The U.S. Geological Survey (USGS) completed hydrologic and hydraulic analyses for selected reaches of the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan, in cooperation with the city of Lansing. The study comprised a 3.1-mile reach of the Grand River, a 30.3-mile reach of the Red Cedar River, and a 12.0-mile reach of Sycamore Creek. The information produced from the study can be used to update and expand an existing Federal Emergency Management Agency Flood Insurance Study for Ingham County, Mich.
Historical streamflow data from USGS streamgages on Grand River at Lansing, Mich. (station number 04113000); Red Cedar River at East Lansing, Mich. (station number 04112500); Red Cedar River near Williamston, Mich. (station number 04111379); and Sycamore Creek at Holt Road near Holt, Mich. (station number 04112850) were used to estimate instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities (AEPs) and a “1-percent plus” AEP.
The Hydrologic Engineering Center’s River Analysis System step-backwater model was used to determine water-surface elevation profiles for the 10-, 4-, 2-, 1-, and 0.2-percent AEP floods, the 1-percent plus AEP flood, and a regulatory floodway for each stream reach. The hydraulic models were calibrated based on stage-streamflow ratings at USGS streamgages. Flood-inundation boundaries for the 1- and 0.2-percent annual exceedance probability floods and regulatory floodway were created for each stream.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205144","collaboration":"Prepared in cooperation with the city of Lansing, Michigan","usgsCitation":"Whitehead, M.T., and Ostheimer, C.J., 2021, Hydrologic and hydraulic analyses of the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan: U.S. Geological Survey Scientific Investigations Report 2020–5144, \n17 p., https://doi.org/10.3133/sir2020–5144.","productDescription":"Report: iv, 17 p.; Data Realease","onlineOnly":"Y","ipdsId":"IP-118378","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":382823,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5144/coverthb.jpg"},{"id":382824,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5144/sir20205144.pdf","text":"Report","size":"3.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5144"},{"id":382825,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91CQ755","text":"USGS data release","linkHelpText":"Geospatial datasets and hydraulic models for the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan"}],"country":"United States","state":"Michigan","otherGeospatial":"Grand River, Red Cedar River, Sycamore Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.57550048828125,\n 42.48526384858916\n ],\n [\n -83.9959716796875,\n 42.48526384858916\n ],\n [\n -83.9959716796875,\n 42.76465818533266\n ],\n [\n -84.57550048828125,\n 42.76465818533266\n ],\n [\n -84.57550048828125,\n 42.48526384858916\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Science Center
U.S. Geological Survey
6460 Busch Blvd., Suite 100
Columbus, OH 43229
The Yellowstone Volcano Observatory (YVO) monitors volcanic and hydrothermal activity associated with the Yellowstone magmatic system, conducts research into magmatic processes occurring beneath Yellowstone Caldera, and issues timely warnings and guidance related to potential future geologic hazards. This report summarizes the activities and findings of YVO during the year 2018, focusing on the Yellowstone magmatic system. The most noteworthy seismic activity of the year was a February swarm of hundreds of earthquakes in the same area as the 2017 Maple Creek earthquake swarm. The February 2018 activity is viewed as a continuation of the 2017 swarm. Ground deformation trends were mostly unchanged throughout the year, with uplift of the Norris Geyser Basin area and subsidence of the caldera.
Field work in 2018, conducted under research permits granted by the National Park Service, included routine maintenance visits to seismic and geodetic stations as well as deployment of a semipermanent Global Positioning System network during the summer months; installation of an eddy covariance system for tracking carbon dioxide emissions and heat flux near Norris Geyser Basin; deployment of nodal seismic arrays on Geyser Hill, near Steamboat Geyser, and around Yellowstone Lake; and collection of water and gas samples from the Bechler River area in the southwest part of Yellowstone National Park. In addition, examination of satellite thermal imagery resulted in the discovery of a new thermal area on the east side of the Sour Creek resurgent dome, near west Tern Lake. This thermal area appears to have started forming in the early 2000s; before then it was an area of healthy forest. The year might best be remembered, however, for some extraordinary geyser and hot spring activity, specifically at Steamboat Geyser and Ear Spring.
Yellowstone Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court, Suite 100
Vancouver, WA 98683
Email: yvowebteam@usgs.gov
","tableOfContents":"Endocrine-disrupting compounds (EDCs), specifically estrogenic endocrine-disrupting compounds, vary in concentration and composition in surface waters under the influence of different landscape sources and landcover gradients. Estrogenic activity in surface waters may lead to adverse effects in aquatic species at both individual and population levels, often observed through the presence of intersex and vitellogenin induction in male fish. In the Chesapeake Bay Watershed, located on the mid-Atlantic coast of the USA, intersex has been observed in several sub-watersheds where previous studies have identified specific landscape sources of EDCs in tandem with observed fish health effects. Previous work in the Potomac River Watershed (PRW), the largest basin within the Chesapeake Bay Watershed, was leveraged to build random forest regression models to predict estrogenic activity at unsampled reaches in both the Potomac River and larger Chesapeake Bay Watersheds (CBW). Model outputs including important variables, partial dependence plots, and predicted values of estrogenic activity at unsampled reaches provide insight into drivers of estrogenic activity at different seasons and scales. Using the US Environmental Protection Agency effects-based threshold of 1.0 ng/L 17 β-estradiol equivalents, catchments predicted to exceed this value were categorized as at risk for adverse effects from exposure to estrogenic compounds and evaluated relative to healthy watersheds and recreation access locations throughout the PRW. Results show immediate catchment scale models are more reliable than upstream models, and the best predictive variables differ by season and scale. A small percentage of healthy watersheds (< 13%) and public access sites were classified as at risk using the “Total” (annual) model in the CBW. This study is the first Potomac River Watershed assessment of estrogenic activity, providing a new foundation for future risk assessment and management design efforts, with additional context provided for the entire Chesapeake Bay Watershed.
Decades of acidic deposition have adversely affected aquatic and terrestrial ecosystems in acid-sensitive watersheds in parts of the eastern United States. The national Acid Rain Program (Title IV of the 1990 Clean Air Act Amendments - CAAA) helped reduce emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) and resulted in sharp decreases in the acidity of atmospheric deposition. The decrease in acidic deposition produced a steady decline in the acidity of streams in many poorly buffered waters across the western Adirondacks and parts of the Catskill Mountains of New York. Until recently, however, there has been little evidence of biological recovery in most acid-sensitive streams in both regions. Long-term deposition and stream-chemistry records and fish-community data from quantitative surveys done during 1991–93 and again during 2012–19 at 13 sites in the upper Neversink River and its tributaries were evaluated to determine if chemical and biological recovery were evident in this Catskill Mountain watershed and if they could be linked to regional declines in acidic deposition. Between 1991 and 2019, large decreases in sulfate and nitrate deposition in the basin mirrored declines in total nationwide SO2 and NOx emissions. There were corresponding decreases in sulfate and nitrate concentrations in deposition at a National Trends Network station at Frost Valley (NY68) and coincident declines in sulfate concentrations at four long-term monitoring sites in the Neversink River watershed. Mean acid neutralizing capacity and pH increased and inorganic aluminum (Ali) concentrations from routine summertime samples decreased significantly at most moderately to severely acidified sites between the two study periods. Richness, density, and biomass of fish communities increased at most sites, while the density and biomass of brook trout Salvelinus fontinalis populations increased at fewer sites that were undergoing chemical recovery. Although recovery is far from complete, trends in deposition chemistry, water quality, and fish assemblages in streams of the upper Neversink watershed indicate that the 1990 CAAA is having positive impacts on aquatic ecosystems in the Catskill Mountain region, New York.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2021.118235","usgsCitation":"Baldigo, B.P., George, S.D., Winterhalter, D., and McHale, M., 2021, Biological and chemical recovery of acidified Catskill Mountain streams in response to the Clean Air Act Amendments of 1990: Atmospheric Environment, v. 249, 118235, 18 p., https://doi.org/10.1016/j.atmosenv.2021.118235.","productDescription":"118235, 18 p.","ipdsId":"IP-121887","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":453636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2021.118235","text":"Publisher Index Page"},{"id":383377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Neversink watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.63973999023438,\n 41.81175536180908\n ],\n [\n -74.53399658203125,\n 41.873139978873574\n ],\n [\n -74.4275665283203,\n 41.937019660425264\n ],\n [\n -74.33967590332031,\n 41.963064211132306\n ],\n [\n -74.28680419921875,\n 42.039094188385945\n ],\n [\n -74.34104919433594,\n 42.10382653879911\n ],\n [\n -74.40696716308594,\n 42.11859868281563\n ],\n [\n -74.45571899414062,\n 42.08395512413707\n ],\n [\n -74.62806701660156,\n 41.95080927751363\n ],\n [\n -74.70291137695312,\n 41.86700416724044\n ],\n [\n -74.67750549316406,\n 41.81021999190292\n ],\n [\n -74.63973999023438,\n 41.81175536180908\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"249","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winterhalter, Dylan R. 0000-0003-1774-8034","orcid":"https://orcid.org/0000-0003-1774-8034","contributorId":251765,"corporation":false,"usgs":true,"family":"Winterhalter","given":"Dylan R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249479,"text":"70249479 - 2021 - Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","interactions":[],"lastModifiedDate":"2023-10-10T14:16:37.55892","indexId":"70249479","displayToPublicDate":"2021-01-30T09:10:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","docAbstract":"Cleveland and Tana are remote volcanoes located in the central Aleutian volcanic arc on the eastern end of the Islands of Four Mountains (IFM). The persistently active Mount Cleveland volcano, on the western side of Chuginadak Island, is surrounded by several closely spaced Quaternary volcanic centers including Carlisle, Herbert, Kagamil, Tana, and Uliaga, and numerous small satellite vents on Chiginadak between Cleveland and Tana. The Alaska Volcano Observatory (AVO) installed two permanent broadband seismometers on Chuginadak Island in 2014, and we operated a temporary broadband network focused on the western side of the island in 2015–2016. Collectively, these stations provided the first seismic observations of this frequently active volcano and the surrounding Holocene-aged volcanic vents. During the study period (July 2014–January 2019), eruptive activity at Cleveland was characterized by small explosions separated by periods of lava effusion that formed small domes in the volcano's summit crater. We characterize seismicity beneath Chuginadak Island through automated analysis of event waveform frequency content, development of a one-dimensional P-wave velocity model, calculation of earthquake hypocenters, magnitudes, focal mechanisms, and identification of earthquake families. This analysis reveals the full range of seismic event types expected in a highly active volcanic environment and includes Volcano-Tectonic (VT) earthquakes, Long-Period (LP) events, and explosion signals. LP events appear to cluster at shallow depth beneath the active crater of Mount Cleveland and almost all of the explosions occur without identifiable short-term (hours to days) seismic precursors. VT earthquakes beneath Mount Cleveland occur at depths of 2 to 8 km below sea level (BSL) and range in magnitude from −0.2 to 1.8. VT focal mechanisms have horizontal P-axes that align with the regional axis of maximum stress. These observations, and a relatively slow one-dimensional seismic velocity model, are consistent with a shallow body of magma that is fed through a deeper conduit system. The time-history of VT earthquakes and shallow LP events suggest their occurrence may track the transfer of magma and fluids from the mid-crust to the shallow portions of the conduit system and may provide a means to anticipate future explosions and periods of dome growth. VT hypocenters also extend ~7 km northeast of Cleveland's summit at depths of 5 to 10 km BSL, under a group of Holocene-aged vents between Mount Cleveland and Tana. These earthquakes have vertically-oriented P-axes and a greater percentage occur in families. These observations, combined with observations of vent orientation and morphology and gas flux, suggest the area between Cleveland and Tana represents a zone of complicated volcano-tectonic interaction, similar to calderas elsewhere in the Aleutian arc. The presence of a larger volcanic system in the eastern IFM could influence magmatism and account for the multiple closely spaced volcanic centers in this region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107182","usgsCitation":"Power, J., Roman, D., Lyons, J.J., Haney, M.M., Rasmussen, D.J., Plank, T., Nicolaysen, K., Izbekov, P., Werner, C., and Kaufman, A., 2021, Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting: Journal of Volcanology and Geothermal Research, v. 412, 107182, 18 p., https://doi.org/10.1016/j.jvolgeores.2021.107182.","productDescription":"107182, 18 p.","ipdsId":"IP-121823","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107182","text":"Publisher Index Page"},{"id":421816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chuginadak Island, Cleveland Volcano, Tana Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.65098413866693,\n 52.904805932105404\n ],\n [\n -169.83106863712771,\n 52.8971644246661\n ],\n [\n -170.01036155537554,\n 52.86086066337441\n ],\n [\n -170.01669419707966,\n 52.78767701983992\n ],\n [\n -169.66364942207514,\n 52.76373370379605\n ],\n [\n -169.65098413866693,\n 52.904805932105404\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roman, Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":885874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":885875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":885876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rasmussen, Daniel J.","contributorId":237828,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Plank, Terry","contributorId":237829,"corporation":false,"usgs":false,"family":"Plank","given":"Terry","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicolaysen, K. P.","contributorId":330792,"corporation":false,"usgs":false,"family":"Nicolaysen","given":"K. P.","affiliations":[{"id":79020,"text":"Whitman College Geology Department","active":true,"usgs":false}],"preferred":false,"id":885879,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Izbekov, Pavel","contributorId":237833,"corporation":false,"usgs":false,"family":"Izbekov","given":"Pavel","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":885880,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Werner, C.","contributorId":330793,"corporation":false,"usgs":false,"family":"Werner","given":"C.","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":885881,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kaufman, A","contributorId":330794,"corporation":false,"usgs":false,"family":"Kaufman","given":"A","email":"","affiliations":[{"id":79021,"text":"Alaska Volcano Observatory, UAFGI, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":885882,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70217730,"text":"sir20205132 - 2021 - Characterization of groundwater quality and discharge with emphasis on selenium in an irrigated agricultural drainage near Delta, Colorado, 2017–19","interactions":[],"lastModifiedDate":"2021-08-18T22:10:40.433467","indexId":"sir20205132","displayToPublicDate":"2021-01-29T13:45:00","publicationYear":"2021","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":"2020-5132","displayTitle":"Characterization of Groundwater Quality and Discharge with Emphasis on Selenium in an Irrigated Agricultural Drainage near Delta, Colorado, 2017–19","title":"Characterization of groundwater quality and discharge with emphasis on selenium in an irrigated agricultural drainage near Delta, Colorado, 2017–19","docAbstract":"Selenium is a water-quality constituent of concern for aquatic ecosystems in the lower Gunnison River Basin. Selenium is derived from bedrock of the Mancos Shale and is mobilized and transported to groundwater and surface water by application of irrigation water. Although it is recognized that groundwater contributes an appreciable amount of selenium to surface water, few studies have addressed interactions between the two. The U.S. Geological Survey in cooperation with the Colorado Water Conservation Board conducted a study during 2017–19 to characterize the quality and quantity of groundwater discharging to an agricultural drainage near Delta, Colorado, locally known as Sunflower Drain.
Water quality in the study area is characterized by high dissolved solids with elevated concentrations of selenium and nitrate resulting from dissolution of soluble salts in the Mancos Shale. Selenium concentrations have decreased by 50 percent since the early 2000s, possibly in response to irrigation system improvements. Stable water isotopes indicate streamflow is dominated by canal water during the irrigation season (April to October) and, during the nonirrigation season (November to March), is dominated by groundwater that has undergone some degree of evaporation. Pesticide and pharmaceutical compounds were infrequently detected, and results indicate they were derived from sources outside the study area such that they do not appear to be useful as tracers of groundwater sources. Stable isotopes of nitrate indicate that nitrate originates from the Mancos Shale, and the isotopic composition is enriched by denitrification in the groundwater system. Using a mass-balance approach, estimated groundwater discharge rates to Sunflower Drain ranged from 0.15 to 0.27 cubic feet per second per mile with one losing reach identified. Selenium, sulfate, and nitrate concentrations in groundwater estimated by mass-balance calculations were similar to concentrations measured in the Poly 17 observation well, located in a largely irrigated area in east tributary. One tributary reach had higher concentrations of selenium, sulfate, and nitrate likely reflecting localized inputs of more concentrated groundwater, similar to the concentrations in the Poly 7 observation well, which is downgradient from a residential area in the west tributary.
Three pilot studies were conducted, including fiber optic distributed temperature sensing to detect groundwater discharge zones in the stream channel, a passive seismic technique to estimate depth to bedrock, and use of radon-222 as a geochemical tracer of groundwater discharge. All three techniques show promise as additional approaches for investigating groundwater discharge surface-water systems in irrigated drainage areas on Mancos Shale.
The factors that affect groundwater movement mainly include when and where irrigation water is transported and applied, and the distribution of bedrock of the Mancos Shale and overlying alluvial deposits. The average groundwater recharge rate for the study area was estimated at 8.1 inches per year, based on mass balance calculations from synoptic survey data. Along the western tributary of Sunflower Drain, there was evidence that spills from the East Canal may recharge the groundwater aquifer adjacent to the stream channel. Groundwater movement to the stream channel may be controlled by the topography of the alluvial/bedrock interface or focused along human-made features, such as tile drains and ditches constructed around irrigated fields. On larger scales, the top of bedrock was also important, creating a topographic constriction that caused a zone of groundwater discharge. The groundwater system is complex, and further study could better define the system, possibly through application of a groundwater flow model and more extensive studies using some of the exploratory methods evaluated in this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205132","collaboration":"Prepared in cooperation with Colorado Water Conservation Board","usgsCitation":"Mast, M.A., 2021, Characterization of groundwater quality and discharge with emphasis on selenium in an irrigated agricultural drainage near Delta, Colorado, 2017–19: U.S. Geological Survey Scientific Investigations Report 2020–5132, 34 p., https://doi.org/10.3133/sir20205132.","productDescription":"Report: vi, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119514","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":382809,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LKYX9H","text":"USGS data release","linkHelpText":"Near-surface geophysical data collected in the Sunflower Drain study area near Delta, Colorado, March 2018"},{"id":382805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5132/coverthb.jpg"},{"id":382806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5132/sir20205132.pdf","text":"Report","size":"5.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5132"}],"country":"United States","state":"Colorado","city":"Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.21945190429688,\n 38.638327308061875\n ],\n [\n -107.97019958496094,\n 38.638327308061875\n ],\n [\n -107.97019958496094,\n 38.82205601494022\n ],\n [\n -108.21945190429688,\n 38.82205601494022\n ],\n [\n -108.21945190429688,\n 38.638327308061875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
The 2018 US Geological Survey National Seismic Hazard Model (NSHM) incorporates new data and updated science to improve the underlying earthquake and ground motion forecasts for the conterminous United States. The NSHM considers many new data and component input models: (1) new earthquakes between 2013 and 2017 and updated earthquake magnitudes for some earlier earthquakes; (2) two updated smoothed seismicity models to forecast earthquake rates; (3) two suites of new central and eastern US (CEUS) ground motion models (GMMs) to translate ground shaking for various earthquake sizes and source-to-site distances considered in the model; (4) two CEUS GMMs for aleatory variability; (5) two CEUS site-effect models that modify ground shaking based on alternative shallow site conditions; (6) more advanced western US (WUS) lithologic and structural information to assess basin site effects for selected urban regions; and (7) a more comprehensive range of outputs (22 periods and 8 site classes) than in previous versions of the NSHMs. Each of these new datasets and models produces changes in the probabilistic ground shaking levels that are spatially and statistically analyzed. Recent earthquakes or changes to some older earthquake magnitudes and locations mostly result in probabilistic ground shaking levels that are similar to previous models, but local changes can reach up to +80% and −60% compared to the 2014 model. Newly developed CEUS models for GMMs, aleatory variability, and site effects cause overall changes up to ±64%. The addition of the WUS basin amplifications causes changes of up to +60% at longer periods for sites overlying deep soft soils. Across the conterminous United States, the hazard changes in the model are mainly caused by new GMMs in the CEUS, by sedimentary basin effects for long periods (≥1 s) in the WUS, and by seismicity changes for short (0.2 s) and long (1 s) periods for both areas.
","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/8755293020988016","usgsCitation":"Petersen, M.D., Shumway, A., Powers, P.M., Mueller, C.S., Moschetti, M.P., Frankel, A.D., Rezaeian, S., McNamara, D., Luco, N., Boyd, O.S., Rukstales, K.S., Jaiswal, K.S., Thompson, E.M., Hoover, S., Clayton, B., Field, E.H., and Zeng, Y., 2021, The 2018 update of the US National Seismic Hazard Model: Where, why, and how much probabilistic ground motion maps changed: Earthquake Spectra, v. 37, no. 2, p. 959-987, https://doi.org/10.1177/8755293020988016.","productDescription":"29 p.","startPage":"959","endPage":"987","ipdsId":"IP-123826","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436531,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PCEE26","text":"USGS data release","linkHelpText":"Data Release for the 2018 Update of the U.S. National Seismic Hazard Model: Where, Why, and How Much Probabilistic Ground Motion Maps Changed"},{"id":391082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"37","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shumway, Allison 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Charles S 0000-0002-1868-9710","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":268155,"corporation":false,"usgs":false,"family":"Mueller","given":"Charles","email":"","middleInitial":"S","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":825961,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825962,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":825963,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825964,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McNamara, Daniel 0000-0001-6860-0350","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":265165,"corporation":false,"usgs":false,"family":"McNamara","given":"Daniel","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":825965,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825966,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":825967,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825968,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825969,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825970,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hoover, Susan M. 0000-0002-8682-6668","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":268156,"corporation":false,"usgs":false,"family":"Hoover","given":"Susan M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":825971,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Clayton, Brandon 0000-0003-0502-7184 bclayton@usgs.gov","orcid":"https://orcid.org/0000-0003-0502-7184","contributorId":197196,"corporation":false,"usgs":true,"family":"Clayton","given":"Brandon","email":"bclayton@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825972,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825973,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825974,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70217716,"text":"70217716 - 2021 - Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density","interactions":[],"lastModifiedDate":"2021-01-29T13:41:03.444159","indexId":"70217716","displayToPublicDate":"2021-01-28T07:33:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density","docAbstract":"Lyme disease is common in the northeastern United States, but rare in the southeast, even though the tick vector is found in both regions. Infection prevalence of Lyme spirochetes in host-seeking ticks, an important component to the risk of Lyme disease, is also high in the northeast and northern midwest, but declines sharply in the south. As ticks must acquire Lyme spirochetes from infected vertebrate hosts, the role of wildlife species composition on Lyme disease risk has been a topic of lively academic discussion. We compared tick–vertebrate host interactions using standardized sampling methods among 8 sites scattered throughout the eastern US. Geographical trends in diversity of tick hosts are gradual and do not match the sharp decline in prevalence at southern sites, but tick–host associations show a clear shift from mammals in the north to reptiles in the south. Tick infection prevalence declines north to south largely because of high tick infestation of efficient spirochete reservoir hosts (rodents and shrews) in the north but not in the south. Minimal infestation of small mammals in the south results from strong selective attachment to lizards such as skinks (which are inefficient reservoirs for Lyme spirochetes) in the southern states. Selective host choice, along with latitudinal differences in tick host-seeking behavior and variations in tick densities, explains the geographic pattern of Lyme disease in the eastern US.
This report provides a groundwater-flow conceptualization that integrates geologic, hydrologic, hydraulic-property, and radionuclide data in the Pahute Mesa–Oasis Valley (PMOV) groundwater basin, southern Nevada. Groundwater flow in the PMOV basin is of interest because 82 underground nuclear tests were detonated, most near or below the water table. A potentiometric map and nine sets of hydrostratigraphic and hydrologic cross sections supplement the conceptualization.
Potentiometric contours indicate that groundwater in the PMOV basin generally flows south-southwest and discharges at Oasis Valley. Groundwater encounters an alternating sequence of low- and high-transmissivity rocks, referred to as dams and pools, respectively, as it moves from east to west across eastern Pahute Mesa. Flow from all Pahute Mesa nuclear tests is to Oasis Valley and is well-constrained by water-level data. Flow converges along a corridor of high transmissivity between Pahute Mesa and Oasis Valley.
The location of the lateral PMOV basin boundary is well defined, and this boundary, with a few minor exceptions, represents a no-flow boundary. Some boundary uncertainty exists in the northeastern part of the basin, but potential flow-rate estimates across the northeastern boundary resulting from this uncertainty are small relative to the basin groundwater budget.
Recharge in the PMOV basin is derived from episodic pulses of modern water and the diffuse percolation of old water (greater than 1,000 years). Episodic recharge is a minor recharge component observed as a rise in groundwater levels that occurs 3 months to 1 year following a wet winter. Minor amounts of episodic recharge through an unsaturated zone in excess of 1,000 feet (ft) requires preferential flow through faults and fractures. The dominant recharge component is slow, steady, diffuse percolation of old water through the unsaturated zone. A large component of old water recharging the groundwater system is consistent with observations of isotopically light deuterium and oxygen 18 compositions in water from wells on Pahute Mesa and central Oasis Valley. About half the recharge in the PMOV basin is derived from the eastern Pahute Mesa area. The remaining recharge is derived primarily from other highland areas including Timber Mountain, Belted and Kawich Ranges, and Black Mountain.
The PMOV groundwater system is nearly steady state, where recharge is balanced by the 5,900 acre-feet per year of natural discharge at Oasis Valley. This assumption is reasonable because the basin is dominated by steady-state conditions, where long-term changes in groundwater storage are minimal. Total groundwater withdrawals from 1963 to 2018 have amounted to less than 10 percent of annual groundwater discharge and less than 0.2 percent of the basin’s groundwater storage. Therefore, present-day (2020) conditions are considered representative of predevelopment (pre-1950) conditions in nearly all areas of the basin.
The lower PMOV basin boundary is defined at 4,000 ft below the water table to encompass all underground nuclear tests and tritium plumes. This boundary defines the lower boundary of radionuclide migration. However, nearly all flow and tritium transport occur in the upper 1,600 ft of the saturated zone because a transmissivity-with-depth relation indicates that greater than 90 percent of the transmissivity contributing to groundwater flow occurs within 1,600 ft of the water table. Rocks at deeper depths have low transmissivity because argillic and mineralized alterations plug the fractures.
Volcanic rocks form the primary aquifers and confining units in the PMOV basin. Volcanic hydrogeologic units (HGUs) and hydrostratigraphic units (HSUs) have transmissivity distributions that span up to eight orders of magnitude with considerable overlap between distributions. Despite the large overlap between units, mean transmissivities of aquifers are one-to-two orders of magnitude greater than the confining units. However, all volcanic-rock HGUs and HSUs are composite units, meaning that they can function spatially as either an aquifer or confining unit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205134","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office, Office of Environmental Management under Interagency Agreement, DE-EM0004969","usgsCitation":"Jackson, T.R., Fenelon, J.M., and Paylor, R.L., 2021, Groundwater flow conceptualization of the Pahute Mesa–Oasis Valley Groundwater Basin, Nevada—A synthesis of geologic, hydrologic, hydraulic-property, and tritium data: U.S. Geological Survey Scientific Investigations Report 2020–5134, 100 p., https://doi.org/10.3133/sir20205134.","productDescription":"Report: viii, 100 p.; 2 Plates: 26.00 x 42.00 inches and 120.01 x 36.00 inches; 7 Appendixes","onlineOnly":"Y","ipdsId":"IP-095406","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":382683,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix2.xlsx","text":"Appendix 2","size":"78 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 2"},{"id":382684,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix3.xlsm","text":"Appendix 3","size":"530 KB xlsm","description":"SIR 2020-5134 Appendix 3"},{"id":382685,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix4.xlsx","text":"Appendix 4","size":"6.1 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 4"},{"id":382681,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_plate02.pdf","text":"Plate 2","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5134 Plate 2"},{"id":382678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5134/coverthb.jpg"},{"id":382679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134.pdf","text":"Report","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5134"},{"id":382680,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_plate01.pdf","text":"Plate 1","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5134 Plate 1"},{"id":382682,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix1.xlsx","text":"Appendix 1","size":"2.5 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 1"},{"id":382688,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix7.xlsx","text":"Appendix 7","size":"433 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 7"},{"id":382687,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix6.xlsx","text":"Appendix 6","size":"856 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 6"},{"id":382686,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix5.xlsx","text":"Appendix 5","size":"799 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 5"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahute Mesa–Oasis Valley Groundwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.00,\n 36.65079252503471\n ],\n [\n -116.00,\n 36.65079252503471\n ],\n [\n -116.00,\n 38.00\n ],\n [\n -117.00,\n 38.00\n ],\n [\n -117.00,\n 36.65079252503471\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
Society and the environment in the arid southwestern United States depend on reliable water availability, yet current water use outpaces supply. Water demand is projected to grow in the future and climate change is expected to reduce supply. To adapt, water managers need robust estimates of future regional water supply to support management decisions. To address this need, we estimate future streamflow in seven water resource regions in the southwestern U.S. using a new SPAtially Referenced Regressions On Watershed attributes (SPARROW) streamflow model. We present streamflow projections corresponding to input data from seven climate models and two greenhouse gas Representative Concentration Pathways (RCP4.5 and 8.5) for three, thirty-year intervals centered on the 2030s, 2050s, and 2080s, and for a historical thirty year interval centered on the 1990s. Across water resource regions, about half of the RCP4.5 models (51%) and two thirds of the RCP8.5 models (67%) indicate decreases in streamflow in the 2080s relative to the historical period. Models project maximum decreases in streamflow of 36–80% in all water resource regions for all periods and RCPs relative to historical streamflow, and maximum streamflow decreases of up to 20–45% in the 2080s at sites along the Colorado River used for measuring compliance with interstate and international water agreements. Headwaters are projected to experience the greatest declines, with substantial downstream implications. Among these estimates, the streamflows from models forced with RCP8.5 tend to be lower than those forced with RCP4.5. Not all climate models, times, and RCPs project widespread streamflow declines. The most ubiquitous streamflow increases are projected to occur in the 2030s under RCP4.5. Later time periods and enhanced greenhouse gas forcings indicate smaller regions of streamflow increase and lower accumulated streamflows, suggesting that limiting or reducing greenhouse gas concentrations could support future water availability. Although some possible streamflow increases are promising, the modest and spatially limited increases in streamflow projected for later time periods are still unlikely to be sufficient to meet the projected water demand. These results inform the likelihood of future water agreement compliance, and support developing strategies to balance water supply and demand.
The M 6.5 Monte Cristo Range earthquake that occurred in the central Walker Lane on 15 May 2020 was the largest earthquake in Nevada in 66 yr and resulted in a multidisciplinary scientific field response. The earthquake was the result of left‐lateral slip along largely unmapped parts of the Candelaria fault, one of a series of east–northeast‐striking faults that comprise the Mina deflection, a major right step in the north–northwest structural grain of the central Walker Lane. We describe the characteristics of the surface rupture and document distinct differences in the style and orientation of fractures produced along the 28 km long rupture zone. Along the western part of the rupture, left‐lateral and extensional displacements occurred along northeasterly and north‐striking planes that splay off the eastern termination of the mapped Candelaria fault. To the east, extensional and right‐lateral displacements occurred along predominantly north‐striking planes that project toward well‐defined Quaternary and bedrock faults. Although, the largest left‐lateral displacement observed was ∼20 cm, the majority of displacements were <5 cm and were distributed across broad zones up to 800 m wide, which are not likely to be preserved in the geologic record. The complex pattern of surface rupture is consistent with a network of faults defined in the shallow subsurface by aftershock seismicity and suggests that slip partitioning between east‐striking left‐lateral faults and north to northwest‐striking right‐lateral faults plays an important role in accommodating northwest‐directed transtension in the central Walker Lane.
New paleoseismic trenching indicates late Quaternary oblique right‐lateral slip on the Leech River fault, southern Vancouver Island, Canada, and constrains permanent forearc deformation in northern Cascadia. A south‐to‐north reduction in northward Global Navigation Satellite System velocities and seismicity across the Olympic Mountains, Strait of Juan de Fuca (JDF), and the southern Strait of Georgia, has been used as evidence for permanent north–south crustal shortening via thrust faulting between a northward migrating southern forearc and rigid northern backstop in southwestern Canada. However, previous paleoseismic studies indicating late Quaternary oblique right‐lateral slip on west‐northwest‐striking forearc faults north of the Olympic Mountains and in the southern Strait of Georgia are more consistent with forearc deformation models that invoke oroclinal bending and(or) westward extrusion of the Olympic Mountains. To help evaluate strain further north across the Strait of JDF, we present the results from two new paleoseismic trenches excavated across the Leech River fault. In the easternmost Good Hope trench, we document a vertical fault zone and a broad anticline deforming glacial till. Comparison of till clast orientations in faulted and undeformed glacial till shows evidence for postdeposition faulted till clast rotation, indicating strike‐slip shear. The orientation of opening mode fissuring during surface rupture is consistent with right‐lateral slip and the published regional
Hazards from induced earthquakes are a growing concern with a need for effective management. One aspect of that concern is the “nuisance” from unexpected ground motions, which have the potential to cause public alarm and discontent. In this article, we borrow earthquake engineering concepts to quantify the chance of building damage states and adapt them to quantify felt thresholds for induced earthquakes in the Central and Eastern United States. We compare binary data of felt or not-felt reports from the “Did You Feel It” database with ShakeMap ground motion intensity measures (IM) for ∼360 earthquakes. We use a Monte Carlo logistic regression to discern the likelihood of perceiving various degrees of felt intensity, given a particular IM. These best-fit nuisance functions are reported in this article and are readily transferable. Of the shaking types considered, we find that peak ground velocity tends to be the best predictor of a felt earthquake. We also find that felt thresholds tended to decrease with increasing earthquake magnitude, after M ∼3.9. We interpret this effect as related to the duration of the event, where events smaller than M 3.9 are perceived as “impulsive” to the human senses. Improved quantification of the nuisance from induced earthquake ground motions could be utilized in management of the public perception of their causal operations. Although aimed at anthropogenic earthquakes, thresholds we derive could be useful in other realms, such as establishing best practices and protocols for earthquake early warning.
Soil calcium depletion has been strongly linked to acidic deposition in eastern North America and recent studies have begun to document the recovery of soils in response to large decreases in acidic deposition. However, increased calcium availability has not yet been seen in the B horizon, where calcium depletion has been most acute, but mineral weathering is critically important for resupplying ecosystem calcium. This study provides new data in seven watersheds in the Adirondack region (New York, USA), where acidic deposition impacts on soils and surface waters have been substantial and recovery remains slow. Initial sampling in 1997–1998 and 2003–2004 was repeated in 2009–2010, 2014, 2016 and 2017. Exchangeable calcium concentrations increased by an average of 43% in the Oe horizon of three watersheds where this horizon was sampled (10.7–15.3 cmolc kg−1). Changes in calcium were not seen in the individual watersheds of the Oa and B horizons, but as a group, a significant increase in calcium was measured in the upper B horizon. Liming of a calcium-depleted watershed also tripled calcium concentration in the upper B horizon in 5 years. However, stream calcium in unlimed watersheds decreased over the study period. Small increases in B-horizon calcium may be underway
","language":"English","publisher":"MDPI","doi":"10.3390/soilsystems5010006","usgsCitation":"Lawrence, G.B., Siemion, J., Antidormi, M.R., Bonville, D.B., and McHale, M., 2021, Have sustained acidic deposition decreases led to increased calcium availability in recovering watersheds of the Adirondack region of New York, USA?: Soil Systems, v. 5, no. 1, 6, 23 p., https://doi.org/10.3390/soilsystems5010006.","productDescription":"6, 23 p.","ipdsId":"IP-123192","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":453740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/soilsystems5010006","text":"Publisher Index Page"},{"id":383149,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.69580078125001,\n 43.77109381775648\n ],\n [\n -75.06958007812501,\n 42.988576458321816\n ],\n [\n -73.32275390625,\n 43.11702412135048\n ],\n [\n -73.1689453125,\n 45.07352060670971\n ],\n [\n -74.89379882812501,\n 44.91035917458492\n ],\n [\n -75.69580078125001,\n 43.77109381775648\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siemion, Jason 0000-0001-5635-6469 jsiemion@usgs.gov","orcid":"https://orcid.org/0000-0001-5635-6469","contributorId":127562,"corporation":false,"usgs":true,"family":"Siemion","given":"Jason","email":"jsiemion@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Antidormi, Michael R. 0000-0002-3967-1173 mantidormi@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-1173","contributorId":150722,"corporation":false,"usgs":true,"family":"Antidormi","given":"Michael","email":"mantidormi@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810069,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonville, Donald B. 0000-0003-4480-9381","orcid":"https://orcid.org/0000-0003-4480-9381","contributorId":248849,"corporation":false,"usgs":true,"family":"Bonville","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810071,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217434,"text":"sir20205130 - 2021 - Water-quality trends of urban streams in Independence, Missouri, 2005–18","interactions":[],"lastModifiedDate":"2021-01-21T12:48:49.595303","indexId":"sir20205130","displayToPublicDate":"2021-01-20T17:15:00","publicationYear":"2021","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":"2020-5130","displayTitle":"Water-Quality Trends of Urban Streams in Independence, Missouri, 2005–18","title":"Water-quality trends of urban streams in Independence, Missouri, 2005–18","docAbstract":"The U.S. Geological Survey and the city of Independence, Missouri, Water Pollution Control Department has studied the water quality and ecological condition of urban streams within Independence since 2005. Selected physical properties, nutrients, chloride, fecal indicator bacteria (Escherichia coli and total coliform), total dissolved solids, and suspended-sediment concentration data for base-flow and stormflow samples were used to document temporal trends in concentrations and flow-weighted concentrations; and annual loads were computed and investigated for selected nutrients, chloride, and suspended sediment. The six study sites included in this report are located on five urban streams: Rock Creek, a tributary in the city that drains to the Missouri River; three tributaries of the Little Blue River within the city (East Fork Little Blue River, Adair Creek, and Spring Branch Creek); and two sites on the main stem of the Little Blue River (one upstream from the city and one downstream from the three tributaries).
Many factors such as population, land use, and climate, and combinations of these factors contributed to the significant changes in the concentrations and transport of nutrients, chloride, fecal indicator bacteria, and suspended sediment in the urban streams within Independence. The population of Independence and the amount of developed land in the urban watersheds remained unchanged during the 2005–18 study. Differences were noted in precipitation and in streamflow during the study. Annual precipitation and streamflow were separated into two time periods within the study—period 1 (2006–10), having greater annual streamflow and precipitation, and period 2 (2011–18), having about 30 percent lower annual streamflow and less precipitation. Streamflow was an important factor in the transport of nitrogen, phosphorus, chloride, and suspended sediment from the urban watersheds. Changes in data collection methodology during the study period and improvements to the city stormwater and wastewater infrastructure also could have contributed to some of the trends. Between 2009 and 2015, more than 35 million dollars of improvements were made to stormwater and wastewater infrastructure within the city. These improvements, such as additional sewage overflow holding tanks, removal of septic tanks, and improved and expanded sanitary sewer lines and storm overflows, also could have affected the decreased nutrients and fecal indicator bacteria trends among the urban streams in the study area.
Models were used for analyzing streamflow-related variability in constituent concentrations and loads to determine if the water quality changed significantly during the study period. Trends in concentration data at four sites were analyzed using a statistical package called R–QWTREND and trends in load data were analyzed at six sites using a statistical package called Weighted Regressions on Time, Discharge, and Season-Kalman filter (WRTDS–K); both developed by the U.S. Geological Survey and publicly available for use.
Statistically significant trends in flow-weighted nutrient concentrations and loads generally were downward during the study period. The only nutrient compound with a statistically significant upward trend in flow-weighted concentration was dissolved orthophosphate as phosphorus at the Rock Creek site and the upstream site on the Little Blue River. A statistically significant downward trend in annual dissolved ammonia load was identified at the downstream Little Blue River site. A significant upward linear trend in annual orthophosphate as phosphorus load was identified on Adair Creek.
A statistically significant upward trend in dissolved chloride concentrations was identified at the downstream Little Blue River site. Road salt application near the site during the winter could have resulted in higher concentrated runoff during wet weather conditions. Annual chloride loads significantly decreased in Adair Creek and Spring Branch Creek. The mean annual chloride load transported in the drier (2011–18) period 2 was significantly less than during the wetter (2006–10) period 1, indicating that trends in precipitation runoff are an important factor in trends in annual transport of chloride.
Statistically significant downward trends in flow-weighted fecal indicator bacteria Escherichia coli (E. coli) population densities were noted for Rock Creek and the down-stream site on the Little Blue River. However, no trend was identified in E. coli population density at the upstream Little Blue River site. The downward trend in E. coli population density at the downstream site could be a result of decreased streamflow and precipitation over the study period, storage of fecal indicator bacteria in the Little Blue River streambed within the study area, die-off of fecal indicator bacteria during travel from upstream to downstream, changes in the sample collection methodology, improvements to the city’s storm-water and wastewater infrastructures, or a combination of these factors.
The statistically significant downward trend in suspended-sediment concentration identified at the upstream Little Blue River site could be affected by the decreased streamflow and precipitation during the study period, by changes in sampling methods within the study period, and by the decrease in construction and urban land development upstream from the city.
No statistically significant change was indicated in the annual suspended-sediment load transported from Independence to the Little Blue River during the study period. More than one-half the suspended sediment transported in the Little Blue River originated in the watershed upstream from Independence.
The Little Blue River and many of its tributaries that drain Independence have been designated as recreational waters classified for whole-body contact class B and secondary contact recreation, and some have been listed as impaired for E. coli by the Missouri Department of Natural Resources from urban runoff and storm sewers. Observations were made among the available E. coli population density data for both Little Blue River sites to further understand water-quality conditions over the study period. Both Little Blue River sites had similar medians and geometric means for the recreational season (April through October) and during the full study period, both of which are greater than the regulatory population density for both recreational classes. The Little Blue River drainage area nearly doubles in size from the upstream to downstream site; therefore, the consistent geometric mean and median of E. coli population densities at the upstream and downstream Little Blue River sites could be primarily due to the larger volume of streamflow creating a dilution effect. Other possible factors could be storage of fecal indicator bacteria in stream bed sediments, die-off of fecal indicator bacteria during transport, improvements to the city’s wastewater and stormwater infrastructure, changes to sampling methodology, or a combination of these factors. Specific sources of the E. coli are currently (2019) unknown.
Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Treated wastewater with high levels of ammonia has been injected, since March 1983 into the deep saline units of the Lower Floridan aquifer (LFA) from a treatment plant near the east coast of Miami-Dade County in southeastern Florida. Monitoring wells in the plant recorded ammonia concentrations above ambient levels at hydrogeologic units located about 1000 ft (304.8 m) above injection depths between 2500 and 2800 ft (762 and 853 m) below sea level. A solute-transport model was developed to assess the horizontal and vertical extent of the injected ammonia, with ammonia moving from the injected zone into the overlying units: the upper semiconfining unit, the uppermost permeable zone of the LFA, and the middle semiconfining units of the Avon Park Formation. Ammonia is assumed to be transported under the effects of local heterogeneity in a porous limestone aquifer with high-salinity ambient groundwater and via upward migration through quasi-vertical pathways. A flow model of the migration of the injected ammonia was calibrated with PEST using head, salinity, and ammonia concentration data measured from 1983 to 2013. Borehole geophysical data support the high permeability of the uppermost permeable zone in the LFA. Average simulated head, normalized salinity, and ammonia concentration residuals over all monitoring wells were −1.37 ft, 0.01, and −0.67 mg/L, respectively. Model results are consistent with undetectable ammonia concentrations in the Upper Floridan aquifer.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13076","usgsCitation":"Sepulveda, N., and Lohmann, M., 2021, Migration of injected wastewater with high levels of ammonia in a saline aquifer in south Florida: Groundwater, v. 59, no. 4, p. 597-613, https://doi.org/10.1111/gwat.13076.","productDescription":"17 p.","startPage":"597","endPage":"613","ipdsId":"IP-107330","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":436559,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EWI8N0","text":"USGS data release","linkHelpText":"Data Sets for Simulation of Migration of Injected Wastewater with High Levels of Ammonia in a Saline Aquifer in South Florida, using SEAWAT v 4"},{"id":388589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.9088134765625,\n 25.175116531621764\n ],\n [\n -79.42291259765625,\n 25.175116531621764\n ],\n [\n -79.42291259765625,\n 26.04444515079636\n ],\n [\n -80.9088134765625,\n 26.04444515079636\n ],\n [\n -80.9088134765625,\n 25.175116531621764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":822044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lohmann, Melinda A. 0000-0003-1472-159X","orcid":"https://orcid.org/0000-0003-1472-159X","contributorId":216660,"corporation":false,"usgs":true,"family":"Lohmann","given":"Melinda A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":822045,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217188,"text":"ofr20201136 - 2021 - Development and application of surrogate models, calculated loads, and aquatic export of carbon based on specific conductance, Big Cypress National Preserve, south Florida, 2015–17","interactions":[],"lastModifiedDate":"2021-01-15T12:46:29.556276","indexId":"ofr20201136","displayToPublicDate":"2021-01-14T12:15:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1136","displayTitle":"Development and Application of Surrogate Models, Calculated Loads, and Aquatic Export of Carbon Based on Specific Conductance, Big Cypress National Preserve, South Florida, 2015–17","title":"Development and application of surrogate models, calculated loads, and aquatic export of carbon based on specific conductance, Big Cypress National Preserve, south Florida, 2015–17","docAbstract":"Understanding the carbon transport within aquatic environments is crucial to quantifying global and local carbon budgets, yet limited empirical data currently (2021) exist. This report documents methodology and provides data for quantifying the aquatic export of carbon from a cypress swamp within Big Cypress National Preserve and is part of a larger carbon budget study. The U.S. Geological Survey operated two continuous monitoring stations, 022889001 and 022909471, that measured flow volume and water quality within the Big Cypress National Preserve in South Florida from September 2015 to October 2017. Station 022889001 represented the flow into the study area and station 022909471 represented the flow out of the study area. Site-specific regression models were developed by using continuously measured specific conductance and concomitant, discretely collected dissolved organic carbon, dissolved inorganic carbon, and particulate carbon samples to calculate total carbon (TC) concentrations at 15-minute intervals.
Calculated TC concentrations typically increased as flow was decreasing and decreased as flow was increasing. TC loads were calculated by multiplying concentrations and flow volume, and the difference between the load calculations for input/output locations of the swamp flow system was used to determine the aquatic carbon export from the study area.
Calculated monthly TC loads ranged from 0 metric tons in spring 2017 at both stations to 3,145 and 7,821 metric tons in September 2017 at 022889001 and 022909471, respectively. During 2016, the annual loads were 10,479 and 15,243 metric tons at 022889001 and 022909471, respectively. Calculated monthly aquatic TC exports from the study area ranged from −0.7 gram of carbon per square meter in May 2016 to 44.1 grams of carbon per square meter during September 2017. The carbon export from the study area varied monthly, increased as flow increased, and was greatly influenced by Hurricane Irma in September 2017. The aquatic TC export from the Sweetwater Strand study area was 42.0 grams of carbon per square meter per year in 2016, which is substantially (about 15 times) larger than the estimated overall mean riverine carbon export per square meter for the eastern United States; however, it was also less than the monthly export of carbon in September 2017. The monthly aquatic carbon export from the study area in September 2017 alone was greater than the aquatic carbon export from all of 2016, which is largely the result of the substantial increase in flow attributed to Hurricane Irma.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201136","collaboration":"Greater Everglades Priority Ecosystem Science Program","usgsCitation":"Booth, A.C., 2021, Development and application of surrogate models, calculated loads, and aquatic export of carbon based on specific conductance, Big Cypress National Preserve, South Florida, 2015–17: U.S. Geological Survey Open-File Report 2020–1136, 14 p., https://doi.org/10.3133/ofr20201136.","productDescription":"Report: v, 14 p.; Data Release; 2 Appendixes","onlineOnly":"Y","ipdsId":"IP-112929","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":382104,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix2.rtf","text":"Appendix 2","size":"960 kB","description":"OFR 2020-1136 Appendix 2 rtf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022909471: Loop Road Culverts Monroe Station to Florida Trail, Florida (rtf file)"},{"id":382062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1136/coverthb.jpg"},{"id":382063,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1136/ofr20201136.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136"},{"id":382064,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EXZLJT","text":"USGS data release","linkHelpText":"Calculated carbon concentrations, loads, and export in Big Cypress National Preserve, South Florida, 2015-2017"},{"id":382101,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix1.pdf","text":"Appendix 1","size":"424 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136 Appendix 1 pdf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022889001: Tamiami Canal 11 Mile Road to Monroe Station, Florida"},{"id":382102,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix2.pdf","text":"Appendix 2","size":"356 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136 Appendix 2 pdf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022909471: Loop Road Culverts Monroe Station to Florida Trail, Florida"},{"id":382103,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix1.rtf","text":"Appendix 1","size":"2.91 MB","description":"OFR 2020-1136 Appendix 1 rtf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022889001: Tamiami Canal 11 Mile Road to Monroe Station, Florida (rtf file)"}],"country":"United States","state":"Florida","otherGeospatial":"Big Cypress National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.22604370117186,\n 25.812254545273433\n ],\n [\n -80.8978271484375,\n 25.812254545273433\n ],\n [\n -80.8978271484375,\n 26.058016587844723\n ],\n [\n -81.22604370117186,\n 26.058016587844723\n ],\n [\n -81.22604370117186,\n 25.812254545273433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Although Arctic ringed seals Phoca hispida hispida are currently abundant and broadly distributed, their numbers are projected to decline substantially by the year 2100 due to climate warming. While understanding population structure could provide insight into the impact of environmental changes on this subspecies, detecting demographically important levels of exchange can be difficult in taxa with high abundance. We used a next-generation sequencing approach (DArTseq) to genotype ~5700 single nucleotide polymorphisms in 79 seals from 4 Pacific Arctic regions. Comparison of the 2 most geographically separated strata (eastern Bering vs. northeastern Chukchi-Beaufort Seas) revealed a statistically significant level of genetic differentiation (FST = 0.001, p = 0.005) that, while small, was 1 to 2 orders of magnitude greater than expected based on divergence estimated for similarly sized populations connected by low (1% yr-1) dispersal. A relatively high proportion (72 to 88%) of individuals within these strata could be genetically assigned to their stratum of origin. These results indicate that demographically important structure may be present among Arctic ringed seals breeding in different areas, increasing the risk that declines in the number of seals breeding in areas most negatively affected by environmental warming could occur.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01087","usgsCitation":"Lang, A.R., Boveng, P.L., Quakenbush, L., Robertson, K., Lauf, M., Rode, K.D., Ziel, H., and Taylor, B., 2021, Re-examination of population structure in Arctic ringed seals using DArTseq genotyping: Endangered Species Research, v. 44, p. 11-31, https://doi.org/10.3354/esr01087.","productDescription":"21 p.","startPage":"11","endPage":"31","ipdsId":"IP-104727","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":453844,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01087","text":"Publisher Index Page"},{"id":382277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -172.0458984375,\n 62.57310578449978\n ],\n [\n -168.046875,\n 62.57310578449978\n ],\n [\n -168.046875,\n 64.1297836764257\n ],\n [\n -172.0458984375,\n 64.1297836764257\n ],\n [\n -172.0458984375,\n 62.57310578449978\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167.080078125,\n 60.994423108456154\n ],\n [\n -163.8720703125,\n 60.994423108456154\n ],\n [\n -163.8720703125,\n 62.57310578449978\n ],\n [\n -167.080078125,\n 62.57310578449978\n ],\n [\n -167.080078125,\n 60.994423108456154\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167.03613281249997,\n 66.63555577803261\n ],\n [\n -164.00390625,\n 66.63555577803261\n ],\n [\n -164.00390625,\n 67.35678538806071\n ],\n [\n -167.03613281249997,\n 67.35678538806071\n ],\n [\n -167.03613281249997,\n 66.63555577803261\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -169.365234375,\n 68.31814602144938\n ],\n [\n -166.9482421875,\n 68.31814602144938\n ],\n [\n -166.9482421875,\n 69.2249968541159\n ],\n [\n -169.365234375,\n 69.2249968541159\n ],\n [\n -169.365234375,\n 68.31814602144938\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.36816406249997,\n 70.17020068549206\n ],\n [\n -142.60253906249997,\n 70.17020068549206\n ],\n [\n -142.60253906249997,\n 71.62214274510511\n ],\n [\n -157.36816406249997,\n 71.62214274510511\n ],\n [\n -157.36816406249997,\n 70.17020068549206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lang, Aimee R.","contributorId":247810,"corporation":false,"usgs":false,"family":"Lang","given":"Aimee","email":"","middleInitial":"R.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boveng, Peter L.","contributorId":171523,"corporation":false,"usgs":false,"family":"Boveng","given":"Peter","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":808401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quakenbush, L.","contributorId":243091,"corporation":false,"usgs":false,"family":"Quakenbush","given":"L.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":808402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, K.","contributorId":247811,"corporation":false,"usgs":false,"family":"Robertson","given":"K.","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lauf, M.","contributorId":247812,"corporation":false,"usgs":false,"family":"Lauf","given":"M.","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":808405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ziel, H.","contributorId":247813,"corporation":false,"usgs":false,"family":"Ziel","given":"H.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Taylor, B .L.","contributorId":181914,"corporation":false,"usgs":false,"family":"Taylor","given":"B .L.","affiliations":[],"preferred":false,"id":808407,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217247,"text":"ofr20201135 - 2021 - An assessment of the economic potential of lignite and leonardite resources in the Williston Basin, North Dakota","interactions":[],"lastModifiedDate":"2021-01-15T12:52:49.599044","indexId":"ofr20201135","displayToPublicDate":"2021-01-13T16:30:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1135","displayTitle":"An Assessment of the Economic Potential of Lignite and Leonardite Resources in the Williston Basin, North Dakota","title":"An assessment of the economic potential of lignite and leonardite resources in the Williston Basin, North Dakota","docAbstract":"The Bureau of Land Management (BLM) requested assistance from the U.S. Geological Survey (USGS) to conduct an assessment study to identify areas that may have economic potential for the future extraction of lignite and leonardite resources in the Williston Basin in North Dakota. The study will be used by the BLM to assist with the preparation of a revised resource management plan for the Williston Basin, in accordance with BLM planning policies.
The assessment of the economic potential of lignite resources required the establishment of criteria defining an economic lignite deposit. In consultation with the BLM, criteria were established to delineate drill holes that contained economic lignite beds. The criteria established are a minimum lignite bed thickness, a minimum cumulative lignite thickness, a maximum cumulative stripping ratio, and a maximum overburden. Likewise, an assessment of the economic potential of leonardite deposits required the establishment of criteria delineating drill holes that contained economic leonardite deposits. The criteria established are a minimum leonardite bed thickness, a minimum cumulative leonardite thickness, and a maximum overburden.
The drill hole data utilized in this study were obtained from the National Coal Resources Data System database and from several coal companies. Data from more than 20,000 drill holes, both proprietary and nonproprietary, were used to compile areas of economic potential for lignite or leonardite.
Areas delineated as having lignite or leonardite resources with economic potential, based on the established criteria, were present in 24 counties in the western portion of North Dakota. Areas of economic potential were delineated using a visual best-fit method without croplines. Areas defined as having economic potential for certain lignite beds or leonardite deposits may extend beyond known croplines in this study.
Stratigraphically, the lignite and leonardite deposits in the Williston Basin in North Dakota are mostly found in the Paleocene Fort Union Formation. Thick (greater than 20 feet) and laterally extensive (greater than 5 square miles) lignite beds are present in the Fort Union Formation throughout the Sentinel Butte and Tongue River Members. Lignite beds are also present in the Ludlow Member of the Fort Union Formation, although they are not as numerous or thick as they are in the overlying Sentinel Butte and Tongue River Members. As a result of lateral facies changes and migrating fluvial channel complexes in the Fort Union Formation, lignite beds of varying thickness occupy different stratigraphic horizons vertically throughout the Williston Basin.
The calculation of volumes for lignite and leonardite resources was not part of the scope of this study requested by the BLM, but a future study by the USGS may involve a comprehensive assessment of lignite resources and reserves in the Williston Basin. This future study could combine geologic data compiled in this study with geologic data from a previously unpublished 2019 assessment study by the USGS in the Williston Basin in eastern Montana. This future USGS study could also include the calculation of volumes for lignite resources and reserves, based on economic models derived using analogs from active mining operations in the Williston Basin and available spot market or contract coal prices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201135","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Shaffer, B.N., 2021, An assessment of the economic potential of lignite and leonardite resources in the Williston Basin, North Dakota: U.S. Geological Survey Open-File Report 2020–1135, 14 p., https://doi.org/10.3133/ofr20201135.","productDescription":"vi, 14 p.","onlineOnly":"Y","ipdsId":"IP-120360","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":436582,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93GGU6P","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Mercer and Oliver Counties, North Dakota"},{"id":436581,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93GGU6P","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Mercer and Oliver Counties, North Dakota"},{"id":436580,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWIHEE","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in McLean County, North Dakota"},{"id":436579,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWIHEE","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in McLean County, North Dakota"},{"id":436578,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94V9WV8","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Billings County, North Dakota"},{"id":436577,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94V9WV8","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Billings County, North Dakota"},{"id":436576,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90636SP","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Golden Valley County, North Dakota"},{"id":436575,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90636SP","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Golden Valley County, North Dakota"},{"id":436574,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FHHH4T","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Dunn County, North Dakota"},{"id":382138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1135/coverthb.jpg"},{"id":382139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1135/ofr20201135.pdf","text":"Report","size":"6.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1135"}],"country":"United States","state":"North Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0625,\n 45.89000815866184\n ],\n [\n -99.931640625,\n 45.89000815866184\n ],\n [\n -99.931640625,\n 49.009050809382046\n ],\n [\n -104.0625,\n 49.009050809382046\n ],\n [\n -104.0625,\n 45.89000815866184\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The 2020 Magna, Utah, earthquake produced observable crustal deformation over a ∼ 100 km2 area around the southeast margin of Great Salt Lake, but it did not produce any surface rupture. To obtain a detailed picture of the fault slip, we combine strong motion seismic waveforms with GPS static offsets and Interferometric Synthetic Aperture Radar (InSAR) observations to obtain kinematic and static slip models of the event. We sample the regional seismic wavefield with 3-component records from 68 stations of the University of Utah Seismograph Stations network. We find that coseismic slip and afterslip, with predominantly normal slip, distributed on a shallowly west-dipping plane, possibly augmented by afterslip on a steeply northeast-dipping plane, best fits the joint dataset. The west-dipping plane locates near previously inferred sources of interseismic creep at depth. Hence the earthquake may have occurred on the downdip ex-tension of the Wasatch fault and activated further slip (afterslip) at shallow depth east of the hypocenter. This inferred afterslip may have driven the vigorous aftershock activity that was concentrated east of the hypocenter.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0220200312","usgsCitation":"Pollitz, F., Wicks, C., and Svarc, J.L., 2021, Coseismic fault slip and afterslip associated with the M5.7 March 18, 2020 Magna, Utah, earthquake: Seismological Research Letters, v. 92, no. 2A, p. 741-754, https://doi.org/10.1785/0220200312.","productDescription":"14 p.","startPage":"741","endPage":"754","ipdsId":"IP-122052","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Magna","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.10921941420736,\n 40.723327593996174\n ],\n [\n -112.10921941420736,\n 40.684935353345196\n ],\n [\n -112.05066964819599,\n 40.684935353345196\n ],\n [\n -112.05066964819599,\n 40.723327593996174\n ],\n [\n -112.10921941420736,\n 40.723327593996174\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"92","issue":"2A","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wicks, Charles 0000-0002-0809-1328","orcid":"https://orcid.org/0000-0002-0809-1328","contributorId":9023,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Svarc, Jerry L. 0000-0002-2802-4528","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":212736,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926886,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218764,"text":"70218764 - 2021 - Geochemistry of coastal permafrost and erosion-driven organic matter fluxes to the Beaufort Sea near Drew Point, Alaska","interactions":[],"lastModifiedDate":"2021-03-12T14:36:45.473522","indexId":"70218764","displayToPublicDate":"2021-01-08T08:31:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7753,"text":"Frontiers in Earth Science","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry of coastal permafrost and erosion-driven organic matter fluxes to the Beaufort Sea near Drew Point, Alaska","docAbstract":"Accelerating erosion of the Alaska Beaufort Sea coast is increasing inputs of organic matter from land to the Arctic Ocean, and improved estimates of organic matter stocks in eroding coastal permafrost are needed to assess their mobilization rates under contemporary conditions. We collected three permafrost cores (4.5–7.5 m long) along a geomorphic gradient near Drew Point, Alaska, where recent erosion rates average 17.2 m year−1. Down-core patterns indicate that organic-rich soils and lacustrine sediments (12–45% total organic carbon; TOC) in the active layer and upper permafrost accumulated during the Holocene. Deeper permafrost (below 3 m elevation) mainly consists of Late Pleistocene marine sediments with lower organic matter content (∼1% TOC), lower C:N ratios, and higher δ13C values. Radiocarbon-based estimates of organic carbon accumulation rates were 11.3 ± 3.6 g TOC m−2 year−1 during the Holocene and 0.5 ± 0.1 g TOC m−2 year−1 during the Late Pleistocene (12–38 kyr BP). Within relict marine sediments, porewater salinities increased with depth. Elevated salinity near sea level (∼20–37 in thawed samples) inhibited freezing despite year-round temperatures below 0°C. We used organic matter stock estimates from the cores in combination with remote sensing time-series data to estimate carbon fluxes for a 9 km stretch of coastline near Drew Point. Erosional fluxes of TOC averaged 1,369 kg C m−1 year−1 during the 21st century (2002–2018), nearly doubling the average flux of the previous half-century (1955–2002). Our estimate of the 21st century erosional TOC flux year−1 from this 9 km coastline (12,318 metric tons C year−1) is similar to the annual TOC flux from the Kuparuk River, which drains a 8,107 km2 area east of Drew Point and ranks as the third largest river on the North Slope of Alaska. Total nitrogen fluxes via coastal erosion at Drew Point were also quantified, and were similar to those from the Kuparuk River. This study emphasizes that coastal erosion represents a significant pathway for carbon and nitrogen trapped in permafrost to enter modern biogeochemical cycles, where it may fuel food webs and greenhouse gas emissions in the marine environment.
The U.S. Geological Survey (USGS), in cooperation with the Rosebud Sioux Tribe, completed a study to characterize water-level fluctuations in observation wells to examine driving factors that affect water levels in and near the Rosebud Indian Reservation, which comprises all of Todd County. The study investigates concerns regarding potential effects of groundwater withdrawals and climate conditions on groundwater levels within an area that includes Todd County and a surrounding area that extends 10 miles north, east, and west of the county border. Characterization of water-level fluctuations in observation wells and relative driving factors was accomplished by statistical trend analysis.
Two statistical methods were used for analysis of temporal trends for climatic and hydrologic data. To determine which trend analysis to use, applicable datasets were tested for statistically significant short-term persistence (STP). In the absence of significant STP, existence of statistical trends was determined using the standard Mann-Kendall test for probability values less than or equal to 0.10 (90-percent confidence level); however, a modified Mann-Kendall test was used for datasets where statistically significant STP was detected. Trend magnitudes were computed using the Sen’s slope estimator.
Monthly data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) were aggregated to obtain annual and seasonal datasets for total precipitation, minimum air temperature (Tmin), and maximum air temperature (Tmax) for the study area and a surrounding buffer area. Trend tests for total precipitation, Tmin, and Tmax were completed for annual and seasonal time series for water years 1956–2017, which is about 2 years before the earliest available water-level measurements. A 2-year offset was arbitrarily selected because scrutiny of water-level and precipitation data indicated that responses of groundwater levels for many of the observation wells lagged major changes in precipitation patterns by about 2 years. Statistically significant upward trends were detected for annual precipitation and annual Tmin for almost all of the study area and the surrounding buffer area. Statistically significant downward trends in Tmax were detected for a very small part of the study area; however, the sparse spatial coverage reduces confidence that these are true trends. Spatial distributions of statistically significant trends in seasonal climate data were generally similar to the annual trends, but with substantial differences in the spatial density of the trends.
Groundwater trends for 58 observation wells were analyzed for three separate water-level parameters (minimum, median, and maximum) because wells are measured sporadically and data are biased towards more frequent measurements during periods of heaviest irrigation demand. Trends in the time series of annual precipitation (from PRISM) starting 2 years earlier than for the associated water-level trend also were analyzed for the location of each individual observation well. Sen’s slope and Mann-Kendall probability values (p-values) were computed for the three water-level parameters and for the annual precipitation time series. Graphs showing results of trend analyses for each observation well also showed changes over time in the sum of licensed groundwater withdrawals within six specified radii (0.5, 1, 2, 3, 4, and 5 miles) of each well as a qualitative indicator of proximal groundwater demand.
Of all 58 observation wells considered, 28 wells had significant upward trends for at least one of the three water-level parameters, 11 wells had significant downward trends for at least one water-level parameter, and 19 wells did not have any significant trends. Significant upward trends in annual precipitation were detected for 48 of the 58 wells.
Results of trend analyses likely show the effects of groundwater withdrawals on water levels in the Ogallala aquifer in areas of substantial demand. Precipitation trends are significantly upward for 43 of the 48 wells completed in the Ogallala aquifer that were analyzed. Of the 48 Ogallala aquifer wells, 24 had significant upward trends for at least one water-level parameter (17 with all 3); however, 10 wells had statistically significant downward trends for at least one water-level parameter (8 with all 3 parameters). All but one of the wells with significant downward trends are located in the south-central part of the study area where licensed irrigation withdrawals are concentrated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205119","collaboration":"Prepared in cooperation with the Rosebud Sioux Tribe","usgsCitation":"Valseth, K.J., and Driscoll, D.G., 2021, Trends in groundwater levels in and near the Rosebud Indian Reservation, South Dakota, water years 1956–2017: U.S. Geological Survey Scientific Investigations Report 2020–5119, 46 p., https://doi.org/10.3133/sir20205119.","productDescription":"Report: v, 46 p.; 2 Appendixes; Data Release","onlineOnly":"Y","ipdsId":"IP-111377","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":382008,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release","linkHelpText":"National Water Information System"},{"id":381910,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5119/sir20205119_appendix2.pdf","text":"Appendix 2","size":"132 kB","description":"SIR 2020-5119 Appendix 2"},{"id":381909,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5119/sir20205119_appendix1.pdf","text":"Appendix 1","size":"404 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5119 Appendix 1"},{"id":381908,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5119/sir20205119.pdf","text":"Report","size":"4.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5119"},{"id":381907,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5119/coverthb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Rosebud Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.612548828125,\n 43.01268088642034\n ],\n [\n -99.8492431640625,\n 43.01268088642034\n ],\n [\n -99.8492431640625,\n 43.600284023536325\n ],\n [\n -101.612548828125,\n 43.600284023536325\n ],\n [\n -101.612548828125,\n 43.01268088642034\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
The first eruption at Kīlauea’s summit in 25 years began on March 19, 2008, and persisted for 10 years. The onset of the eruption marked the first explosive activity at the summit since 1924, forming the new “Overlook crater” (as the 2008 summit eruption crater has been informally named) within the existing crater of Halemaʻumaʻu. The first year consisted of sporadic lava activity deep within the Overlook crater. Occasional small explosions deposited spatter and small wall-rock lithic pieces around the Halemaʻumaʻu rim. After a month-long pause at the end of 2008, deep sporadic lava lake activity returned in 2009. Continuous lava lake activity began in February 2010. The lake rose significantly in late 2010 and early 2011, before subsequently draining briefly in March 2011. This disruption of the summit eruption was triggered by eruptive activity on the East Rift Zone. Rising lake levels through 2012 established a more stable, larger lake in 2013, with continued enlargement over the subsequent 5 years. Lava reached the Overlook crater rim and overflowed on the Halemaʻumaʻu floor in brief episodes in 2015, 2016, and 2018, but the lake level was more commonly 20–60 meters below the rim during 2014–18. The lake was approximately 280×200 meters (~42,000 square meters) by early 2018 and formed one of the two largest lava lakes on Earth.
A new eruption began in the lower East Rift Zone on May 3, 2018, causing magma to drain from the summit reservoir complex. The lava in Halemaʻumaʻu had drained below the crater floor by May 10, followed by collapse of the Overlook and Halemaʻumaʻu craters. The collapse region expanded as much of the broader summit caldera floor subsided incrementally during June and July. By early August 2018, the collapse sequence had ended, and the summit was quiet. The historical changes in May–August 2018 brought a dramatic end to the decade of sustained activity at Kīlauea’s summit.
The unique accessibility of the 2008–18 lava lake provided new observations of lava lake behavior and open-vent basaltic outgassing. Data indicated that explosions were triggered by rockfalls from the crater walls, that the lake consisted of a low-density foamy lava, that cycles of gas pistoning were rooted at shallow depths in the lake, and that lake level fluctuations were closely tied to the pressure of the summit magma reservoir. Lava chemistry added further support for an efficient hydraulic connection between the summit and East Rift Zone. Notwithstanding the benefits to scientific understanding, the eruption presented a persistent hazard of volcanic air pollution (vog) that commonly extended far from Kīlauea’s summit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1867A","usgsCitation":"Patrick, M., Orr, T., Swanson, D., Houghton, B., Wooten, K., Desmither, L., Parcheta, C., and Fee, D., 2021, Kīlauea’s 2008–2018 summit lava lake—Chronology and eruption insights, chap. A of Patrick, M., Orr, T., Swanson, D., and Houghton, B., eds., The 2008–2018 summit lava lake at Kīlauea Volcano, Hawai‘i: U.S. Geological Survey Professional Paper 1867, 50 p., https://doi.org/10.3133/pp1867A.","productDescription":"viii, 50 p.","numberOfPages":"50","onlineOnly":"N","ipdsId":"IP-109081","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":436595,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ULRPMM","text":"USGS data release","linkHelpText":"Elevation of the lava lake in Halemaʻumaʻu crater, Kīlauea Volcano, from 2009 to 2018"},{"id":436594,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ULRPMM","text":"USGS data release","linkHelpText":"Elevation of the lava lake in Halemaʻumaʻu crater, Kīlauea Volcano, from 2009 to 2018"},{"id":381957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1867/a/covrthb.jpg"},{"id":381958,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1867/a/pp1867a.pdf","text":"Report","size":"32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1867 Chapter A"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.32539367675778,\n 19.378522756179393\n ],\n [\n -155.21072387695312,\n 19.378522756179393\n ],\n [\n -155.21072387695312,\n 19.456233596018\n ],\n [\n -155.32539367675778,\n 19.456233596018\n ],\n [\n -155.32539367675778,\n 19.378522756179393\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact HVO
Hawaiian Volcano Observatory
U.S. Geological Survey
1266 Kamehameha Avenue
Suite A-8
Hilo, HI 96720