The Biscayne and Southern Everglades Coastal Transport (BISECT) model was developed by the U.S. Geological Survey under the Greater Everglades Priority Ecosystem Studies Initiative to evaluate, both separately and in conjunction, the likely effects on surface-water stages and flows, hydroperiod, and groundwater levels and salinity in south Florida of (1) a vertical Biscayne aquifer barrier to maintain higher wetland levels, (2) possible future changes to current water-management practices, and (3) sea-level rise. The BISECT model is a combination of the Tides and Inflows to the Mangrove Everglades (TIME) and Biscayne models of the western and eastern parts of south Florida including Everglades National Park, the southern Miami-Dade urban area, and the Biscayne Bay coast and simulates hydrodynamic surface-water flow and three-dimensional groundwater conditions dynamically for the period 1996–2004 by using the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) simulator. BISECT includes a number of parameter and algorithmic refinements that improve simulation results relative to the TIME and Biscayne models and represents the hydrologic system more explicitly, including (1) improved topographic representations, (2) refined Manning’s friction coefficients, (3) improved evapotranspiration computation through spatially variable albedo, (4) increased vertical aquifer discretization, and (5) extension of the western boundary farther offshore.
Sensitivity analyses demonstrate that simulated flows into Long Sound have a different pattern of response to tidal amplitude, wind, and frictional resistance changes than do other coastal streams in the model; flows at Broad River and Lostmans River are most sensitive to tidal amplitude, wind, and frictional resistance changes; and flow to the Everglades coastal streams is substantially affected by surface-water/groundwater interactions in the eastern urban areas. Insight into the hydrologic system came from scenario simulations that represent proposed management actions, such as grouting of the aquifer to prevent seepage from the wetlands and changes to water deliveries proposed by the Comprehensive Everglades Restoration Plan (CERP), and projected sea-level rise. These scenario management changes are considered separately to isolate their specific effects and also in conjunction with sea-level rise. Scenario simulations show that (1) attempts to prevent seepage from the wetlands by grouting the aquifer along the L 31N levee produce minimal effects on surface-water levels; (2) the increased water deliveries proposed in the CERP redistribute flow to the northwestern coastal part of the study area with a minimal reduction to the southeast and a more substantial reduction in flows in the intervening coastal zones, mitigating some sea-level rise effects; (3) sea-level rise has a larger effect on the hydrology (water levels, flow, and salinity) than does CERP restoration; and (4) support for ecological models and hydrologic studies can be provided by applying BISECT to scenarios influenced by climatic and anthropogenic changes or by meteorological variability, such as extreme wet or dry periods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195045","collaboration":"USGS Greater Everglades Priority Ecosystem Studies Initiative","usgsCitation":"Swain, E.D., Lohmann, M.A., and Goodwin, C.R., 2019, The hydrologic system of the south Florida peninsula—Development and application of the Biscayne and Southern Everglades Coastal Transport (BISECT) model: U.S. Geological Survey Scientific Investigations Report 2019–5045, 114 p., https://doi.org/10.3133/sir20195045.","productDescription":"Report: viii, 114 p.; Data Release","numberOfPages":"126","onlineOnly":"Y","ipdsId":"IP-062750","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":367710,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/P9MDUQPK","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"FTLOADDS (combined SWIFT2D surface-water model and SEAWAT groundwater model) simulator used to assess proposed sea-level rise response and water-resource management plans for the hydrologic system of the south Florida peninsula for the Biscayne and Southern Everglades Coastal Transport (BISECT) model"},{"id":367709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5045/sir20195045.pdf","text":"Report","size":"24.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5045"},{"id":367708,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5045/coverthb2.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 -81.49795532226562,\n 25.11544539706194\n ],\n [\n -80.15213012695312,\n 25.11544539706194\n ],\n [\n -80.15213012695312,\n 25.856751966503136\n ],\n [\n -81.49795532226562,\n 25.856751966503136\n ],\n [\n -81.49795532226562,\n 25.11544539706194\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The inland extent of saltwater at the base of the Biscayne aquifer in eastern Miami-Dade County, Florida, was mapped in 2011, and it was mapped in the Model Land Area in 2016. The saltwater interface has continued to move inland in some areas and is now near several active well fields. An updated approximation of the inland extent of saltwater has been created by using data collected during March 8–December 13, 2018, from 111 monitoring wells open to the Biscayne aquifer near its base. Chloride concentrations in water samples from the monitoring wells and bulk conductivity from geophysical logs and measurements of the specific conductance of groundwater were used to approximate the position of the isochlor representing a chloride concentration of 1,000 milligrams per liter (mg/L) at the base of the Biscayne aquifer.
An average rate of saltwater interface movement of about 102 meters per year in the Model Land Area along SW 360 Street was estimated from the approximated dates of arrival of the 250-, 500-, and 1,000-mg/L isochlors at wells TPGW-7L (2013–2014) and ACI-MW-05-FS (2017–2018). This estimate assumes that the interface is traveling in a path parallel to an imaginary line connecting the two monitoring wells.
Of the 111 wells from which data were used, 80 wells have open intervals of ≤ 4 meters, 20 of the wells have open intervals that range from 4.3 to 39.6 meters, and the lengths of the open intervals could not be determined in 11 wells. Studies have shown that long open intervals might allow water from various depths to mix under ambient or pumped conditions, which in turn could alter the maximum chloride concentration sampled in the well, or it might change the depth at which the maximum specific conductance is measured within a well, relative to its depth in the aquifer. The approximation of the inland extent of the saltwater interface and the estimated rate of movement of the interface are dependent on the quality of existing data. Improved estimates could be obtained by installing uniformly designed monitoring wells in systematic transects extending landward of the advancing saltwater interface. To achieve this goal, Miami-Dade County and some other organizations are routinely adding new monitoring wells with short open intervals and replacing poorly designed or positioned monitoring wells to improve spatial coverage of the network.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3438","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., 2019, Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in Miami-Dade County, Florida, 2018: U.S. Geological Survey Scientific Investigations Map 3438, 10-p. pamphlet, 1 sheet, https://doi.org/10.3133/sim3438.","productDescription":"Pamphlet: vii, 10 p.; 1 Plate: 35.8 x 46.0 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107371","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":367675,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3438/sim3438.pdf","text":"Sheet","size":"898 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3438"},{"id":367674,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3438/coverthb3.jpg"},{"id":367676,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3438/sim3438_pamphlet.pdf","text":"Pamphlet","size":"857 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3438 Pamphlet"},{"id":367677,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZIC1O4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Pertaining to Mapping the Approximate Inland Extent of Saltwater at the Base of the Biscayne Aquifer in Miami-Dade County, Florida, 2018"}],"country":"United States","state":"Florida","county":"Miami-Dade County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.8538818359375,\n 25.095548539604252\n ],\n [\n -79.9969482421875,\n 25.095548539604252\n ],\n [\n -79.9969482421875,\n 26.892679095908164\n ],\n [\n -80.8538818359375,\n 26.892679095908164\n ],\n [\n -80.8538818359375,\n 25.095548539604252\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
Geologic cross section A–A′ is the fifth in a series of cross sections constructed by the U.S. Geological Survey (USGS) to document and improve understanding of the geologic framework and petroleum systems of the Appalachian basin. Cross section A–A′ provides a regional view of the structural and stratigraphic framework of the Appalachian basin from the southern margin of the Ontario Lowlands province in western New York, across the Allegheny Plateau province of central New York and north-central Pennsylvania, to the Valley and Ridge province in north-central Pennsylvania, a distance of approximately 176 miles. This cross section is a companion to cross sections E–E′, D–D′, C–C′, and I–I′ that are located approximately 100 to 500 miles to the southwest. Cross section A–A′ complements earlier geologic or stratigraphic cross sections through the central New York and north-central Pennsylvania part of the Appalachian basin. Although some of these other cross sections show more structural and stratigraphic detail, they are of more limited extent geographically and stratigraphically.
Cross section A–A′ contains much information that is useful for evaluating energy resources in the Appalachian basin. Although the Appalachian basin petroleum systems are not shown on the cross section, many of their key elements (such as source rocks, reservoir rocks, seals, and traps) can be inferred from lithologic units, unconformities, and geologic structures shown on the cross section. Important oil- and gas-bearing formations like the Oriskany Sandstone, Medina Group sandstones, Tuscarora Sandstone, and the Marcellus and Utica Shales are present on cross-section A–A′.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3425","usgsCitation":"Trippi, M.H., Ryder, R.T., and Enomoto, C.B., 2019, Geologic cross section A–A′ through the Appalachian basin from the southern margin of the Ontario Lowlands province, Genesee County, western New York, to the Valley and Ridge province, Lycoming County, north-central Pennsylvania: U.S. Geological Survey Scientific Investigations Map 3425, 2 sheets, 74-p. pamphlet, https://doi.org/10.3133/sim3425.","productDescription":"Report: iii, 74 p.; 2 Sheets: 35.25 x 41.00 inches and 44.25 x 41.00 inches","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-069102","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":367495,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3425/sim3425_xsec-A-A_sheet2.pdf","text":"Sheet 2","size":"7.12 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York\",\"nation\":\"USA \"}}]}","contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
954 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
This report presents a 1:24,000-scale geologic map, cross sections, and descriptive and interpretative text for the Poncha Pass area in central Colorado. The map area is irregular in shape, covering all of one 7 ½' quadrangle (Poncha Pass) and parts of five others (Mount Ouray, Maysville, Salida West, Salida East, and Wellsville). The map boundaries were drawn to cover all of the “Poncha mountain block,” our designation for the approximately 15-kilometer-long northwestern end of the Sangre de Cristo Mountains. The map conveys the areal distribution of (1) Proterozoic basement rocks forming the core of the Poncha mountain block, (2) overlying Eocene and Oligocene volcanic rocks, (3) Miocene and younger basin-fill deposits, (4) Quaternary surficial glacial and alluvial deposits, and (5) faults and folds affecting all of the above units. The Poncha mountain block, which lies within the Rio Grande rift, is topographically and geologically distinctive. Generally, the Rio Grande rift is internally characterized by subsided structural basins or grabens and subdued, low-relief topography rather than elevated mountain blocks. The intrarift, topographically high Poncha mountain block spans the axial part of the rift and separates the low-lying basins of the west-tilted upper Arkansas River half graben and east-northeast-tilted San Luis half graben. These distinctive aspects of the Poncha mountain block were the primary motivations to conduct geologic mapping in the area. Important questions addressed by geologic mapping and related studies in the Poncha Pass area include (1) what were the structural controls and tectonic mechanism(s) that resulted in development of the Poncha mountain block in an intrarift environment; (2) did surface uplift of the Poncha block occur during rift development in the Neogene and Quaternary, and at what rate(s); (3) how was extensional strain accommodated and relayed across the Poncha block between the opposite-polarity rift basins and flanking mountain blocks; (4) is there a clear Laramide deformational signal in rocks of the map area; and (5) have earlier Laramide contractional structures, if they exist, influenced later rift-related extensional deformation through reactivation or strain localization. Prior to our mapping, the geology of much of the Poncha Pass area had only been mapped in reconnaissance fashion, reflecting the area’s poor bedrock exposures, poor access due to the rugged terrain, and geologic complexity. The map presented here provides new details of the geology of this difficult area and helps elucidate the development of the Poncha block and improves understanding of the geologic framework and geologic history of the area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3436","usgsCitation":"Minor, S.A., Caine, J.S., Ruleman, C.A., Fridrich, C.J., Chan, C.F., Brandt, T.R., Holm-Denoma, C.S., Morgan, L.E., Cosca, M.A., and Grauch, V.J.S., 2019, Geologic map of the Poncha Pass area, Chaffee, Fremont, and Saguache Counties, Colorado: U.S. Geological Survey Scientific Investigations Map 3436, 4 sheets, scale 1:24,000, https://doi.org/10.3133/sim3436.","productDescription":"4 Sheets: 60.5 x 36 inches or smaller; Data Release; Read Me","onlineOnly":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":437342,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PV6J8X","text":"USGS data release","linkHelpText":"Argon data for Poncha Pass Geologic Map"},{"id":367261,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3436/sim3436_sheet1_georeferenced.pdf","text":"Sheet 1—Georeferenced Geologic Map of the Poncha Pass Area, Chaffee, Fremont, and Saguache Counties, Colorado","size":"135 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Georeferenced SIM 3436 Sheet 1"},{"id":367301,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GYYF4F","text":"USGS data release","description":"USGS data release","linkHelpText":"Data release for Geologic Map of the Poncha Pass Area, Chaffee, Fremont, and Saguache Counties, Colorado"},{"id":367260,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3436/sim3436_sheet1.pdf","text":"Sheet 1—Geologic Map of the Poncha Pass Area, Chaffee, Fremont, and Saguache Counties, Colorado","size":"35.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3436 Sheet 1"},{"id":367263,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3436/sim3436_sheet3.pdf","text":"Sheet 3—Explanation of Map Units","size":"9.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3436 Explanation of Map Units"},{"id":367259,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3436/coverthb_sheet1.jpg"},{"id":367298,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3436/sim3436_ReadMe.txt","text":"Read Me","size":"16.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3436 Read Me"},{"id":367262,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3436/sim3436_sheet2.pdf","text":"Sheet 2—Cross Sections, Geologic Map of the Poncha Pass Area, Chaffee, Fremont, and Saguache Counties, Colorado","size":"2.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3436 Cross Sections"}],"country":"United States","state":"Colorado","county":"Chaffee County, Fremont County, Saguache County","otherGeospatial":"Poncha Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.20733642578125,\n 37.51626173528878\n ],\n [\n -105.02655029296875,\n 37.51626173528878\n ],\n [\n -105.02655029296875,\n 39.07464374293251\n ],\n [\n -107.20733642578125,\n 39.07464374293251\n ],\n [\n -107.20733642578125,\n 37.51626173528878\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
The rare earth elements (REEs) are a group of 17 elements sharing similar chemical properties. They include yttrium (Y, atomic number 39), scandium (Sc, atomic number 21), and the 15 elements of the lanthanide series, atomic numbers 57 (lanthanum, La) to 71 (lutetium, Lu). Because promethium (Pm, atomic number 61) does not occur in the Earth’s crust and scandium typically has different geological occurrences from other REEs, they are not discussed further herein.
REEs are, on average, more abundant than precious metals (for example, gold, silver, and platinum), but because of their unique geochemical properties, they do not commonly form economically viable ore deposits. Nevertheless, REEs are increasingly required for a range of modern applications in defense and renewable energy technologies and in commercial products, primarily as magnets, batteries, and catalysts. The United States currently (2018) produces REEs from a single mine in California, accounting for just 9 percent of global production, whereas 70 percent of global REE production comes from China. For these reasons, REEs are considered a critical resource, and the U.S. Geological Survey (USGS) has an interest in helping to identify new sources of REEs for domestic production.
In 2017, coal use accounted for about 30 percent of the electric power generated in the United States. Fly ash, produced during the burning of coal, is a fine-grained solid derived from noncombustible constituents of coal, such as clay minerals and quartz. When coal is burned, REEs are retained and enriched in the fly ash and, as a result, fly ash has long been considered a potential resource for REEs.
The United States has the world’s largest coal reserves and, even though gas-fired power generation has increased significantly in the last decade, the United States continues to produce vast quantities of fly ash, about half of which is beneficially reused, primarily in construction materials. The remainder is stored, mostly in landfills and impoundments. Thus, annual fly ash production, combined with fly ash already in storage, constitutes a large potential resource.
Research into how to utilize coal and coal fly ash as sources of REEs is ongoing. Viable recovery of REEs from coal and coal ash requires identification of coals and ashes with the highest REE concentrations and development of workable methods for REE extraction and recovery. Understanding how REEs occur within fly ash, described in this fact sheet, is one of the keys to developing possible methods for their recovery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193048","usgsCitation":"Scott, C., and Kolker, A., 2019, Rare earth elements in coal and coal fly ash: U.S. Geological Survey Fact Sheet 2019-3048, 4 p., https://doi.org/10.3133/fs20193048.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-098987","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":367383,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3048/fs20193048.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2019-3048"},{"id":367382,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3048/coverthb.jpg"}],"contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192
https://energy.usgs.gov/
Nuclear research activities at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) produced liquid and solid chemical and radiochemical wastes that were disposed to the subsurface resulting in detectable concentrations of some waste constituents in the eastern Snake River Plain (ESRP) aquifer. These waste constituents may affect the water quality of the aquifer and may pose risks to the eventual users of the aquifer water. To understand these risks to water quality the U.S. Geological Survey, in cooperation with the DOE, conducted geochemical mass-balance modeling of the ESRP aquifer to improve the understanding of chemical reactions, sources of recharge, mixing of water, and groundwater flow directions in the shallow (upper 250 feet) aquifer at the INL.
Modeling was conducted using the water chemistry of 127 water samples collected from sites at and near the INL. Water samples were collected between 1952 and 2017 with most of the samples collected during the mid-1990s. Geochemistry and isotopic data used in geochemical modeling consisted of dissolved oxygen, carbon dioxide, major ions, silica, aluminum, iron, and the stable isotope ratios of hydrogen, oxygen, and carbon.
Geochemical modeling results indicated that the primary chemical reactions in the aquifer were precipitation of calcite and dissolution of plagioclase (An60) and basalt volcanic glass. Secondary minerals other than calcite included calcium montmorillonite and goethite. Reverse cation exchange, consisting of sodium exchanging for calcium on clay minerals, occurred near site facilities where large amounts of sodium were released to the ESRP aquifer in wastewater discharge. Reverse cation exchange acted to retard the movement of wastewater-derived sodium in the aquifer.
Regional groundwater inflow was the primary source of recharge to the aquifer underlying the Northeast and Southeast INL Areas. Birch Creek (BC), the Big Lost River (BLR), and groundwater from BC valley provided recharge to the North INL Area, and the BLR and groundwater from BC and Little Lost River (LLR) valleys provided recharge to the Central INL Area. The BLR, groundwater from the BLR and LLR valleys and the Lost River Range, and precipitation provided recharge to the Northwest and Southwest INL Areas. The primary source of recharge west and southwest of the INL was groundwater inflow from BLR valley. Upwelling geothermal water was a small source of recharge at two wells. Aquifer recharge from surface water in the northern, central, and western parts of the INL indicated that the aquifer in these areas was a dynamic, open system, whereas the aquifer in the eastern part of the INL, which receives little recharge from surface water, was a relatively static and closed system.
Sources of recharge identified from isotope ratios and geochemical modeling (major ion concentrations) were nearly identical for the North, Northeast, Southeast, and Central INL Areas, which indicated that both methods probably accurately identified the sources of recharge in these areas. Conversely, isotope ratios indicated that the BLR and groundwater from the LLR valley provided most recharge to the western parts of the Northwest and Southwest INL Areas, whereas geochemical modeling results indicated a smaller area of recharge from the BLR and groundwater from the LLR valley, a larger area of recharge from the Lost River Range, and recharge of groundwater from the BLR valley that extended to the west INL boundary. The results from geochemical modeling probably were more accurate because major ion concentrations, but not isotope ratios, were available to characterize groundwater from the BLR valley and the Lost River Range.
Sources of recharge identified with a groundwater flow model (using particle tracking) and geochemical modeling were similar for the Northeast and Southeast INL Areas. However, differences between the models were that the geochemical model represented (1) recharge of groundwater from the Lost River Range in the western part of the INL, whereas the flow model did not, (2) recharge of groundwater from the BC and BLR valleys extending farther south and east, respectively, than the flow model, and (3) more recharge from the BLR in the Southwest INL Area than the flow model.
Mixing of aquifer water beneath the INL included (1) mixing of regional groundwater and water from the BC valley in the Northeast and Southeast INL Areas and (2) mixing of surface water (primarily from the BLR) and groundwater across much of the North, Central, Northwest, and Southwest INL Areas. Localized recharge from precipitation mixed with groundwater in the Northwest and Southwest INL Areas, and localized upwelling geothermal water mixed with groundwater in the Central and Northeast INL Areas. Flow directions of regional groundwater were south in the eastern part of the INL and south-southwest at downgradient locations. Groundwater from the BC and LLR valleys initially flowed southeast before changing to south-southwest flow directions that paralleled regional groundwater, and groundwater from the BLR valley initially flowed south before changing to a southsouthwest direction.
Wastewater-contaminated groundwater flowed south from the Idaho Nuclear Technology and Engineering Center (INTEC) infiltration ponds in a narrow plume, with the percentage of wastewater in groundwater decreasing due to dilution, dispersion, and (or) degradation from about 60‒80 percent wastewater 0.7‒0.8 mile (mi) south of the INTEC infiltration ponds to about 1.4 percent wastewater about 15.5 mi south of the INTEC infiltration ponds. Wastewater contaminated groundwater flowed southeast and then southwest from the Naval Reactors Facility industrial waste ditch, with the percentage of wastewater in groundwater decreasing from about 100 percent wastewater adjacent to the waste ditch to about 2 percent wastewater about 0.6 mi south of the waste ditch.
Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
The Paradox Valley in southwestern Colorado is a collapsed anticline formed by movement of the salt-rich Paradox Formation at the core of the anticline. The salinity of the Dolores River, a tributary of the Colorado River, increases substantially as it crosses the valley because of discharge of brine-rich groundwater derived from the underlying salts. Although the brine is naturally occurring, it increases the salinity of the Colorado River, which is a major concern to downstream agricultural, municipal, and industrial water users. The U.S. Geological Survey in cooperation with the Bureau of Reclamation conducted a study to improve the characterization of processes controlling spatial and temporal variations in brine discharge to the Dolores River. For the study, three geophysical surveys were conducted in March, May, and September 2017, and water levels were monitored in selected ponds and groundwater wells from November 2016 to May 2018. The study also utilized streamflow and specific conductance data from two U.S. Geological Survey streamflow-gaging stations on the Dolores River to estimate salt load to the river.
River-based continuous resistivity profiling and frequency domain electromagnetic induction surveys made during low-flow conditions indicated a zone of brine-rich groundwater close to the riverbed along an approximately 4-kilometer reach of the river. Under high-flow conditions, the brine was depressed as much as 2 meters below the riverbed, and brine discharge to the river was reduced to a minimum. Direct current electrical resistivity surveys show that the freshwater lens overlying the brine is much thicker (up to 10 meters) on the west bank than on the east bank (less than 5 meters). A large low-conductivity anomaly at river distance 6,800 meters was observed in all surveys and may represent a freshwater discharge zone or a losing reach of the river.
Filling and draining of the wildlife ponds on the west side of the river had a negligible effect on salt loads in the river during the study period. Groundwater monitoring showed there was active exchange of water between the river and the adjacent alluvial aquifer. When river stage was low, groundwater flowed towards the river, and brine discharge to the river increased. When the river stage was high, the gradient was reversed, and fresh surface water recharged the alluvial aquifer minimizing brine discharge. Most of the salt load to the river occurred during the winter and appeared to be enhanced by diurnal stage fluctuations.
A conceptual model of brine discharge to the river is presented at three scales. Groundwater at the regional scale drives dissolution of salt in the Paradox Formation and flow of brine into the base of the alluvial aquifer. Surface water–groundwater interactions at the scale of the alluvial aquifer control brine discharge to the river seasonally and interannually. At the finest scale, diurnal fluctuations in river stage drive exchange of freshwater with saltier pore water in the hyporheic zone, which appears to increase brine discharge to the river during winter.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195058","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Mast, M.A., and Terry, N., 2019, Controls on spatial and temporal variations of brine discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18: U.S. Geological Survey Scientific Investigations Report 2019–5058, 25 p., https://doi.org/10.3133/sir20195058.\n","productDescription":"vi, 25 p.","onlineOnly":"Y","ipdsId":"IP-103865","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437347,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77080NB","text":"USGS data release","linkHelpText":"Raw Data from Continuous Resistivity Profiles and Electromagnetic Surveys Collected in and adjacent to the Dolores River in the Paradox Valley, Colorado (2017)"},{"id":367271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5058/sir20195058.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5058"},{"id":367270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5058/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Montrose County","otherGeospatial":"Paradox Valley","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-108.3772,38.6678],[-108.1472,38.6675],[-107.965,38.6664],[-107.9279,38.6661],[-107.9084,38.6664],[-107.8589,38.6663],[-107.8206,38.6664],[-107.7782,38.6661],[-107.7658,38.6663],[-107.741,38.6662],[-107.5011,38.6657],[-107.4992,38.6304],[-107.4989,38.6172],[-107.4992,38.5737],[-107.499,38.5356],[-107.4989,38.4717],[-107.4991,38.4531],[-107.4991,38.4504],[-107.4989,38.4445],[-107.4995,38.4404],[-107.4991,38.4246],[-107.4994,38.4096],[-107.4993,38.4033],[-107.4997,38.3656],[-107.4995,38.3248],[-107.4995,38.3008],[-107.5213,38.301],[-107.6333,38.3005],[-107.6358,38.3095],[-107.633,38.3172],[-107.6314,38.3223],[-107.6292,38.3286],[-107.6339,38.3286],[-107.6867,38.3288],[-107.7049,38.329],[-107.7236,38.3287],[-107.7964,38.329],[-107.8146,38.3292],[-107.8522,38.3291],[-107.8715,38.3293],[-107.9079,38.3292],[-107.9449,38.3295],[-107.9631,38.3296],[-108.0007,38.3304],[-108.0206,38.3305],[-108.1127,38.3312],[-108.1274,38.331],[-108.1276,38.3183],[-108.1165,38.3185],[-108.1163,38.3121],[-108.0987,38.312],[-108.0985,38.283],[-108.0815,38.2828],[-108.0807,38.2547],[-108.0085,38.2537],[-108.0084,38.2482],[-107.9814,38.2477],[-107.981,38.2328],[-107.9628,38.2326],[-107.9627,38.2263],[-107.9468,38.2265],[-107.9466,38.2184],[-107.9367,38.2185],[-107.9367,38.1732],[-107.946,38.1731],[-107.946,38.1517],[-107.9654,38.1519],[-108.0549,38.1522],[-108.2235,38.152],[-108.2411,38.1522],[-108.2587,38.1523],[-108.3336,38.1523],[-108.3506,38.1519],[-108.4641,38.1524],[-108.4841,38.1525],[-108.5397,38.1527],[-108.6304,38.153],[-108.6492,38.1531],[-109.041,38.1531],[-109.0409,38.1603],[-109.0607,38.2768],[-109.0608,38.3304],[-109.0608,38.3521],[-109.0607,38.378],[-109.0607,38.4052],[-109.0606,38.4197],[-109.0604,38.4555],[-109.0604,38.4637],[-109.0602,38.4981],[-109.0602,38.4991],[-108.6635,38.4992],[-108.3791,38.4999],[-108.3771,38.6116],[-108.3772,38.6678]]]},\"properties\":{\"name\":\"Montrose\",\"state\":\"CO\"}}]}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
We evaluated the prevalence of influenza A virus (IAV) in different species of bivalves inhabiting natural water bodies in waterfowl habitat along the Delmarva Peninsula and Chesapeake Bay in eastern Maryland. Bivalve tissue from clam and mussel specimens (Macoma balthica, Macoma phenax, Mulinia sp., Rangia cuneata, Mya arenaria, Guekensia demissa, and an undetermined mussel species) from five collection sites was analyzed for the presence of type A influenza virus by qPCR targeting the matrix gene. Of the 300 tissue samples analyzed, 13 samples (4.3%) tested positive for presence of influenza virus A matrix gene. To our knowledge, this is the first report of detection of IAV in the tissue of any bivalve mollusk from a natural water body.
","language":"English","publisher":"MDPI","doi":"10.3390/microorganisms7090334","usgsCitation":"Densmore, C., Iwanowicz, D., McLaughlin, S.M., Ottinger, C., Spires, J.E., and Iwanowicz, L., 2019, Influenza A virus detected in native bivalves in waterfowl habitat of the Delmarva Peninsula, USA: Microorganisms, v. 7, 334, 7p., https://doi.org/10.3390/microorganisms7090334.","productDescription":"334, 7p.","ipdsId":"IP-111178","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":459879,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/microorganisms7090334","text":"Publisher Index Page"},{"id":367415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay, Delmarva Penninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.9921875,\n 37.709899354855125\n ],\n [\n -75.487060546875,\n 37.709899354855125\n ],\n [\n -75.487060546875,\n 39.58875727696545\n ],\n [\n -76.9921875,\n 39.58875727696545\n ],\n [\n -76.9921875,\n 37.709899354855125\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Densmore, Christine L. 0000-0001-6440-0781","orcid":"https://orcid.org/0000-0001-6440-0781","contributorId":204739,"corporation":false,"usgs":true,"family":"Densmore","given":"Christine L.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":770785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":213902,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":770786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McLaughlin, Shawn M.","contributorId":218966,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Shawn","email":"","middleInitial":"M.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":770787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ottinger, Christopher 0000-0003-2551-1985","orcid":"https://orcid.org/0000-0003-2551-1985","contributorId":205874,"corporation":false,"usgs":true,"family":"Ottinger","given":"Christopher","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":770788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spires, Jason E.","contributorId":218967,"corporation":false,"usgs":false,"family":"Spires","given":"Jason","email":"","middleInitial":"E.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":770789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":205661,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":770790,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227911,"text":"70227911 - 2019 - Effects of distribution, behavior, and climate on mule deer survival","interactions":[],"lastModifiedDate":"2022-02-03T12:06:36.134671","indexId":"70227911","displayToPublicDate":"2019-09-05T14:13:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of distribution, behavior, and climate on mule deer survival","docAbstract":"Mule deer (Odocoileus hemionus hemionus) populations in North America are a valuable economic wildlife resource, with the managed harvest of this species reflecting societal values and recreational opportunities in many parts of the western United States. Managing mule deer populations while allowing for harvest requires an understanding of the species’ population dynamics, including the specific factors associated with population change. We conducted a 7-year (2005–2012) study designed to investigate habitat use and survival of mule deer in eastern Oregon, USA. We used known-fate data for 408 adult female radio-collared mule deer to estimate monthly survival rates and to investigate factors that might affect these rates, including seasonal distribution, temporal effects (seasonal, annual, and trends across season and year), movement behavior, and local weather and regional climatic covariates. Variation in survival rates of female mule deer was best explained by an additive effect of migration behavior, differences in survival during the fall migration period compared to the rest of the annual cycle, and precipitation levels on winter ranges of individual deer. Estimates of annual survival were higher for migrants (0.81–0.82), compared to residents (0.76–0.77). Survival was lower for migrants and residents during fall migration (Oct–Nov) and higher amounts of winter precipitation increased survival of both groups. The results of our study suggest that migrating to potentially higher quality summer foraging areas outweighed the cost of traveling through unfamiliar habitats and energy expenditure associated with migration. © 2018 The Wildlife Society.
The National Park Service (NPS) and the Bureau of Land Management (BLM) are concerned about cumulative effects of groundwater development on groundwater-dependent resources managed by, and other groundwater resources of interest to, these agencies in Snake Valley and adjacent areas, Utah and Nevada. Of particular concern to the NPS and BLM are withdrawals from all existing approved, perfected, certified, permitted, and vested groundwater rights in Snake Valley totaling about 55,272 acre-feet per year (acre-ft/yr), and from several senior water-right applications filed by the Southern Nevada Water Authority (SNWA) totaling 50,680 acre-ft/yr.
An existing groundwater-flow model of the eastern Great Basin was used to investigate where potential drawdown and capture of natural discharge is likely to result from potential groundwater withdrawals from existing groundwater rights in Snake Valley, and from groundwater withdrawals proposed in several applications filed by the SNWA. To evaluate the potential effects of the existing and proposed SNWA groundwater withdrawals, 11 withdrawal scenarios were simulated. All scenarios were run as steady state to estimate the ultimate long-term effects of the simulated withdrawals. This assessment provides a general understanding of the relative susceptibility of the groundwater resources of interest to the NPS and BLM, and the groundwater system in general, to existing and future groundwater development in the study area.
At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from withdrawals based on existing approved, perfected, certified, permitted, and vested groundwater rights within Snake Valley ranged between 0 and 159 feet (ft) without accounting for irrigation return flow, and between 0 and 123 ft with accounting for irrigation return flow. With the addition of proposed SNWA withdrawals of 35,000 acre-ft/yr (equal to the Unallocated Groundwater portion allotted to Nevada in a draft interstate agreement), simulated drawdowns at the NPS and BLM sites of interest increased to range between 0 and 2,074 ft without irrigation return flow, and between 0 and 2,002 ft with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts (50,680 acre-ft/yr), simulated drawdowns at the NPS and BLM sites of interest increased to range between 1 and 3,119 ft without irrigation return flow, and between 1 and 3,044 ft with irrigation return flow.
At the NPS and BLM groundwater resource sites of interest, simulated capture of natural discharge resulting from withdrawals based on existing groundwater rights in Snake Valley, both with and without irrigation return flow, ranged between 0 and 100 percent; simulated capture of 100 percent occurred at four sites. With the addition of proposed SNWA withdrawals of an amount equal to the Unallocated Groundwater portion allotted to Nevada in the draft interstate agreement, simulated capture of 100 percent occurred at nine additional sites without irrigation return flow, and at eight additional sites with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts, simulated capture of 100 percent occurred at 11 additional sites without irrigation return flow, and at 9 additional sites with irrigation return flow.
The large simulated drawdowns produced in the scenarios that include large portions or all of the proposed SNWA withdrawals indicate that the groundwater system may not be able to support the amount of withdrawals from the proposed points of diversion (PODs) in the current SNWA water-right applications. Therefore, four additional scenarios were simulated where the withdrawal rates at the SNWA PODs were constrained by not allowing drawdowns to be deeper than the assumed depth of the PODs (about 2,000 ft). In the constrained scenarios, total withdrawals at the SNWA PODs were reduced to about 48 percent of the Unallocated Groundwater portion allotted to Nevada (35,000 acre-ft/yr reduced to 16,817 acre-ft/yr or 16,914 acre-ft/yr, without or with irrigation return flow, respectively), and about 44 percent of the full application amounts (50,680 acre-ft/yr reduced to 22,048 acre-ft/yr or 22,165 acre-ft/yr, without or with irrigation return flow, respectively). This indicates that the SNWA may need to add more PODs, or PODs in different locations, in order to withdraw large portions or all of the groundwater that has been applied for.
At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount ranged between 0 and 290 ft without irrigation return flow, and between 0 and 252 ft with irrigation return flow. With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated drawdowns at the NPS and BLM sites of interest ranged between 0 and 358 ft without irrigation return flow, and between 0 and 313 ft with irrigation return flow.
At the NPS and BLM groundwater resource sites of interest, with the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount, simulated capture of 100 percent of the natural discharge occurred at five additional sites without irrigation return flow, and at two additional sites with irrigation return flow (in addition to the four captured from existing water rights both with and without irrigation return flow). With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated capture of 100 percent occurred at six additional sites both with and without irrigation return flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191083","collaboration":"Prepared in cooperation with the National Park Service and the Bureau of Land Management","usgsCitation":"Masbruch, M.D., 2019, Numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada: U.S. Geological Survey Open-File Report 2019–1083, 49 p., https://doi.org/10.3133/ofr20191083.","productDescription":"Report: vi, 49 p.; Data Release","numberOfPages":"49","onlineOnly":"Y","ipdsId":"IP-103457","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":367115,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1083/coverthb_.jpg"},{"id":367116,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1083/ofr20191083.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1083"},{"id":367119,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LQDQGM","text":"Data Release","linkHelpText":"MODFLOW-2005 files for numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.48828125000001,\n 35.53222622770337\n ],\n [\n -110.302734375,\n 39.36827914916014\n ],\n [\n -110.12695312499999,\n 40.97989806962013\n ],\n [\n -111.005859375,\n 42.68243539838623\n ],\n [\n -114.78515624999999,\n 41.244772343082076\n ],\n [\n -117.59765625,\n 37.64903402157866\n ],\n [\n -115.48828125000001,\n 35.53222622770337\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000
Mother Nature was not making it easy. It was February 18, 2009, and winds were gusting, sleet was falling, and temperatures were hovering around 40° F. Our crew of 9 which consisted of personnel from the USDA Forest Service Southern Research Station, the Cherokee National Forest, and The University of Tennessee’s Tree Improvement Program, was attempting to establish the first test planting of American chestnuts (Castanea dentata) bred for resistance to an exotic fungal pathogen, the chestnut blight (Cryphonectria parasitica). With each hole dug and seedlings tamped into the ground, our hope was that we were one step closer to restoring an important wildlife food to eastern hardwood forests.
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]\n}","volume":"13","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Staci L","contributorId":219206,"corporation":false,"usgs":false,"family":"Clark","given":"Staci","email":"","middleInitial":"L","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":771619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlarbaum, Scott E.","contributorId":168715,"corporation":false,"usgs":false,"family":"Schlarbaum","given":"Scott","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":771620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":771618,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211228,"text":"70211228 - 2019 - Site response in the Oklahoma region from seismic recordings of the 2011 Mw 5.7 Prague earthquake","interactions":[],"lastModifiedDate":"2020-07-21T14:45:02.774951","indexId":"70211228","displayToPublicDate":"2019-08-30T15:57:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Site response in the Oklahoma region from seismic recordings of the 2011 Mw 5.7 Prague earthquake","docAbstract":"We invert the shear-wave displacement spectra obtained from 30 three-component, broadband waveforms recorded within 300 km of the 6 November 2011 Mw 5.7 Prague, Oklahoma earthquake to recover the site-response contribution using an inversion method that simultaneously inverts for source, path, and site effects. Site-response functions identify resonant frequencies within a range of 0.1-10 Hz that generally coincide with spectral peaks in H/V curves derived from the recorded waveforms. S-wave velocity profiles available for several sites were also used to calculate theoretical SH transfer functions that predict the site amplification due to the near-surface soil structure down to depths of 30-50 m. These transfer functions are generally flat below about 8 Hz in the frequency range sampled by the spectral inversion process, indicating that the spectral peaks in the site response obtained from the waveform analysis result from deeper velocity variations. A 0.3-Hz spectral peak observed at several stations, for example, coincides with the strong, surface-wave amplitudes observed at 3s periods for induced M ≥ 3 earthquakes in Oklahoma and Kansas, suggesting that this resonant peak may be due to surface waves trapped in the upper sedimentary layer of the crust. Both shallow and deep contributions to the site response are important for the characterization of ground motion from Central and Eastern North America (CENA) earthquakes. We obtain a seismic moment of 4.32 × 1024 dyne-cm and a corner frequency of 0.229, consistent with the magnitude of the event. A frequency-dependent attenuation relation of Q(f)=1107f 0.398 consistent with prior measurements of path properties in CENA is also derived.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180388","usgsCitation":"Mendoza, C., and Hartzell, S.H., 2019, Site response in the Oklahoma region from seismic recordings of the 2011 Mw 5.7 Prague earthquake: Seismological Research Letters, v. 90, no. 5, p. 2015-2027, https://doi.org/10.1785/0220180388.","productDescription":"13 p.","startPage":"2015","endPage":"2027","ipdsId":"IP-108626","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":376529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Prague","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.99554443359375,\n 35.22094130403182\n ],\n [\n -96.328125,\n 35.22094130403182\n ],\n [\n -96.328125,\n 35.70414710206052\n ],\n [\n -96.99554443359375,\n 35.70414710206052\n ],\n [\n -96.99554443359375,\n 35.22094130403182\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"90","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Mendoza, C.","contributorId":229471,"corporation":false,"usgs":false,"family":"Mendoza","given":"C.","affiliations":[{"id":36644,"text":"Centro de Geociencias, Universidad Nacional Autónoma de México, Campus Juriquilla, Queretaro, Mexico","active":true,"usgs":false}],"preferred":false,"id":793279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":793280,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206098,"text":"70206098 - 2019 - Water velocity regulates macro-consumer herbivory on the benthic macrophyte Podostemum ceratophyllum Michx.","interactions":[],"lastModifiedDate":"2019-10-23T08:10:39","indexId":"70206098","displayToPublicDate":"2019-08-29T08:09:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Water velocity regulates macro-consumer herbivory on the benthic macrophyte Podostemum ceratophyllum Michx.","docAbstract":"1) Macrophytes influence aquatic ecosystems by increasing habitat complexity and providing trophic resources for aquatic fauna. While herbivory on freshwater macrophytes is widely documented in lakes, low-velocity riverine habitats, the influence of herbivory on macrophytes in higher-velocity habitats has rarely been examined. \n\n2) We investigated the hypothesis that high water velocity can reduce consumption rates of the submerged macrophyte, Podostemum ceratophyllum, an angiosperm which grows attached to stable substrates in high water-velocity riverine habitats throughout eastern North America. \n\n3) We estimated grazing-pressure by conducting short-term (up to 77-d) transplant and consumer-exclosure experiments, and quantified changes in Podostemum stem length when the plant was eposed to low (<0.5 m s-1) and higher velocities in two Piedmont rivers in Georgia (USA). Podostemum transplanted into low-velocity habitats rapidly lost stem length unless macro-consumers were excluded from accessing the plant. In contrast, Podostemum tranplanted into high-velocity habitats showed little change or gained stem length. \n\n4) We estimated that 85% (67 – 98%; 95% credible interval) of the daily stem growth (0.026 cm cm-1 day-1) in Podostemum was consumed during a 77-d paired consumer-access versus exclosure experiment conducted in mean water velocities of 0.35-0.5 m s-1. We also found a positive relation (R2 = 0.58) between Podostemum biomass and water velocity (ranging between ~0.1 -1.4 m s-1) in benthic samples collected over a two-month period. \n\n5) We conclude that high water velocity reduces herbivory on Podostemum, and that water velocity can thus control the acural of benthic plant biomass and the movement of plant-derived materials through benthic food webs. Our research has implications for estimating resource storage and flux in lotic food webs and illuminates a mechanism by which flow regulation and management may affect basal resources in rivers.","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13393","usgsCitation":"Wood, J.L., Skaggs, J.W., Conn, C.C., and Freeman, M., 2019, Water velocity regulates macro-consumer herbivory on the benthic macrophyte Podostemum ceratophyllum Michx.: Freshwater Biology, v. 64, no. 11, p. 2037-2045, https://doi.org/10.1111/fwb.13393.","productDescription":"9 p.","startPage":"2037","endPage":"2045","ipdsId":"IP-095841","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":368506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"64","issue":"11","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, James L","contributorId":219912,"corporation":false,"usgs":false,"family":"Wood","given":"James","email":"","middleInitial":"L","affiliations":[{"id":40096,"text":"West Liberty University","active":true,"usgs":false}],"preferred":false,"id":773571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skaggs, Jon W","contributorId":219913,"corporation":false,"usgs":false,"family":"Skaggs","given":"Jon","email":"","middleInitial":"W","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":773572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conn, Caitlin C","contributorId":219914,"corporation":false,"usgs":false,"family":"Conn","given":"Caitlin","email":"","middleInitial":"C","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":773573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773570,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205094,"text":"70205094 - 2019 - Characterizing and imaging sedimentary strata using depth-converted spectral ratios: An example from the Atlantic Coastal Plain of the Eastern U.S.","interactions":[],"lastModifiedDate":"2019-09-03T09:49:54","indexId":"70205094","displayToPublicDate":"2019-08-28T09:47:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing and imaging sedimentary strata using depth-converted spectral ratios: An example from the Atlantic Coastal Plain of the Eastern U.S.","docAbstract":"Unconsolidated, near-surface sediments can have a profound influence on the amplitudes and frequencies of ground shaking during earthquakes, and these effects should be accounted for when using amplitude observations for seismic hazard assessments. This study explores methods to use teleseismic arrivals recorded on linear receiver arrays to characterize widespread, shallow sedimentary deposits, including estimation of the velocities, determination of the fundamental resonance peaks, and imaging of the major reflectors. The examples used are the extensive Atlantic Coastal Plain (ACP) and associated Mississippi Embayment (ME) strata of the Central and Eastern United States. The large contrast in material properties at the bedrock surface beneath these sediments produces a strong fundamental resonance peak in the 0.2 to 4 Hz frequency range, which is estimated here by computing spectral ratios at each receiver site relative to bedrock sites at the ends of the receiver arrays. Sediment thicknesses derived from published contour maps made from drill hole data allow for the computation of average velocities to match the observed frequencies of resonance peaks with theoretical values at each receiver site, with the sloping bedrock surface allowing for computation of an average velocity versus depth function if horizontal layers are assumed. The velocity function is then used to convert the spectral ratios from frequency to depth, resulting in an image of the subsurface similar to that of a seismic reflection profile. The results demonstrate the use of teleseismic signals for characterizing and imaging shallow sedimentary strata.\n ","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180046","usgsCitation":"Pratt, T.L., 2019, Characterizing and imaging sedimentary strata using depth-converted spectral ratios: An example from the Atlantic Coastal Plain of the Eastern U.S.: Bulletin of the Seismological Society of America, v. 108, no. 5A, p. 2801-2815, https://doi.org/10.1785/0120180046.","productDescription":"15 p.","startPage":"2801","endPage":"2815","ipdsId":"IP-098671","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":367129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Atlantic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.498046875,\n 39.198205348894795\n ],\n [\n -77.7392578125,\n 38.71980474264237\n ],\n [\n -86.9677734375,\n 33.7243396617476\n ],\n [\n -92.0654296875,\n 32.58384932565662\n ],\n [\n -85.2978515625,\n 30.524413269923986\n ],\n [\n -81.1669921875,\n 27.994401411046148\n ],\n [\n -80.85937499999999,\n 26.391869671769022\n ],\n [\n -77.607421875,\n 31.052933985705163\n ],\n [\n -74.0478515625,\n 34.813803317113155\n ],\n [\n -75.1904296875,\n 39.13006024213511\n ],\n [\n -75.498046875,\n 39.198205348894795\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"108","issue":"5A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":770000,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70204522,"text":"sir20195072 - 2019 - Arsenic, antimony, mercury, and water temperature in streams near Stibnite mining area, central Idaho, 2011–17","interactions":[],"lastModifiedDate":"2019-08-28T10:27:00","indexId":"sir20195072","displayToPublicDate":"2019-08-27T13:23:40","publicationYear":"2019","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":"2019-5072","displayTitle":"Arsenic, Antimony, Mercury, and Water Temperature in Streams near Stibnite Mining Area, Central Idaho, 2011–17","title":"Arsenic, antimony, mercury, and water temperature in streams near Stibnite mining area, central Idaho, 2011–17","docAbstract":"Mineralization and historical mining of stibnite (antimony sulfide), tungsten, gold, silver, and mercury in the headwaters of the East Fork of the South Fork Salmon River (EFSFSR) near the former town of Stibnite in central Idaho resulted in water-quality impairments related to mercury, antimony, and arsenic. Additionally, mining-related disturbances and wildfires have resulted in a lack of riparian shade in some areas, likely impacting water temperatures. In 2011, the U.S. Geological Survey, in cooperation with Midas Gold Corporation and the Idaho Department of Lands, began a study to characterize the spatial and temporal occurrence of trace metals to the EFSFSR. Five sites on the EFSFSR and its tributaries (Meadow and Sugar Creeks) were sampled about six times annually during 2011–17, during a range of streamflow conditions, for a total of 36–40 samples per location. Continuous water temperature, specific conductance, and streamflow also were measured at each site. The purpose of this report is to update previously reported information related to arsenic, antimony, mercury, and water temperature.\n\nConcentrations of dissolved arsenic and antimony generally increased from upstream to downstream in the EFSFSR. At the upstream site, upstream of the Meadow Creek confluence, dissolved arsenic and antimony concentrations averaged 8.86 and 0.93 micrograms per liter (μg/L), respectively. Downstream, upstream from the Sugar Creek confluence, average dissolved concentrations increased to 56.5 and 27.9 μg/L, respectively. All samples from the downstream EFSFSR site exceeded the human-health based criterion for both dissolved arsenic (10 µg/L) and dissolved antimony (5.6 µg/L). The chronic aquatic life criterion for dissolved arsenic (150 μg/L) was not exceeded (the maximum sample concentration was 108 μg/L), and aquatic life criteria for antimony have not been established. The highest concentrations of both dissolved arsenic and dissolved antimony occurred during low-flow periods (July–March), suggesting the constituents are present in groundwater. In contrast, total mercury concentrations were highest during high-flow periods (April–June) and were particulate-associated, suggesting that mercury is present in surface materials. At Sugar Creek, where the highest total mercury concentrations were measured, 97 percent of samples exceeded the chronic aquatic life criterion (0.012 μg/L) and 11 percent exceeded the acute criterion (2.1 μg/L). At all sites, summertime water temperatures frequently exceeded criteria related to salmonid spawning.\n\nSurrogate models previously developed to estimate continuous concentrations of arsenic, antimony, and mercury were reevaluated and updated, and the importance of explanatory variables on constituent concentrations is discussed. Results from this study can help guide future remediation locations and strategies, and provide a baseline against which future changes can be measured.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195072","collaboration":"Prepared in cooperation with the Idaho Department of Lands and Midas Gold Idaho, Inc.","usgsCitation":"Baldwin, A.K., and Etheridge, A.B., 2019, Arsenic, antimony, mercury, and water temperature in streams near Stibnite mining area, central Idaho, 2011–17: U.S. Geological Survey Scientific Investigations Report 2019-5072, 20 p., plus appendix, https://doi.org/10.3133/sir20195072.","productDescription":"Report: vi, 20 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-093353","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":366989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5072/coverthb.jpg"},{"id":366990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5072/sir20195072.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5072"},{"id":366991,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5072/sir20195072_appendix.pdf","text":"Appendix","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5072 Appendix","linkHelpText":" — Surrogate Regression Model Archive Summaries."}],"country":"United States","state":"Idaho","otherGeospatial":"Stibnite Mining Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.67985534667969,\n 44.793530904744074\n ],\n [\n -115.14564514160158,\n 44.793530904744074\n ],\n [\n -115.14564514160158,\n 45.15541134861056\n ],\n [\n -115.67985534667969,\n 45.15541134861056\n ],\n [\n -115.67985534667969,\n 44.793530904744074\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Hyperalkaline (pH greater than 12) ponds and groundwater exist at Big Marsh near Lake Calumet, Chicago, Illinois, a site used by the steel industry during the mid-1900s to deposit steel- and iron-making waste, in particular, slag. The hyperalkaline ponds may pose a hazard to human health and the environment. The U.S. Geological Survey (USGS), in cooperation with the Environmental Protection Agency (EPA) and in collaboration with the City of Chicago’s Park District, completed a study to evaluate the hydrologic balance, water quality, and chemical-mass balance of hyperalkaline ponds at Big Marsh and geochemical modeling used to evaluate remediation options for water quality at the site based on data collected in 2016–17.
Synoptic measurements of surface-water and groundwater elevations were used to determine flow directions and to enable a preliminary estimate of the hydrologic balance for the ponds. Water-quality samples also were collected and analyzed for selected constituents including major anions and cations, nutrients, metals, and trace elements. The results of the water-quality analyses were used to develop a geochemical model to evaluate concentrations, factors affecting pH, and the state of equilibrium between surface waters and atmospheric carbon dioxide. The geochemical model was used to evaluate remediation scenarios using riprap, spillways, or active aeration. The results indicate that active aeration will decrease the pH to near 7.5 in about 8 hours, the fastest rate of the scenarios. Passive aeration, such as riprap or spillways, also can be effective at decreasing the pH in about 45 hours, but spatial obstacles limit their implementation. Seasonal variations in temperature also affect the rate of equilibration, where colder temperatures may have a lower pH than warmer temperatures and may affect the timing and frequency of remediation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195078","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Brownfields Program, and in collaboration with the City of Chicago’s Park District","usgsCitation":"Gahala, A.M., Seal, R.R., and Piatak, N.M., 2019, Hydrologic balance, water quality, chemical-mass balance, and geochemical modeling of hyperalkaline ponds at Big Marsh, Chicago, Illinois, 2016–17: U.S. Geological Survey Scientific Investigations Report 2019–5078, 31 p., https://doi.org/10.3133/sir20195078.","productDescription":"Report: vi, 31 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-091826","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":366917,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5078/sir20195078.pdf","text":"SIR 2019–5078","size":"3.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5078"},{"id":366918,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VUAQ35","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Water level data from single-well (slug) tests at a monitoring well in Big Marsh, Chicago, Illinois"},{"id":366916,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5078/coverthb.jpg"}],"country":"United States","state":"Illinois","county":"Cook 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Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
Conversion of agricultural lands to wetlands and native prairie is widely viewed as beneficial because it can restore natural ecological and hydrologic functions. Some of these functions, such as reduced peak flows and improved water quality, are often attributed to restoration; however, such benefits have not been quantified at a small scale. To inform future restoration efforts, especially in northern prairie settings, the U.S. Geological Survey, in cooperation with the Minnesota Environment and Natural Resources Trust Fund, the U.S. Fish and Wildlife Service, and the Red Lake Watershed District, compared the hydrology of the Nation’s largest wetland and prairie restoration, Glacial Ridge National Wildlife Refuge, before and after restoration.
Wetland and prairie restorations resulted in substantial changes in flows through the hydrologic cycle, in reduction of overland runoff and ditch flow during storms, and in improvements in water quality. Wetland and prairie restorations within the six basins characterized in this study resulted in a 14-percent decrease of cropland, a 6-percent increase of wetlands, and a 19-percent increase of native prairie between 2002 and 2015. During the same period, runoff rate decreased 33 percent (as a proportion of precipitation) and ditch flow rate decreased by 23 percent. Areal groundwater recharge rate increased from 30 to 35 percent (16 percent relative change in flow rate). Base flow as a proportion of total ditch flow increased from 25 to 35 percent (a 40-percent relative change). Peak ditch flow from storms decreased, ditch-flow recessions lengthened, and base flow from groundwater discharge increased, though only a small amount in some basins. These changes reduce the amount of ditch water leaving the study area, reducing flows that contribute to downstream flooding. Median surficial groundwater and ditch-water nitrate concentrations decreased by 79 and 53 percent, respectively. Median ditch-water suspended-sediment concentration decreased by 64 percent.
Neither the density of restorations nor the beneficial changes in hydrology were evenly distributed in the study area. The amount of hydrologic benefits within an individual ditch basin did not relate directly with the amount of restoration in that basin; however, the landscape characteristics that related most closely with hydrologic benefits were the area of a basin underlain by a surficial aquifer and the area of drained wetlands (indicating the potential for wetland restoration). In western Minnesota, the basins underlain by surficial aquifers that contain large areas of drained wetlands are the uplands of the Alexandria Moraine Complex and the beaches of glacial Lake Agassiz on the eastern side of the western one-third of Minnesota, north of Wilmar, Minnesota. These findings provide resource managers with information that can help focus restoration resources in areas where the greatest hydrologic benefits can be realized.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195041","collaboration":"Prepared in cooperation with the Minnesota Environment and Natural Resources Trust Fund, the U.S. Fish and Wildlife Service, and the Red Lake Watershed District","usgsCitation":"Cowdery, T.K., Christenson, C.A., and Ziegeweid, J.R., 2019, The hydrologic benefits of wetland and prairie restoration in western Minnesota—Lessons learned at the Glacial Ridge National Wildlife Refuge, 2002–15: U.S. Geological Survey Scientific Investigations Report 2019–5041, 81 p., https://doi.org/10.3133/sir20195041.","productDescription":"Report: ix, 81 p.; Data Release","numberOfPages":"96","onlineOnly":"Y","ipdsId":"IP-093837","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":366811,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5041/sir20195041.pdf","text":"Report","size":"7.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5041"},{"id":366812,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QRD7A3","text":"USGS data release ","linkHelpText":"A Soil-Water-Balance model and precipitation data used for HEC/HMS modelling at the Glacial Ridge National Wildlife Refuge area, northwestern Minnesota, 2002–15"},{"id":366810,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5041/coverthb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Glacial Ridge National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.52107238769531,\n 47.584399766577576\n ],\n [\n -96.12007141113281,\n 47.584399766577576\n ],\n [\n -96.12007141113281,\n 47.823298103444806\n ],\n [\n -96.52107238769531,\n 47.823298103444806\n ],\n [\n -96.52107238769531,\n 47.584399766577576\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN
The 2018 eruption of Kīlauea volcano, Hawai‘i, was its most effusive in over 200 years. We apply the airborne Glacier and Ice Surface Topography Interferometer (GLISTIN‐A) interferometric synthetic aperture radar (InSAR) instrument to measure topographic change associated with the eruption. The GLISTIN‐A radar flew in response to the eruption, acquiring observations of Kīlauea on seven days between May 18 and September 15, 2018. Topography differences were computed relative to GLISTIN‐A observations in 2017. Bare‐earth topography and off‐shore bathymetry were used to correct for vegetation and creation of new coastal land within the Lower East Rift Zone (LERZ) lava flow field. We estimate that the LERZ subaerial flows total bulk volume is 0.593 ± 0.011 km3 and that the summit collapse volume is ‐0.836 ± 0.002 km3. Within the temporal sampling and uncertainty from submarine flow volumes, we find that both the LERZ and caldera volume changes were approximately linear.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL083501","usgsCitation":"Lundgren, P.R., Bagnardi, M., and Dietterich, H., 2019, Topographic changes during the 2018 Kīlauea eruption from Single-pass Airborne InSAR: Geophysical Research Letters, v. 46, no. 16, p. 9554-9562, https://doi.org/10.1029/2019GL083501.","productDescription":"9 p.","startPage":"9554","endPage":"9562","ipdsId":"IP-109727","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":499832,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/9809feb9307f47abbabb80b6bb69da82","text":"External Repository"},{"id":366860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.53070068359375,\n 19.189271694646738\n ],\n [\n -155.0994873046875,\n 19.189271694646738\n ],\n [\n -155.0994873046875,\n 19.540378338405763\n ],\n [\n -155.53070068359375,\n 19.540378338405763\n ],\n [\n -155.53070068359375,\n 19.189271694646738\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"16","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Lundgren, Paul R","contributorId":218338,"corporation":false,"usgs":false,"family":"Lundgren","given":"Paul","email":"","middleInitial":"R","affiliations":[{"id":39807,"text":"NASA Jet Propulsion Lab","active":true,"usgs":false}],"preferred":false,"id":769038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagnardi, Marco","contributorId":124560,"corporation":false,"usgs":false,"family":"Bagnardi","given":"Marco","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":769039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":769037,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204869,"text":"70204869 - 2019 - Case study: Thomas Fire","interactions":[],"lastModifiedDate":"2019-08-21T09:43:57","indexId":"70204869","displayToPublicDate":"2019-08-21T09:42:43","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Case study: Thomas Fire","docAbstract":"No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"California's Fourth Climate Change Assessment","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"State of California Energy Commission","usgsCitation":"Kreitler, J.R., East, A.E., Sankey, J.B., and Tague, C., 2019, Case study: Thomas Fire, 6 p.","productDescription":"6 p.","startPage":"79","endPage":"84","ipdsId":"IP-096159","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":366778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366768,"type":{"id":15,"text":"Index Page"},"url":"https://www.energy.ca.gov/sites/default/files/2019-07/Reg%20Report-%20SUM-CCCA4-2018-006%20CentralCoast.pdf"}],"country":"United States","state":"California","county":"Ventura County","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":768812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":768814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tague, Christina (Naomi)","contributorId":207524,"corporation":false,"usgs":false,"family":"Tague","given":"Christina (Naomi)","affiliations":[{"id":37552,"text":"Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":768815,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204870,"text":"70204870 - 2019 - A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent","interactions":[],"lastModifiedDate":"2019-08-26T09:30:13","indexId":"70204870","displayToPublicDate":"2019-08-21T09:33:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent","docAbstract":"Harmful algal blooms (HABs) have been increasing in intensity across many waterbodies worldwide, including the western basin of Lake Erie. Substantial efforts have been made to track these blooms using in situ sampling and remote sensing. However, such measurements do not fully capture HAB spatial and temporal dynamics due to the limitations of discrete shipboard sampling over large areas and the effects of clouds and winds on remote sensing estimates. To address these limitations, we develop a space-time geostatistical modeling framework to improve estimates of HAB timing, extent, and intensity using five independent sets of chlorophyll a (chl-a) data sampled from June to October, 2008 to 2017. Based on the Bayesian information criterion for model selection, trend variables explain bloom northerly and easterly expansion from Maumee Bay, wind effects over depth, and variability among sampling methods. Cross validation results indicate the model can estimate daily, location-specific chl-a concentrations with reasonable accuracy (R2 = 55%) between monitoring cruises. Conditional simulations provide probabilistic estimates of algal biomass and surface areal extent, which are compared to remote sensing estimates. The simulations also provide, for the first time, comprehensive estimates of overall bloom biomass based on depth-integrated concentrations, with quantified uncertainties. These estimates enhance our understanding of HAB variability and can inform HAB monitoring network design, predictive modeling, and management.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.133776","usgsCitation":"Fang, S., Giudice, D.D., Scavia, D., Binding, C.E., Bridgeman, T.B., Chaffin, J.D., Evans, M.A., Guinness, J., Johengen, T.H., and Obenour, D.R., 2019, A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent: Science of the Total Environment, v. 695, 133776, 12 p., https://doi.org/10.1016/j.scitotenv.2019.133776.","productDescription":"133776, 12 p.","ipdsId":"IP-107890","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467354,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.133776","text":"Publisher Index 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2016–17","interactions":[],"lastModifiedDate":"2024-03-04T19:35:54.980435","indexId":"ofr20191064","displayToPublicDate":"2019-08-20T15:30:00","publicationYear":"2019","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":"2019-1064","displayTitle":"Molecular Identification of Fecal Contamination in the Elks Run Watershed, Jefferson County, West Virginia, 2016–17","title":"Molecular identification of fecal contamination in the Elks Run Watershed, Jefferson County, West Virginia, 2016–17","docAbstract":"The U.S. Geological Survey conducted a study using modern methods of molecular analysis aimed at attempting to identify the source(s) of fecal contamination that had been identified in previous studies conducted by the West Virginia Conservation Agency in the Elk Run watershed, Jefferson County, West Virginia. Water samples from multiple sites showing elevated fecal coliform counts were analyzed using molecular markers associated with general mammalian fecal contamination (AllBac), human Bacteroides (HF183), bovine Bacteroides (BoBac), and human polyomavirus (HPyV). Samples were also analyzed by quantitative polymerase chain reaction (qPCR) for human and bovine cytochrome b (mitochondrial DNA marker). A headwater site (Elk Branch at Shenandoah Junction) was found to be severely affected by both human and bovine contamination in May 2017. Although many of the molecular marker levels as well as Escherichia coli numbers had declined by a repeat sampling in June 2017, total coliform bacterial numbers remained high. Examination of the data indicated that this site had probably been affected by two separate contamination events, an influx of bovine contamination close to the time of the May sampling and a human contamination event that had occurred earlier. Samples from all sites contained bovine mitochondrial DNA, whereas only one revealed relatively high levels of human mitochondrial DNA. The Elk Run watershed appears to be widely affected by bovine influences with human influence episodically playing a role. Surface runoff caused by rain events exacerbates both.
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Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430