Montane fens are biologically diverse peat-forming wetlands that develop at points of groundwater discharge. To protect these ecosystems, it is critical to understand their locations on the landscape and the hydrogeologic systems that support them. The upper Deschutes Basin has a groundwater flow system that supports baseflow in many rivers, but little is known about the wetland types and groundwater dependence of the thousands of wetlands within the watershed. In 292 randomly selected wetlands, we quantified landscape metrics thought useful for discriminating montane fens from non-peat-forming wetlands. We inspected these wetlands and classified 67 of them as fens. Of the landscape metrics, only geology reliably differentiated fens from other types of wetlands. Nearly all fens develop in low-permeability glacial till found at approximately 1400–1800 m in elevation, and are concentrated in areas mantled by pumice deposits that originated primarily from the eruption of Mt. Mazama approximately 7700 years BP. Stratigraphic and hydrologic factors indicate the fens are supplied by perched aquifers in glacial till, instead of the deeper regional aquifer system. Their hydrogeologic setting makes the fens highly vulnerable to expected changes to recharge associated with climate change, but not to groundwater pumping from the regional aquifer.
","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-015-0667-x","usgsCitation":"Aldous, A., Gannett, M.W., Keith, M., and O'Connor, J., 2015, Geologic and geomorphic controls on the occurrence of fens in the Oregon Cascades and implications for vulnerability and conservation: Wetlands, v. 35, no. 4, p. 757-767, https://doi.org/10.1007/s13157-015-0667-x.","productDescription":"11 p.","startPage":"757","endPage":"767","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057994","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":314922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Cascade Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.42663574218749,\n 44.33956524809713\n ],\n [\n -120.42663574218749,\n 44.64911632343077\n ],\n [\n -120.87158203125,\n 45.089035564831015\n ],\n [\n -121.4208984375,\n 45.02695045318546\n ],\n [\n -121.7340087890625,\n 44.92591837128869\n ],\n [\n -121.761474609375,\n 44.31205742666618\n ],\n [\n -121.81640624999999,\n 43.92559366355069\n ],\n [\n -121.89331054687499,\n 43.492782808225\n ],\n [\n -121.34948730468749,\n 43.30119623257966\n ],\n [\n -120.7452392578125,\n 43.50075243569041\n ],\n [\n -120.5419921875,\n 43.96119063892024\n ],\n [\n -120.42663574218749,\n 44.33956524809713\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-13","publicationStatus":"PW","scienceBaseUri":"56a9f844e4b012c193aa3eca","contributors":{"authors":[{"text":"Aldous, A.","contributorId":105517,"corporation":false,"usgs":true,"family":"Aldous","given":"A.","email":"","affiliations":[],"preferred":false,"id":589937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keith, Mackenzie K. mkeith@usgs.gov","contributorId":4140,"corporation":false,"usgs":true,"family":"Keith","given":"Mackenzie K.","email":"mkeith@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":589938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O'Connor, James E. oconnor@usgs.gov","contributorId":138998,"corporation":false,"usgs":true,"family":"O'Connor","given":"James E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":589939,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70144268,"text":"sir20155025 - 2015 - Physical characteristics and fish assemblage composition at site and mesohabitat scales over a range of streamflows in the Middle Rio Grande, New Mexico, winter 2011-12, summer 2012","interactions":[],"lastModifiedDate":"2016-08-05T12:01:51","indexId":"sir20155025","displayToPublicDate":"2015-06-12T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5025","title":"Physical characteristics and fish assemblage composition at site and mesohabitat scales over a range of streamflows in the Middle Rio Grande, New Mexico, winter 2011-12, summer 2012","docAbstract":"In winter 2011–12 and summer 2012, the U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, Albuquerque District and the U.S. Fish and Wildlife Service New Mexico Fish and Wildlife Conservation Office in Albuquerque, New Mexico, evaluated the physical characteristics and fish assemblage composition of available mesohabitats over a range of streamflows at 15 sites on the Middle Rio Grande in New Mexico. The fish assemblage of the Middle Rio Grande includes several minnow species adapted to hydrologically variable but seasonably predictable rivers, including theHybognathus amarus (Rio Grande silvery minnow), a federally listed endangered species. Gaining a better understanding of habitat usage by the Rio Grande silvery minnow was the impetus for studying physical characteristics and fish assemblages in the Middle Rio Grande during different streamflow conditions. Data were collected at all 15 sites during winter 2011–12 (moderate streamflow), and a subset was collected at the 13 most downstream sites in summer 2012 (low streamflow). Sites were grouped into four river reaches separated by diversion dams listed in downstream order (names of the diversion dams are followed by short names of the sites nearest each dam in parentheses, listed in downstream order): (1) Cochiti (Peña Blanca), (2) Angostura (Bernalillo, La Orilla, Barelas, Los Padillas), (3) Isleta (Los Lunas I, Los Lunas II, Abeytas, La Joya, Rio Salado), and (4) San Acacia (Lemitar, Arroyo del Tajo, San Pedro, Bosque del Apache I, and Bosque del Apache II). Stream habitat was mapped in the field by using a geographic information system in conjunction with a Global Positioning System. Fish assemblage composition was determined during both streamflow regimes, and fish were collected by seining in each mesohabitat where physical characteristic data (depth, velocity, dominant substrate type and size, and percent embeddedness) and water-quality properties (temperature, dissolved oxygen, specific conductance, and pH; during summer 2012 only) were measured.
\nNineteen species of fish were collected among the 15 sites and four reaches over both sampling periods; 10 of these 19 species are introduced. Fish-species richness (total number of fish species collected at each site during each sampling event) among sites that were sampled during both sampling periods ranged from 6 at Rio Salado to 12 at La Orilla. Fish were most abundant at the Lemitar site (1,786 individuals) and least abundant at the San Pedro site (275 individuals). The native Cyprinella lutrensis (red shiner) was the most abundant species collected among all of the sites, accounting for about 42 percent of fish collected. Fish-species richness and catch per unit effort (CPUE) were higher (or equivalent) at all sites during summer 2012 compared to winter 2011–12.
\nThe relations between fish assemblage composition (that is, total abundance, which refers to the number of individuals of each species that were collected) and selected environmental variables (physical characteristic data collected at the mesohabitat scale [depth, velocity, and substrate particle size], and mesohabitat types) were explored by using canonical correspondence analysis. Environmental variables explained 8 percent (p=0.48) of the variability in the Middle Rio Grande fish assemblage during winter 2011–12, and Rio Grande silvery minnow were weakly associated with sand substrates, relatively moderate velocities (qualitative descriptors are derived from synthetic gradients extracted from CCAs), and relatively shallow depths. Environmental variables explained 14 percent (p < 0.01) of the variability in the Middle Rio Grande fish assemblage during summer 2012, when Rio Grande silvery minnow were associated with run mesohabitats, relatively high velocities, sand substrates, and relatively moderate depths.
\nThe mean fish-species richness was greater in summer 2012 than in winter 2011–12 for each mesohabitat type, and the overall fish-species richness across all mesohabitat types was 0.62 during winter 2011–12, compared to 1.49 during summer 2012. The highest mean CPUE during winter 2011–12 was in isolated pools (54.3 fish per 100 square meters [m2]), whereas the lowest was in flats (18.9 fish per 100 m2). Ranges in CPUE were higher in summer 2012 relative to winter 2011–12 in each mesohabitat type sampled. As in winter 2011–12, the highest mean CPUE during summer 2012 was in isolated pools (233 fish per 100 m2), whereas the lowest was in flats (29.6 fish per 100 m2). Overall mean CPUE per mesohabitat across all mesohabitat types was 29.1 fish per 100 m2 during winter 2011–12 compared to 85.3 fish per 100 m2 during summer 2012.
\nFour species of minnows (red shiner, Rio Grande silvery minnow, Pimephales promelas [fathead minnow], and Platygobio gracilis[flathead chub]) were selected to compare preferred mesohabitat characteristics because all are small-bodied minnows and because more than 200 individuals of each of these species were collected. Red shiner were collected across the largest range of depths in both winter 2011–12 (0.02–4.31 feet [ft]) and summer 2012 (0.05–3.4 ft), as well as the largest range of velocities (0.0–4.31 feet per second [ft/s]) during winter 2011–12 among the four minnow species of interest. Rio Grande silvery minnow occurred in the narrowest range of depths (0.30–2.1 ft) during summer 2012, as well as the narrowest range of velocities in both winter 2011–12 (0.0–3.18 ft/s) and summer 2012 (0.02–1.51 ft/s).
\nWater-quality properties were only collected during summer 2012, when low-streamflow conditions existed and water-quality properties were thought to be potentially most limiting to aquatic life. Area-weighted mean water temperatures tended to be higher at the sites that were sampled in August 2012 (25.57 degrees Celsius [°C]) compared to June 2012 (24.61 °C). The highest area-weighted mean water temperature at a given site (29.03 °C) was measured at the Lemitar site on August 7, 2012, coincident with the lowest measured discharge (4.13 cubic feet per second [ft3/s]). Area-weighted mean dissolved oxygen concentrations tended to be lower in August (7.46 milligrams per liter [mg/L]) compared to June (8.33 mg/L). The highest area-weighted mean dissolved oxygen concentration (9.13 mg/L) was measured at the Lemitar site on August 7, 2012, and the lowest area-weighted mean dissolved oxygen concentration (6.23 mg/L) was measured at the Los Padillas site on August 10, 2012. Area-weighted specific conductance in the sites upstream from La Joya did not exceed 400 microsiemens per centimeter (μS/cm) at 25 °C, whereas the area-weighted mean specific conductance at La Joya (837 μs/cm at 25 °C), Rio Salado (857 μs/cm at 25 °C), and Lemitar (1,300 μs/cm at 25 °C) were all well above the average of the area-weighted means for the 10 remaining sites (433 μs/cm at 25 °C). Lower area-weighted mean pH values were measured at the 3 sites in and near Albuquerque (La Orilla, Barelas, and Los Padillas—7.98, 8.08, and 7.81, respectively) compared to any of the 10 remaining sites, which had an overall mean pH of 8.44.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155025","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Albuquerque District, and the U.S. Fish and Wildlife Service","usgsCitation":"Braun, C.L., Pearson, D., Porter, M., and Moring, J.B., 2015, Physical characteristics and fish assemblage composition at site and mesohabitat scales over a range of streamflows in the Middle Rio Grande, New Mexico, winter 2011-12, summer 2012: U.S. Geological Survey Scientific Investigations Report 2015-5025, Report: viii, 90 p.; Downloads Directory, https://doi.org/10.3133/sir20155025.","productDescription":"Report: viii, 90 p.; Downloads Directory","startPage":"90","numberOfPages":"102","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-056792","costCenters":[{"id":583,"text":"Texas Water Science 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dpearson@usgs.gov","contributorId":1525,"corporation":false,"usgs":true,"family":"Pearson","given":"Daniel K.","email":"dpearson@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":548602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Porter, Michael D.","contributorId":139912,"corporation":false,"usgs":false,"family":"Porter","given":"Michael D.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":548604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moring, J. Bruce","contributorId":139911,"corporation":false,"usgs":false,"family":"Moring","given":"J.","email":"","middleInitial":"Bruce","affiliations":[{"id":13311,"text":"Plateau Land and Wildlife Mgmt.","active":true,"usgs":false}],"preferred":false,"id":548603,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148417,"text":"ofr20151111 - 2015 - First steps of integrated spatial modeling of titanium, zirconium, and rare earth element resources within the Coastal Plain sediments of the southeastern United States","interactions":[],"lastModifiedDate":"2015-06-12T09:37:02","indexId":"ofr20151111","displayToPublicDate":"2015-06-12T08:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1111","title":"First steps of integrated spatial modeling of titanium, zirconium, and rare earth element resources within the Coastal Plain sediments of the southeastern United States","docAbstract":"The Coastal Plain of the southeastern United States has extensive, unconsolidated sedimentary deposits that are enriched in heavy minerals containing titanium, zirconium, and rare earth element resources. Areas favorable for exploration and development of these resources are being identified by geochemical data, which are supplemented with geological, geophysical, hydrological, and geographical data. The first steps of this analysis have been completed. The concentrations of lanthanum, yttrium, and titanium tend to decrease as distance from the Piedmont (which is the likely source of these resources) increases and are moderately correlated with airborne measurements of equivalent thorium concentration. The concentrations of lanthanum, yttrium, and titanium are relatively high in those watersheds that adjoin the Piedmont, south of the Cape Fear Arch. Although this relation suggests that the concentrations are related to the watersheds, it may be simply an independent regional trend. The concentration of zirconium is unrelated to the distance from the Piedmont, the equivalent thorium concentration, and the watershed. These findings establish a foundation for more sophisticated analyses using integrated spatial modeling.
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Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":548597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budahn, James R. 0000-0001-9794-8882 jbudahn@usgs.gov","orcid":"https://orcid.org/0000-0001-9794-8882","contributorId":1175,"corporation":false,"usgs":true,"family":"Budahn","given":"James","email":"jbudahn@usgs.gov","middleInitial":"R.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Steven M. 0000-0003-3591-5377 smsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-3591-5377","contributorId":1460,"corporation":false,"usgs":true,"family":"Smith","given":"Steven","email":"smsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548599,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":548600,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148457,"text":"sir20155065 - 2015 - Dam failure analysis for the Lago de Matrullas Dam, Orocovis, Puerto Rico","interactions":[],"lastModifiedDate":"2015-06-12T08:41:07","indexId":"sir20155065","displayToPublicDate":"2015-06-12T08:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5065","title":"Dam failure analysis for the Lago de Matrullas Dam, Orocovis, Puerto Rico","docAbstract":"The U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, completed a hydrologic and hydraulic study to assess the potential hazard to human life and property associated with the hypothetical failure of the Lago de Matrullas Dam, located within the headwaters of the Río Grande de Manatí. The hydrologic study yielded outflow hydrographs and peak discharges for Lago de Matrullas and other subbasins in the Río Grande de Manatí hydrographic basin for three extreme rainfall events: (1) a 6-hour probable maximum precipitation (PMP) event, (2) a 24-hour PMP event, and (3) a 100-year-recurrence, 24-hour rainfall event. The hydraulic study simulated the hypothetical dam failure of Lago de Matrullas using hypothetical flood hydrographs generated from the hydrologic study and selected dam breach parameters. The flood wave resulting from the failure was downstream-routed through the lower reaches of the Río Matrullas, the Río Toro Negro, and the Río Grande de Manatí for determination of water-surface profiles developed from the event-based hydrologic scenarios and “sunny day” (no precipitation) conditions. The Hydrologic Modeling System (HEC–HMS) and the River Analysis System (HEC–RAS) computer programs, developed by the Hydrologic Engineering Center (HEC) of the U.S. Army Corps of Engineers, were used for the hydrologic and hydraulic modeling, respectively. The flow routing in the hydraulic analyses was performed using the unsteady-state flow module available in the HEC–RAS model.
\nAt the Lago de Matrullas Dam, inflow peak discharges of about 1,104 and 1,032 cubic meters per second (m3/s) were estimated with HEC–HMS for the 6- and 24-hour PMP events, respectively. The 100-year recurrence, 24-hour rainfall event simulation resulted in a peak discharge of about 418 m3/s. For the hydrologic analysis, no dam failure conditions were considered with the model. The results of the hydrologic simulations indicated, however, that the dam would be overtopped by the simulated 6- and 24-hour PMP events. Unlike the 6- and 24-hour PMP events, no overtopping was observed during the simulated 100-year recurrence, 24-hour rainfall event.
\nFor the dam-breach hydraulic analysis, the hypothetical failures of the Lago de Matrullas Dam included two possible failure modes: overtopping and piping. Overtopping failure was evaluated in this study for the 6- and 24- hour probable-maximum-precipitation breach scenarios. Piping dam failure was simulated for sunny day conditions and for the 100-year-recurrence, 24-hour rainfall scenario.
\nResults from the simulated dam failure of the Lago de Matrullas Dam using the HEC–RAS model for the 6- and 24-hour PMP events showed peak discharges at the dam of 3,149.33 and 3,604.70 m3/s, respectively. Dam failure during the 100-year-recurrence, 24-hour rainfall event resulted in a peak discharge of 2,103.12 m3/s directly downstream from the dam. Dam failure under sunny day conditions produced a peak discharge of 1,695.91 m3/s at the dam assuming the antecedent lake level was at the morning-glory spillway invert elevation. Flood-inundation maps prepared as part of the study depict the flood extent and provide valuable information for preparing an Emergency Action Plan. Results of the failure analysis indicate that a failure of the Lago de Matrullas Dam could cause flooding to many of the inhabited areas along stream banks from the Lago de Matrullas Dam to the mouth of the Río Grande de Manatí. Among the areas most affected are the low-lying regions in the vicinity of the towns of Ciales, Manatí, and Barceloneta. The delineation of the flood boundaries near the town of Barceloneta considered the effects of a levee constructed during 2000 at Barceloneta in the flood plain of the Río Grande de Manatí to provide protection against flooding to the near-by low-lying populated areas. The results showed overtopping can be expected in the aforementioned levee during 6- and 24-hour probable-maximum-precipitation dam failure scenarios. No overtopping of the levee was simulated, however, during dam failure scenarios under the 100-year recurrence, 24-hour rainfall event or sunny day conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155065","collaboration":"Prepared in cooperation with the Puerto Rico Electric Power Authority","usgsCitation":"Torres-Sierra, H., and Gómez-Fragoso, J., 2015, Dam failure analysis for the Lago de Matrullas Dam, Orocovis, Puerto Rico: U.S. Geological Survey Scientific Investigations Report 2015-5065, Report: viii, 54 p.; 4 Plates: 30.0 x 35.0 inches, https://doi.org/10.3133/sir20155065.","productDescription":"Report: viii, 54 p.; 4 Plates: 30.0 x 35.0 inches","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-023008","costCenters":[{"id":156,"text":"Caribbean Water Science 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water flow and retention in an unsaturated fracture-facial domain","docAbstract":"Hydrologically significant flow and storage of water occur in macropores and fractures that are only partially filled. To accommodate such processes in flow models, we propose a three-domain framework. Two of the domains correspond to water flow and water storage in a fracture-facial region, in addition to the third domain of matrix water. The fracture-facial region, typically within a fraction of a millimeter of the fracture wall, includes a flowing phase whose fullness is determined by the availability and flux of preferentially flowing water, and a static storage portion whose fullness is determined by the local matric potential. The flow domain can be modeled with the source-responsive preferential flow model, and the roughness-storage domain can be modeled with capillary relations applied on the fracture-facial area. The matrix domain is treated using traditional unsaturated flow theory. We tested the model with application to the hydrology of the Chalk formation in southern England, coherently linking hydrologic information including recharge estimates, streamflow, water table fluctuation, imaging by electron microscopy, and surface roughness. The quantitative consistency of the three-domain matrix-microcavity-film model with this body of diverse data supports the hypothesized distinctions and active mechanisms of the three domains and establishes the usefulness of this framework.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fluid dynamics in complex fractured-porous systems","language":"English","publisher":"Wiley","doi":"10.1002/9781118877517.ch12","usgsCitation":"Nimmo, J.R., and Malek-Mohammadi, S., 2015, Quantifying water flow and retention in an unsaturated fracture-facial domain, chap. of Fluid dynamics in complex fractured-porous systems, p. 169-182, https://doi.org/10.1002/9781118877517.ch12.","productDescription":"14 p.","startPage":"169","endPage":"182","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054366","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":324559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-12","publicationStatus":"PW","scienceBaseUri":"57739fb5e4b07657d1a90d33","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":580104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malek-Mohammadi, Siamak","contributorId":149944,"corporation":false,"usgs":false,"family":"Malek-Mohammadi","given":"Siamak","email":"","affiliations":[{"id":17862,"text":"Bradley University","active":true,"usgs":false}],"preferred":false,"id":580105,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155002,"text":"70155002 - 2015 - Organic carbon burial in lakes and reservoirs of the conterminous United States","interactions":[],"lastModifiedDate":"2018-08-09T12:49:27","indexId":"70155002","displayToPublicDate":"2015-06-10T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Organic carbon burial in lakes and reservoirs of the conterminous United States","docAbstract":"Organic carbon (OC) burial in lacustrine sediments represents an important sink in the global carbon cycle; however, large-scale OC burial rates are poorly constrained, primarily because of the sparseness of available data sets. Here we present an analysis of OC burial rates in water bodies of the conterminous U.S. (CONUS) that takes advantage of recently developed national-scale data sets on reservoir sedimentation rates, sediment OC concentrations, lake OC burial rates, and water body distributions. We relate these data to basin characteristics and land use in a geostatistical analysis to develop an empirical model of OC burial in water bodies of the CONUS. Our results indicate that CONUS water bodies sequester 20.8 (95% CI: 9.4–65.8) Tg C yr–1, and spatial patterns in OC burial are strongly influenced by water body type, size, and abundance; land use; and soil and vegetation characteristics in surrounding areas. Carbon burial is greatest in the central and southeastern regions of the CONUS, where cultivation and an abundance of small water bodies enhance accumulation of sediment and OC in aquatic environments.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b00373","usgsCitation":"Clow, D.W., Stackpoole, S.M., Verdin, K.L., Butman, D.E., Zhu, Z., Krabbenhoft, D.P., and Striegl, R.G., 2015, Organic carbon burial in lakes and reservoirs of the conterminous United States: Environmental Science & Technology, v. 49, no. 13, p. 7614-7622, https://doi.org/10.1021/acs.est.5b00373.","productDescription":"9 p.","startPage":"7614","endPage":"7622","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064948","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":305957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n","volume":"49","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-22","publicationStatus":"PW","scienceBaseUri":"55b361b5e4b09a3b01b5dab1","chorus":{"doi":"10.1021/acs.est.5b00373","url":"http://dx.doi.org/10.1021/acs.est.5b00373","publisher":"American Chemical Society (ACS)","authors":"Clow David W., Stackpoole Sarah M., Verdin Kristine L., Butman David E., Zhu Zhiliang, Krabbenhoft David P., Striegl Robert G.","journalName":"Environmental Science & Technology","publicationDate":"7/7/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stackpoole, Sarah M. 0000-0002-5876-4922 sstackpoole@usgs.gov","orcid":"https://orcid.org/0000-0002-5876-4922","contributorId":3784,"corporation":false,"usgs":true,"family":"Stackpoole","given":"Sarah","email":"sstackpoole@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":564538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butman, David E.","contributorId":145535,"corporation":false,"usgs":false,"family":"Butman","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":16142,"text":"School of Environmental and Forest Sciences & Environmental Engineering, University of Washington, Seattle","active":true,"usgs":false}],"preferred":false,"id":564540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhu, Zhi-Liang zzhu@usgs.gov","contributorId":3636,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhi-Liang","email":"zzhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":564541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":564542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":564543,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189621,"text":"70189621 - 2015 - Surface monitoring of microseismicity at the Decatur, Illinois, CO2 sequestration demonstration site","interactions":[],"lastModifiedDate":"2019-06-03T13:25:10","indexId":"70189621","displayToPublicDate":"2015-06-10T00:00:00","publicationYear":"2015","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":"Surface monitoring of microseismicity at the Decatur, Illinois, CO2 sequestration demonstration site","docAbstract":"Sequestration of CO2 into subsurface reservoirs can play an important role in limiting future emission of CO2 into the atmosphere (e.g., Benson and Cole, 2008). For geologic sequestration to become a viable option to reduce greenhouse gas emissions, large-volume injection of supercritical CO2 into deep sedimentary formations is required. These formations offer large pore volumes and good pore connectivity and are abundant (Bachu, 2003; U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team, 2013). However, hazards associated with injection of CO2 into deep formations require evaluation before widespread sequestration can be adopted safely (Zoback and Gorelick, 2012). One of these hazards is the potential to induce seismicity on pre-existing faults or fractures. If these faults or fractures are large and critically stressed, seismic events can occur with magnitudes large enough to pose a hazard to surface installations and, possibly more critical, the seal integrity of the cap rock.
The Decatur, Illinois, carbon capture and storage (CCS) demonstration site is the first, and to date, only CCS project in the United States that injects a large volume of supercritical CO2 into a regionally extensive, undisturbed saline formation. The first phase of the Decatur CCS project was completed in November 2014 after injecting a million metric tons of supercritical CO2 over three years. This phase was led by the Illinois State Geological Survey (ISGS) and included seismic monitoring using deep borehole sensors, with a few sensors installed within the injection horizon. Although the deep borehole network provides a more comprehensive seismic catalog than is presented in this paper, these deep data are not publicly available. We contend that for monitoring induced microseismicity as a possible seismic hazard and to elucidate the general patterns of microseismicity, the U.S. Geological Survey (USGS) surface and shallow borehole network described below provides an adequate event detection threshold.
The formation targeted for injection is the Mount Simon Sandstone, which is laterally extensive, has high porosity and permeability and has the potential to host future CCS projects due to its favorable hydrologic characteristics and proximity to industrial sources of CO2 (Birkholzer and Zhou, 2009). At Decatur, CO2, a byproduct of ethanol production at the Archer Daniels Midland (ADM) facility, is compressed to supercritical state and injected at 2.1 km depth into the 460 m thick Mount Simon Sandstone. This sandstone has varying properties, ranging from the lower, fine- to coarse-grained sandstone with high permeability and porosity, to the middle and upper Mount Simon, which consist of planar, cross-bedded layers of varied permeability and porosity (Leetaru and Freiburg, 2014). The changes in permeability and porosity within the Mount Simon Sandstone, due to depositional and diagenetic differences, create horizontal baffles, which inhibit vertical flow and restrict the injected CO2 to remain near the injection horizon (Bowen et al., 2011). The lowest portion of the Mount Simon Sandstone overlying the Precambrian rhyolite basement is the Pre-Mount Simon interval, generally < 15 m in thickness and composed of fine- to medium-grain size sandstone that is highly deformed (Leetaru and Freiburg, 2014). The basement rhyolite has a clayrich matrix and is fractured, with significant alterations within the fractures. The primary sealing cap rock is the Eau Claire Formation, a 100–150 m thick unit at a depth of roughly 1.69 km (Leetaru and Freiburg, 2014). The Maquoketa Shale Group and the New Albany Shale serve as secondary and tertiary seals at shallower depths of ∼820 and ∼650 m, respectively.
The ISGS managed the Illinois Basin–Decatur Project (IBDP), a three-year project beginning in November 2011, during which carbon dioxide was injected at a rate of ∼1000 metric tons per day until November 2014 (Finley et al., 2011, 2013). ADM manages the Illinois Industrial CCS (ICCS) project, which will inject ∼3000 metric tons/day into a second injection well starting in the summer of 2015.
The USGS began monitoring microseismicity with a 13- station seismic network at Decatur in July 2013 (Fig. 1). This network provides good detection capabilities and azimuthal (focal sphere) coverage for microseismicity with moment magnitudes (Mw) above about −0:5. Here, we report on 19 months of microseismicity monitoring at the Decatur CO2 sequestration site, which permits a detailed look at the evolution and character of injection-induced seismicity.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220150062","usgsCitation":"Kaven, J., Hickman, S.H., McGarr, A.F., and Ellsworth, W.L., 2015, Surface monitoring of microseismicity at the Decatur, Illinois, CO2 sequestration demonstration site: Seismological Research Letters, v. 86, no. 4, p. 1096-1101, https://doi.org/10.1785/0220150062.","productDescription":"6 p. ","startPage":"1096","endPage":"1101","ipdsId":"IP-064149","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","city":"Decatur","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.09088134765625,\n 39.706130149279325\n ],\n [\n -88.78326416015625,\n 39.706130149279325\n ],\n [\n -88.78326416015625,\n 39.9634381223102\n ],\n [\n -89.09088134765625,\n 39.9634381223102\n ],\n [\n -89.09088134765625,\n 39.706130149279325\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-10","publicationStatus":"PW","scienceBaseUri":"59706fb9e4b0d1f9f065a8c5","contributors":{"authors":[{"text":"Kaven, J. Ole 0000-0003-2625-2786 okaven@usgs.gov","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":3993,"corporation":false,"usgs":true,"family":"Kaven","given":"J. Ole","email":"okaven@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":705467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellsworth, William L. ellsworth@usgs.gov","contributorId":787,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William","email":"ellsworth@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148471,"text":"sir20155045 - 2015 - Hydrologic model of the Modesto Region, California, 1960-2004","interactions":[],"lastModifiedDate":"2015-06-09T08:50:49","indexId":"sir20155045","displayToPublicDate":"2015-06-09T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5045","title":"Hydrologic model of the Modesto Region, California, 1960-2004","docAbstract":"Strategies for managing water supplies and groundwater quality in the Modesto region of the eastern San Joaquin Valley, California, are being formulated and evaluated by the Stanislaus and Tuolumne Rivers Groundwater Basin Association. Management issues and goals in the basin include an area in the lower part of the basin that requires drainage of the shallow water table to sustain agriculture, intra- and inter-basin migration of poor-quality groundwater, and efficient management of surface and groundwater supplies. To aid in the evaluation of water-management strategies, the U.S. Geological Survey and the Stanislaus and Tuolumne Rivers Groundwater Basin Association have developed a hydrologic model that simulates monthly groundwater and surface-water flow as governed by aquifer-system properties, annual and seasonal variations in climate, surface-water flow and availability, water use, and land use. The model was constructed by using the U.S. Geological Survey groundwater-modeling software MODFLOW-OWHM with the Farm Process.
\nAvailable measurements of groundwater pumped for municipal, irrigation, and drainage purposes are specified in the model, as are deliveries of surface water. Private irrigation pumping and recharge associated with agricultural land use were estimated by using the Farm Process in MODFLOW-OWHM, which simulates landscape processes associated with irrigated agriculture and other land uses. The distribution of hydraulic conductivity in the aquifer system was constrained by using data from more than 3,500 drillers' logs. The model was calibrated to 4,061 measured groundwater levels in 109 wells and 2,739 mean monthly surface-water flows measured at 6 streamgages during 1960-2004 by using a semi-automated method of parameter estimation.
\nThe model fit to groundwater levels was good, with an absolute mean residual of 0.8 feet; 74 percent of simulated heads were within 10 feet of those observed. The model fit to streamflow was biased low, but reasonable overall; the absolute mean residual of streamflow was 780 cubic feet per second, and 68 percent of simulated streamflows were within 500 cubic feet per second of observed. Hydrographs both of groundwater levels and streamflow indicated overall an acceptable fit to observed trends.
\nSimulated private agricultural pumpage ranged from about 780,000 to 1,380,000 acre-feet per year and averaged about 1,000,000 acre-feet per year from 1960 to 2004. Simulated deep percolation, or groundwater recharge from precipitation and irrigation, varied with climate and land use from about 1,100,000 to 1,700,000 acre-feet per year, averaging 1,360,000 acre-feet per year. Key limitations of the model with respect to estimating these large components of the water budget are the uncertainty associated with actual irrigation deliveries and irrigation efficiencies and the lack of metered data for private agricultural groundwater pumping. Different assumptions with respect to irrigation deliveries and efficiencies, and other model input, would result in different estimates of private agricultural groundwater use.
\nThe simulated exchange between groundwater and surface water was a small percentage of streamflow, typically ranging within a loss or gain of about 2 cubic feet per second per mile. The simulated exchange compared reasonably with limited independent estimates available, but substantial uncertainty is associated with these estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155045","collaboration":"Prepared in cooperation with the Stanislaus and Tuolumne Rivers Groundwater Basin Association","usgsCitation":"Phillips, S.P., Rewis, D.L., and Traum, J.A., 2015, Hydrologic model of the Modesto Region, California, 1960-2004: U.S. Geological Survey Scientific Investigations Report 2015-5045, x, 69 p., https://doi.org/10.3133/sir20155045.","productDescription":"x, 69 p.","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-014014","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":301085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155045.jpg"},{"id":301082,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5045/"},{"id":301084,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5045/downloads/sir2015-5045_fig21supplement.xls","text":"Supplement to figure 21","size":"3.1 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5045 Supplement to figure 21"},{"id":301083,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5045/pdf/sir2015-5045.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5045 Report"}],"projection":"Albers equal area conic projection","datum":"North American Datum of 1983","country":"United States","state":"California","otherGeospatial":"Modesto","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.38381958007812,\n 37.56308554496544\n ],\n [\n -121.38381958007812,\n 37.565262680889965\n ],\n [\n -121.34948730468749,\n 37.565262680889965\n ],\n [\n -121.34948730468749,\n 37.56308554496544\n ],\n [\n -121.38381958007812,\n 37.56308554496544\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.33575439453126,\n 37.57505900514994\n ],\n [\n -120.838623046875,\n 37.9051994823157\n ],\n [\n -120.39093017578125,\n 37.470498470798724\n ],\n [\n -120.96633911132812,\n 37.11543110112874\n ],\n [\n -121.33575439453126,\n 37.57505900514994\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5578001de4b032353cbeb6b3","contributors":{"authors":[{"text":"Phillips, Steven P. 0000-0002-5107-868X sphillip@usgs.gov","orcid":"https://orcid.org/0000-0002-5107-868X","contributorId":1506,"corporation":false,"usgs":true,"family":"Phillips","given":"Steven","email":"sphillip@usgs.gov","middleInitial":"P.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rewis, Diane L. dlrewis@usgs.gov","contributorId":1511,"corporation":false,"usgs":true,"family":"Rewis","given":"Diane","email":"dlrewis@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548353,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70147788,"text":"ds933 - 2015 - Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico","interactions":[],"lastModifiedDate":"2015-06-05T12:48:35","indexId":"ds933","displayToPublicDate":"2015-06-05T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"933","title":"Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico","docAbstract":"In 2010, in cooperation with the Mining and Minerals Division (MMD) of the State of New Mexico Energy, Minerals and Natural Resources Department, the U.S. Geological Survey (USGS) initiated a 4-year assessment of hydrologic conditions at the San Juan coal mine (SJCM), located about 14 miles west-northwest of the city of Farmington, San Juan County, New Mexico. The mine produces coal for power generation at the adjacent San Juan Generating Station (SJGS) and stores coal-combustion byproducts from the SJGS in mined-out surface-mining pits. The purpose of the hydrologic assessment is to identify groundwater flow paths away from SJCM coal-combustion-byproduct storage sites that might allow metals that may be leached from coal-combustion byproducts to eventually reach wells or streams after regional dewatering ceases and groundwater recovers to predevelopment levels. The hydrologic assessment, undertaken between 2010 and 2013, included compilation of existing data. The purpose of this report is to present data that were acquired and compiled by the USGS for the SJCM hydrologic assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds933","collaboration":"Prepared in cooperation with the Mining and Minerals Division of the State of New Mexico Energy, Minerals and Natural Resources Department","usgsCitation":"Stewart, A.M., and Thomas, N., 2015, Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico: U.S. Geological Survey Data Series 933, HTML Document, https://doi.org/10.3133/ds933.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059091","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":301053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds933.jpg"},{"id":301051,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0933/"},{"id":301052,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0933/ds933.html","text":"Report","size":"19 KB","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"New Mexico","county":"San Juan County","otherGeospatial":"San Juan coal mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.24623107910156,\n 36.72402574695313\n ],\n [\n -108.19747924804688,\n 36.76584198280488\n ],\n [\n -108.18168640136719,\n 36.791140738852704\n ],\n [\n -108.18168640136719,\n 36.8037869853087\n ],\n [\n -108.15284729003906,\n 36.86039455866718\n ],\n [\n -108.1391143798828,\n 36.88401445049676\n ],\n [\n -108.13156127929686,\n 36.90762703795211\n ],\n [\n -108.13499450683594,\n 36.929036787414525\n ],\n [\n -108.16932678222656,\n 36.93836736111466\n ],\n [\n -108.20091247558592,\n 36.94001381436853\n ],\n [\n -108.22288513183594,\n 36.92848789456677\n ],\n [\n -108.24829101562499,\n 36.89499795802219\n ],\n [\n -108.26133728027344,\n 36.8631414329529\n ],\n [\n -108.28125,\n 36.83346996591306\n ],\n [\n -108.3306884765625,\n 36.82797398619907\n ],\n [\n -108.39317321777344,\n 36.832370801556834\n ],\n [\n -108.48518371582031,\n 36.79718920417815\n ],\n [\n -108.49067687988281,\n 36.74328605437939\n ],\n [\n -108.29498291015624,\n 36.72017310567465\n ],\n [\n -108.24623107910156,\n 36.72402574695313\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5572ba25e4b077dba76c1b90","contributors":{"authors":[{"text":"Stewart, Anne M. astewart@usgs.gov","contributorId":3938,"corporation":false,"usgs":true,"family":"Stewart","given":"Anne","email":"astewart@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Nicole nithomas@usgs.gov","contributorId":5649,"corporation":false,"usgs":true,"family":"Thomas","given":"Nicole","email":"nithomas@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548226,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70147914,"text":"sir20155056 - 2015 - Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014","interactions":[],"lastModifiedDate":"2015-06-03T14:00:29","indexId":"sir20155056","displayToPublicDate":"2015-06-03T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5056","title":"Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014","docAbstract":"From August 28 to 29, 2011, Tropical Storm Irene delivered rainfall ranging from about 4 inches to more than 7 inches in the White River Basin. The rainfall resulted in severe flooding throughout the basin and significant damage along the White River and Tweed River. In response to the flooding, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, conducted a new flood study to aid in the flood recovery and restoration. This flood study includes a 20.7-mile reach of the White River from the downstream end at about 2,000 feet downstream from the State Route 107 bridge in the Village of Bethel, Vermont, to the upstream end at about 1,000 feet upstream from the River Brook Drive bridge in the Village of Rochester, Vt., and a 7.9-mile reach of the Tweed River from its mouth in Stockbridge, Vt., to the confluence of the West and South Branches of the Tweed River and continuing upstream on the South Branch Tweed River to the Pittsfield, Vt., town line.
\nThis report presents water-surface elevations determined for the study reaches using the U.S. Army Corps of Engineers one-dimensional step-backwater Hydrologic Engineering Center River Analysis System model, also known as HEC– RAS. The water-surface elevations were determined for floods having a 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability (AEP) and for the floodway.
\nEighteen high-water marks from Tropical Storm Irene were available along the studied reaches. The discharges in the Tropical Storm Irene HEC–RAS model were adjusted so that the resulting water-surface elevations matched the high-water mark elevations along the study reaches. This allowed for an estimation of the water-surface profile throughout the study area resulting from Tropical Storm Irene. From a comparison of the estimated water-surface profile of Tropical Storm Irene to the water-surface profiles of the 1- and 0.2-percent AEP floods, it was determined that the high-water elevations resulting from Tropical Storm Irene exceeded the estimated 1-percent AEP flood throughout the White River and Tweed River study reaches and exceeded the estimated 0.2-percent AEP flood in 16.7 of the 28.6 study reach miles. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 18.2-centimeter vertical accuracy at the 95-percent confidence level and 1-meter horizontal resolution to delineate the area flooded for each water-surface profile.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155056","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2015, Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014: U.S. Geological Survey Scientific Investigations Report 2015-5056, Report: vi, 32 p.; Readme; Map file and datasets; Metadata, https://doi.org/10.3133/sir20155056.","productDescription":"Report: vi, 32 p.; Readme; Map file and datasets; Metadata","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-057993","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":301023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155056.jpg"},{"id":301018,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5056/"},{"id":301019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5056/pdf/sir2015-5056.pdf","text":"Report","size":"2.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301020,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_readme.txt","text":"Readme","size":"1.09 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Readme"},{"id":301021,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_map.zip","text":"Map file and datasets","size":"2.11 GB","linkFileType":{"id":6,"text":"zip"},"description":"Map file and datasets","linkHelpText":"Contains the published map file and the map dataset. For use with ArcReader, which is free and available at http://www.esri.com/software/argis/arcreader"},{"id":301022,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_metadata.zip","text":"Metadata","size":"162 KB","linkFileType":{"id":6,"text":"zip"},"description":"Metadata","linkHelpText":"The metadata for the map contents"}],"country":"United States","state":"Vermont","city":"Bethel, Pittsfield, Rochester, Stockbridge","otherGeospatial":"Tweed River, White River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.8122329711914,\n 43.88205730390537\n ],\n [\n -72.80502319335938,\n 43.88279966767229\n ],\n [\n -72.80261993408203,\n 43.877355451898595\n ],\n [\n -72.806396484375,\n 43.87017822557581\n ],\n [\n -72.80296325683594,\n 43.86151490472453\n ],\n [\n -72.79747009277344,\n 43.84938414031938\n ],\n [\n -72.78820037841797,\n 43.83650797709095\n ],\n [\n -72.7840805053711,\n 43.81991343882605\n ],\n [\n -72.77961730957031,\n 43.806287608590075\n ],\n [\n -72.76485443115234,\n 43.79984522482957\n ],\n [\n -72.74253845214844,\n 43.7715896488274\n ],\n [\n -72.73017883300781,\n 43.761672246385025\n ],\n [\n -72.71781921386719,\n 43.7715896488274\n ],\n [\n -72.70511627197266,\n 43.78398408962279\n ],\n [\n -72.68383026123047,\n 43.79612814894592\n ],\n [\n -72.66975402832031,\n 43.79959742696462\n ],\n [\n -72.67284393310547,\n 43.80901302334783\n ],\n [\n -72.65876770019531,\n 43.81718852149039\n ],\n [\n -72.64572143554688,\n 43.81842713569542\n ],\n [\n -72.63988494873047,\n 43.82536290042666\n ],\n [\n -72.63988494873047,\n 43.83180253191123\n ],\n [\n -72.62889862060547,\n 43.83205019617054\n ],\n [\n -72.62306213378906,\n 43.82734439949711\n ],\n [\n -72.62237548828125,\n 43.82164741238288\n ],\n [\n -72.62992858886719,\n 43.81966572420698\n ],\n [\n -72.63404846191406,\n 43.81099506506452\n ],\n [\n -72.65464782714844,\n 43.808269740746574\n ],\n [\n -72.66082763671875,\n 43.8033142870288\n ],\n [\n -72.65808105468749,\n 43.79191518340848\n ],\n [\n -72.66735076904297,\n 43.78943682964683\n ],\n [\n -72.67387390136719,\n 43.78993250862075\n ],\n [\n -72.69893646240234,\n 43.773325025204\n ],\n [\n -72.72056579589842,\n 43.755968995444164\n ],\n [\n -72.7408218383789,\n 43.75646495188919\n ],\n [\n -72.7573013305664,\n 43.77134173380578\n ],\n [\n -72.76966094970703,\n 43.77109381775651\n ],\n [\n -72.79163360595703,\n 43.774812450590474\n ],\n [\n -72.806396484375,\n 43.77233338772627\n ],\n [\n -72.81017303466797,\n 43.76315996157264\n ],\n [\n -72.81566619873047,\n 43.74530493763506\n ],\n [\n -72.81669616699219,\n 43.72769268338755\n ],\n [\n -72.8177261352539,\n 43.725707879311514\n ],\n [\n -72.83042907714844,\n 43.725707879311514\n ],\n [\n -72.82527923583984,\n 43.763903805293104\n ],\n [\n -72.81909942626953,\n 43.776547733448844\n ],\n [\n -72.80158996582031,\n 43.782496892381175\n ],\n [\n -72.78579711914062,\n 43.78398408962279\n ],\n [\n -72.77069091796875,\n 43.78076178217298\n ],\n [\n -72.7621078491211,\n 43.77877873741692\n ],\n [\n -72.77824401855469,\n 43.79612814894592\n ],\n [\n -72.7950668334961,\n 43.80504874259129\n ],\n [\n -72.79884338378906,\n 43.82164741238288\n ],\n [\n -72.80570983886717,\n 43.83848910616803\n ],\n [\n -72.81257629394531,\n 43.85557361417025\n ],\n [\n -72.81669616699219,\n 43.862257524417934\n ],\n [\n -72.8122329711914,\n 43.88205730390537\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5570171ae4b0d9246a9fd14b","contributors":{"authors":[{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546370,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203357,"text":"70203357 - 2015 - Modeling and management of pit lake water chemistry 1: Theory","interactions":[],"lastModifiedDate":"2019-05-07T13:27:13","indexId":"70203357","displayToPublicDate":"2015-06-01T13:22:41","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Modeling and management of pit lake water chemistry 1: Theory","docAbstract":"Pit lakes are permanent hydrologic/landscape features that can result from open pit mining for metals, coal, uranium, diamonds, oil sands, and aggregates. Risks associated with pit lakes include local and regional impacts to water quality and related impacts to aquatic and terrestrial ecosystems. Stakeholders rely on predictive models of water chemistry to prepare for and manage these risks. This paper is the first of a two part series on the modeling and management of pit lakes. Herein, we review approaches that have been used to quantify wall-rock runoff geochemistry, wall-rock leachate geochemistry, pit lake water balance, pit lake limnology (i.e. extent of vertical mixing), and pit lake water quality, and conclude with guidance on the application of models within the mine life cycle. The purpose of this paper is to better prepare stakeholders, including future modelers, mine managers, consultants, permitting agencies, land management agencies, regulators, research scientists, academics, and other interested parties, for the challenges of predicting and managing future pit lakes in un-mined areas.
Copper oxide (CuO) nanoparticles (NPs) are widely used, and likely released into the aquatic environment. Both aqueous (i.e., dissolved Cu) and particulate Cu can be taken up by organisms. However, how exposure routes influence the bioavailability and subsequent toxicity of Cu remains largely unknown. Here, we assess the importance of exposure routes (water and sediment) and Cu forms (aqueous and nanoparticulate) on Cu bioavailability and toxicity to the freshwater oligochaete, Lumbriculus variegatus, a head-down deposit-feeder. We characterize the bioaccumulation dynamics of Cu in L. variegatus across a range of exposure concentrations, covering both realistic and worst-case levels of Cu contamination in the environment. Both aqueous Cu (Cu-Aq; administered as Cu(NO3)2) and nanoparticulate Cu (CuO NPs), whether dispersed in artificial moderately hard freshwater or mixed into sediment, were weakly accumulated by L. variegatus. Once incorporated into tissues, Cu elimination was negligible, i.e., elimination rate constants were in general not different from zero for either exposure route or either Cu form. Toxicity was only observed after waterborne exposure to Cu-Aq at very high concentration (305 µgL-1), where all worms died. There was no relationship between exposure route, Cu form or Cu exposure concentration on either worm survival or growth. Slow feeding rates and low Cu assimilation efficiency (approximately 30%) characterized the uptake of Cu from the sediment for both Cu forms. In nature, L. variegatus is potentially exposed to Cu via both water and sediment. However, sediment progressively becomes the predominant exposure route for Cu in L. variegatus as Cu partitioning to sediment increases.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.aquatox.2015.04.022","usgsCitation":"Ramskov, T., Thit, A., Croteau, M.N., and Selck, H., 2015, Biodynamics of copper oxide nanoparticles and copper ions in an oligochaete: Part I: relative importance of water and sediment as exposure routes: Aquatic Toxicology, v. 164, p. 81-91, https://doi.org/10.1016/j.aquatox.2015.04.022.","productDescription":"11 p.","startPage":"81","endPage":"91","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061794","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":300967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"164","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"556ed3b7e4b0d9246a9fa7c7","contributors":{"authors":[{"text":"Ramskov, Tina","contributorId":140202,"corporation":false,"usgs":false,"family":"Ramskov","given":"Tina","email":"","affiliations":[{"id":13410,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, PO Box 260, Universitetsvej 1, DK-4000 Roskilde, Denmark","active":true,"usgs":false}],"preferred":false,"id":547998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thit, Amalie","contributorId":141022,"corporation":false,"usgs":false,"family":"Thit","given":"Amalie","email":"","affiliations":[{"id":13657,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, Denmark","active":true,"usgs":false}],"preferred":false,"id":547999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":547997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Selck, Henriette","contributorId":28475,"corporation":false,"usgs":false,"family":"Selck","given":"Henriette","affiliations":[{"id":13410,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, PO Box 260, Universitetsvej 1, DK-4000 Roskilde, Denmark","active":true,"usgs":false}],"preferred":false,"id":548000,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159048,"text":"70159048 - 2015 - Hydrology: The interdisciplinary science of water","interactions":[],"lastModifiedDate":"2015-10-15T09:08:54","indexId":"70159048","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hydrology: The interdisciplinary science of water","docAbstract":"We live in a world where biophysical and social processes are tightly coupled. Hydrologic systems change in response to a variety of natural and human forces such as climate variability and change, water use and water infrastructure, and land cover change. In turn, changes in hydrologic systems impact socioeconomic, ecological, and climate systems at a number of scales, leading to a coevolution of these interlinked systems. The Harvard Water Program, Hydrosociology, Integrated Water Resources Management, Ecohydrology, Hydromorphology, and Sociohydrology were all introduced to provide distinct, interdisciplinary perspectives on water problems to address the contemporary dynamics of human interaction with the hydrosphere and the evolution of the Earth’s hydrologic systems. Each of them addresses scientific, social, and engineering challenges related to how humans influence water systems and vice versa. There are now numerous examples in the literature of how holistic approaches can provide a structure and vision of the future of hydrology. We review selected examples, which taken together, describe the type of theoretical and applied integrated hydrologic analyses and associated curricular content required to address the societal issue of water resources sustainability. We describe a modern interdisciplinary science of hydrology needed to develop an in-depth understanding of the dynamics of the connectedness between human and natural systems and to determine effective solutions to resolve the complex water problems that the world faces today. Nearly, every theoretical hydrologic model introduced previously is in need of revision to accommodate how climate, land, vegetation, and socioeconomic factors interact, change, and evolve over time.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR017049","usgsCitation":"Vogel, R.M., Lall, U., Cai, X., Rajagopalan, B., Weiskel, P.K., Hooper, R.P., and Matalas, N.C., 2015, Hydrology: The interdisciplinary science of water: Water Resources Research, v. 51, no. 6, p. 4409-4430, https://doi.org/10.1002/2015WR017049.","productDescription":"22 p.","startPage":"4409","endPage":"4430","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065855","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":472065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017049","text":"Publisher Index Page"},{"id":309897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-21","publicationStatus":"PW","scienceBaseUri":"5620ce77e4b06217fc478aee","contributors":{"authors":[{"text":"Vogel, Richard M.","contributorId":66811,"corporation":false,"usgs":true,"family":"Vogel","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":577535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lall, Upmanu","contributorId":101172,"corporation":false,"usgs":true,"family":"Lall","given":"Upmanu","affiliations":[],"preferred":false,"id":577536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cai, Ximing","contributorId":149230,"corporation":false,"usgs":false,"family":"Cai","given":"Ximing","email":"","affiliations":[{"id":17685,"text":"University of Illinois, Champagne-Urbana","active":true,"usgs":false}],"preferred":false,"id":577537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rajagopalan, Balaji","contributorId":145813,"corporation":false,"usgs":false,"family":"Rajagopalan","given":"Balaji","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":577538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weiskel, Peter K. pweiskel@usgs.gov","contributorId":1099,"corporation":false,"usgs":true,"family":"Weiskel","given":"Peter","email":"pweiskel@usgs.gov","middleInitial":"K.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":577534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooper, Richard P.","contributorId":19144,"corporation":false,"usgs":true,"family":"Hooper","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":577539,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matalas, Nicholas C.","contributorId":34535,"corporation":false,"usgs":true,"family":"Matalas","given":"Nicholas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":577540,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70191256,"text":"70191256 - 2015 - Applied Geochemistry Special Issue on Environmental geochemistry of modern mining","interactions":[],"lastModifiedDate":"2020-03-10T14:38:56","indexId":"70191256","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Applied Geochemistry Special Issue on Environmental geochemistry of modern mining","docAbstract":"Environmental geochemistry is an integral part of the mine-life cycle, particularly for modern mining. The critical importance of environmental geochemistry begins with pre-mining baseline characterization and the assessment of environmental risks related to mining, continues through active mining especially in water and waste management practices, and culminates in mine closure. The enhanced significance of environmental geochemistry to modern mining has arisen from an increased knowledge of the impacts that historical and active mining can have on the environment, and from new regulations meant to guard against these impacts. New regulations are commonly motivated by advances in the scientific understanding of the environmental impacts of past mining. The impacts can be physical, chemical, and biological in nature. The physical challenges typically fall within the purview of engineers, whereas the chemical and biological challenges typically require a multidisciplinary array of expertise including geologists, geochemists, hydrologists, microbiologists, and biologists. The modern mine-permitting process throughout most of the world now requires that potential risks be assessed prior to the start of mining. The strategies for this risk assessment include a thorough characterization of pre-mining baseline conditions and the identification of risks specifically related to the manner in which the ore will be mined and processed, how water and waste products will be managed, and what the final configuration of the post-mining landscape will be.
In the Fall 2010, the Society of Economic Geologists held a short course in conjunction with the annual meeting of the Geological Society of America in Denver, Colorado (USA) to examine the environmental geochemistry of modern mining. The intent was to focus on issues that are pertinent to current and future mines, as opposed to abandoned mines, which have been the focus of numerous previous short courses. The geochemical challenges of current and future mines share similarities with abandoned mines, but differences also exist. Mining and ore processing techniques have changed; the environmental footprint of waste materials has changed; environmental protection has become a more integral part of the mine planning process; and most historical mining was done with limited regard for the environment. The 17 papers in this special issue evolved from the Society of Economic Geologists’ short course.
The relevant geochemical processes encompass the source, transport, and fate of contaminants related to the life cycle of a mine. Contaminants include metals and other inorganic species derived from geologic sources such as ore and solid mine waste, and substances brought to the site for ore processing, such as cyanide to leach gold. Factors, such as mine-waste mineralogy, hydrologic setting, mine-drainage chemistry, and microbial activity, that affect the hydrochemical risks from mining are reviewed by Nordstrom et al. In another paper, Nordstrom discusses baseline characterization at mine sites in a regulatory framework, and emphasizes the influence of mineral deposits in producing naturally elevated concentrations of many trace elements in surface water and groundwater. Surface water quality in mineralized watersheds is influenced by a number of processes that act on daily (diel) cycles and can produce dramatic variations in trace element concentrations as described by Gammons et al. Pre-mining baseline characterization studies should strive to capture the magnitude of these diel variations. Desbarats et al., using a case study of mine drainage from a gold mine, illustrate how elements that commonly occur as negatively charged species (anions) in solution, such as arsenic as arsenate, behave in an opposite fashion than most metals, which occur as positively charged species (cations). Significant improvement in the understanding of factors that influence the toxicity of metals to aquatic organisms in surface water has highlighted the importance of aqueous chemistry, particularly dissolved organic carbon, as described by Smith et al. Stream sediment contamination is another important pathway for affecting aquatic organisms, as reviewed by Besser et al. Understanding and predicting environmental consequences from mining begins with knowing the mineralogy and mineral reactivity of the ore, the wastes, and of secondary minerals formed later. Jamieson et al. review the importance of mineralogical studies in mine planning and remediation. A number of types of site-specific studies are needed to identify environmental risks related to individual mines. Lapakko reviews the general framework of mine waste characterization studies that are integral to the mine planning process. Hageman et al. present a comparative study of several static tests commonly used to characterize mine waste.
The mining and ore processing practices employed at a specific mine site will vary on the basis of the commodities being targeted, the geology of the deposit, the geometry of the deposit, and the mining and ore processing methods used. Thus, these factors, in addition to the waste management practices used, can result in a variety of end-member mine waste features, each of which has its own set of challenges. Open pit mines and underground mines require waste rock to be removed to access ore. Waste rock presents unique problems because the rock is commonly mineralized at sub-economic grades and has not been processed to remove potentially problematic minerals, such as pyrite. Amos et al. examine the salient aspects of the geochemistry of waste rock. Mill tailings – the waste material after ore minerals have been removed – are a volumetrically important solid waste at many mine sites. Their fine grain size and the options for their management make their behavior in the environment distinct from that of waste rock. Lindsay et al. describe some of these differences through three case-study examples. Subaqueous disposal of tailings is another option described by Moncur et al. Cyanide leaching for gold extraction is a common method throughout the world. Johnson describes environmental aspects of cyanidation. Uranium mining presents unique environmental challenges, particularly since in-situ recovery has seen widespread use. Campbell et al. review the environmental geochemistry of uranium mining and current research on bioremediation. Ore concentrates from many types of metal mining undergo a pyrometallurgical technique known as smelting to extract the metal. Slag is the result of smelting, and it may be an environmental liability or a valuable byproduct, as described by Piatak et al. Finally, the open pits that result from surface mining commonly reach below the water table. At the end of mining, these pits may fill to form lakes that become part of the legacy of the mine. Castendyk et al., in two papers, review theoretical aspects of the environmental limnology of pit lakes. They also describe approaches that have been used to model pit lake water balance, wall-rock contributions to pit lake chemistry, pit lake water quality, and limnological processes, such as vertical mixing, through the use of three case studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.04.019","usgsCitation":"Seal, R., and Nordstrom, D.K., 2015, Applied Geochemistry Special Issue on Environmental geochemistry of modern mining: Applied Geochemistry, v. 57, p. 1-2, https://doi.org/10.1016/j.apgeochem.2015.04.019.","productDescription":"2 p.","startPage":"1","endPage":"2","ipdsId":"IP-063499","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":346319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d3502ae4b05fe04cc34d6f","contributors":{"authors":[{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":711701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":711702,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178268,"text":"70178268 - 2015 - Biogeochemical aspects of uranium mineralization, mining, milling, and remediation","interactions":[],"lastModifiedDate":"2018-09-18T16:14:31","indexId":"70178268","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Biogeochemical aspects of uranium mineralization, mining, milling, and remediation","docAbstract":"Natural uranium (U) occurs as a mixture of three radioactive isotopes: 238U, 235U, and 234U. Only 235U is fissionable and makes up about 0.7% of natural U, while 238U is overwhelmingly the most abundant at greater than 99% of the total mass of U. Prior to the 1940s, U was predominantly used as a coloring agent, and U-bearing ores were mined mainly for their radium (Ra) and/or vanadium (V) content; the bulk of the U was discarded with the tailings (Finch et al., 1972). Once nuclear fission was discovered, the economic importance of U increased greatly. The mining and milling of U-bearing ores is the first step in the nuclear fuel cycle, and the contact of residual waste with natural water is a potential source of contamination of U and associated elements to the environment. Uranium is mined by three basic methods: surface (open pit), underground, and solution mining (in situ leaching or in situ recovery), depending on the deposit grade, size, location, geology and economic considerations (Abdelouas, 2006). Solid wastes at U mill tailings (UMT) sites can include both standard tailings (i.e., leached ore rock residues) and solids generated on site by waste treatment processes. The latter can include sludge or “mud” from neutralization of acidic mine/mill effluents, containing Fe and a range of coprecipitated constituents, or barium sulfate precipitates that selectively remove Ra (e.g., Carvalho et al., 2007). In this chapter, we review the hydrometallurgical processes by which U is extracted from ore, the biogeochemical processes that can affect the fate and transport of U and associated elements in the environment, and possible remediation strategies for site closure and aquifer restoration.
This paper represents the fourth in a series of review papers from the U.S. Geological Survey (USGS) on geochemical aspects of UMT management that span more than three decades. The first paper (Landa, 1980) in this series is a primer on the nature of tailings and radionuclide mobilization from them. The second paper (Landa, 1999) includes coverage of research carried out under the U.S. Department of Energy’s Uranium Mill Tailings Remedial Action Program (UMTRA). The third paper (Landa, 2004) reflects the increased focus of researchers on biotic effects in UMT environs. This paper expands the focus to U mining, milling, and remedial actions, and includes extensive coverage of the increasingly important alkaline in situ recovery and groundwater restoration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.07.022","usgsCitation":"Campbell, K.M., Gallegos, T.J., and Landa, E.R., 2015, Biogeochemical aspects of uranium mineralization, mining, milling, and remediation: Applied Geochemistry, v. 57, p. 206-235, https://doi.org/10.1016/j.apgeochem.2014.07.022.","productDescription":"30 p.","startPage":"206","endPage":"235","ipdsId":"IP-053469","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":331114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582ecff0e4b04d580bd43534","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":653459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallegos, Tanya J. 0000-0003-3350-6473 tgallegos@usgs.gov","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":2206,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya","email":"tgallegos@usgs.gov","middleInitial":"J.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":654048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landa, Edward R. erlanda@usgs.gov","contributorId":2112,"corporation":false,"usgs":true,"family":"Landa","given":"Edward","email":"erlanda@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":654049,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156306,"text":"70156306 - 2015 - Plant-plant interactions in a subtropical mangrove-to-marsh transition zone: effects of environmental drivers","interactions":[],"lastModifiedDate":"2015-10-19T12:17:40","indexId":"70156306","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Plant-plant interactions in a subtropical mangrove-to-marsh transition zone: effects of environmental drivers","docAbstract":"Does the presence of herbaceous vegetation affect the establishment success of mangrove tree species in the transition zone between subtropical coastal mangrove forests and marshes? How do plant–plant interactions in this transition zone respond to variation in two primary coastal environmental drivers?
\nSubtropical coastal region of the southern United States.
\nWe conducted a greenhouse study to better understand how abiotic factors affect plant species interactions in the mangrove-to-marsh transition zone, or ecotone. We manipulated salinity (fresh, brackish or salt water) and hydrologic conditions (continuously saturated or 20-cm tidal range) to simulate ecotonal environments. Propagules of the mangroves Avicennia germinans and Laguncularia racemosa were introduced to mesocosms containing an established marsh community. Both mangrove species were also introduced to containers lacking other vegetation. We monitored mangrove establishment success and survival over 22 mo. Mangrove growth was measured as stem height and above-ground biomass. Stem height, stem density and above-ground biomass of the dominant marsh species were documented.
\nEstablishment success of A. germinans was reduced under saturated saltwater conditions, but establishment of L. racemosa was not affected by experimental treatments. There was complete mortality of A. germinans in mesocosms under freshwater conditions, and very low survival of L. racemosa. In contrast, survival of both species in monoculture under freshwater conditions exceeded 62%. The marsh species Distichlis spicata and Eleocharis cellulosa suppressed growth of both mangroves throughout the experiment, whereas the mangroves did not affect herbaceous species growth. The magnitude of growth suppression by marsh species varied with environmental conditions; suppression was often higher in saturated compared to tidal conditions, and higher in fresh and salt water compared to brackish water.
\nOur results indicate that herbaceous marsh species can suppress mangrove early seedling growth. Depending on species composition and density, marsh plants can slow mangrove landward migration under predicted climate change scenarios as salinity in freshwater and oligohaline wetlands increases with rising sea levels. Change in the relative coverage of mangrove forests and marshes will depend on both the ability of marsh species to migrate further inland as mangroves advance, and the ability of shoreline mangroves to adjust to rising sea level through accretionary processes.
\nHydrologic processes during extreme rainfall events are poorly characterized because of the rarity of measurements. Improved understanding of hydrologic controls on natural hazards is needed because of the potential for substantial risk during extreme precipitation events. We present field measurements of the degree of soil saturation and estimates of available soil-water storage during the September 2013 Colorado extreme rainfall event at burned (wildfire in 2010) and unburned hillslopes with north- and south-facing slope aspects. Soil saturation was more strongly correlated with slope aspect than with recent fire history; south-facing hillslopes became fully saturated while north-facing hillslopes did not. Our results suggest multiple explanations for why aspect-dependent hydrologic controls favor saturation development on south-facing slopes, causing reductions in effective stress and triggering of slope failures during extreme rainfall. Aspect-dependent hydrologic behavior may result from (1) a larger gravel and stone fraction, and hence lower soil-water storage capacity, on south-facing slopes, and (2) lower weathered-bedrock permeability on south-facing slopes, because of lower tree density and associated deep roots penetrating bedrock as well as less intense weathering, inhibiting soil drainage.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G36741.1","usgsCitation":"Ebel, B.A., Rengers, F., and Tucker, G.E., 2015, Aspect-dependent soil saturation and insight into debris-flow initiation during extreme rainfall in the Colorado Front Range: Geology, v. 43, no. 8, p. 659-662, https://doi.org/10.1130/G36741.1.","productDescription":"4 p.","startPage":"659","endPage":"662","ipdsId":"IP-065569","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":335827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-23","publicationStatus":"PW","scienceBaseUri":"58ac0e2fe4b0ce4410e7d5fc","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":669910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengers, Francis K.","contributorId":181893,"corporation":false,"usgs":false,"family":"Rengers","given":"Francis K.","affiliations":[],"preferred":false,"id":669911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Gregory E.","contributorId":177811,"corporation":false,"usgs":false,"family":"Tucker","given":"Gregory","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":669912,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182185,"text":"70182185 - 2015 - Suburbanization, estrogen contamination, and sex ratio in wild amphibian populations","interactions":[],"lastModifiedDate":"2018-09-04T15:47:41","indexId":"70182185","displayToPublicDate":"2015-06-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Suburbanization, estrogen contamination, and sex ratio in wild amphibian populations","docAbstract":"Research on endocrine disruption in frog populations, such as shifts in sex ratios and feminization of males, has predominantly focused on agricultural pesticides. Recent evidence suggests that suburban landscapes harbor amphibian populations exhibiting similar levels of endocrine disruption; however the endocrine disrupting chemical (EDC) sources are unknown. Here, we show that sex ratios of metamorphosing frogs become increasingly female-dominated along a suburbanization gradient. We further show that suburban ponds are frequently contaminated by the classical estrogen estrone and a variety of EDCs produced by plants (phytoestrogens), and that the diversity of organic EDCs is correlated with the extent of developed land use and cultivated lawn and gardens around a pond. Our work also raises the possibility that trace-element contamination associated with human land use around suburban ponds may be contributing to the estrogenic load within suburban freshwaters and constitutes another source of estrogenic exposure for wildlife. These data suggest novel, unexplored pathways of EDC contamination in human-altered environments. In particular, we propose that vegetation changes associated with suburban neighborhoods (e.g., from forests to lawns and ornamental plants) increase the distribution of phytoestrogens in surface waters. The result of frog sex ratios varying as a function of human land use implicates a role for environmental modulation of sexual differentiation in amphibians, which are assumed to only have genetic sex determination. Overall, we show that endocrine disruption is widespread in suburban frog populations and that the causes are likely diverse.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1501065112","usgsCitation":"Lambert, M.R., Giller, G.S., Barber, L.B., Fitzgerald, K.C., and Skelly, D.K., 2015, Suburbanization, estrogen contamination, and sex ratio in wild amphibian populations: Proceedings of the National Academy of Sciences of the United States of America, v. 112, no. 38, p. 11881-11886, https://doi.org/10.1073/pnas.1501065112.","productDescription":"6 p.","startPage":"11881","endPage":"11886","ipdsId":"IP-062730","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":472068,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1501065112","text":"External Repository"},{"id":335838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"38","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-08","publicationStatus":"PW","scienceBaseUri":"58ac0e2ee4b0ce4410e7d5fa","contributors":{"authors":[{"text":"Lambert, Max R.","contributorId":181897,"corporation":false,"usgs":false,"family":"Lambert","given":"Max","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":669920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giller, Geoffrey S. J.","contributorId":181898,"corporation":false,"usgs":false,"family":"Giller","given":"Geoffrey","email":"","middleInitial":"S. J.","affiliations":[],"preferred":false,"id":669921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":669919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzgerald, Kevin C. kcfitzgerald@usgs.gov","contributorId":5534,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Kevin","email":"kcfitzgerald@usgs.gov","middleInitial":"C.","affiliations":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"preferred":true,"id":669922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skelly, David K.","contributorId":181900,"corporation":false,"usgs":false,"family":"Skelly","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":669923,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189467,"text":"70189467 - 2015 - Sediment source apportionment in Laurel Hill Creek, PA, using Bayesian chemical mass balance and isotope fingerprinting","interactions":[],"lastModifiedDate":"2017-07-13T13:29:57","indexId":"70189467","displayToPublicDate":"2015-05-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Sediment source apportionment in Laurel Hill Creek, PA, using Bayesian chemical mass balance and isotope fingerprinting","docAbstract":"A Bayesian chemical mass balance (CMB) approach was used to assess the contribution of potential sources for fluvial samples from Laurel Hill Creek in southwest Pennsylvania. The Bayesian approach provides joint probability density functions of the sources' contributions considering the uncertainties due to source and fluvial sample heterogeneity and measurement error. Both elemental profiles of sources and fluvial samples and 13C and 15N isotopes were used for source apportionment. The sources considered include stream bank erosion, forest, roads and agriculture (pasture and cropland). Agriculture was found to have the largest contribution, followed by stream bank erosion. Also, road erosion was found to have a significant contribution in three of the samples collected during lower-intensity rain events. The source apportionment was performed with and without isotopes. The results were largely consistent; however, the use of isotopes was found to slightly increase the uncertainty in most of the cases. The correlation analysis between the contributions of sources shows strong correlations between stream bank and agriculture, whereas roads and forest seem to be less correlated to other sources. Thus, the method was better able to estimate road and forest contributions independently. The hypothesis that the contributions of sources are not seasonally changing was tested by assuming that all ten fluvial samples had the same source contributions. This hypothesis was rejected, demonstrating a significant seasonal variation in the sources of sediments in the stream.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10364","usgsCitation":"Stewart, H., Massoudieh, A., and Gellis, A.C., 2015, Sediment source apportionment in Laurel Hill Creek, PA, using Bayesian chemical mass balance and isotope fingerprinting: Hydrological Processes, v. 29, no. 11, p. 2545-2560, https://doi.org/10.1002/hyp.10364.","productDescription":"16 p.","startPage":"2545","endPage":"2560","ipdsId":"IP-060412","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":343802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Laurel Hill Creek","volume":"29","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-12-03","publicationStatus":"PW","scienceBaseUri":"596886a2e4b0d1f9f05f59c1","contributors":{"authors":[{"text":"Stewart, Heather","contributorId":173199,"corporation":false,"usgs":false,"family":"Stewart","given":"Heather","affiliations":[{"id":27188,"text":"Alaska Department of Natural Resources Division of Agriculture","active":true,"usgs":false}],"preferred":false,"id":704793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massoudieh, Arash","contributorId":194625,"corporation":false,"usgs":false,"family":"Massoudieh","given":"Arash","email":"","affiliations":[],"preferred":false,"id":704794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":172245,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":704795,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70136357,"text":"sir20145236 - 2015 - Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","interactions":[],"lastModifiedDate":"2015-11-04T12:07:21","indexId":"sir20145236","displayToPublicDate":"2015-05-27T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5236","title":"Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","docAbstract":"A series of nine digital flood-inundation maps were developed for an 8-mile reach of the Hoosic River in North Adams and Williamstown, Massachusetts, by the U.S. Geological Survey (USGS) in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence with the North Branch Hoosic River to the Vermont State line. Peak flows with 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations, and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using the current (2014) stage-discharge relation at the USGS streamgage Hoosic River near Williamstown, Massachusetts (01332500), and from documented high-water marks from the tropical storm Irene flood, which had approximately a 1-percent annual exceedance probability.
\nThe hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from 9 feet (ft; 624.45 ft North American Vertical Datum of 1988 [NAVD 1988]), which is near bankfull, to 16.1 ft (631.59 ft NAVD 1988), which exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft. The mapped stages, 10.9 to 16.1 ft, were selected to match the stages of flows with annual exceedance probabilities between 20 and 0.2 percent, and thus do not fall at exact 1-ft increments. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps.
\nThe availability of the flood-inundation maps, combined with information regarding current (near real-time) stage from USGS streamgage Hoosic River near Williamstown, and forecasted flood stages from the National Weather Service Advanced Hydrologic Prediction Service will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and post-flood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145236","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Lombard, P., and Bent, G.C., 2015, Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line: U.S. Geological Survey Scientific Investigations Report 2014-5236, Report: vi, 15 p.; Downloads Directory, https://doi.org/10.3133/sir20145236.","productDescription":"Report: vi, 15 p.; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059673","costCenters":[{"id":371,"text":"Maine Water Science 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MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300828,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5236/downloads/sir2014-5236_flood-inundation_gis.zip","text":"Hoosic flood inundation gis grids","size":"11.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"Shapefiles"},{"id":300829,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2014/5236/downloads/sir2014-5236_flood-inundation_gis_metadata.xml","text":"Hoosic flood inundation gis metadata","size":"12.2 KB","linkFileType":{"id":6,"text":"zip"},"description":"Shapefiles metadata"}],"country":"United States","state":"Massachusetts","county":"North Adams County, Williamstown County","otherGeospatial":"Hoosic River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.11504364013672,\n 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Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa.
\nTwenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart.
\nFor the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013).
\nFor drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias.
\nAn examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1-4 from the 1987 single-variable RREs and for flood regions 1-3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155055","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR-678)","usgsCitation":"Eash, D.A., 2015, Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013: U.S. Geological Survey Scientific Investigations Report 2015-5055, viii, 37 p., https://doi.org/10.3133/sir20155055.","productDescription":"viii, 37 p.","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058580","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":300734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155055.jpg"},{"id":300732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5055/pdf/sir2015-5055.pdf","text":"Report","size":"2.06 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5055"},{"id":300731,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5055/"},{"id":300733,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5055/downloads/","text":"Downloads Directory","linkFileType":{"id":3,"text":"xlsx"},"description":"Contains: Table 3, 4, 8, 9, and 10 in XLSX format","linkHelpText":"SIR 2015-5055 Downloads Directory"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.7236328125,\n 43.51668853502906\n ],\n [\n -91.2744140625,\n 43.51668853502906\n ],\n [\n -91.01074218749999,\n 43.29320031385282\n ],\n [\n -91.20849609375,\n 43.11702412135048\n ],\n [\n -91.01074218749999,\n 42.79540065303723\n ],\n [\n -90.703125,\n 42.65012181368022\n ],\n [\n -90.06591796875,\n 42.08191667830631\n ],\n [\n -90.32958984375,\n 41.508577297439324\n ],\n [\n -91.01074218749999,\n 41.37680856570233\n ],\n [\n -90.85693359375,\n 40.896905775860006\n ],\n [\n -91.47216796875,\n 40.29628651711716\n ],\n [\n -91.8017578125,\n 40.58058466412761\n ],\n [\n -95.73486328124999,\n 40.54720023441049\n ],\n [\n -95.97656249999999,\n 40.713955826286046\n ],\n [\n -96.70166015624999,\n 42.73087427928485\n ],\n [\n -96.70166015624999,\n 43.14909399920127\n ],\n [\n -96.7236328125,\n 43.51668853502906\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560451be4b0afeb70724141","contributors":{"authors":[{"text":"Eash, David A. 0000-0002-2749-8959 daeash@usgs.gov","orcid":"https://orcid.org/0000-0002-2749-8959","contributorId":1887,"corporation":false,"usgs":true,"family":"Eash","given":"David","email":"daeash@usgs.gov","middleInitial":"A.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544976,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141461,"text":"sir20155015 - 2015 - Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","interactions":[],"lastModifiedDate":"2015-05-28T09:27:59","indexId":"sir20155015","displayToPublicDate":"2015-05-22T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5015","title":"Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","docAbstract":"The South Platte River and underlying alluvial aquifer form an important hydrologic resource in northeastern Colorado that provides water to population centers along the Front Range and to agricultural communities across the rural plains. Water is regulated based on seniority of water rights and delivered using a network of administration structures that includes ditches, reservoirs, wells, impacted river sections, and engineered recharge areas. A recent addendum to Colorado water law enacted during 2002-2003 curtailed pumping from thousands of wells that lacked authorized augmentation plans. The restrictions in pumping were hypothesized to increase water storage in the aquifer, causing groundwater to rise near the land surface at some locations. The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board and the Colorado Water Institute, completed an assessment of 60 years (yr) of historical groundwater-level records collected from 1953 to 2012 from 1,669 wells. Relations of \"high\" groundwater levels, defined as depth to water from 0 to 10 feet (ft) below land surface, were compared to precipitation, river discharge, and 36 geographic and administrative attributes to identify natural and human controls in areas with shallow groundwater.
\nAveraged per decade and over the entire aquifer, depths to groundwater varied between 24 and 32 ft over the 60-yr record. The shallowest average depth to water was identified during 1983-1992, which also recorded the highest levels of decadal precipitation. Average depth to water was greatest (32 ft) during 1953-1962 and intermediate (30 ft) in the recent decade (2003-2012) following curtailment of pumping. Between the decades 1993-2002 and 2003-2012, groundwater levels declined about 2 ft across the aquifer. In comparison, in areas where groundwater levels were within 20 ft of the land surface, observed groundwater levels rose about 0.6 ft, on average, during the same period, which demonstrated preferential rise in areas with shallow groundwater.
\nApproximately 29 percent of water-level observations were identified as high groundwater in the South Platte River alluvial aquifer over the 60-yr record. High groundwater levels were found in 17 to 33 percent of wells examined by decade, with the largest percentages occurring over three decades from 1963 to 1992. The recent decade (2003-2012) exhibited an intermediate percentage (25 percent) of wells with high groundwater levels but also had the highest percentage (30 percent) of high groundwater observations, although results by observations were similar (26-29 percent) over three decades prior, from 1963 to 1992. Major sections of the aquifer from north of Sterling to Julesburg and areas near Greeley, La Salle, and Gilcrest were identified with the highest frequencies of high groundwater levels.
\nChanges in groundwater levels were evaluated using Kendal line and least trimmed squares regression methods using a significance level of 0.01 and statistical power of 0.8. During 2003-2012, following curtailment of pumping, 88 percent of wells and 81 percent of subwatershed areas with significant trends in groundwater levels exhibited rising water levels. Over the complete 60-yr record, however, 66 percent of wells and 57 percent of subwatersheds with significant groundwater-level trends still showed declining water levels; rates of groundwater-level change were typically less than 0.125 ft/yr in areas near the South Platte River, with greater declines along the southern tributaries. In agreement, 58 percent of subwatersheds evaluated between 1963-1972 and 2003-2012 showed net declines in average decadal groundwater levels. More areas had groundwater decline in upgradient sections to the west and rise in downgradient sections to the east, implying a redistribution of water has occurred in some areas of the aquifer.
\nPrecipitation was identified as having the strongest statistically significant correlations to river discharge over annual and decadal periods (Pearson correlation coefficients of 0.5 and 0.8, respectively, and statistical significance defined by p-values less than 0.05). Correlation coefficients between river discharge and frequency of high groundwater levels were statistically significant at 0.4 annually and 0.6 over decadal periods, indicating that periods of high river flow were often coincident with high groundwater conditions. Over seasonal periods in five of the six decades examined, peak high groundwater levels occurred after spring runoff from July to September when administrative structures were most active. Between 1993-2002 and 2003-2012, groundwater levels rose while river discharge decreased, in part from greater reliance on surface water and curtailed pumping from wells without augmentation plans.
\nGeographic attributes of elevation and proximity to streams and rivers showed moderate correlations to high groundwater levels in wells used for observing groundwater levels (correlation coefficients of 0.3 to 0.4). Local depressions and regional lows within the aquifer were identified as areas of potential shallow groundwater. Wells close to the river regularly indicated high groundwater levels, while those within depleted tributaries tended to have low frequencies of high groundwater levels. Some attributes of administrative structures were spatially correlated to high groundwater levels at moderate to high magnitudes (correlation coefficients of 0.3 to 0.7). The number of affected river reaches or recharge areas that surround a well where groundwater levels were observed and its distance from the nearest well field showed the strongest controls on high groundwater levels. Influences of administrative structures on groundwater levels were in some cases local over a mile or less but could extend to several miles, often manifesting as diffuse effects from multiple surrounding structures.
\nA network of candidate monitoring wells was proposed to initiate a regional monitoring program. Consistent monitoring and analysis of groundwater levels will be needed for informed decisions to optimize beneficial use of water and to limit high groundwater levels in susceptible areas. Finalization of the network will require future field reconnaissance to assess local site conditions and discussions with State authorities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155015","collaboration":"Prepared in cooperation with the Colorado Water Institute and Colorado Water Conservation Board","usgsCitation":"Wellman, T., 2015, Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels: U.S. Geological Survey Scientific Investigations Report 2015-5015, viii, 68 p., https://doi.org/10.3133/sir20155015.","productDescription":"viii, 68 p.","numberOfPages":"79","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1953-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-057966","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":300710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155015.jpg"},{"id":300708,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5015/pdf/sir2015-5015.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5015 Report"},{"id":300709,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5015/"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.13818359375,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 36.98500309285596\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55604523e4b0afeb70724143","contributors":{"authors":[{"text":"Wellman, Tristan 0000-0003-3049-6214 twellman@usgs.gov","orcid":"https://orcid.org/0000-0003-3049-6214","contributorId":2166,"corporation":false,"usgs":true,"family":"Wellman","given":"Tristan","email":"twellman@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547513,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70156183,"text":"70156183 - 2015 - Modeling apple snail population dynamics on the Everglades landscape","interactions":[],"lastModifiedDate":"2019-07-25T15:01:35","indexId":"70156183","displayToPublicDate":"2015-05-22T01:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling apple snail population dynamics on the Everglades landscape","docAbstract":"Context
\nThe Florida Everglades has diminished in size and its existing wetland hydrology has been altered. The endangered snail kite (Rostrhamus sociabilis) has nearly abandoned the Everglades, and its prey, the apple snail (Pomacea paludosa), has declined.
\nObjective
\nWe developed a population model (EverSnail) to understand apple snail response to inter- and intra-annual fluctuations in water depths over the Everglades landscape. EverSnail was developed as a tool to understand how apple snails respond to different hydrologic scenarios.
\nMethods
\nEverSnail is an age- and size-structured, spatially-explicit landscape model of P. paludosa in the Everglades. Landscape-level inputs are water depth and air temperature. We conducted sensitivity analyses by running EverSnail with ± 20 % the baseline value of eight parameters.
\nResults
\nEverSnail was sensitive to changes in survival and water depth associated with reproduction. The EverSnail population varied with changes and/or differences in depth generally consistent with empirical data; site-specific comparisons to field data proved less reliable. A simulated 3-year wet period resulted in a shift in apple snail distribution, but little change in total abundance over the landscape. In contrast, a simulated 3-year succession of relatively dry years resulted in overall lower snail abundances.
\nConclusions
\nComparisons of model output to empirical data indicate the need for more data to better understand, and eventually parameterize, several aspects of snail ecology in support of EverSnail. A primary value of EverSnail is its capacity to describe the relative response of snail abundance to alternative hydrologic scenarios considered for Everglades water management and restoration.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s10980-015-0205-5","usgsCitation":"Darby, P., DeAngelis, D., Romanach, S.S., Suir, K.J., and Bridevaux, J.L., 2015, Modeling apple snail population dynamics on the Everglades landscape: Landscape Ecology, v. 30, no. 8, p. 1497-1510, https://doi.org/10.1007/s10980-015-0205-5.","productDescription":"14 p.","startPage":"1497","endPage":"1510","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056099","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":306812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.1060791015625,\n 25.199970890386023\n ],\n [\n -83.1060791015625,\n 28.338230147025865\n ],\n [\n -79.8486328125,\n 28.338230147025865\n ],\n [\n -79.8486328125,\n 25.199970890386023\n ],\n [\n -83.1060791015625,\n 25.199970890386023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"8","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-22","publicationStatus":"PW","scienceBaseUri":"560bb6d5e4b058f706e53d8b","contributors":{"authors":[{"text":"Darby, Phil","contributorId":146459,"corporation":false,"usgs":false,"family":"Darby","given":"Phil","email":"","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":567951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":138934,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":567949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":567950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suir, Kevin J. 0000-0003-1570-9648 suirk@usgs.gov","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":4894,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","email":"suirk@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":567952,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bridevaux, Joshua L.","contributorId":103567,"corporation":false,"usgs":true,"family":"Bridevaux","given":"Joshua","email":"","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":567953,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70144908,"text":"pp1813 - 2015 - Mercury and methylmercury in reservoirs in Indiana","interactions":[],"lastModifiedDate":"2015-05-20T15:39:27","indexId":"pp1813","displayToPublicDate":"2015-05-20T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1813","title":"Mercury and methylmercury in reservoirs in Indiana","docAbstract":"Mercury (Hg) is an element that occurs naturally, but evidence suggests that human activities have resulted in increased amounts being released to the atmosphere and land surface. When Hg is converted to methylmercury (MeHg) in aquatic ecosystems, MeHg accumulates and increases in the food web so that some fish contain levels which pose a health risk to humans and wildlife that consume these fish. Reservoirs unlike natural lakes, are a part of river systems that are managed for flood control. Data compiled and interpreted for six flood-control reservoirs in Indiana showed a relation between Hg transport, MeHg formation in water, and MeHg in fish that was influenced by physical, chemical, and biological differences among the reservoirs. Existing information precludes a uniform comparison of Hg and MeHg in all reservoirs in the State, but factors and conditions were identified that can indicate where and when Hg and MeHg levels in reservoirs could be highest.
\nAs part of a statewide monitoring network for Hg and MeHg in Indiana streams, 66 water samples were collected from four reservoir tailwater sites (downstream near the dams) on a quarterly schedule for 5 years. The reservoirs were Brookville Lake, Cagles Mill Lake, J. Edward Roush Lake, and Mississinewa Lake. Particulate-bound Hg concentrations were significantly lower in tailwater samples than in samples from free-flowing streams in the statewide network. (Free-flowing streams were not affected by dams and were not upstream from these reservoirs.) These data indicated the reduced flow velocity of water upstream from dams was allowing particulate-bound Hg to settle out of the water in the reservoir pools. The concentration ratios of MeHg to Hg were significantly higher in the tailwater samples than in samples from free-flowing streams, and the MeHg to Hg ratios were significantly higher in summer than in other seasons.
\nTo evaluate the conditions related to MeHg formation, pools of three reservoirs (Brookville Lake, Monroe Lake, and Patoka Lake) were investigated during summer hydrologic conditions. Water temperature and dissolved oxygen were measured from the water surface to the lake bottom at 10 to 17 transects across each reservoir to identify three thermal strata, defined by water temperature, dissolved oxygen concentration, and depth. Depth-specific water samples were collected from these thermal strata throughout each reservoir, from the headwaters to the dam and from the tailwater. Mercury concentrations higher than 0.04 nanogram per liter (ng/L) were detected in all 53 samples, and MeHg concentrations higher than 0.04 ng/L were detected in 53 percent of the samples.
\nThe investigation found a zone of water below 8 or 9 meters, with temperatures less than 18 degrees Celsius and dissolved oxygen less than 3.5 milligrams per liter, extending through nearly half the reservoir area in Monroe Lake and Patoka Lake. This zone had abundant dissolved MeHg and concentration ratios of dissolved MeHg to Hg that ranged from 25 to 82 percent. This zone also had water with pH less than 7 and decreased dissolved sulfate, conditions indicating sulfate reduction by microorganisms that promoted a high potential for the conversion of Hg to MeHg. Reservoir outflow came from this zone at Monroe Lake and contributed to a tailwater concentration ratio for dissolved MeHg to Hg of 56 percent. Reservoir outflow at Patoka Lake was not from this zone, and dissolved MeHg was not detected in the tailwater. In contrast, samples from the summer pool at Brookville Lake had no MeHg detections even though Hg was detected, probably because the water pH higher than 7 inhibited sulfate reduction and did not promote the conversion of Hg to MeHg.
\nMercury and MeHg concentrations and the concentration ratios of MeHg to Hg in water varied among the six reservoirs in Indiana, and the differences were related to a combination of factors that could apply to other reservoirs. In areas with moderate to high rates of atmospheric Hg wet and dry deposition, Hg runoff and transport to streams and reservoirs was potentially highest for reservoirs with heavily forested watersheds in steep terrains of near-surface bedrock. Methylmercury concentrations and concentration ratios of MeHg to Hg were highest for reservoirs with the longest summer pools and highest inflow-to-outflow retention times, where water-chemistry conditions favoring sulfate reduction promoted conversion of Hg to MeHg.
\nMethylmercury (reported as Hg) in fish-tissue samples collected for the State fish consumption advisory program was used to describe MeHg food-web accumulation and magnification in the reservoirs. The highest percentages of fish-tissue samples with Hg concentrations that exceeded the criterion of 0.30 milligram per kilogram for protection of human health were from Monroe Lake (38 percent) and Patoka Lake (33 percent). A review of the number and size of fish species caught from these two reservoirs resulted in two implications for fish consumption by humans. First, the highest numbers of fish harvested for potential human consumption were species more likely to have MeHg concentrations lower than the human-health criterion (crappie, bluegill, and catfish). Second, although largemouth bass were likely to have MeHg concentrations higher than the human-health criterion, they were caught and released more often than they were harvested. However, the average size largemouth bass (in both reservoirs) and above-average size walleye (in Monroe Lake) that were harvested for potential human consumption were likely to have MeHg concentrations higher than the human-health criterion.
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Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3326","title":"Water-table and potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers of Long Island, New York, April-May 2013","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with State and local agencies, systematically collects groundwater data at varying measurement frequencies to monitor the hydrologic conditions on Long Island, New York. Each year during April and May, the USGS conducts a synoptic survey of water levels to define the spatial distribution of the water table and potentiometric surfaces within the three main water-bearing units underlying Long Island—the upper glacial, Magothy, and Lloyd aquifers (Smolensky and others, 1989)—and the hydraulically connected Jameco (Soren, 1971) and North Shore aquifers (Stumm, 2001). These data and the maps constructed from them are commonly used in studies of Long Island's hydrology and are utilized by water managers and suppliers for aquifer management and planning purposes.
\nWater-level measurements made in 502 monitoring wells (observation and supply wells) and 16 streamgage locations across Long Island during April–May 2013 were used to prepare the maps in this report. Groundwater measurements were made by the wetted-tape method to the nearest hundredth of a foot. Contours of water-table and potentiometric-surface altitudes were created by using the groundwater measurements. The water-table contours were interpreted by using water-level data collected from 16 streamgages, 334 observation wells, and 1 supply well screened in the upper glacial aquifer or the shallow Magothy aquifer; the Magothy aquifer's potentiometric-surface contours were interpreted from measurements at 70 observation wells and 31 supply wells screened in the middle to deep Magothy aquifer and the contiguous and hydraulically connected Jameco aquifer. The Lloyd aquifer's potentiometric-surface contours were interpreted from measurements at 58 observation wells and 8 supply wells screened in the Lloyd aquifer and the contiguous and hydraulically connected North Shore aquifer. Many of the supply wells are in continuous operation and therefore, were turned off for a minimum of 24 hours before measurements were made to allow the water levels in the wells to recover to ambient (non-pumping) conditions. Full recovery time at some of these supply wells can exceed 24 hours; therefore, water levels measured at these wells are assumed to be less accurate than those measured at observation wells, which are not pumped (Busciolano, 2002). In addition to pumping stresses, elevated chloride concentrations (saline water) also lower the water levels measured in certain wells. This reduction in water level is the result of saline water being denser than freshwater (Lusczynski, 1961). In this report, all water-level altitudes are referenced to the National Geodetic Vertical Datum of 1929 (NGVD 29).
\nThe land surface or topography was downloaded from the National Map portal (http://nationalmap.gov), which represents the most currently available terrain representation as a 10-meter digital elevation model (DEM). The National Map terrain representation was combined with additional land surface terrain models of Suffolk County and New York City, which were collected using lidar to produce a high accuracy three-dimensional land surface altitude model based on the geospatial product for coastal flood mapping. The datum for land surface altitude is North American Vertical Datum of 1988 (NAVD 88). On Long Island NAVD 88 is approximately 1-foot lower than NGVD 29.
\nHydrographs are included on these maps for selected wells that have digital recording equipment. These hydrographs are representative of the 2013 water year to show the changes that have occurred throughout that period. The synoptic survey water level measured at the well is included on each hydrograph.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3326","collaboration":"Prepared in cooperation with the Long Island Water Conference, Nassau County Department of Public Works, New York City Department of Environmental Protection, Port Washington Water District, Suffolk County Department of Health Services, Towns of North Hempstead and Shelter Island, Manhasset-Lakeville Water District, Nassau Suffolk Water Commissioners Association, New York State Department of Environmental Conservation, Sands Point Water Department, Suffolk County Water Authority, Water Authority of Great Neck North","usgsCitation":"Como, M.D., Noll, M.L., Finkelstein, J.S., Monti, J., and Busciolano, R., 2015, Water-table and potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers of Long Island, New York, April-May 2013: U.S. Geological Survey Scientific Investigations Map 3326, Pamphlet: 8 p.; 4 Plates: 72.0 x 34.0 inches, https://doi.org/10.3133/sim3326.","productDescription":"Pamphlet: 8 p.; 4 Plates: 72.0 x 34.0 inches","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2013-04-01","temporalEnd":"2013-05-31","ipdsId":"IP-060337","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":300539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3326.JPG"},{"id":300535,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s1p.pdf","text":"Sheet 1 (Water table)","size":"11.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (11.3 MB)","linkHelpText":"SIM 3326 Sheet 1"},{"id":300533,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3326/"},{"id":300538,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s4p.pdf","text":"Sheet 4 (Depth to water table)","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (11.1 MB)","linkHelpText":"SIM 3326 Sheet 4"},{"id":300534,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326.pdf","text":"Text Pamphlet","size":"78 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIM 3326 Text"},{"id":300536,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s2p.pdf","text":"Sheet 2 (Potentiometric surface in the Magothy and Jameco aquifers)","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (11.2 MB)","linkHelpText":"SIM 3326 Sheet 2"},{"id":300537,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3326/pdf/sim3326_s3p.pdf","text":"Sheet 3 (Potentiometric surface in the Lloyd and North Shore aquifers)","size":"17.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"72\" X 34\" Print size (17.8 MB)","linkHelpText":"SIM 3326 Sheet 3"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.80615234375,\n 40.80965166748856\n ],\n [\n -73.9434814453125,\n 40.78054143186031\n ],\n [\n -74.014892578125,\n 40.730608477796636\n ],\n [\n -74.0643310546875,\n 40.61812224225511\n ],\n [\n -74.0093994140625,\n 40.56389453066509\n ],\n [\n -73.9324951171875,\n 40.53050177574321\n ],\n [\n -73.2843017578125,\n 40.60561205826018\n ],\n [\n -72.8668212890625,\n 40.72644570551446\n ],\n [\n -71.8011474609375,\n 41.075210270566636\n ],\n [\n -71.949462890625,\n 41.08763212467916\n ],\n [\n -72.125244140625,\n 41.13729606112276\n ],\n [\n -72.257080078125,\n 41.15797827873605\n ],\n [\n -72.333984375,\n 41.166249339091976\n ],\n [\n -72.6251220703125,\n 41.0130657870063\n ],\n [\n -73.1524658203125,\n 40.98819156349393\n ],\n [\n -73.4051513671875,\n 40.95915977213492\n ],\n [\n -73.7127685546875,\n 40.89275342420696\n ],\n [\n -73.80615234375,\n 40.80965166748856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180
(518) 285-5600
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