part of this study, the potential to monitor water-quality changes in real time may be of value to resource managers and decision makers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175094","isbn":"ISBN 978-1-4113-4181-4","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Sorenson, J.R., Granato, G.E., and Smith, K.P., 2018, Nutrient and metal loads estimated by using discrete, automated, and continuous water-quality monitoring techniques for the Blackstone River at the Massachusetts-Rhode Island State line, water years 2013–14: U.S. Geological Survey Scientific Investigations Report 2017–5094, 41 p., https://doi.org/10.3133/sir20175094.","productDescription":"Report: ix, 41 p.; 4 Tables","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-079789","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":350359,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5094/sir20175094.pdf","text":"Report","size":"4.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5094"},{"id":350366,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table6.csv","text":"Table 6","size":"19.4 csv","linkHelpText":"- Concentrations of nutrients, trace metals, and suspended sediment in manually collected samples from the upstream railroad bridge and from the collection point at the Blackstone River at Millville, Massachusetts, station (01111230) during water years 2013 and 2014."},{"id":350368,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table7.csv","text":"Table 7","size":"13.1 KB csv","linkHelpText":"- Loads of nutrients based on 14-day nutrient composite samples, and loads of dissolved trace metals and total aluminum based on 4-day metal composite samples collected by the automated sampling system from the point location at the Blackstone River at Millville, Massachusetts, station (01111230) during water years 2013 and 2014."},{"id":350361,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table4.xlsx","text":"Table 4 (Microsoft Excel)","size":"48.5 KB"},{"id":350358,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5094/coverthb.jpg"},{"id":350360,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table4.csv","text":"Table 4","size":"15 KB csv","linkHelpText":"- Concentrations of nutrients, trace metals, and suspended sediment in sample pairs collected from the upstream railroad bridge and from the point location at the Blackstone River at Millville, Massachusetts, station (01111230)."},{"id":350367,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table7.xlsx","text":"Table 7 (Microsoft Excel)","size":"44 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":350364,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table5.csv","text":"Table 5","size":"13.7 KB csv","linkHelpText":"- Concentrations of nutrients, total aluminum, and dissolved trace metals in 14-day nutrient composite samples and 4-day metal composite samples collected by using the automated sampling system from the point location at the Blackstone River at Millville, Massachusetts, station (01111230) during water years 2013 and 2014."},{"id":350365,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table6.xlsx","text":"Table 6 (Microsoft Excel)","size":"46.7 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":350363,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table5.xlsx","text":"Table 5 (Microsoft Excel)","size":"39.6 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","state":"Massachusetts, Rhode Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.9167,\n 41.8333\n ],\n [\n -71.3333,\n 41.8333\n ],\n [\n -71.3333,\n 42.3333\n ],\n [\n -71.9167,\n 42.3333\n ],\n [\n -71.9167,\n 41.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
","tableOfContents":"
The Geospatial Semantic Web (GSW) is an emerging technology that uses the Internet for more effective knowledge engineering and information extraction. Among the aims of the GSW are to structure the semantic specifications of data to reduce ambiguity and to link those data more efficiently. The data are stored as triples, the basic data unit in graph databases, which are similar to the vector data model of geographic information systems (GIS); that is, a node-edge-node model that forms a graph of semantically related information. The GSW is supported by emerging technologies such as linked geospatial data, described below, that enable it to store and manage geographical data that require new cartographic methods for visualization. This report describes a map that can interact with linked geospatial data using a simulation of a data query approach called the browsable graph to find information that is semantically related to a subject of interest, visualized using the Data Driven Documents (D3) library. Such a semantically enabled map functions as a map knowledge base (MKB) (Varanka and Usery, 2017).
A MKB differs from a database in an important way. The central element of a triple, alternatively called the edge or property, is composed of a logic formalization that structures the relation between the first and third parts, the nodes or objects. Node-edge-node represents the graphic form of the triple, and the subject-property-object terms represent the data structure. Object classes connect to build a federated graph, similar to a network in visual form. Because the triple property is a logical statement (a predicate), the data graph represents logical propositions or assertions accepted to be true about the subject matter. These logical formalizations can be manipulated to calculate new triples, representing inferred logical assertions, from the existing data.
To demonstrate a MKB system, a technical proof-of-concept is developed that uses geographically attributed Resource Description Framework (RDF) serializations of linked data for mapping. The proof-of-concept focuses on accessing triple data from visual elements of a geographic map as the interface to the MKB. The map interface is embedded with other essential functions such as SPARQL Protocol and RDF Query Language (SPARQL) data query endpoint services and reasoning capabilities of Apache Marmotta (Apache Software Foundation, 2017). An RDF database of the Geographic Names Information System (GNIS), which contains official names of domestic feature in the United States, was linked to a county data layer from The National Map of the U.S. Geological Survey. The county data are part of a broader Government Units theme offered to the public as Esri shapefiles. The shapefile used to draw the map itself was converted to a geographic-oriented JavaScript Object Notation (JSON) (GeoJSON) format and linked through various properties with a linked geodata version of the GNIS database called “GNIS–LD” (Butler and others, 2016; B. Regalia and others, University of California-Santa Barbara, written commun., 2017). The GNIS–LD files originated in Terse RDF Triple Language (Turtle) format but were converted to a JSON format specialized in linked data, “JSON–LD” (Beckett and Berners-Lee, 2011; Sorny and others, 2014). The GNIS–LD database is composed of roughly three predominant triple data graphs: Features, Names, and History. The graphs include a set of namespace prefixes used by each of the attributes. Predefining the prefixes made the conversion to the JSON–LD format simple to complete because Turtle and JSON–LD are variant specifications of the basic RDF concept.
To convert a shapefile into GeoJSON format to capture the geospatial coordinate geometry objects, an online converter, Mapshaper, was used (Bloch, 2013). To convert the Turtle files, a custom converter written in Java reconstructs the files by parsing each grouping of attributes belonging to one subject and pasting the data into a new file that follows the syntax of JSON–LD. Additionally, the Features file contained its own set of geometries, which was exported into a separate JSON–LD file along with its elevation value to form a fourth file, named “features-geo.json.” Extracted data from external files can be represented in HyperText Markup Language (HTML) path objects. The goal was to import multiple JSON–LD files using this approach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171150","usgsCitation":"Powell, L.J., and Varanka, D.E., 2018, A linked GeoData map for enabling information access: U.S. Geological Survey Open–File Report 2017–1150, 6 p, https://doi.org/10.3133/ofr20171150.","productDescription":"iv, 6 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-090452","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":350413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1150/coverthb.jpg"},{"id":350414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1150/ofr20171150.pdf","text":"Report","size":"376 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1150"}],"contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
PDEPTH is an interactive, graphical computer program used to construct interpreted geological source models for observed potential-field geophysical profile data. The current version of PDEPTH has been adapted to the Windows platform from an earlier DOS-based version. The input total-field magnetic anomaly and vertical gravity anomaly profiles can be filtered to produce derivative products such as reduced-to-pole magnetic profiles, pseudogravity profiles, pseudomagnetic profiles, and upward-or-downward-continued profiles. A variety of source-location methods can be applied to the original and filtered profiles to estimate (and display on a cross section) the locations and physical properties of contacts, sheet edges, horizontal line sources, point sources, and interface surfaces. Two-and-a-half-dimensional source bodies having polygonal cross sections can be constructed using a mouse and keyboard. These bodies can then be adjusted until the calculated gravity and magnetic fields of the source bodies are close to the observed profiles. Auxiliary information such as the topographic surface, bathymetric surface, seismic basement, and geologic contact locations can be displayed on the cross section using optional input files. Test data files, used to demonstrate the source location methods in the report, and several utility programs are included.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7: Automated data processing and computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C17","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office under Interagency Agreement number IAG DE-AI52-12NA30865/DE-NA0001654. The USGS does not provide technical support for the software associated with this publication.","usgsCitation":"Phillips, J.D., 2018, PDEPTH—A computer program for the geophysical interpretation of magnetic and gravity profiles through Fourier filtering, source-depth analysis, and forward modeling: U.S. Geological Survey Techniques and Methods, book 7, chap. C17, 23 p., https://doi.org/10.3133/tm7C17.","productDescription":"viii, 23 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-032003","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":425658,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/tm/07/c17/readme.txt","text":"Read Me","size":"4.00 KB","linkFileType":{"id":2,"text":"txt"}},{"id":425657,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c17/PDepthDataFiles.zip","size":"2.21 MB","linkFileType":{"id":6,"text":"zip"}},{"id":350415,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c17/coverthb.jpg"},{"id":350416,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c17/tm7c17.pdf","text":"Report","size":"776 kB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C17"}],"publicComments":"This report is Chapter 17 of Section C: Computer programs in Book 7: Automated data processing and computations.","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Impact crater populations crucially help us to understand solar system dynamics, planetary surface histories, and surface modification processes. A single previous effort to standardize how crater data are displayed in graphs, tables, and archives, was in a 1978 NASA report by the Crater Analysis Techniques Working Group, published in 1979 in Icarus. The report had a significant lasting effect, but later decades brought major advances in statistical and computer sciences while the crater field has remained fairly stagnant. In this new work, we revisit the fundamental techniques for displaying and analyzing crater population data and demonstrate better statistical methods that can be used. Specifically, we address (1) how crater size-frequency distributions (SFDs) are constructed, (2) how error bars are assigned to SFDs, and (3) how SFDs are fit to power laws and other models. We show how the new methods yield results similar to those of previous techniques in that the SFDs have familiar shapes but better account for multiple sources of uncertainty. We also recommend graphic, display, and archiving methods that reflect computers' capabilities and fulfill NASA's current requirements for Data Management Plans.
","language":"English","publisher":"The Meteoritical Society","doi":"10.1111/maps.12990","usgsCitation":"Robbins, S.J., Riggs, J.D., Weaver, B.P., Bierhaus, E.B., Chapman, C.R., Kirchoff, M.R., Singer, K.N., and Gaddis, L., 2018, Revised recommended methods for analyzing crater size-frequency distributions: Meteoritics and Planetary Science, v. 53, no. 4, p. 891-931, https://doi.org/10.1111/maps.12990.","productDescription":"41 p.","startPage":"891","endPage":"931","ipdsId":"IP-080708","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/maps.12990","text":"Publisher Index Page"},{"id":355669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-10","publicationStatus":"PW","scienceBaseUri":"5b6fc4bbe4b0f5d57878eac6","contributors":{"authors":[{"text":"Robbins, Stuart J.","contributorId":204229,"corporation":false,"usgs":false,"family":"Robbins","given":"Stuart","email":"","middleInitial":"J.","affiliations":[{"id":36712,"text":"Southwest Research Institute","active":true,"usgs":false}],"preferred":false,"id":739951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riggs, Jamie D.","contributorId":204236,"corporation":false,"usgs":false,"family":"Riggs","given":"Jamie","email":"","middleInitial":"D.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":739952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, Brian P.","contributorId":204237,"corporation":false,"usgs":false,"family":"Weaver","given":"Brian","email":"","middleInitial":"P.","affiliations":[{"id":36891,"text":"Statistical Sciences, CCS-6, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":739953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bierhaus, Edward B.","contributorId":206277,"corporation":false,"usgs":false,"family":"Bierhaus","given":"Edward","email":"","middleInitial":"B.","affiliations":[{"id":37297,"text":"Lockheed Martin Space Systems Company","active":true,"usgs":false}],"preferred":false,"id":739954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Clark R.","contributorId":206278,"corporation":false,"usgs":false,"family":"Chapman","given":"Clark","email":"","middleInitial":"R.","affiliations":[{"id":37298,"text":"Southwest Research Institute, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":739955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirchoff, Michelle R.","contributorId":206279,"corporation":false,"usgs":false,"family":"Kirchoff","given":"Michelle","email":"","middleInitial":"R.","affiliations":[{"id":37298,"text":"Southwest Research Institute, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":739956,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singer, Kelsi N.","contributorId":196151,"corporation":false,"usgs":false,"family":"Singer","given":"Kelsi","email":"","middleInitial":"N.","affiliations":[{"id":7037,"text":"Southwest Research Institute, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":739957,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gaddis, Lisa 0000-0001-9953-5483 lgaddis@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-5483","contributorId":206276,"corporation":false,"usgs":true,"family":"Gaddis","given":"Lisa","email":"lgaddis@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739950,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70193581,"text":"tm6B9 - 2018 - Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)","interactions":[],"lastModifiedDate":"2018-01-09T09:46:12","indexId":"tm6B9","displayToPublicDate":"2018-01-08T16:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-B9","title":"Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)","docAbstract":"This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Surface water in Book 6: Modeling techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B9","usgsCitation":"Regan, R.S., Markstrom, S.L., Hay, L.E., Viger, R.J., Norton, P.A., Driscoll, J.M., LaFontaine, J.H., 2018, Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS): U.S. Geological Survey Techniques and Methods, book 6, chap B9, 38 p., https://doi.org/10.3133/tm6B9.","productDescription":"vii, 38 p.","onlineOnly":"Y","ipdsId":"IP-084916","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":438059,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TYOJKN","text":"USGS data release","linkHelpText":"National Hydrologic Model v1.0 water budget components aggregated to 10 and 12-digit Hydrologic Unit Code boundaries"},{"id":350326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/b09/coverthb.jpg"},{"id":350327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/b09/tm6b9.pdf","text":"Report","size":"5.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-B9"}],"publicComments":"This report is Chapter 9 of Section B: Surface Water in Book 6 Modeling Techniques.","contact":"Director, Integrated Modeling and Prediction Division
U.S. Geological Survey
Mail Stop 415
12201 Sunrise Valley Drive
Reston, VA 20192
The analysis described in this report is part of a longterm project monitoring the biological communities, habitat, and water quality of the Fountain Creek Basin. Biology, habitat, and water-quality data have been collected at 10 sites since 2003. These data include annual samples of aquatic invertebrate communities, fish communities, water quality, and quantitative riverine habitat. This report examines trends in biological communities from 2003 to 2016 and explores relationships between biological communities and abiotic variables (antecedent streamflow, physical habitat, and water quality). Six biological metrics (three invertebrate and three fish) and four individual fish species were used to examine trends in these data and how streamflow, habitat, and (or) water quality may explain these trends. The analysis of 79 trends shows that the majority of significant trends decreased over the trend period. Overall, 19 trends before adjustments for streamflow in the fish (12) and invertebrate (7) metrics were all decreasing except for the metric Invertebrate Species Richness at the most upstream site in Monument Creek. Seven of these trends were explained by streamflow and four trends were revealed that were originally masked by variability in antecedent streamflow. Only two sites (Jimmy Camp Creek at Fountain, CO and Fountain Creek near Pinon, CO) had no trends in the fish or invertebrate metrics. Ten of the streamflow-adjusted trends were explained by habitat, one was explained by water quality, and five were not explained by any of the variables that were tested. Overall, from 2003 to 2016, all the fish metric trends were decreasing with an average decline of 40 percent, and invertebrate metrics decreased on average by 9.5 percent. A potential peak streamflow threshold was identified above which there is severely limited production of age-0 flathead chub (Platygobio gracilis).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175162","collaboration":"Prepared in cooperation with the City of Colorado Springs, Water Resources Engineering Division, Public Works Department and Colorado Springs Utilities","usgsCitation":"Roberts, J.J., Bruce, J.F., and Zuellig, R.E., 2018, Changes in biological communities of the Fountain Creek Basin, Colorado, 2003–2016, in relation to antecedent streamflow, water quality, and habitat: U.S. Geological Survey Scientific Investigations Report 2017–5162, 20 p., https://doi.org/10.3133/sir20175162.","productDescription":"Report: vi, 20 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-088880","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":350235,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/f747493V","text":"USGS data release","linkHelpText":"Datasets of ecological communities (invertebrates and fish), streamflow, habitat, and water quality to examine the presence of trends in ecological communities from the Fountain Creek Basin, Colorado, USA, 2003-2016"},{"id":438060,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F747493V","text":"USGS data release","linkHelpText":"Datasets of ecological communities (invertebrates and fish), streamflow, habitat, and water quality to examine the presence of trends in ecological communities from the Fountain Creek basin, Colorado, USA, 2003-2016."},{"id":350234,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5162/sir20175162.pdf","text":"Report","size":"5.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5162"},{"id":350233,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5162/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Fountain Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105,\n 38.25\n ],\n [\n -104.5,\n 38.25\n ],\n [\n -104.5,\n 39\n ],\n [\n -105,\n 39\n ],\n [\n -105,\n 38.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Fugitive dust from unpaved roads creates human health hazards, degrades road surfaces, and increases the cost of road maintenance. As a result, many different chemical treatments are applied to unpaved roads in an attempt to control dust and stabilize the wearing course. However, investigations of the effectiveness of these treatments have often been poorly planned or executed. The objective of this study was to use a combination of real-time dust monitoring and objective road condition evaluations to assess the success of two chemical treatments for a period of 19?months post-application, to provide quantitative information in support of road management decisions. Dust production from road sections treated with calcium chloride-based durablend-C™ or the synthetic fluid EnviroKleen® was monitored on five dates using a vehicle-mounted particulate matter meter. Both products reduced dust by up to 99% relative to an untreated control section during the monitoring period, and quantitative data from the meter were consistent with qualitative observations of dust conditions. Linear models of dust production indicated that road treatment and humidity explained 69% of the variation in dust over time. Road sections treated with either product developed less rutting and fewer potholes than the untreated control. Overall, the combination of real-time dust monitoring and surface condition evaluation was an effective approach for generating quantitative data on endpoints of interest to road managers.
","language":"English","publisher":"Sage Publications","doi":"10.1177/0361198118799167","usgsCitation":"Kunz, B.K., Green, N., Albers, J.L., Wildhaber, M.L., and Little, E.E., 2018, Use of real-time dust monitoring and surface condition to evaluate success of unpaved road treatments: Transportation Research Record, v. 2672, no. 52, p. 195-204, https://doi.org/10.1177/0361198118799167.","productDescription":"10 p.","startPage":"195","endPage":"204","ipdsId":"IP-092378","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":362798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Loess Bluffs 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 -95.26691436767577,\n 40.096457912121444\n ],\n [\n -95.26811599731445,\n 40.07491896000657\n ],\n [\n -95.25678634643555,\n 40.05219060659433\n ],\n [\n -95.2488899230957,\n 40.051665005850715\n ],\n [\n -95.24940490722656,\n 40.05337319344778\n ],\n [\n -95.24614334106445,\n 40.053898781018304\n ],\n [\n -95.23086547851562,\n 40.07386810509482\n ],\n [\n -95.22897720336914,\n 40.10315461168825\n ],\n [\n -95.23721694946289,\n 40.110638378278054\n ],\n [\n -95.24288177490234,\n 40.110638378278054\n ],\n [\n -95.26691436767577,\n 40.096457912121444\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2672","issue":"52","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Kunz, Bethany K. 0000-0002-7193-9336 bkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-7193-9336","contributorId":3798,"corporation":false,"usgs":true,"family":"Kunz","given":"Bethany","email":"bkunz@usgs.gov","middleInitial":"K.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, Nicholas S. 0000-0002-8538-4191","orcid":"https://orcid.org/0000-0002-8538-4191","contributorId":202040,"corporation":false,"usgs":true,"family":"Green","given":"Nicholas S.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760473,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Little, Edward E. 0000-0003-0034-3639 elittle@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3639","contributorId":1746,"corporation":false,"usgs":true,"family":"Little","given":"Edward","email":"elittle@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760474,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227940,"text":"70227940 - 2018 - River otter distribution in Nebraska","interactions":[],"lastModifiedDate":"2022-02-02T16:47:55.910735","indexId":"70227940","displayToPublicDate":"2018-01-07T10:44:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"River otter distribution in Nebraska","docAbstract":"The river otter (Lontra canadensis) was extirpated from Nebraska, USA, in the early 1900s and reintroduced starting in 1986. Information is needed regarding the distribution of river otters in Nebraska before decisions can be made regarding its conservation status. Understanding distribution of a species is critically important for effective management. We investigated river otter distribution in Nebraska with occupancy modeling and maximum entropy (Maxent) modeling using 190 otter sign observations on Nebraska's navigable rivers and 380 historical otter records from November 1977 to April 2014. Both methods identified the Platte River, Elkhorn River, central and eastern Niobrara River, and southern Loup River system as core areas within the distribution of otters in Nebraska. The Maxent model provided more liberal estimates of site occupancy and identified some smaller rivers as being within the distribution of otters in Nebraska, which were not identified using occupancy modeling. We recommend that multiple data sets and analysis methods be used to estimate species distribution because this allows for the broadest geographical coverage and decreases the likelihood of overlooking areas with fewer animal records. If further reintroduction efforts or translocation efforts are to take place in the future, we recommend focusing on areas with high modeled occupancy but few historical and survey records
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.843","usgsCitation":"Bieber, N.R., Wilson, S.P., and Allen, C.R., 2018, River otter distribution in Nebraska: Wildlife Society Bulletin, v. 42, no. 1, p. 136-143, https://doi.org/10.1002/wsb.843.","productDescription":"8 p.","startPage":"136","endPage":"143","ipdsId":"IP-094064","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/08bde403cf22458cbb0e4cf09a97b49e","text":"External Repository"},{"id":395281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.053249,41.001406],[-104.053127,43.000585],[-101.849982,42.999329],[-101.625424,42.996238],[-100.472742,42.999288],[-98.49855,42.99856],[-98.490483,42.977948],[-98.467356,42.947556],[-98.448309,42.936428],[-98.444145,42.929242],[-98.437285,42.928393],[-98.430934,42.931504],[-98.42074,42.931924],[-98.34623,42.902747],[-98.325864,42.8865],[-98.280007,42.874996],[-98.25181,42.872824],[-98.219826,42.853157],[-98.189765,42.841628],[-98.167523,42.836925],[-98.14806,42.840013],[-98.137912,42.832728],[-98.127489,42.820127],[-98.107688,42.810633],[-98.094574,42.799309],[-98.067388,42.784759],[-98.062913,42.781119],[-98.059838,42.772772],[-98.056625,42.770781],[-98.035034,42.764205],[-98.013046,42.762299],[-98.005739,42.764167],[-98.000348,42.763256],[-97.977588,42.769923],[-97.950147,42.769619],[-97.936716,42.775754],[-97.921434,42.788352],[-97.908983,42.794909],[-97.888562,42.817251],[-97.879878,42.835395],[-97.878976,42.843673],[-97.875849,42.847725],[-97.877003,42.854394],[-97.875345,42.858724],[-97.84527,42.867734],[-97.828496,42.868797],[-97.817075,42.861781],[-97.774456,42.849774],[-97.72045,42.847439],[-97.686506,42.842435],[-97.657846,42.844626],[-97.611811,42.858367],[-97.603762,42.858329],[-97.591916,42.853837],[-97.561928,42.847552],[-97.531867,42.850105],[-97.504847,42.858477],[-97.49149,42.851625],[-97.470529,42.850455],[-97.452177,42.846048],[-97.442279,42.846224],[-97.431951,42.851542],[-97.417066,42.865918],[-97.408315,42.868334],[-97.393966,42.86425],[-97.376695,42.865195],[-97.368643,42.858419],[-97.359569,42.854816],[-97.336156,42.856802],[-97.306677,42.867604],[-97.289859,42.855499],[-97.267946,42.852583],[-97.248556,42.855386],[-97.218825,42.845848],[-97.217411,42.843519],[-97.218269,42.829561],[-97.213957,42.820143],[-97.213084,42.813007],[-97.210126,42.809296],[-97.200431,42.805485],[-97.166978,42.802087],[-97.150763,42.795566],[-97.138216,42.783428],[-97.134461,42.774494],[-97.131331,42.771929],[-97.096128,42.76934],[-97.065592,42.772189],[-97.033229,42.765904],[-97.02485,42.76243],[-96.99282,42.759481],[-96.97912,42.76009],[-96.96888,42.754278],[-96.96123,42.740623],[-96.965833,42.727096],[-96.964776,42.722455],[-96.961576,42.719841],[-96.948902,42.719465],[-96.924156,42.730327],[-96.906797,42.7338],[-96.886845,42.725222],[-96.860436,42.720797],[-96.843419,42.712024],[-96.806223,42.704154],[-96.801652,42.698774],[-96.800485,42.692466],[-96.802178,42.672237],[-96.800986,42.669758],[-96.793238,42.666024],[-96.76406,42.661985],[-96.746949,42.666223],[-96.728024,42.666882],[-96.691269,42.6562],[-96.687669,42.653126],[-96.687788,42.645992],[-96.709485,42.621932],[-96.711546,42.614758],[-96.7093,42.603753],[-96.681369,42.574486],[-96.658754,42.566426],[-96.643589,42.557604],[-96.63533,42.54764],[-96.632882,42.528987],[-96.628179,42.516963],[-96.625958,42.513576],[-96.611489,42.506088],[-96.603468,42.50446],[-96.591121,42.50541],[-96.567896,42.517877],[-96.548791,42.520547],[-96.538036,42.518131],[-96.528753,42.513273],[-96.520683,42.504761],[-96.515891,42.49427],[-96.508587,42.486691],[-96.501321,42.482749],[-96.478792,42.479635],[-96.443408,42.489495],[-96.423892,42.48898],[-96.396107,42.484095],[-96.386007,42.474495],[-96.381307,42.461694],[-96.380707,42.446394],[-96.387608,42.432494],[-96.413609,42.407894],[-96.41498,42.393442],[-96.408436,42.376092],[-96.417093,42.361443],[-96.417786,42.351449],[-96.413895,42.343393],[-96.407998,42.337408],[-96.384169,42.325874],[-96.375307,42.318339],[-96.369212,42.308344],[-96.368454,42.291848],[-96.365792,42.285875],[-96.356406,42.276493],[-96.336003,42.264806],[-96.328905,42.254734],[-96.327706,42.249992],[-96.330004,42.240224],[-96.322868,42.233637],[-96.323723,42.229887],[-96.336323,42.218922],[-96.356591,42.215182],[-96.35987,42.210545],[-96.348066,42.194747],[-96.347243,42.186721],[-96.350323,42.17744],[-96.347752,42.166806],[-96.33798,42.157197],[-96.319528,42.146647],[-96.310085,42.132523],[-96.301023,42.128042],[-96.279203,42.12348],[-96.2689,42.11359],[-96.266594,42.103262],[-96.267636,42.096177],[-96.276758,42.081416],[-96.279079,42.074026],[-96.278445,42.060399],[-96.275548,42.051976],[-96.271427,42.044988],[-96.263886,42.039858],[-96.256087,42.03808],[-96.246832,42.041616],[-96.238392,42.041088],[-96.225656,42.035217],[-96.221901,42.029558],[-96.223611,42.022652],[-96.238859,42.012315],[-96.241932,42.006965],[-96.240713,41.999351],[-96.236487,41.996428],[-96.225463,41.994734],[-96.215225,42.006701],[-96.206083,42.009267],[-96.194556,42.008662],[-96.188067,42.006323],[-96.183568,41.999987],[-96.192141,41.984461],[-96.186265,41.977417],[-96.177203,41.976325],[-96.156538,41.980137],[-96.141228,41.978063],[-96.129505,41.971673],[-96.129186,41.965136],[-96.133318,41.955732],[-96.144583,41.941544],[-96.136613,41.927167],[-96.136743,41.920826],[-96.142265,41.915379],[-96.159098,41.910057],[-96.161988,41.905553],[-96.161756,41.90182],[-96.148826,41.888132],[-96.146083,41.874988],[-96.142045,41.868865],[-96.135253,41.863128],[-96.116202,41.854869],[-96.110246,41.84885],[-96.107911,41.840339],[-96.11081,41.828172],[-96.107592,41.820685],[-96.09827,41.814206],[-96.075548,41.807811],[-96.069662,41.803509],[-96.064879,41.79623],[-96.066413,41.788913],[-96.077543,41.777824],[-96.079915,41.757895],[-96.084673,41.753314],[-96.102772,41.746339],[-96.106425,41.73789],[-96.105582,41.731647],[-96.10261,41.728016],[-96.079682,41.717962],[-96.073376,41.710674],[-96.073063,41.705004],[-96.082429,41.698159],[-96.090579,41.697425],[-96.105119,41.699917],[-96.111968,41.697773],[-96.117751,41.694221],[-96.121401,41.688522],[-96.120983,41.677861],[-96.114978,41.67122],[-96.099837,41.66103],[-96.095415,41.652736],[-96.095046,41.647365],[-96.100701,41.635507],[-96.116233,41.621574],[-96.117558,41.609999],[-96.109387,41.596871],[-96.101496,41.59158],[-96.085771,41.585746],[-96.081152,41.577289],[-96.082406,41.571229],[-96.093613,41.558271],[-96.096186,41.547192],[-96.09409,41.539265],[-96.08822,41.530595],[-96.07307,41.525052],[-96.05369,41.508859],[-96.040701,41.507076],[-96.036603,41.509047],[-96.034305,41.512853],[-96.027289,41.541081],[-96.023182,41.544364],[-96.016474,41.546085],[-96.005079,41.544004],[-96.001161,41.541146],[-95.993891,41.523412],[-95.992833,41.512002],[-95.997903,41.504789],[-96.019224,41.489296],[-96.019542,41.486617],[-96.011757,41.476212],[-96.004708,41.472342],[-95.982962,41.469778],[-95.962329,41.46281],[-95.946465,41.466166],[-95.936801,41.46519],[-95.925713,41.459382],[-95.920281,41.451566],[-95.921833,41.442062],[-95.933169,41.42943],[-95.929721,41.411331],[-95.93749,41.393095],[-95.92879,41.370096],[-95.93099,41.364696],[-95.93549,41.360596],[-95.954891,41.351796],[-95.956691,41.345496],[-95.946891,41.334096],[-95.92569,41.322197],[-95.88869,41.319097],[-95.883089,41.316697],[-95.874689,41.307097],[-95.871489,41.295797],[-95.872889,41.289497],[-95.88239,41.281397],[-95.90249,41.273398],[-95.912491,41.279498],[-95.90429,41.293497],[-95.90429,41.299597],[-95.920291,41.301097],[-95.927491,41.298397],[-95.929591,41.292297],[-95.928691,41.281398],[-95.913991,41.271398],[-95.920391,41.268398],[-95.921891,41.264598],[-95.921291,41.258498],[-95.910891,41.233998],[-95.912591,41.226998],[-95.924891,41.211198],[-95.927491,41.202198],[-95.923219,41.191046],[-95.91459,41.185098],[-95.864789,41.188298],[-95.850188,41.184798],[-95.844088,41.180598],[-95.841288,41.174998],[-95.841888,41.171098],[-95.846188,41.166698],[-95.852788,41.165398],[-95.867344,41.168734],[-95.871912,41.168122],[-95.880936,41.160269],[-95.883489,41.154898],[-95.882088,41.143998],[-95.865888,41.117898],[-95.86545,41.101266],[-95.862587,41.088399],[-95.865463,41.080367],[-95.878103,41.069587],[-95.882415,41.060411],[-95.879487,41.053299],[-95.861782,41.039427],[-95.859654,41.035695],[-95.859918,41.025403],[-95.869486,41.009399],[-95.867286,41.001599],[-95.860116,40.995242],[-95.838908,40.986484],[-95.833537,40.98266],[-95.829074,40.975688],[-95.829829,40.963857],[-95.837951,40.950618],[-95.839743,40.93278],[-95.836438,40.921642],[-95.830699,40.915004],[-95.814302,40.902936],[-95.809775,40.895447],[-95.809474,40.891228],[-95.815933,40.879846],[-95.824989,40.875],[-95.838735,40.872191],[-95.844073,40.869248],[-95.847785,40.864328],[-95.847084,40.854174],[-95.837186,40.835347],[-95.838601,40.826175],[-95.843921,40.817686],[-95.845342,40.811324],[-95.843745,40.803783],[-95.834523,40.787778],[-95.835232,40.779151],[-95.84662,40.768619],[-95.869982,40.759645],[-95.883643,40.747831],[-95.888697,40.736292],[-95.885349,40.721093],[-95.883178,40.717579],[-95.859378,40.708055],[-95.852615,40.702262],[-95.847931,40.694197],[-95.846034,40.682605],[-95.842801,40.677496],[-95.822913,40.66724],[-95.804307,40.664886],[-95.786568,40.657253],[-95.772832,40.642496],[-95.768926,40.621264],[-95.749685,40.606842],[-95.748858,40.599965],[-95.753148,40.59284],[-95.768527,40.583296],[-95.773549,40.578205],[-95.774704,40.573574],[-95.763833,40.553873],[-95.763624,40.548298],[-95.769281,40.536656],[-95.76692,40.531563],[-95.762857,40.528371],[-95.74868,40.524275],[-95.73725,40.52393],[-95.725214,40.527773],[-95.714291,40.527208],[-95.708591,40.521551],[-95.69721,40.528477],[-95.69505,40.533124],[-95.697281,40.536985],[-95.694147,40.556942],[-95.678718,40.56256],[-95.671754,40.562626],[-95.665486,40.556686],[-95.662097,40.549959],[-95.655848,40.546609],[-95.652262,40.538114],[-95.655674,40.523557],[-95.661687,40.517309],[-95.699969,40.505275],[-95.694726,40.493602],[-95.696756,40.478849],[-95.694651,40.471452],[-95.671742,40.456695],[-95.65819,40.44188],[-95.65563,40.434736],[-95.661463,40.415947],[-95.659134,40.40869],[-95.643934,40.386849],[-95.641027,40.366399],[-95.627124,40.3528],[-95.623728,40.346567],[-95.622704,40.340856],[-95.625204,40.334288],[-95.633807,40.329297],[-95.653729,40.322582],[-95.657764,40.315788],[-95.657328,40.310856],[-95.651507,40.306684],[-95.645329,40.305693],[-95.617931,40.313728],[-95.610439,40.31397],[-95.598657,40.309809],[-95.581787,40.29958],[-95.562157,40.297359],[-95.55162,40.288666],[-95.551488,40.281061],[-95.556275,40.270761],[-95.552473,40.261904],[-95.521925,40.24947],[-95.490333,40.248966],[-95.477501,40.24272],[-95.472548,40.236078],[-95.469718,40.227908],[-95.471393,40.217333],[-95.482319,40.200667],[-95.48254,40.192283],[-95.479193,40.185652],[-95.460746,40.169173],[-95.442818,40.163261],[-95.436348,40.15872],[-95.432165,40.141025],[-95.428749,40.135577],[-95.419186,40.130586],[-95.409481,40.130052],[-95.398667,40.126419],[-95.393347,40.119212],[-95.394216,40.108263],[-95.407591,40.09803],[-95.410643,40.091531],[-95.408455,40.079158],[-95.409856,40.07432],[-95.418345,40.066509],[-95.42164,40.058952],[-95.41932,40.048442],[-95.413588,40.038424],[-95.402665,40.030567],[-95.391527,40.027058],[-95.382957,40.027112],[-95.363983,40.031498],[-95.348777,40.029297],[-95.336242,40.019104],[-95.315271,40.01207],[-95.311163,40.007806],[-95.30829,39.999998],[-98.193483,40.002614],[-99.756835,40.001342],[-102.051744,40.003078],[-102.051614,41.002377],[-104.053249,41.001406]]]},\"properties\":{\"name\":\"Nebraska\",\"nation\":\"USA \"}}]}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bieber, N. R.","contributorId":273158,"corporation":false,"usgs":false,"family":"Bieber","given":"N.","email":"","middleInitial":"R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":832635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, S. P.","contributorId":273159,"corporation":false,"usgs":false,"family":"Wilson","given":"S.","email":"","middleInitial":"P.","affiliations":[{"id":56368,"text":"Nebraska Game and Parks","active":true,"usgs":false}],"preferred":false,"id":832636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263443,"text":"70263443 - 2018 - River otter distribution in Nebraska","interactions":[],"lastModifiedDate":"2025-02-11T15:28:17.418219","indexId":"70263443","displayToPublicDate":"2018-01-07T09:25:34","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"River otter distribution in Nebraska","docAbstract":"The river otter (Lontra canadensis) was extirpated from Nebraska, USA, in the early 1900s and reintroduced starting in 1986. Information is needed regarding the distribution of river otters in Nebraska before decisions can be made regarding its conservation status. Understanding distribution of a species is critically important for effective management. We investigated river otter distribution in Nebraska with occupancy modeling and maximum entropy (Maxent) modeling using 190 otter sign observations on Nebraska's navigable rivers and 380 historical otter records from November 1977 to April 2014. Both methods identified the Platte River, Elkhorn River, central and eastern Niobrara River, and southern Loup River system as core areas within the distribution of otters in Nebraska. The Maxent model provided more liberal estimates of site occupancy and identified some smaller rivers as being within the distribution of otters in Nebraska, which were not identified using occupancy modeling. We recommend that multiple data sets and analysis methods be used to estimate species distribution because this allows for the broadest geographical coverage and decreases the likelihood of overlooking areas with fewer animal records. If further reintroduction efforts or translocation efforts are to take place in the future, we recommend focusing on areas with high modeled occupancy but few historical and survey records.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.843","usgsCitation":"Bieber, N., Wilson, S., and Allen, C.R., 2018, River otter distribution in Nebraska: Wildlife Society Bulletin, v. 42, no. 1, p. 136-143, https://doi.org/10.1002/wsb.843.","productDescription":"8 p.","startPage":"136","endPage":"143","ipdsId":"IP-097555","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499837,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/08bde403cf22458cbb0e4cf09a97b49e","text":"External Repository"},{"id":481929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.053249,41.001406],[-104.053127,43.000585],[-101.849982,42.999329],[-101.625424,42.996238],[-100.472742,42.999288],[-98.49855,42.99856],[-98.490483,42.977948],[-98.467356,42.947556],[-98.448309,42.936428],[-98.444145,42.929242],[-98.437285,42.928393],[-98.430934,42.931504],[-98.42074,42.931924],[-98.34623,42.902747],[-98.325864,42.8865],[-98.280007,42.874996],[-98.25181,42.872824],[-98.219826,42.853157],[-98.189765,42.841628],[-98.167523,42.836925],[-98.14806,42.840013],[-98.137912,42.832728],[-98.127489,42.820127],[-98.107688,42.810633],[-98.094574,42.799309],[-98.067388,42.784759],[-98.062913,42.781119],[-98.059838,42.772772],[-98.056625,42.770781],[-98.035034,42.764205],[-98.013046,42.762299],[-98.005739,42.764167],[-98.000348,42.763256],[-97.977588,42.769923],[-97.950147,42.769619],[-97.936716,42.775754],[-97.921434,42.788352],[-97.908983,42.794909],[-97.888562,42.817251],[-97.879878,42.835395],[-97.878976,42.843673],[-97.875849,42.847725],[-97.877003,42.854394],[-97.875345,42.858724],[-97.84527,42.867734],[-97.828496,42.868797],[-97.817075,42.861781],[-97.774456,42.849774],[-97.72045,42.847439],[-97.686506,42.842435],[-97.657846,42.844626],[-97.611811,42.858367],[-97.603762,42.858329],[-97.591916,42.853837],[-97.561928,42.847552],[-97.531867,42.850105],[-97.504847,42.858477],[-97.49149,42.851625],[-97.470529,42.850455],[-97.452177,42.846048],[-97.442279,42.846224],[-97.431951,42.851542],[-97.417066,42.865918],[-97.408315,42.868334],[-97.393966,42.86425],[-97.376695,42.865195],[-97.368643,42.858419],[-97.359569,42.854816],[-97.336156,42.856802],[-97.306677,42.867604],[-97.289859,42.855499],[-97.267946,42.852583],[-97.248556,42.855386],[-97.218825,42.845848],[-97.217411,42.843519],[-97.218269,42.829561],[-97.213957,42.820143],[-97.213084,42.813007],[-97.210126,42.809296],[-97.200431,42.805485],[-97.166978,42.802087],[-97.150763,42.795566],[-97.138216,42.783428],[-97.134461,42.774494],[-97.131331,42.771929],[-97.096128,42.76934],[-97.065592,42.772189],[-97.033229,42.765904],[-97.02485,42.76243],[-96.99282,42.759481],[-96.97912,42.76009],[-96.96888,42.754278],[-96.96123,42.740623],[-96.965833,42.727096],[-96.964776,42.722455],[-96.961576,42.719841],[-96.948902,42.719465],[-96.924156,42.730327],[-96.906797,42.7338],[-96.886845,42.725222],[-96.860436,42.720797],[-96.843419,42.712024],[-96.806223,42.704154],[-96.801652,42.698774],[-96.800485,42.692466],[-96.802178,42.672237],[-96.800986,42.669758],[-96.793238,42.666024],[-96.76406,42.661985],[-96.746949,42.666223],[-96.728024,42.666882],[-96.691269,42.6562],[-96.687669,42.653126],[-96.687788,42.645992],[-96.709485,42.621932],[-96.711546,42.614758],[-96.7093,42.603753],[-96.681369,42.574486],[-96.658754,42.566426],[-96.643589,42.557604],[-96.63533,42.54764],[-96.632882,42.528987],[-96.628179,42.516963],[-96.625958,42.513576],[-96.611489,42.506088],[-96.603468,42.50446],[-96.591121,42.50541],[-96.567896,42.517877],[-96.548791,42.520547],[-96.538036,42.518131],[-96.528753,42.513273],[-96.520683,42.504761],[-96.515891,42.49427],[-96.508587,42.486691],[-96.501321,42.482749],[-96.478792,42.479635],[-96.443408,42.489495],[-96.423892,42.48898],[-96.396107,42.484095],[-96.386007,42.474495],[-96.381307,42.461694],[-96.380707,42.446394],[-96.387608,42.432494],[-96.413609,42.407894],[-96.41498,42.393442],[-96.408436,42.376092],[-96.417093,42.361443],[-96.417786,42.351449],[-96.413895,42.343393],[-96.407998,42.337408],[-96.384169,42.325874],[-96.375307,42.318339],[-96.369212,42.308344],[-96.368454,42.291848],[-96.365792,42.285875],[-96.356406,42.276493],[-96.336003,42.264806],[-96.328905,42.254734],[-96.327706,42.249992],[-96.330004,42.240224],[-96.322868,42.233637],[-96.323723,42.229887],[-96.336323,42.218922],[-96.356591,42.215182],[-96.35987,42.210545],[-96.348066,42.194747],[-96.347243,42.186721],[-96.350323,42.17744],[-96.347752,42.166806],[-96.33798,42.157197],[-96.319528,42.146647],[-96.310085,42.132523],[-96.301023,42.128042],[-96.279203,42.12348],[-96.2689,42.11359],[-96.266594,42.103262],[-96.267636,42.096177],[-96.276758,42.081416],[-96.279079,42.074026],[-96.278445,42.060399],[-96.275548,42.051976],[-96.271427,42.044988],[-96.263886,42.039858],[-96.256087,42.03808],[-96.246832,42.041616],[-96.238392,42.041088],[-96.225656,42.035217],[-96.221901,42.029558],[-96.223611,42.022652],[-96.238859,42.012315],[-96.241932,42.006965],[-96.240713,41.999351],[-96.236487,41.996428],[-96.225463,41.994734],[-96.215225,42.006701],[-96.206083,42.009267],[-96.194556,42.008662],[-96.188067,42.006323],[-96.183568,41.999987],[-96.192141,41.984461],[-96.186265,41.977417],[-96.177203,41.976325],[-96.156538,41.980137],[-96.141228,41.978063],[-96.129505,41.971673],[-96.129186,41.965136],[-96.133318,41.955732],[-96.144583,41.941544],[-96.136613,41.927167],[-96.136743,41.920826],[-96.142265,41.915379],[-96.159098,41.910057],[-96.161988,41.905553],[-96.161756,41.90182],[-96.148826,41.888132],[-96.146083,41.874988],[-96.142045,41.868865],[-96.135253,41.863128],[-96.116202,41.854869],[-96.110246,41.84885],[-96.107911,41.840339],[-96.11081,41.828172],[-96.107592,41.820685],[-96.09827,41.814206],[-96.075548,41.807811],[-96.069662,41.803509],[-96.064879,41.79623],[-96.066413,41.788913],[-96.077543,41.777824],[-96.079915,41.757895],[-96.084673,41.753314],[-96.102772,41.746339],[-96.106425,41.73789],[-96.105582,41.731647],[-96.10261,41.728016],[-96.079682,41.717962],[-96.073376,41.710674],[-96.073063,41.705004],[-96.082429,41.698159],[-96.090579,41.697425],[-96.105119,41.699917],[-96.111968,41.697773],[-96.117751,41.694221],[-96.121401,41.688522],[-96.120983,41.677861],[-96.114978,41.67122],[-96.099837,41.66103],[-96.095415,41.652736],[-96.095046,41.647365],[-96.100701,41.635507],[-96.116233,41.621574],[-96.117558,41.609999],[-96.109387,41.596871],[-96.101496,41.59158],[-96.085771,41.585746],[-96.081152,41.577289],[-96.082406,41.571229],[-96.093613,41.558271],[-96.096186,41.547192],[-96.09409,41.539265],[-96.08822,41.530595],[-96.07307,41.525052],[-96.05369,41.508859],[-96.040701,41.507076],[-96.036603,41.509047],[-96.034305,41.512853],[-96.027289,41.541081],[-96.023182,41.544364],[-96.016474,41.546085],[-96.005079,41.544004],[-96.001161,41.541146],[-95.993891,41.523412],[-95.992833,41.512002],[-95.997903,41.504789],[-96.019224,41.489296],[-96.019542,41.486617],[-96.011757,41.476212],[-96.004708,41.472342],[-95.982962,41.469778],[-95.962329,41.46281],[-95.946465,41.466166],[-95.936801,41.46519],[-95.925713,41.459382],[-95.920281,41.451566],[-95.921833,41.442062],[-95.933169,41.42943],[-95.929721,41.411331],[-95.93749,41.393095],[-95.92879,41.370096],[-95.93099,41.364696],[-95.93549,41.360596],[-95.954891,41.351796],[-95.956691,41.345496],[-95.946891,41.334096],[-95.92569,41.322197],[-95.88869,41.319097],[-95.883089,41.316697],[-95.874689,41.307097],[-95.871489,41.295797],[-95.872889,41.289497],[-95.88239,41.281397],[-95.90249,41.273398],[-95.912491,41.279498],[-95.90429,41.293497],[-95.90429,41.299597],[-95.920291,41.301097],[-95.927491,41.298397],[-95.929591,41.292297],[-95.928691,41.281398],[-95.913991,41.271398],[-95.920391,41.268398],[-95.921891,41.264598],[-95.921291,41.258498],[-95.910891,41.233998],[-95.912591,41.226998],[-95.924891,41.211198],[-95.927491,41.202198],[-95.923219,41.191046],[-95.91459,41.185098],[-95.864789,41.188298],[-95.850188,41.184798],[-95.844088,41.180598],[-95.841288,41.174998],[-95.841888,41.171098],[-95.846188,41.166698],[-95.852788,41.165398],[-95.867344,41.168734],[-95.871912,41.168122],[-95.880936,41.160269],[-95.883489,41.154898],[-95.882088,41.143998],[-95.865888,41.117898],[-95.86545,41.101266],[-95.862587,41.088399],[-95.865463,41.080367],[-95.878103,41.069587],[-95.882415,41.060411],[-95.879487,41.053299],[-95.861782,41.039427],[-95.859654,41.035695],[-95.859918,41.025403],[-95.869486,41.009399],[-95.867286,41.001599],[-95.860116,40.995242],[-95.838908,40.986484],[-95.833537,40.98266],[-95.829074,40.975688],[-95.829829,40.963857],[-95.837951,40.950618],[-95.839743,40.93278],[-95.836438,40.921642],[-95.830699,40.915004],[-95.814302,40.902936],[-95.809775,40.895447],[-95.809474,40.891228],[-95.815933,40.879846],[-95.824989,40.875],[-95.838735,40.872191],[-95.844073,40.869248],[-95.847785,40.864328],[-95.847084,40.854174],[-95.837186,40.835347],[-95.838601,40.826175],[-95.843921,40.817686],[-95.845342,40.811324],[-95.843745,40.803783],[-95.834523,40.787778],[-95.835232,40.779151],[-95.84662,40.768619],[-95.869982,40.759645],[-95.883643,40.747831],[-95.888697,40.736292],[-95.885349,40.721093],[-95.883178,40.717579],[-95.859378,40.708055],[-95.852615,40.702262],[-95.847931,40.694197],[-95.846034,40.682605],[-95.842801,40.677496],[-95.822913,40.66724],[-95.804307,40.664886],[-95.786568,40.657253],[-95.772832,40.642496],[-95.768926,40.621264],[-95.749685,40.606842],[-95.748858,40.599965],[-95.753148,40.59284],[-95.768527,40.583296],[-95.773549,40.578205],[-95.774704,40.573574],[-95.763833,40.553873],[-95.763624,40.548298],[-95.769281,40.536656],[-95.76692,40.531563],[-95.762857,40.528371],[-95.74868,40.524275],[-95.73725,40.52393],[-95.725214,40.527773],[-95.714291,40.527208],[-95.708591,40.521551],[-95.69721,40.528477],[-95.69505,40.533124],[-95.697281,40.536985],[-95.694147,40.556942],[-95.678718,40.56256],[-95.671754,40.562626],[-95.665486,40.556686],[-95.662097,40.549959],[-95.655848,40.546609],[-95.652262,40.538114],[-95.655674,40.523557],[-95.661687,40.517309],[-95.699969,40.505275],[-95.694726,40.493602],[-95.696756,40.478849],[-95.694651,40.471452],[-95.671742,40.456695],[-95.65819,40.44188],[-95.65563,40.434736],[-95.661463,40.415947],[-95.659134,40.40869],[-95.643934,40.386849],[-95.641027,40.366399],[-95.627124,40.3528],[-95.623728,40.346567],[-95.622704,40.340856],[-95.625204,40.334288],[-95.633807,40.329297],[-95.653729,40.322582],[-95.657764,40.315788],[-95.657328,40.310856],[-95.651507,40.306684],[-95.645329,40.305693],[-95.617931,40.313728],[-95.610439,40.31397],[-95.598657,40.309809],[-95.581787,40.29958],[-95.562157,40.297359],[-95.55162,40.288666],[-95.551488,40.281061],[-95.556275,40.270761],[-95.552473,40.261904],[-95.521925,40.24947],[-95.490333,40.248966],[-95.477501,40.24272],[-95.472548,40.236078],[-95.469718,40.227908],[-95.471393,40.217333],[-95.482319,40.200667],[-95.48254,40.192283],[-95.479193,40.185652],[-95.460746,40.169173],[-95.442818,40.163261],[-95.436348,40.15872],[-95.432165,40.141025],[-95.428749,40.135577],[-95.419186,40.130586],[-95.409481,40.130052],[-95.398667,40.126419],[-95.393347,40.119212],[-95.394216,40.108263],[-95.407591,40.09803],[-95.410643,40.091531],[-95.408455,40.079158],[-95.409856,40.07432],[-95.418345,40.066509],[-95.42164,40.058952],[-95.41932,40.048442],[-95.413588,40.038424],[-95.402665,40.030567],[-95.391527,40.027058],[-95.382957,40.027112],[-95.363983,40.031498],[-95.348777,40.029297],[-95.336242,40.019104],[-95.315271,40.01207],[-95.311163,40.007806],[-95.30829,39.999998],[-98.193483,40.002614],[-99.756835,40.001342],[-102.051744,40.003078],[-102.051614,41.002377],[-104.053249,41.001406]]]},\"properties\":{\"name\":\"Nebraska\",\"nation\":\"USA \"}}]}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bieber, N.R.","contributorId":350797,"corporation":false,"usgs":false,"family":"Bieber","given":"N.R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":927011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, S.P.","contributorId":341215,"corporation":false,"usgs":false,"family":"Wilson","given":"S.P.","email":"","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":927012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":927013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194678,"text":"sir20175157 - 2018 - Simulation of hydrodynamics, water quality, and lake sturgeon habitat volumes in Lake St. Croix, Wisconsin and Minnesota, 2013","interactions":[],"lastModifiedDate":"2019-10-23T12:29:22","indexId":"sir20175157","displayToPublicDate":"2018-01-05T16:45:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5157","title":"Simulation of hydrodynamics, water quality, and lake sturgeon habitat volumes in Lake St. Croix, Wisconsin and Minnesota, 2013","docAbstract":"Lake St. Croix is a naturally impounded, riverine lake that makes up the last 40 kilometers of the St. Croix River. Substantial land-use changes during the past 150 years, including increased agriculture and urban development, have reduced Lake St. Croix water-quality and increased nutrient loads delivered to Lake St. Croix. A recent (2012–13) total maximum daily load phosphorus-reduction plan set the goal to reduce total phosphorus loads to Lake St. Croix by 20 percent by 2020 and reduce Lake St. Croix algal bloom frequencies. The U.S. Geological Survey, in cooperation with the National Park Service, developed a two-dimensional, carbon-based, laterally averaged, hydrodynamic and water-quality model, CE–QUAL–W2, that addresses the interaction between nutrient cycling, primary production, and trophic dynamics to predict responses in the distribution of water temperature, oxygen, and chlorophyll a. Distribution is evaluated in the context of habitat for lake sturgeon, including a combination of temperature and dissolved oxygen conditions termed oxy-thermal habitat.
The Lake St. Croix CE–QUAL–W2 model successfully reproduced temperature and dissolved oxygen in the lake longitudinally (from upstream to downstream), vertically, and temporally over the seasons. The simulated water temperature profiles closely matched the measured water temperature profiles throughout the year, including the prediction of thermocline transition depths (often within 1 meter), the absolute temperature of the thermocline transitions (often within 1.0 degree Celsius), and profiles without a strong thermocline transition. Simulated dissolved oxygen profiles matched the trajectories of the measured dissolved oxygen concentrations at multiple depths over time, and the simulated concentrations matched the depth and slope of the measured concentrations.
Additionally, trends in the measured water-quality data were captured by the model simulation, gaining some potential insights into the underlying mechanisms of critical Lake St. Croix metabolic processes. The CE–QUAL–W2 model tracked nitrate plus nitrite, total nitrogen, and total phosphorus throughout the year. Inflow nutrient contributions (loads), largely dominated by upstream St. Croix River loads, were the most important controls on Lake St. Croix water quality. Close to 60 percent of total phosphorus to the lake was from phosphorus derived from organic matter, and about 89 percent of phosphorus to Lake St. Croix was delivered by St. Croix River inflows. The Lake St. Croix CE–QUAL–W2 model offered potential mechanisms for the effect of external and internal loadings on the biotic response regarding the modeled algal community types of diatoms, green algae, and blue-green algae. The model also suggested the seasonal dominance of blue-green algae in all four pools of the lake.
A sensitivity analysis was completed to test the total maximum daily load phosphorus-reduction scenario responses of total phosphorus and chlorophyll a. The modeling indicates that phosphorus reductions would result in similar Lake St. Croix reduced concentrations, although chlorophyll a concentrations did not decrease in the same proportional amounts as the total phosphorus concentrations had decreased. The smaller than expected reduction in algal growth rates highlighted that although inflow phosphorus loads are important, other constituents also can affect the algal response of the lake, such as changes in light penetration and the breakdown of organic matter releasing nutrients.
The available habitat suitable for lake sturgeon was evaluated using the modeling results to determine the total volume of good-growth habitat, optimal growth habitat, and lethal temperature habitat. Overall, with the calibrated model, the fish habitat volume in general contained a large proportion of good-growth habitat and a sustained period of optimal growth habitat in the summer. Only brief periods of lethal oxy-thermal habitat were present in Lake St. Croix during the model simulation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175157","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Smith, E.A., Kiesling, R.L., Ziegeweid, J.R., Elliott, S.M., and Magdalene, Suzanne, 2018, Simulation of hydrodynamics, water quality, and lake sturgeon habitat volumes in Lake St. Croix, Wisconsin and Minnesota, 2013: U.S. Geological Survey Scientific Investigations Report 2017–5157, 60 p., https://doi.org/10.3133/sir20175157.","productDescription":"Report: ix, 60 p.; Data Release","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-075804","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":350333,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7319V2J","text":"USGS data release","description":"USGS data release","linkHelpText":"CE–QUAL–W2 water-quality model and supporting LOADEST models for Lake St. Croix, Wisconsin and Minnesota, 2013"},{"id":350332,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5157/sir20175157.pdf","text":"Report","size":"3.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5157"},{"id":350331,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5157/coverthb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Lake St. Croix","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.81936645507811,\n 44.74136858658327\n ],\n [\n -92.73216247558594,\n 44.74136858658327\n ],\n [\n -92.73216247558594,\n 45.07352060670971\n ],\n [\n -92.81936645507811,\n 45.07352060670971\n ],\n [\n -92.81936645507811,\n 44.74136858658327\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
From August 2016 to March 2017, the U.S. Geological Survey (USGS) collected representative samples of filtered and unfiltered water and suspended sediment (including the colloidal fraction) at USGS streamgage 12113390 (Duwamish River at Golf Course, at Tukwila, Washington) during 13 periods of differing flow conditions. Samples were analyzed by Washington-State-accredited laboratories for a large suite of compounds, including metals, dioxins/furans, semivolatile compounds including polycyclic aromatic hydrocarbons, butyltins, the 209 polychlorinated biphenyl (PCB) congeners, and total and dissolved organic carbon. Concurrent with the chemistry sampling, water-quality field parameters were measured, and representative water samples were collected and analyzed for river suspended-sediment concentration and particle-size distribution. The results provide new data that can be used to estimate sediment and chemical loads transported by the Green River to the Lower Duwamish Waterway.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1073","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Conn, K.E., Black, R.W., Peterson, N.T., Senter, C.A., and Chapman, E.A., 2018, Chemical concentrations in water and\nsuspended sediment, Green River to Lower Duwamish Waterway near Seattle, Washington, 2016–17: U.S. Geological\nSurvey Data Series 1073, 17 p., https://doi.org/10.3133/ds1073.","productDescription":"Report: v, 17 p.; Appendix","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-091233","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":350280,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1073/ds1073_appendixa.xlsx","text":"Appendix A","size":"259 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 1073 Appendix A"},{"id":350278,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1073/coverthb.jpg"},{"id":350279,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1073/ds1073.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1073"}],"country":"United States","state":"Washington","city":"Seattle","otherGeospatial":"Green River, Lower Duwamish Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.35507965087889,\n 47.50931654292719\n ],\n [\n -122.29499816894531,\n 47.50931654292719\n ],\n [\n -122.29499816894531,\n 47.572124991940015\n ],\n [\n -122.35507965087889,\n 47.572124991940015\n ],\n [\n -122.35507965087889,\n 47.50931654292719\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Maps of geoelectric amplitude covering about half the continental United States are presented that will be exceeded, on average, once per century in response to an extreme-intensity geomagnetic disturbance. These maps are constructed using an empirical parameterization of induction: convolving latitude-dependent statistical maps of extreme-value geomagnetic disturbances, obtained from decades of 1-minute magnetic observatory data, with local estimates of Earth-surface impedance obtained at discrete geographic sites from magnetotelluric surveys. Geoelectric amplitudes are estimated for geomagnetic waveforms having a 240-s (and 1200-s) sinusoidal period and amplitudes over 10 min (1 h) that exceed a once-per-century threshold. As a result of the combination of geographic differences in geomagnetic variation and Earth-surface impedance, once-per-century geoelectric amplitudes span more than two orders of magnitude and are a highly granular function of location. Specifically for north-south 240-s induction, once-per-century geoelectric amplitudes across large parts of the United States have a median value of 0.34 V/km; for east-west variation, they have a median value of 0.23 V/km. In Northern Minnesota, amplitudes exceed 14.00 V/km for north-south geomagnetic variation (23.34 V/km for east-west variation), while just over 100 km away, amplitudes are only 0.08 V/km (0.02 V/km). At some sites in the northern-central United States, once-per-century geoelectric amplitudes exceed the 2 V/km realized in Québec during the March 1989 storm.
The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover. Performance among algorithms varies across complex natural systems, and it is reasonable to ask if aggregating the strengths of an ensemble of classifiers might result in increased overall accuracy. Relatively simple rules have been used in the past to aggregate classifications among remotely sensed maps (e.g. using majority predictions), and in other fields, empirical models have been used to create situationally specific algorithm weights. The latter process, called “stacked generalization” (or “stacking”), typically uses a parametric model for the fusion of algorithm outputs. We tested the performance of several leading forest disturbance detection algorithms against ensembles of the outputs of those same algorithms based upon stacking using both parametric and Random Forests-based fusion rules. Stacking using a Random Forests model cut omission and commission error rates in half in many cases in relation to individual change detection algorithms, and cut error rates by one quarter compared to more conventional parametric stacking. Stacking also offers two auxiliary benefits: alignment of outputs to the precise definitions built into a particular set of empirical calibration data; and, outputs which may be adjusted such that map class totals match independent estimates of change in each year. In general, ensemble predictions improve when new inputs are added that are both informative and uncorrelated with existing ensemble components. As increased use of cloud-based computing makes ensemble mapping methods more accessible, the most useful new algorithms may be those that specialize in providing spectral, temporal, or thematic information not already available through members of existing ensembles.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.09.029","usgsCitation":"Healey, S.P., Cohen, W., Yang, Z., Brewer, C.K., Brooks, E.B., Gorelick, N., Hernandez, A.J., Huang, C., Hughes, M.J., Kennedy, R.E., Loveland, T., Moisen, G.G., Schroeder, T.A., Stehman, S.V., Vogelmann, J., Woodcock, C.E., Yang, L., and Zhu, Z., 2018, Mapping forest change using stacked generalization: An ensemble approach: Remote Sensing of Environment, v. 204, p. 717-728, https://doi.org/10.1016/j.rse.2017.09.029.","productDescription":"12 p.","startPage":"717","endPage":"728","ipdsId":"IP-087348","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2017.09.029","text":"Publisher Index Page"},{"id":421645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-66.28243,18.51476],[-65.7713,18.42668],[-65.591,18.22803],[-65.84716,17.97591],[-66.59993,17.98182],[-67.18416,17.94655],[-67.24243,18.37446],[-67.10068,18.5206],[-66.28243,18.51476]]],[[[-155.54211,19.08348],[-155.68817,18.91619],[-155.93665,19.05939],[-155.90806,19.33888],[-156.07347,19.70294],[-156.02368,19.81422],[-155.85008,19.97729],[-155.91907,20.17395],[-155.86108,20.26721],[-155.78505,20.2487],[-155.40214,20.07975],[-155.22452,19.99302],[-155.06226,19.8591],[-154.80741,19.50871],[-154.83147,19.45328],[-155.22217,19.23972],[-155.54211,19.08348]]],[[[-156.07926,20.64397],[-156.41445,20.57241],[-156.58673,20.783],[-156.70167,20.8643],[-156.71055,20.92676],[-156.61258,21.01249],[-156.25711,20.91745],[-155.99566,20.76404],[-156.07926,20.64397]]],[[[-156.75824,21.17684],[-156.78933,21.06873],[-157.32521,21.09777],[-157.25027,21.21958],[-156.75824,21.17684]]],[[[-157.65283,21.32217],[-157.70703,21.26442],[-157.7786,21.27729],[-158.12667,21.31244],[-158.2538,21.53919],[-158.29265,21.57912],[-158.0252,21.71696],[-157.94161,21.65272],[-157.65283,21.32217]]],[[[-159.34512,21.982],[-159.46372,21.88299],[-159.80051,22.06533],[-159.74877,22.1382],[-159.5962,22.23618],[-159.36569,22.21494],[-159.34512,21.982]]],[[[-94.81758,49.38905],[-94.64,48.84],[-94.32914,48.67074],[-93.63087,48.60926],[-92.61,48.45],[-91.64,48.14],[-90.83,48.27],[-89.6,48.01],[-89.27292,48.01981],[-88.37811,48.30292],[-87.43979,47.94],[-86.46199,47.55334],[-85.65236,47.22022],[-84.87608,46.90008],[-84.77924,46.6371],[-84.54375,46.53868],[-84.6049,46.4396],[-84.3367,46.40877],[-84.14212,46.51223],[-84.09185,46.27542],[-83.89077,46.11693],[-83.61613,46.11693],[-83.46955,45.99469],[-83.59285,45.81689],[-82.55092,45.34752],[-82.33776,44.44],[-82.13764,43.57109],[-82.43,42.98],[-82.9,42.43],[-83.12,42.08],[-83.142,41.97568],[-83.02981,41.8328],[-82.69009,41.67511],[-82.43928,41.67511],[-81.27775,42.20903],[-80.24745,42.3662],[-78.93936,42.86361],[-78.92,42.965],[-79.01,43.27],[-79.17167,43.46634],[-78.72028,43.62509],[-77.73789,43.62906],[-76.82003,43.62878],[-76.5,44.01846],[-76.375,44.09631],[-75.31821,44.81645],[-74.867,45.00048],[-73.34783,45.00738],[-71.50506,45.0082],[-71.405,45.255],[-71.08482,45.30524],[-70.66,45.46],[-70.305,45.915],[-69.99997,46.69307],[-69.23722,47.44778],[-68.905,47.185],[-68.23444,47.35486],[-67.79046,47.06636],[-67.79134,45.70281],[-67.13741,45.13753],[-66.96466,44.8097],[-68.03252,44.3252],[-69.06,43.98],[-70.11617,43.68405],[-70.64548,43.09024],[-70.81489,42.8653],[-70.825,42.335],[-70.495,41.805],[-70.08,41.78],[-70.185,42.145],[-69.88497,41.92283],[-69.96503,41.63717],[-70.64,41.475],[-71.12039,41.49445],[-71.86,41.32],[-72.295,41.27],[-72.87643,41.22065],[-73.71,40.9311],[-72.24126,41.11948],[-71.945,40.93],[-73.345,40.63],[-73.982,40.628],[-73.95232,40.75075],[-74.25671,40.47351],[-73.96244,40.42763],[-74.17838,39.70926],[-74.90604,38.93954],[-74.98041,39.1964],[-75.20002,39.24845],[-75.52805,39.4985],[-75.32,38.96],[-75.07183,38.78203],[-75.05673,38.40412],[-75.37747,38.01551],[-75.94023,37.21689],[-76.03127,37.2566],[-75.72205,37.93705],[-76.23287,38.31921],[-76.35,39.15],[-76.54272,38.71762],[-76.32933,38.08326],[-76.99,38.23999],[-76.30162,37.91794],[-76.25874,36.9664],[-75.9718,36.89726],[-75.86804,36.55125],[-75.72749,35.55074],[-76.36318,34.80854],[-77.39763,34.51201],[-78.05496,33.92547],[-78.55435,33.86133],[-79.06067,33.49395],[-79.20357,33.15839],[-80.30132,32.50935],[-80.86498,32.0333],[-81.33629,31.44049],[-81.49042,30.72999],[-81.31371,30.03552],[-80.98,29.18],[-80.53558,28.47213],[-80.53,28.04],[-80.05654,26.88],[-80.08801,26.20576],[-80.13156,25.81677],[-80.38103,25.20616],[-80.68,25.08],[-81.17213,25.20126],[-81.33,25.64],[-81.71,25.87],[-82.24,26.73],[-82.70515,27.49504],[-82.85526,27.88624],[-82.65,28.55],[-82.93,29.1],[-83.70959,29.93656],[-84.1,30.09],[-85.10882,29.63615],[-85.28784,29.68612],[-85.7731,30.15261],[-86.4,30.4],[-87.53036,30.27433],[-88.41782,30.3849],[-89.18049,30.31598],[-89.59383,30.15999],[-89.41373,29.89419],[-89.43,29.48864],[-89.21767,29.29108],[-89.40823,29.15961],[-89.77928,29.30714],[-90.15463,29.11743],[-90.88022,29.14854],[-91.62678,29.677],[-92.49906,29.5523],[-93.22637,29.78375],[-93.84842,29.71363],[-94.69,29.48],[-95.60026,28.73863],[-96.59404,28.30748],[-97.14,27.83],[-97.37,27.38],[-97.38,26.69],[-97.33,26.21],[-97.14,25.87],[-97.53,25.84],[-98.24,26.06],[-99.02,26.37],[-99.3,26.84],[-99.52,27.54],[-100.11,28.11],[-100.45584,28.69612],[-100.9576,29.38071],[-101.6624,29.7793],[-102.48,29.76],[-103.11,28.97],[-103.94,29.27],[-104.45697,29.57196],[-104.70575,30.12173],[-105.03737,30.64402],[-105.63159,31.08383],[-106.1429,31.39995],[-106.50759,31.75452],[-108.24,31.75485],[-108.24194,31.34222],[-109.035,31.34194],[-111.02361,31.33472],[-113.30498,32.03914],[-114.815,32.52528],[-114.72139,32.72083],[-115.99135,32.61239],[-117.12776,32.53534],[-117.29594,33.04622],[-117.944,33.62124],[-118.4106,33.74091],[-118.51989,34.02778],[-119.081,34.078],[-119.43884,34.34848],[-120.36778,34.44711],[-120.62286,34.60855],[-120.74433,35.15686],[-121.71457,36.16153],[-122.54747,37.55176],[-122.51201,37.78339],[-122.95319,38.11371],[-123.7272,38.95166],[-123.86517,39.76699],[-124.39807,40.3132],[-124.17886,41.14202],[-124.2137,41.99964],[-124.53284,42.76599],[-124.14214,43.70838],[-124.02053,44.6159],[-123.89893,45.52341],[-124.07963,46.86475],[-124.39567,47.72017],[-124.68721,48.18443],[-124.5661,48.37971],[-123.12,48.04],[-122.58736,47.096],[-122.34,47.36],[-122.5,48.18],[-122.84,49],[-120,49],[-117.03121,49],[-116.04818,49],[-113,49],[-110.05,49],[-107.05,49],[-104.04826,48.99986],[-100.65,49],[-97.22872,49.0007],[-95.15907,49],[-95.15609,49.38425],[-94.81758,49.38905]]],[[[-153.00631,57.11584],[-154.00509,56.73468],[-154.5164,56.99275],[-154.67099,57.4612],[-153.76278,57.81657],[-153.22873,57.96897],[-152.56479,57.90143],[-152.14115,57.59106],[-153.00631,57.11584]]],[[[-165.57916,59.90999],[-166.19277,59.75444],[-166.84834,59.94141],[-167.45528,60.21307],[-166.46779,60.38417],[-165.67443,60.29361],[-165.57916,59.90999]]],[[[-171.73166,63.78252],[-171.11443,63.59219],[-170.49111,63.69498],[-169.68251,63.43112],[-168.68944,63.29751],[-168.77194,63.1886],[-169.52944,62.97693],[-170.29056,63.19444],[-170.67139,63.37582],[-171.55306,63.31779],[-171.79111,63.40585],[-171.73166,63.78252]]],[[[-155.06779,71.14778],[-154.34417,70.69641],[-153.90001,70.88999],[-152.21001,70.82999],[-152.27,70.60001],[-150.73999,70.43002],[-149.72,70.53001],[-147.61336,70.21403],[-145.68999,70.12001],[-144.92001,69.98999],[-143.58945,70.15251],[-142.07251,69.85194],[-140.98599,69.712],[-140.9925,66.00003],[-140.99777,60.3064],[-140.013,60.27684],[-139.039,60.00001],[-138.34089,59.56211],[-137.4525,58.905],[-136.47972,59.46389],[-135.47583,59.78778],[-134.945,59.27056],[-134.27111,58.86111],[-133.35555,58.41029],[-132.73042,57.69289],[-131.70781,56.55212],[-130.00778,55.91583],[-129.97999,55.285],[-130.53611,54.80275],[-131.08582,55.17891],[-131.96721,55.49778],[-132.25001,56.37],[-133.53918,57.17889],[-134.07806,58.12307],[-135.03821,58.18771],[-136.62806,58.21221],[-137.80001,58.5],[-139.86779,59.53776],[-140.82527,59.72752],[-142.57444,60.08445],[-143.95888,59.99918],[-145.92556,60.45861],[-147.11437,60.88466],[-148.22431,60.67299],[-148.01807,59.97833],[-148.57082,59.91417],[-149.72786,59.70566],[-150.60824,59.36821],[-151.71639,59.15582],[-151.85943,59.74498],[-151.40972,60.7258],[-150.34694,61.03359],[-150.62111,61.28442],[-151.89584,60.7272],[-152.57833,60.06166],[-154.01917,59.35028],[-153.28751,58.86473],[-154.23249,58.14637],[-155.30749,57.72779],[-156.30833,57.42277],[-156.5561,56.97998],[-158.11722,56.46361],[-158.43332,55.99415],[-159.60333,55.56669],[-160.28972,55.64358],[-161.22305,55.36473],[-162.23777,55.02419],[-163.06945,54.68974],[-164.78557,54.40417],[-164.94223,54.57222],[-163.84834,55.03943],[-162.87,55.34804],[-161.80417,55.89499],[-160.5636,56.00805],[-160.07056,56.41806],[-158.68444,57.01668],[-158.4611,57.21692],[-157.72277,57.57],[-157.55027,58.32833],[-157.04167,58.91888],[-158.19473,58.6158],[-158.51722,58.78778],[-159.05861,58.42419],[-159.71167,58.93139],[-159.98129,58.57255],[-160.35527,59.07112],[-161.355,58.67084],[-161.96889,58.67166],[-162.05499,59.26693],[-161.87417,59.63362],[-162.51806,59.98972],[-163.81834,59.79806],[-164.66222,60.26748],[-165.34639,60.5075],[-165.35083,61.0739],[-166.12138,61.50002],[-165.73445,62.075],[-164.91918,62.63308],[-164.56251,63.14638],[-163.75333,63.21945],[-163.06722,63.05946],[-162.26056,63.54194],[-161.53445,63.45582],[-160.77251,63.76611],[-160.95834,64.2228],[-161.51807,64.40279],[-160.77778,64.7886],[-161.39193,64.77724],[-162.45305,64.55944],[-162.75779,64.33861],[-163.54639,64.55916],[-164.96083,64.44695],[-166.42529,64.68667],[-166.845,65.0889],[-168.11056,65.67],[-166.70527,66.08832],[-164.47471,66.57666],[-163.65251,66.57666],[-163.7886,66.07721],[-161.67777,66.11612],[-162.48971,66.73557],[-163.71972,67.11639],[-164.43099,67.61634],[-165.39029,68.04277],[-166.76444,68.35888],[-166.20471,68.88303],[-164.43081,68.91554],[-163.16861,69.37111],[-162.93057,69.85806],[-161.9089,70.33333],[-160.9348,70.44769],[-159.03918,70.89164],[-158.11972,70.82472],[-156.58082,71.35776],[-155.06779,71.14778]]]]},\"properties\":{\"name\":\"United States\"}}]}","volume":"204","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Healey, Sean P.","contributorId":330527,"corporation":false,"usgs":false,"family":"Healey","given":"Sean","email":"","middleInitial":"P.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":885211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Warren B.","contributorId":330528,"corporation":false,"usgs":false,"family":"Cohen","given":"Warren B.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":885212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Zhiqiang","contributorId":330529,"corporation":false,"usgs":false,"family":"Yang","given":"Zhiqiang","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":885213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brewer, C. Kenneth","contributorId":330530,"corporation":false,"usgs":false,"family":"Brewer","given":"C.","email":"","middleInitial":"Kenneth","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":885214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooks, Evan B.","contributorId":330531,"corporation":false,"usgs":false,"family":"Brooks","given":"Evan","email":"","middleInitial":"B.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":885215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gorelick, Noel","contributorId":294417,"corporation":false,"usgs":false,"family":"Gorelick","given":"Noel","affiliations":[{"id":12484,"text":"Google","active":true,"usgs":false}],"preferred":false,"id":885216,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hernandez, Alexander J.","contributorId":330532,"corporation":false,"usgs":false,"family":"Hernandez","given":"Alexander","email":"","middleInitial":"J.","affiliations":[{"id":78925,"text":"Utah State University, Logan, USA","active":true,"usgs":false}],"preferred":false,"id":885217,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huang, Chengquan 0000-0003-0055-9798","orcid":"https://orcid.org/0000-0003-0055-9798","contributorId":198972,"corporation":false,"usgs":false,"family":"Huang","given":"Chengquan","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":885218,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hughes, M. Joseph","contributorId":330534,"corporation":false,"usgs":false,"family":"Hughes","given":"M.","email":"","middleInitial":"Joseph","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":885219,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kennedy, Robert E.","contributorId":196025,"corporation":false,"usgs":false,"family":"Kennedy","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":885220,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885221,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moisen, Gretchen G.","contributorId":15781,"corporation":false,"usgs":false,"family":"Moisen","given":"Gretchen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":885222,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schroeder, Todd A. taschroeder@fs.fed.us","contributorId":190802,"corporation":false,"usgs":false,"family":"Schroeder","given":"Todd","email":"taschroeder@fs.fed.us","middleInitial":"A.","affiliations":[],"preferred":false,"id":885223,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stehman, Stephen V. 0000-0001-5234-2027","orcid":"https://orcid.org/0000-0001-5234-2027","contributorId":216812,"corporation":false,"usgs":false,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[{"id":39524,"text":"College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":885224,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885225,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Woodcock, Curtis E.","contributorId":294423,"corporation":false,"usgs":false,"family":"Woodcock","given":"Curtis","email":"","middleInitial":"E.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":885226,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Yang, Limin 0000-0002-2843-6944","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":313589,"corporation":false,"usgs":false,"family":"Yang","given":"Limin","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":885227,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zhu, Zhe","contributorId":260473,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":885228,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70199960,"text":"70199960 - 2018 - High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA","interactions":[],"lastModifiedDate":"2018-10-05T14:44:36","indexId":"70199960","displayToPublicDate":"2018-01-01T14:44:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA","docAbstract":"Technological improvements in remote sensing and geographic information systems have demonstrated the abundance of artificially constructed water bodies across the landscape. Although research has shown the ubiquity of small ponds globally, and in the southeastern United States in particular, their cumulative impact in terms of evaporative alteration is less well quantified. The objectives of this study are to examine the hydrologic and evaporative importance of small artificial water bodies in the Upper Oconee watershed in the northern Georgia Piedmont, USA, by mapping their locations and modelling these small reservoirs using the Soil Water Assessment Tool. Comparative Soil Water Assessment Tool models were run with and without the inclusion of small reservoir surface area and volume. The models used meteorological inputs from 1990–2013 to represent years with drought, high precipitation, and moderate precipitation for both the calibration and evaluation periods. Statistical comparison of streamflow indicated that the calibration methodology produced results where the default model simulation without reservoirs fit observed flows more closely than the modified model with small reservoirs included (e.g., Nash–Sutcliffe efficiency of 0.72 vs. 0.64, r2 of 0.73 vs. 0.66, and percent bias of 11.4 vs. 21.6). In addition, Penman–Monteith, Hargreaves, and Priestley–Taylor evapotranspiration equations were used to estimate actual evaporation from 2,219 small water bodies identified throughout the 1,936.8 km2 watershed. Depending on the evaporation equation used, water bodies evaporated an average of 0.03–0.036 km3/year for the period 2003–2013. Using Penman–Monteith further, if the reservoirs were not considered and average actual evapotranspiration rates from the rest of the basin were applied, only 0.016 km3 of water would have left the basin as a result of evapotranspiration. This finding suggests construction of small reservoirs increased evaporation by an average of 0.017 km3 per year (approximately 46,500 m3/day). As the construction of small reservoirs continues and high resolution image data used to map these water bodies becomes increasingly available, watershed models that evolve to address the cumulative impacts of small water bodies on evaporation and other hydrologic processes will have greater potential to benefit the water resource management community.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11398","usgsCitation":"Ignatius, A., and Jones, J., 2018, High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA: Hydrological Processes, v. 32, no. 1, p. 51-65, https://doi.org/10.1002/hyp.11398.","productDescription":"15 p.","startPage":"51","endPage":"65","ipdsId":"IP-073606","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11398","text":"Publisher Index Page"},{"id":358190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Upper Oconee watershed","volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-18","publicationStatus":"PW","scienceBaseUri":"5bc0304de4b0fc368eb539ec","contributors":{"authors":[{"text":"Ignatius, Amber R. 0000-0002-2636-836X","orcid":"https://orcid.org/0000-0002-2636-836X","contributorId":193407,"corporation":false,"usgs":false,"family":"Ignatius","given":"Amber R.","affiliations":[],"preferred":false,"id":747475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, John 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":747474,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199946,"text":"70199946 - 2018 - Advancements in hydrochemistry mapping: methods and application to groundwater arsenic and iron concentrations in Varanasi, Uttar Pradesh, India","interactions":[],"lastModifiedDate":"2018-10-05T14:30:40","indexId":"70199946","displayToPublicDate":"2018-01-01T14:30:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3478,"text":"Stochastic Environmental Research and Risk Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Advancements in hydrochemistry mapping: methods and application to groundwater arsenic and iron concentrations in Varanasi, Uttar Pradesh, India","docAbstract":"The area east of Varanasi is one of numerous places along the watershed of the Ganges River with groundwater concentrations of arsenic surpassing the maximum value of 10 parts per billion (ppb) recommended by the World Health Organization in drinking water. Here we apply geostatistics and compositional data analysis for the mapping of arsenic and iron to help in understanding the conditions leading to the occurrence of elevated level of arsenic in groundwater. The methodology allows for displaying concentrations of arsenic and iron as maps consistent with the limited information from 95 water wells across an area of approximately 210 km2; visualization of the uncertainty associated with the sampling; and summary of the findings in the form of probability maps. For thousands of years, Varanasi has been on the erosional side in a meander of the river that is free of arsenic values above 10 ppb. Maps reveal two anomalies of high arsenic concentrations on the depositional side of the valley, which has started seeing urban development. The methodology using geostatistics combined with compositional data analysis is completely general, so this study could be used as a prototype for hydrochemistry mapping in other areas.
","language":"English","publisher":"Springer","doi":"10.1007/s00477-017-1390-3","usgsCitation":"Olea, R., Raju, N.J., Egozcue, J.J., Pawlowsky-Glahn, V., and Singh, S., 2018, Advancements in hydrochemistry mapping: methods and application to groundwater arsenic and iron concentrations in Varanasi, Uttar Pradesh, India: Stochastic Environmental Research and Risk Assessment, v. 32, no. 1, p. 241-259, https://doi.org/10.1007/s00477-017-1390-3.","productDescription":"19 p.","startPage":"241","endPage":"259","ipdsId":"IP-102331","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469109,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10256/14599","text":"External Repository"},{"id":358185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","state":"Uttar Pradesh","city":"Varanasi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 82.94094085693358,\n 25.22171429348812\n ],\n [\n 83.16032409667969,\n 25.22171429348812\n ],\n [\n 83.16032409667969,\n 25.353644304321104\n ],\n [\n 82.94094085693358,\n 25.353644304321104\n ],\n [\n 82.94094085693358,\n 25.22171429348812\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-13","publicationStatus":"PW","scienceBaseUri":"5bc0304de4b0fc368eb539ee","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":47873,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":747416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raju, N. Janardhana","contributorId":208504,"corporation":false,"usgs":false,"family":"Raju","given":"N.","email":"","middleInitial":"Janardhana","affiliations":[],"preferred":false,"id":747476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Egozcue, Juan J.","contributorId":208010,"corporation":false,"usgs":false,"family":"Egozcue","given":"Juan","email":"","middleInitial":"J.","affiliations":[{"id":37677,"text":"Dept. Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":747477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pawlowsky-Glahn, Vera","contributorId":208011,"corporation":false,"usgs":false,"family":"Pawlowsky-Glahn","given":"Vera","email":"","affiliations":[{"id":37678,"text":"Dept. Informatics, Applied Matematics and Statistics, Universitat de Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":747478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singh, Shubhra","contributorId":208505,"corporation":false,"usgs":false,"family":"Singh","given":"Shubhra","email":"","affiliations":[],"preferred":false,"id":747479,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199759,"text":"70199759 - 2018 - Characterizing aquatic habitats for long‐term monitoring of a fourth‐order, regulated river in the Pacific Northwest, USA","interactions":[],"lastModifiedDate":"2018-09-27T13:53:21","indexId":"70199759","displayToPublicDate":"2018-01-01T13:53:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing aquatic habitats for long‐term monitoring of a fourth‐order, regulated river in the Pacific Northwest, USA","docAbstract":"A pragmatic approach to the long‐term monitoring of rivers leverages available information with targeted field investigations to address key uncertainties relevant to management decisions. An over‐arching management issue for many rivers is how reservoir operation affects the amount and location of in‐channel sediment and the resulting distribution of aquatic habitats. We integrate remotely acquired and field‐survey morphologic data for the Cedar River, Washington, to constitute the current status of aquatic habitats and benchmarks for long‐term monitoring that will inform streamflow management. Four key habitats (river edge, side channels, riffles, and pools) are feasible to monitor with high‐resolution aerial imagery, a longitudinal profile of the river, and a side channel inventory, but full characterization of the functional differences within these habitats requires additional information. Habitat use information such as redd surveys will continue to be important for long‐term monitoring where it cannot be inferred reliably from physical habitat characteristics.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3230","usgsCitation":"Konrad, C.P., Burton, K., Little, R., Gendaszek, A.S., Munn, M.D., and Anderson, S.W., 2018, Characterizing aquatic habitats for long‐term monitoring of a fourth‐order, regulated river in the Pacific Northwest, USA: River Research and Applications, v. 34, no. 1, p. 24-33, https://doi.org/10.1002/rra.3230.","productDescription":"10 p.","startPage":"24","endPage":"33","ipdsId":"IP-084622","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":469110,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3230","text":"Publisher Index Page"},{"id":357837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124,\n 46\n ],\n [\n -120,\n 46\n ],\n [\n -120,\n 49\n ],\n [\n -124,\n 49\n ],\n [\n -124,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-30","publicationStatus":"PW","scienceBaseUri":"5bc0304de4b0fc368eb539f0","contributors":{"authors":[{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burton, K.","contributorId":208244,"corporation":false,"usgs":false,"family":"Burton","given":"K.","email":"","affiliations":[],"preferred":false,"id":746516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Little, R.","contributorId":208245,"corporation":false,"usgs":false,"family":"Little","given":"R.","email":"","affiliations":[],"preferred":false,"id":746517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munn, Mark D. 0000-0002-7154-7252 mdmunn@usgs.gov","orcid":"https://orcid.org/0000-0002-7154-7252","contributorId":976,"corporation":false,"usgs":true,"family":"Munn","given":"Mark","email":"mdmunn@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746519,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":107001,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":746520,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202569,"text":"70202569 - 2018 - Correlation of the Eagle Ford Group, Woodbine Group, and equivalent Cenomanian-Turonian Mudstones using regional wireline-log cross sections across the Texas Gulf Coast, U.S.A.","interactions":[],"lastModifiedDate":"2019-03-12T10:48:40","indexId":"70202569","displayToPublicDate":"2018-01-01T10:48:32","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1871,"text":"Gulf Coast Association of Geological Societies Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Correlation of the Eagle Ford Group, Woodbine Group, and equivalent Cenomanian-Turonian Mudstones using regional wireline-log cross sections across the Texas Gulf Coast, U.S.A.","docAbstract":"As part of the U.S. Geological Survey’s 2018 hydrocarbon assessment of the Eagle Ford Group and associated Cenomanian-Turonian strata, a series of regional wireline-log cross sections were constructed to examine geologic characteristics of this stratigraphic interval across the Texas Gulf Coast from Mexico to Louisiana. The cross sections were used to help define six continuous assessment units based, in part, on stratigraphic thickness, lateral extent, and lithology. The locations of the strike and dip cross sections were selected to address questions pertinent to the hydrocarbon assessment.
Stratigraphic correlation of the Eagle Ford Group and corresponding Cenomanian-Turonian mudstones has been debated for many years, and differences in interpretations remain. Formation tops published in the literature, from IHS MarkitTM, as well as information from a commercial biostratigraphic database were used to define consistent criteria to construct these cross sections from interpreted wireline logs. Specific units of interest include the Austin Chalk, upper and lower Eagle Ford Group, mudstones of the Woodbine Group, and the Buda Limestone.
Wireline gamma-ray (GR) logs through the Eagle Ford Group have values greater than 100 American Petroleum Institute (API) units in several areas of this study, including the Maverick Basin, the Karnes Trough, and the Brazos Basin. High GR values in mudstones may be interpreted to represent potential organic-rich intervals. These high GR zones provide a criterion to identify the lateral variability in potential Cenomanian-Turonian source rock intervals from South Texas to the Texas-Louisiana border.
","language":"English","publisher":"AAPG Datapages","usgsCitation":"Gianoutsos, N.J., Whidden, K.J., Dubiel, R.F., and Rouse, W.A., 2018, Correlation of the Eagle Ford Group, Woodbine Group, and equivalent Cenomanian-Turonian Mudstones using regional wireline-log cross sections across the Texas Gulf Coast, U.S.A.: Gulf Coast Association of Geological Societies Transactions, v. 68, p. 219-228.","productDescription":"10 p.","startPage":"219","endPage":"228","ipdsId":"IP-098051","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":361943,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/gcags/data/068/068001/219_gcags680219.htm"},{"id":362004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":759141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":759142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dubiel, Russell F. 0000-0002-1280-0350 rdubiel@usgs.gov","orcid":"https://orcid.org/0000-0002-1280-0350","contributorId":1294,"corporation":false,"usgs":true,"family":"Dubiel","given":"Russell","email":"rdubiel@usgs.gov","middleInitial":"F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":759143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rouse, William A. 0000-0002-0790-370X wrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0790-370X","contributorId":4172,"corporation":false,"usgs":true,"family":"Rouse","given":"William","email":"wrouse@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":759144,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228715,"text":"70228715 - 2018 - Yellowstone grizzly bear investigations — Annual report of the Interagency Grizzly Bear Study Team 2017","interactions":[],"lastModifiedDate":"2022-09-13T15:26:39.880503","indexId":"70228715","displayToPublicDate":"2018-01-01T09:47:20","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":3,"text":"Annual Report","active":false,"publicationSubtype":{"id":1}},"title":"Yellowstone grizzly bear investigations — Annual report of the Interagency Grizzly Bear Study Team 2017","docAbstract":"This Annual Report summarizes results of grizzly bear (Ursus arctos) monitoring and research conducted in the Greater Yellowstone Ecosystem (GYE) by the Interagency Grizzly Bear Study Team (IGBST) during 2017. This report also contains a summary of grizzly bear management actions to address conflict situations. Annual reports of the IGBST summarize annual data collection. Because additional information may be obtained after publication, data summaries are subject to change. Data, analyses, and summaries presented in this report supersede previously published data and analyses and interpretations may be subject to change contingent on future manuscript publication and the peer review process. The research described in this report complied with current laws of the United States of America, was conducted in accordance with animal care and use guidelines, and was approved by Institutional Animal Care and Use Committees of the respective member agencies.
","language":"English","publisher":"Interagency Grizzly Bear Study Team","usgsCitation":"2018, Yellowstone grizzly bear investigations — Annual report of the Interagency Grizzly Bear Study Team 2017: Annual Report, 140 p.","productDescription":"140 p.","ipdsId":"IP-130272","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":406596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406595,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.sciencebase.gov/catalog/file/get/6266a697d34e76103cce5808?f=__disk__e0%2F09%2Fec%2Fe009ec2027f6b3e73d7fee24a3c94be9e87f4fc0","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.68701171875,\n 42.85985981506279\n ],\n [\n -109.27001953125,\n 42.85985981506279\n ],\n [\n -109.27001953125,\n 45.583289756006316\n ],\n [\n -111.68701171875,\n 45.583289756006316\n ],\n [\n -111.68701171875,\n 42.85985981506279\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":835183,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":835184,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Karabensh, Bryn 0000-0002-2052-5256","orcid":"https://orcid.org/0000-0002-2052-5256","contributorId":219113,"corporation":false,"usgs":true,"family":"Karabensh","given":"Bryn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":835185,"contributorType":{"id":2,"text":"Editors"},"rank":3}]}} ,{"id":70198749,"text":"70198749 - 2018 - Quantifying uncertainty and tradeoffs in resilience assessments","interactions":[],"lastModifiedDate":"2018-08-24T12:20:22","indexId":"70198749","displayToPublicDate":"2018-01-01T09:32:03","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying uncertainty and tradeoffs in resilience assessments","docAbstract":"Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management), end users (farmers, ranchers, landowners, industry), agency/public science (research, university, extension), and NGOs (environmental, citizen, social justice) in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems), and subjectivity in perceptions of resilience among key actors and decision makers and provides an efficient way to develop the mental models that inform our stakeholders and stakeholder categories.
","language":"English","publisher":"Ecology and Society","doi":"10.5751/ES-09920-230103","usgsCitation":"Allen, C.R., Birge, H.E., Angeler, D.G., Arnold, C.A., Chaffin, B.C., DeCaro, D.A., Garmestani, A.S., and Gunderson, L., 2018, Quantifying uncertainty and tradeoffs in resilience assessments: Ecology and Society, v. 1, no. 3, Article 3; 23 p., https://doi.org/10.5751/ES-09920-230103.","productDescription":"Article 3; 23 p.","ipdsId":"IP-089079","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-09920-230103","text":"Publisher Index Page"},{"id":356614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a317e4b0702d0e84302a","contributors":{"authors":[{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":742844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birge, Hannah E.","contributorId":166737,"corporation":false,"usgs":false,"family":"Birge","given":"Hannah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":743039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angeler, David G.","contributorId":205240,"corporation":false,"usgs":false,"family":"Angeler","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":37065,"text":"Swedish University of Agricultural Sciences, Uppsala, Sweden","active":true,"usgs":false}],"preferred":false,"id":743040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arnold, Craig Anthony","contributorId":189230,"corporation":false,"usgs":false,"family":"Arnold","given":"Craig","email":"","middleInitial":"Anthony","affiliations":[],"preferred":false,"id":743041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaffin, Brian C.","contributorId":189131,"corporation":false,"usgs":false,"family":"Chaffin","given":"Brian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":743042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeCaro, Daniel A.","contributorId":198374,"corporation":false,"usgs":false,"family":"DeCaro","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":743043,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":743044,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gunderson, Lance","contributorId":30797,"corporation":false,"usgs":true,"family":"Gunderson","given":"Lance","affiliations":[],"preferred":false,"id":743045,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}