As Australians were spending millions of dollars in 2014 to remove the coral-eating crown of thorns sea star from the Great Barrier Reef, sea stars started washing up dead for free along North America's Pacific Coast. Because North American sea stars are important and iconic predators in marine communities, locals and marine scientists alike were alarmed by what proved to be the world's most widespread marine mass mortality in geographical extent and species affected, especially given its mysterious cause. Investigative research using modern diagnostic techniques implicated a never-before-seen virus [1]. The virus inspired international attention to marine diseases, including this theme issue.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2015.0200","usgsCitation":"Lafferty, K.D., and Hofmann, E.E., 2016, Marine disease impacts, diagnosis, forecasting, management and policy: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 371, no. 1689, Article 20150200; 3 p., https://doi.org/10.1098/rstb.2015.0200.","productDescription":"Article 20150200; 3 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071248","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471203,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rstb.2015.0200","text":"External Repository"},{"id":318408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"371","issue":"1689","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-05","publicationStatus":"PW","scienceBaseUri":"56d56bafe4b015c306f1c123","contributors":{"authors":[{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":621334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hofmann, Eileen E.","contributorId":55726,"corporation":false,"usgs":true,"family":"Hofmann","given":"Eileen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":621335,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168731,"text":"70168731 - 2016 - Lake trout (Salvelinus namaycush) suppression for bull trout (Salvelinus confluentus) recovery in Flathead Lake, Montana, North America","interactions":[],"lastModifiedDate":"2016-11-03T16:35:55","indexId":"70168731","displayToPublicDate":"2016-02-29T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Lake trout (Salvelinus namaycush) suppression for bull trout (Salvelinus confluentus) recovery in Flathead Lake, Montana, North America","docAbstract":"Non-native lake trout Salvelinus namaycush displaced native bull trout Salvelinus confluentus in Flathead Lake, Montana, USA, after 1984, when Mysis diluviana became abundant following its introduction in upstream lakes in 1968–1976. We developed a simulation model to determine the fishing mortality rate on lake trout that would enable bull trout recovery. Model simulations indicated that suppression of adult lake trout by 75% from current abundance would reduce predation on bull trout by 90%. Current removals of lake trout through incentivized fishing contests has not been sufficient to suppress lake trout abundance estimated by mark-recapture or indexed by stratified-random gill netting. In contrast, size structure, body condition, mortality, and maturity are changing consistent with a density-dependent reduction in lake trout abundance. Population modeling indicated total fishing effort would need to increase 3-fold to reduce adult lake trout population density by 75%. We conclude that increased fishing effort would suppress lake trout population density and predation on juvenile bull trout, and thereby enable higher abundance of adult bull trout in Flathead Lake and its tributaries.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10750-016-2703-0","usgsCitation":"Hansen, M.J., Hansen, B.S., and Beauchamp, D.A., 2016, Lake trout (Salvelinus namaycush) suppression for bull trout (Salvelinus confluentus) recovery in Flathead Lake, Montana, North America: Hydrobiologia, v. 783, no. 1, p. 317-334, https://doi.org/10.1007/s10750-016-2703-0.","productDescription":"18 p.","startPage":"317","endPage":"334","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070458","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":318404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Flathead Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n 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michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":621443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Barry S","contributorId":167235,"corporation":false,"usgs":false,"family":"Hansen","given":"Barry","email":"","middleInitial":"S","affiliations":[{"id":24652,"text":"Confederated Salish & Kootenai Tribes","active":true,"usgs":false}],"preferred":false,"id":621444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":621445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168720,"text":"70168720 - 2016 - Long-term reactive nitrogen loading alters soil carbon and microbial community properties in a subalpine forest ecosystem","interactions":[],"lastModifiedDate":"2018-02-22T11:29:44","indexId":"70168720","displayToPublicDate":"2016-02-29T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3416,"text":"Soil Biology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Long-term reactive nitrogen loading alters soil carbon and microbial community properties in a subalpine forest ecosystem","docAbstract":"Elevated nitrogen (N) deposition due to increased fossil fuel combustion and agricultural practices has altered global carbon (C) cycling. Additions of reactive N to N-limited environments are typically accompanied by increases in plant biomass. Soil C dynamics, however, have shown a range of different responses to the addition of reactive N that seem to be ecosystem dependent. We evaluated the effect of N amendments on biogeochemical characteristics and microbial responses of subalpine forest organic soils in order to develop a mechanistic understanding of how soils are affected by N amendments in subalpine ecosystems. We measured a suite of responses across three years (2011–2013) during two seasons (spring and fall). Following 17 years of N amendments, fertilized soils were more acidic (control mean 5.09, fertilized mean 4.68), and had lower %C (control mean 33.7% C, fertilized mean 29.8% C) and microbial biomass C by 22% relative to control plots. Shifts in biogeochemical properties in fertilized plots were associated with an altered microbial community driven by reduced arbuscular mycorrhizal (control mean 3.2 mol%, fertilized mean 2.5 mol%) and saprotrophic fungal groups (control mean 17.0 mol%, fertilized mean 15.2 mol%), as well as a decrease in N degrading microbial enzyme activity. Our results suggest that decreases in soil C in subalpine forests were in part driven by increased microbial degradation of soil organic matter and reduced inputs to soil organic matter in the form of microbial biomass.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.soilbio.2015.10.002","usgsCitation":"Boot, C.M., Hall, E.K., Denef, K., and Baron, J., 2016, Long-term reactive nitrogen loading alters soil carbon and microbial community properties in a subalpine forest ecosystem: Soil Biology and Biochemistry, v. 92, p. 211-220, https://doi.org/10.1016/j.soilbio.2015.10.002.","productDescription":"10 p.","startPage":"211","endPage":"220","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069690","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":318405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56d56bafe4b015c306f1c11e","contributors":{"authors":[{"text":"Boot, Claudia M.","contributorId":167200,"corporation":false,"usgs":false,"family":"Boot","given":"Claudia","email":"","middleInitial":"M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":621387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Ed K.","contributorId":167201,"corporation":false,"usgs":false,"family":"Hall","given":"Ed","email":"","middleInitial":"K.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":621388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denef, Karolien","contributorId":167202,"corporation":false,"usgs":false,"family":"Denef","given":"Karolien","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":621389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":621386,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157311,"text":"ofr20151173 - 2016 - Physical, chemical, and biological characteristics of selected headwater streams along the Allegheny Front, Blair County, Pennsylvania, July 2011–September 2013","interactions":[],"lastModifiedDate":"2016-02-29T10:21:36","indexId":"ofr20151173","displayToPublicDate":"2016-02-29T10:15:00","publicationYear":"2016","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":"2015-1173","title":"Physical, chemical, and biological characteristics of selected headwater streams along the Allegheny Front, Blair County, Pennsylvania, July 2011–September 2013","docAbstract":"The Altoona Water Authority (AWA) obtains all of its water supply from headwater streams that drain western Blair County, an area underlain in part by black shale of the Marcellus Formation. Development of the shale-gas reservoirs will require new access roads, stream crossing, drill-pad construction, and pipeline installation, activities that have the potential to alter existing stream channel morphology, increase runoff and sediment supply, alter streamwater chemistry, and affect aquatic habitat. The U.S. Geological Survey, in cooperation with Altoona Water Authority and Blair County Conservation District, investigated the water quality of 12 headwater streams and biotic health of 10 headwater streams.
\nChannel morphology was characterized at 10 of 12 stream sites using 500-foot (minimum) longitudinal profiles, four cross-sections each, and pebble counts. Channel slopes ranged from 0.008 in Poplar Run near Newry to 0.045 in Mill Run. In general, streams draining watersheds of 5 square miles or less and at higher elevation had the steepest slopes. On the basis of the median particle size, determined during pebble counts, the streambed substrate can be characterized as cobble (Mill Run, Bells Gap Run, Tipton Run, and Sink Run), a mix of gravel and cobble (South Poplar Run, Dry Gap Run, Glenwhite Run, Sugar Run, Blair Gap Run), and gravel (Poplar Run, Newry).
\nDaily mean values of gage height were determined, and continuous (30-minute interval) data consisting of specific conductance and water temperature were collected, at four sites; each site showed typical seasonal fluctuations and the effects of precipitation.
\nStreamflow affected discrete water-quality. Dissolved oxygen always increased with increased streamflow. Most cations (including barium and strontium), along with pH, specific conductance, and total dissolved solids, decreased with greater streamflow, reflecting the dilution effect of moderately acidic surface runoff and precipitation on groundwater discharge (base flow) into the stream channels. Concentrations of trace elements varied by constituent and streamflow.
\nOn the basis of the results of water-quality analyses for the selected constituents, the water quality in 9 of the 12 streams can be considered fair or attaining with no measured constituent exceeding a U.S. Environmental Protection Agency maximum or secondary contaminant level. Abandoned mine drainage (AMD) affects Glenwhite Run, Blair Gap Run, and Sugar Run. For Sugar Run, the AMD is reflected in the elevated iron concentration (greater than 300 micrograms per liter). Manganese concentrations greater than 50 micrograms per liter were measured in Glenwhite Run, Sugar Run, and Blair Gap Run.
\nA mixing curve based upon chloride/bromide ratios for two end points—precipitation and deicing salts—indicate that deicing salt is migrating to the streams. A similar curve representative of late-emerging flowback water from Marcellus gas wells indicated that the surface-water samples had not been influenced by such brines.
\nOn the basis of the concentration of major ions, the streams in the study area generally had mixed cation and anion compositions. Calcium is the dominant cation in one stream. Carbonate and bicarbonate are the dominant anions for two streams, and sulfate is dominant in three streams. The remaining six streams do not have a dominant ion.
\nBiotic health was characterized at 10 of 12 stream sites; the two sites excluded were established late in the study period (May 2013) for refinement of water quality in the headwaters of Poplar Run and the location of Marcellus Formation gas wells. On the basis of the Maryland Index of Biotic Integrity (MdIBI) for fish assemblages, 8 of 10 streams can be considered in fair health. Tipton Run had the highest MdIBI score (3.75) and the greatest number of native species. South Poplar Run had the lowest MdIBI score (1.75); pollution tolerant blacknose dace was dominant. On the basis of the Pennsylvania Department of Environmental Protection macroinvertebrate index of biotic integrity, 9 of 10 streams were characterized as attaining, with scores as high as 88.9 at Tipton Run. Only Sugar Run was characterized as impaired, with a score of 40.4.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151173","collaboration":"Prepared in cooperation with the Altoona Water Authority and the Blair County Conservation District","usgsCitation":"Low, D.J., Brightbill, R.A., Eggleston, H.L., and Chaplin, J.J., 2016, Physical, chemical, and biological characteristics of selected headwater streams along the Allegheny Front, Blair County, Pennsylvania, July 2011–September 2013: U.S. Geological Survey Open-File Report 2015–1173, 66 p., https://dx.doi.org/10.3133/ofr20151173.","productDescription":"Report: viii, 66 p.; Appendixes 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059743","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":314565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173.pdf","text":"Report","size":"3.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1173"},{"id":314564,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1173/coverthb.jpg"},{"id":314566,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173_appendix1-surfacewaterquality.xlsx","text":"Appendix 1 - Surface Water Quality","size":"145 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1173"},{"id":314567,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173_appendix2-fishassemblages.xlsx","text":"Appendix 2 - Fish Assemblages","size":"92.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1173"},{"id":314568,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173_appendix3-ibiscore.xlsx","text":"Appendix 3 - Index of Biotic Integrity","size":"21.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1173"}],"country":"United States","state":"Pennsylvania","county":"Blair County","otherGeospatial":"Allegheny Front","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.35861206054688,\n 40.73581157695217\n ],\n [\n -78.21578979492188,\n 40.677513627085034\n ],\n [\n -78.45474243164062,\n 40.24913603826261\n ],\n [\n -78.62777709960938,\n 40.32665496008367\n ],\n [\n -78.35861206054688,\n 40.73581157695217\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
http://pa.water.usgs.gov/
Interpretation of magnetic and new gravity data provides constraints on the geometry of the Hat Creek Fault, the amount of right-lateral offset in the area between Mt. Shasta and Lassen Peak, and confirmation of the influence of pre-existing structure on Quaternary faulting. Neogene volcanic rocks coincide with short-wavelength magnetic anomalies of both normal and reversed polarity, whereas a markedly smoother magnetic field occurs over the Klamath Mountains and its Paleogene cover. Although the magnetic field over the Neogene volcanic rocks is complex, the Hat Creek Fault, which is one of the most prominent normal faults in the region and forms the eastern margin of the Hat Creek Valley, is marked by the eastern edge of a north-trending magnetic and gravity high 20-30 km long. Modeling of these anomalies indicates that the fault is a steeply dipping (~75-85°) structure. The spatial relationship of the fault as modeled by the potential-field data, the youngest strand of the fault, and relocated seismicity suggests that deformation continues to step westward across the valley, consistent with a component of right-lateral slip in an extensional environment. Filtered aeromagnetic data highlight a concealed magnetic body of Mesozoic or older age north of Hat Creek Valley. The body’s northwest margin strikes northeast and is linear over a distance of ~40 km. Within the resolution of the aeromagnetic data (1-2 km), we discern no right-lateral offset of this body. Furthermore, Quaternary faults change strike or appear to end, as if to avoid this concealed magnetic body and to pass along its southeast edge, suggesting that pre-existing crustal structure influenced younger faulting, as previously proposed based on gravity data.
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The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.
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Their decline is a serious concern as this habitat provides many ecosystem services. Eelgrass (Zostera marina) is the dominant seagrass species in the western North Atlantic. It has recently been established that invasive tunicate species possibly threaten the health of eelgrass beds. Colonization of eelgrass leaves by tunicates can inhibit eelgrass growth and may cause shoot mortality. To document the distribution and diversity of tunicate species that attach to eelgrass in the western North Atlantic, we surveyed twenty-one eelgrass sites from New Jersey to Newfoundland. Eight species of tunicates were found to be colonizing eelgrass, of which 6 are considered invasive. Botrylloides violaceus and Botryllus schlosseri were most commonly attached to eelgrass, with B. schlosseri having the largest latitudinal range of any species. Tunicate faunas attached to eelgrass were less diverse north of Gloucester, Massachusetts, where individual survey sites exhibited two species at most and only 4 of the 8 species observed in this study. Percent tunicate cover on eelgrass tended to fall within the 1–25 range, with occasional coverage up to >75–100. Density of eelgrass was highly variable among sites, ranging from <1 to 820 shoots/m². The solitary tunicate Ciona intestinalis was only found on eelgrass at the highest latitude sampled, in Newfoundland, where it is a new invader. The tunicates observed in this study, both solitary and colonial, are viable when attached to eelgrass and pose a potential threat to overgrow and weaken seagrass shoots and reduce the sustainability of seagrass meadows.
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Combining camera observations with ecosystem carbon dioxide fluxes at forests across rainfall gradients in Amazônia, we show that aggregate canopy phenology, not seasonality of climate drivers, is the primary cause of photosynthetic seasonality in these forests. Specifically, synchronization of new leaf growth with dry season litterfall shifts canopy composition toward younger, more light-use efficient leaves, explaining large seasonal increases (~27%) in ecosystem photosynthesis. Coordinated leaf development and demography thus reconcile seemingly disparate observations at different scales and indicate that accounting for leaf-level phenology is critical for accurately simulating ecosystem-scale responses to climate change.
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Rapid permafrost thaw is producing distinct landscape changes in the Taiga Plains of the Northwest Territories, Canada. As permafrost bodies underlying forested peat plateaus shrink, the landscape slowly transitions into unforested wetlands. The expansion of wetlands has enhanced the hydrologic connectivity of many watersheds via new surface and near-surface flow paths, and increased streamflow has been observed. Furthermore, the decrease in forested peat plateaus results in a net loss of boreal forest and associated ecosystems. This study investigates fundamental processes that contribute to permafrost thaw by comparing observed and simulated thaw development and landscape transition of a peat plateau-wetland complex in the Northwest Territories, Canada from 1970 to 2012. Measured climate data are first used to drive surface energy balance simulations for the wetland and peat plateau. Near-surface soil temperatures simulated in the surface energy balance model are then applied as the upper boundary condition to a three-dimensional model of subsurface water flow and coupled energy transport with freeze-thaw. Simulation results demonstrate that lateral heat transfer, which is not considered in many permafrost models, can influence permafrost thaw rates. Furthermore, the simulations indicate that landscape evolution arising from permafrost thaw acts as a positive feedback mechanism that increases the energy absorbed at the land surface and produces additional permafrost thaw. The modeling results also demonstrate that flow rates in local groundwater flow systems may be enhanced by the degradation of isolated permafrost bodies.
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Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000–2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000–2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990–1999 and 2000–2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974–2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer.
\nMaps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990–1999 and 2000–2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990–1999 and 2000–2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000–2009 than during 1990–1999; and that inland water levels were generally lower during 2000–2009 than during 1990–1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990–1999. Mean October water levels during 2000–2009 were generally higher than during 1990–1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165005","collaboration":"Prepared in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources","usgsCitation":"Prinos, S.T., and Dixon, J.F., 2016, Statistical analysis and mapping of water levels in the Biscayne aquifer, water conservation areas, and Everglades National Park, Miami-Dade County, Florida, 2000–2009: U.S. Geological Survey Scientific Investigations Report 2016–5005, 42 p., https://dx.doi.org/10.3133/sir20165005.","productDescription":"Report: vi, 42 p.; 16 Plates: 23.00 x 30.00 inches or smaller; Appendix; Companion File","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053912","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":318341,"rank":20,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5005/sir20165005_appendix8.pdf","text":"Figure 8-1 - (11x17)","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"Locations of all sites used to map water levels in the Biscayne aquifer, water conservation areas, and Everglades National Park, in Miami-Dade County, Florida, during the 2000-2009 water years. The same index number may be used for adjacent sites."},{"id":318331,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate7.pdf","size":"5.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"50th Percentile of October Water Levels During the 2000–2009 Water Years, Miami-Dade County, Florida"},{"id":318329,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate5.pdf","size":"4.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"75th Percentile of May Water Levels During the 2000–2009 Water Years, Miami-Dade County, Florida"},{"id":318330,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate6.pdf","size":"5.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"25th Percentile of October Water Levels During the 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MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"25th Percentile of May Water Levels During the 2000–2009 Water Years, Miami-Dade County, Florida"},{"id":318339,"rank":18,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate15.pdf","size":"4.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"Difference Between the 50th Percentiles of all Water Levels for Water-year Periods 1990–99 and 2000–2009, Miami-Dade County, Florida"},{"id":318328,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate4.pdf","size":"4.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"50th Percentile of May Water Levels During the 2000–2009 Water Years, Miami-Dade County, Florida"},{"id":318333,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate9.pdf","size":"4.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"50th Percentile of Water Levels From All Months During the 2000–2009 Water Years, Miami-Dade County, Florida"},{"id":318276,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.5066/F7M61H9W","text":"Data, Statistics, and Geographic Information System Files,","description":"SIR 2016-5005","linkHelpText":"Pertaining to Mapping of Water Levels in the Biscayne Aquifer, Water Conservation Areas, and Everglades National Park, Miami-Dade County, Florida, 2000-2009 - Scientific data associated with USGS SIR 2015-5005"},{"id":318336,"rank":15,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate12.pdf","size":"4.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"Difference in May Mean Water Levels From the Water-year Periods 1990–99 and 2000–2009, Miami-Dade County, Florida"},{"id":318325,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5005/plates/sir20165005_plate1.pdf","size":"5.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"Mean of May Water Levels During the 2000–2009 Water Years, Miami-Dade County, Florida"}],"country":"United States","state":"Florida","county":"Miami-Dade","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-80.7769,25.9793],[-80.1236,25.9748],[-80.4387,25.1799],[-80.8621,25.2431],[-80.873,25.9795],[-80.7769,25.9793]]]]},\"properties\":{\"name\":\"Miami-Dade\",\"state\":\"FL\"}}]}","contact":"Director, Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 3355
http://fl.water.usgs.gov/
The Apalachicola-Chattahoochee-Flint (ACF) River Basin encompasses about 20,230 square miles in parts of Alabama, Florida, and Georgia. Increasing population growth and agricultural production from the 1970s to 2010 has prompted increases in water-resources development and substantially increased water demand in the basin. Since the 1980s, Alabama, Florida, Georgia, and the U.S. Army Corps of Engineers are parties to litigation concerning water management in the ACF River Basin.
\nEstimating the 2010 water use in the ACF River Basin is one aspect of a multipart water resources study on the ACF River Basin that began in 2011. This ACF River Basin study is one focus area of the U.S. Geological Survey’s National Water Census program. The 2010 water-use estimates for the ACF River Basin are presented in this report. These estimates include an inventory of the quantity and sources of water withdrawn by category of use and location (State and river basin), and the surface-water returns in the ACF River Basin during 2010. Water-use trends from 1985 to 2010 in the basin also are presented. Offstream water-withdrawal data in the ACF River Basin are presented for each of the following categories: public supply, self-supplied domestic, self-supplied commercial, industrial, mining, agricultural (including crop irrigation, livestock, and aquaculture uses), and thermoelectric-power generation. Water-use data are compiled for the 14 subbasins in the ACF River Basin. For the counties in Alabama, Florida, and Georgia that are partially within the ACF River Basin, data are presented for only that part of the county that lies within the basin. A variety of Federal, State, local, private, and online sources in Alabama, Florida, and Georgia were used to gather surface-water and groundwater withdrawal, surface-water discharges (return flows), and water-use data for the ACF River Basin in 2010.
\nThe population in the ACF River Basin was 3.835 million in 2010, a 45-percent increase from the 1990 population of nearly 2.636 million. About 92 percent of the 2010 ACF population resided in Georgia with nearly 75 percent living in the Atlanta metropolitan area. In 2010, 1,645 million gallons per day (Mgal/d) of water were withdrawn from groundwater (576 Mgal/d) and surface-water (1,069 Mgal/d) sources in the ACF River Basin. About 89 percent of the groundwater and 83 percent of the surface-water withdrawals were from Georgia. About 5.6 percent of the total groundwater and nearly 4 percent of the total surface-water withdrawals in the ACF River Basin were from Florida, whereas about 5.3 percent of groundwater and nearly 16 percent of surface water were withdrawn in Alabama. Total water use (withdrawals plus public-supplied deliveries) in the ACF River Basin was 1,593 Mgal/d in 2010. About 56 Mgal/d of water withdrawn in the ACF River Basin was delivered (interbasin transfer) to basins beyond the ACF River Basin. About 564 Mgal/d of water was returned to surface-water bodies in the ACF River Basin. Most of that amount, 63 percent, was treated wastewater discharged by public wastewater-treatment facilities. Water used for once-through cooling by thermoelectric-power facilities accounted for nearly 24 percent of the surface-water returns in the basin.
\nAbout 70 percent of all water withdrawals in the ACF River Basin were by self-supplied agricultural water users and public water suppliers. Agricultural withdrawals were greatest in the Flint River Basin (501 Mgal/d) with ground-water representing 84 percent of the withdrawals from that basin. Within the Flint River Basin, agricultural withdrawals were greatest in the Lower Flint River and Spring Creek subbasins. About 3.52 million people were served by public water suppliers in the ACF River Basin during 2010, and 88 percent of that population used surface water. Georgia had the largest public-supplied population, representing nearly 93 percent (3.17 million) of the public-supplied population in the ACF River Basin. Public water suppliers served 193,700 people (5.7 percent) in Alabama and 31,880 people in Florida (1.3 percent). Public-supply losses were estimated at 101 Mgal/d.
\nWithdrawals for public supply (483 Mgal/d) and self-supplied industry (141 Mgal/d) were greatest in the Chattahoochee River Basin. Surface water accounted for 96 percent of all withdrawals in the Chattahoochee River Basin. Withdrawals for public supply were greatest in the Upper Chattahoochee River subbasin (366 Mgal/d), whereas self-supplied industrial withdrawals were greatest in the Lower Chattahoochee River subbasin (110 Mgal/d).
\nWater-use trends in the ACF River Basin have varied during the 25 years between 1985 and 2010. Surface-water withdrawals declined between 1985 and 2000, sharply increased in 2000, and declined again between 2000 and 2010. In contrast, groundwater withdrawals increased between 1985 and 2000, declined in 2005, and increased between 2005 and 2010.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165007","collaboration":"Prepared in cooperation with the National Water Census Program","usgsCitation":"Lawrence, S.J., 2016, Water use in the Apalachicola-Chattahoochee-Flint River Basin, Alabama, Florida, and Georgia, 2010, and water-use trends,Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Groundwater represents the terrestrial subsurface component of the hydrologic cycle. As such, groundwater is generally in motion, moving from elevated areas of recharge to lower areas of discharge. Groundwater usually moves in accordance with Darcy’s law (Dalmont, Paris: Les Fontaines Publiques de la Ville de Dijon, 1856). Groundwater residence times can be under a day in small upland catchments to over a million years in subcontinental-sized desert basins. The broadest definition of groundwater includes water in the unsaturated zone, considered briefly here. Water chemically bound to minerals, as in gypsum (CaSO4 • 2H2O) or hydrated clays, cannot flow in response to gradients in total hydraulic head (pressure head plus elevation head); such water is thus usually excluded from consideration as groundwater. In 1940, M. King Hubbert showed Darcy’s law to be a special case of thermodynamically based potential field equations governing fluid motion, thereby establishing groundwater hydraulics as a rigorous engineering science (Journal of Geology 48, pp. 785–944). The development of computer-enabled numerical methods for solving the field equations with real-world approximating geometries and boundary conditions in the mid-1960s ushered in the era of digital groundwater modeling. An estimated 30 percent of global fresh water is groundwater, compared to 0.3 percent that is surface water, 0.04 percent atmospheric water, and 70 percent that exists as ice, including permafrost (Shiklomanov and Rodda 2004, cited under Groundwater Occurrence). Groundwater thus constitutes the vast majority—over 98 percent—of the unfrozen fresh-water resources of the planet, excluding surface-water reservoirs. Environmental dimensions of groundwater are equally large, receiving attention on multiple disciplinary fronts. Riparian, streambed, and spring-pool habitats can be sensitively dependent on the amount and quality of groundwater inputs that modulate temperature and solutes, including nutrients and dissolved oxygen. Groundwater withdrawals can negatively impact riparian habitats by depriving ecosystems of adequate fresh water and fragmenting communities when streams go dry. Biochemical reactions in shallow groundwater can remove anthropogenically elevated nitrogen compounds and reduce—but only to a point—the greening of waterways and shorelines with periphyton and harmful algal blooms. Groundwater extraction for beneficial use is increasingly limited by water-quality constraints imposed by naturally occurring and introduced substances. Overdrafting can cause land-surface subsidence, damaging buildings and roads and disrupting canals, sewers, and other gravity-flow conveyances. Increases in groundwater levels can cause soil salinization in dry regions and erosive sapping and flooding in wet regions. Coastal saltwater intrusion, groundwater flooding, salinization associated with groundwater-irrigated agriculture, induced seismicity from injected wastes, and the detrimental impacts of groundwater depletion are among the major environmental challenges of our time.
","largerWorkTitle":"Oxford Bibliographies in Environmental Science","language":"English","publisher":"Oxford University Press","doi":"10.1093/obo/9780199363445-0053","usgsCitation":"Stonestrom, D.A., 2016, Groundwater, chap. of Oxford Bibliographies in Environmental Science, HTML document, https://doi.org/10.1093/obo/9780199363445-0053.","productDescription":"HTML document","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068189","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":320010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"570e1c32e4b0ef3b7ca24c2d","contributors":{"editors":[{"text":"Wohl, Ellen E.","contributorId":16969,"corporation":false,"usgs":true,"family":"Wohl","given":"Ellen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":626576,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Stonestrom, David A. 0000-0001-7883-3385 dastones@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-3385","contributorId":2280,"corporation":false,"usgs":true,"family":"Stonestrom","given":"David","email":"dastones@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":626222,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70168686,"text":"70168686 - 2016 - A full annual cycle modeling framework for American black ducks","interactions":[],"lastModifiedDate":"2016-02-24T14:30:05","indexId":"70168686","displayToPublicDate":"2016-02-24T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2827,"text":"Natural Resource Modeling","active":true,"publicationSubtype":{"id":10}},"title":"A full annual cycle modeling framework for American black ducks","docAbstract":"American black ducks (Anas rubripes) are a harvested, international migratory waterfowl species in eastern North America. Despite an extended period of restrictive harvest regulations, the black duck population is still below the population goal identified in the North American Waterfowl Management Plan (NAWMP). It has been hypothesized that density-dependent factors restrict population growth in the black duck population and that habitat management (increases, improvements, etc.) may be a key component of growing black duck populations and reaching the prescribed NAWMP population goal. Using banding data from 1951 to 2011 and breeding population survey data from 1990 to 2014, we developed a full annual cycle population model for the American black duck. This model uses the seven management units as set by the Black Duck Joint Venture, allows movement into and out of each unit during each season, and models survival and fecundity for each region separately. We compare model population trajectories with observed population data and abundance estimates from the breeding season counts to show the accuracy of this full annual cycle model. With this model, we then show how to simulate the effects of habitat management on the continental black duck population.
","language":"English","publisher":"Wiley","doi":"10.1111/nrm.12088","usgsCitation":"Robinson, O.J., McGowan, C.P., Devers, P.K., Brook, R.W., Huang, M., Jones, M., McAuley, D.G., and Zimmerman, G.S., 2016, A full annual cycle modeling framework for American black ducks: Natural Resource Modeling, v. 29, no. 1, p. 159-174, https://doi.org/10.1111/nrm.12088.","productDescription":"16 p.","startPage":"159","endPage":"174","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068504","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":318368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-28","publicationStatus":"PW","scienceBaseUri":"56ced42de4b015c306ec2fdc","contributors":{"authors":[{"text":"Robinson, Orin J.","contributorId":167172,"corporation":false,"usgs":false,"family":"Robinson","given":"Orin","email":"","middleInitial":"J.","affiliations":[{"id":33694,"text":"School of Forestry and Wildlife Sciences, Auburn University","active":true,"usgs":false}],"preferred":false,"id":621307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":621264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Devers, Patrick K.","contributorId":167173,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":621308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brook, Rodney W.","contributorId":92083,"corporation":false,"usgs":false,"family":"Brook","given":"Rodney","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":621309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Min","contributorId":167174,"corporation":false,"usgs":false,"family":"Huang","given":"Min","email":"","affiliations":[],"preferred":false,"id":621310,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Malcom","contributorId":167175,"corporation":false,"usgs":false,"family":"Jones","given":"Malcom","email":"","affiliations":[],"preferred":false,"id":621311,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McAuley, Daniel G. dmcauley@usgs.gov","contributorId":5377,"corporation":false,"usgs":true,"family":"McAuley","given":"Daniel","email":"dmcauley@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":621312,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":621313,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70161867,"text":"sir20155185 - 2016 - Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow","interactions":[],"lastModifiedDate":"2017-10-12T19:59:21","indexId":"sir20155185","displayToPublicDate":"2016-02-24T13:00:00","publicationYear":"2016","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":"2015-5185","title":"Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow","docAbstract":"The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.
Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.
A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.
A water-balance model was developed for simulating monthly natural (unregulated) mean streamflow based on precipitation, temperature, and potential evapotranspiration at select streamflow-gaging stations. The model was calibrated using streamflow data from the U.S. Geological Survey and Environment Canada, along with natural (unregulated) streamflow data from the U.S. Army Corps of Engineers. Correlation coefficients between simulated and natural (unregulated) flows generally were high (greater than 0.8), and the seasonal means and standard deviations of the simulated flows closely matched the means and standard deviations of the natural (unregulated) flows. After calibrating the model for a monthly time step, monthly streamflow for each subbasin was disaggregated into three values per month, or an approximately 10-day time step, and a separate routing model was developed for simulating 10-day streamflow for downstream gages.
The stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration was combined with the water-balance model to simulate potential future sequences of 10-day mean streamflow for each of the streamflow-gaging station locations. Flood risk, as determined by equilibrium flow-frequency distributions for the dry (1912–69) and wet (1970–2011) climate states, was considerably higher for the wet state compared to the dry state. Future flood risk will remain high until the wet climate state ends, and for several years after that, because there may be a long lag-time between the return of drier conditions and the onset of a lower soil-moisture storage equilibrium.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155185","collaboration":"Prepared in cooperation with the North Dakota State Water Commission","usgsCitation":"Kolars, K.A., Vecchia, A.V., and Ryberg, K.R., 2016, Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow: U.S. Geological Survey Scientific Investigations Report 2015–5185, 55 p., https://dx.doi.org/10.3133/sir20155185.","productDescription":"viii, 55 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068149","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":318270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5185/sir20155185.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5185"},{"id":318269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5185/coverthb.jpg"}],"country":"Canada, United States","state":"Manitoba, North Dakota, Saskatchewan","otherGeospatial":"Souris River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.04052734375,\n 48.99824008113872\n ],\n [\n -104.74365234375,\n 49.42884000063522\n ],\n [\n -104.7930908203125,\n 50.004208515595614\n ],\n [\n -103.480224609375,\n 50.52041218671901\n ],\n [\n -102.0245361328125,\n 50.604159488561\n ],\n [\n -101.195068359375,\n 50.25071752130677\n ],\n [\n -100.65673828125,\n 49.745781306155735\n ],\n [\n -99.60891723632812,\n 49.648069803718805\n ],\n [\n -99.18594360351562,\n 49.577773933420914\n ],\n [\n -99.2340087890625,\n 49.39131220507362\n ],\n [\n -99.76547241210936,\n 49.413653634531116\n ],\n [\n -99.4482421875,\n 48.100094697973795\n ],\n [\n -101.502685546875,\n 47.99727386804474\n ],\n [\n -103.568115234375,\n 48.52388120259336\n ],\n [\n -104.04052734375,\n 48.99824008113872\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS North Dakota Water Science Center
821 East Interstate Avenue
Bismarck, North Dakota 58503
Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Tempe, AZ","doi":"10.1002/15-1061","usgsCitation":"Behnke, R.J., Stephen J. Vavrus, Allstadt, A., Albright, T.P., Thogmartin, W.E., and Radeloff, V.C., 2016, Evaluation of downscaled, gridded climate data for the conterminous United States: Ecological Applications, v. 26, no. 5, p. 1338-1351, https://doi.org/10.1002/15-1061.","productDescription":"14 p.","startPage":"1338","endPage":"1351","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066648","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/15-1061","text":"Publisher Index Page"},{"id":318680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Vavrus","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":622127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Andrew","contributorId":167392,"corporation":false,"usgs":false,"family":"Allstadt","given":"Andrew","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":622128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Albright, Thomas P.","contributorId":167393,"corporation":false,"usgs":false,"family":"Albright","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24706,"text":"University of Nevada-Reno","active":true,"usgs":false}],"preferred":false,"id":622129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":622125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Radeloff, Volker C.","contributorId":149494,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker","email":"","middleInitial":"C.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":622130,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168825,"text":"70168825 - 2016 - Reconnecting fragmented sturgeon populations in North American rivers","interactions":[],"lastModifiedDate":"2018-02-28T14:35:05","indexId":"70168825","displayToPublicDate":"2016-02-24T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Reconnecting fragmented sturgeon populations in North American rivers","docAbstract":"The majority of large North American rivers are fragmented by dams that interrupt migrations of wide-ranging fishes like sturgeons. Reconnecting habitat is viewed as an important means of protecting sturgeon species in U.S. rivers because these species have lost between 5% and 60% of their historical ranges. Unfortunately, facilities designed to pass other fishes have rarely worked well for sturgeons. The most successful passage facilities were sized appropriately for sturgeons and accommodated bottom-oriented species. For upstream passage, facilities with large entrances, full-depth guidance systems, large lifts, or wide fishways without obstructions or tight turns worked well. However, facilitating upstream migration is only half the battle. Broader recovery for linked sturgeon populations requires safe “round-trip” passage involving multiple dams. The most successful downstream passage facilities included nature-like fishways, large canal bypasses, and bottom-draw sluice gates. We outline an adaptive approach to implementing passage that begins with temporary programs and structures and monitors success both at the scale of individual fish at individual dams and the scale of metapopulations in a river basin. The challenge will be to learn from past efforts and reconnect North American sturgeon populations in a way that promotes range expansion and facilitates population recovery.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/03632415.2015.1132705","usgsCitation":"Jager, H., Parsley, M.J., Cech, J.J., McLaughlin, R.L., Forsythe, P.S., and Elliott, R.S., 2016, Reconnecting fragmented sturgeon populations in North American rivers: Fisheries, v. 41, no. 3, p. 140-148, https://doi.org/10.1080/03632415.2015.1132705.","productDescription":"9 p.","startPage":"140","endPage":"148","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056808","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":490009,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1240513","text":"External Repository"},{"id":318553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United 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L.","contributorId":75736,"corporation":false,"usgs":false,"family":"McLaughlin","given":"R.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":621859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forsythe, Patrick S.","contributorId":167341,"corporation":false,"usgs":false,"family":"Forsythe","given":"Patrick","email":"","middleInitial":"S.","affiliations":[{"id":24696,"text":"Green Bay Fish and Wildlife Conservation Office, USGS, New Franken, Wisconsin","active":true,"usgs":false}],"preferred":false,"id":621860,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Robert S.","contributorId":167342,"corporation":false,"usgs":false,"family":"Elliott","given":"Robert","email":"","middleInitial":"S.","affiliations":[{"id":24697,"text":"Department of Natural and Applied Sciences, University of Wisconsin - Green Bay, Green Bay, WI","active":true,"usgs":false}],"preferred":false,"id":621861,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171334,"text":"70171334 - 2016 - Genetic diversity of Wolbachia endosymbionts in Culex quinquefasciatus from Hawai`i, Midway Atoll, and Samoa","interactions":[],"lastModifiedDate":"2018-01-04T12:43:21","indexId":"70171334","displayToPublicDate":"2016-02-24T07:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-074","title":"Genetic diversity of Wolbachia endosymbionts in Culex quinquefasciatus from Hawai`i, Midway Atoll, and Samoa","docAbstract":"Incompatible insect techniques are potential methods for controlling Culex quinquefasciatus and avian disease transmission in Hawai‘i without the use of pesticides or genetically modified organisms. The approach is based on naturally occurring sperm-egg incompatibilities within the Culex pipiens complex that are controlled by different strains of the bacterial endosymbiont Wolbachia pipientis (wPip). Incompatibilities can be unidirectional (crosses between males infected with strain A and females infected with strain B are fertile, while reciprocal crosses are not) or bidirectional (reciprocal crosses between sexes with different wPip strains are infertile). The technique depends on release of sufficient numbers of male mosquitoes infected with an incompatible wPip strain to suppress mosquito populations and reduce transmission of introduced avian malaria (Plasmodium relictum) and Avipoxvirus in native forest bird habitats. Both diseases are difficult to manage using more traditional methods based on removal and treatment of larval habitats and coordination of multiple approaches may be needed to control this vector. We characterized the diversity of Wolbachia strains in C. quinquefasciatus from Hawai‘i, Kaua‘i, Midway Atoll, and American Samoa with a variety of genetic markers to identify compatibility groups and their distribution within and between islands. We confirmed the presence of wPip with multilocus sequence typing, tested for local genetic variability using 16 WO prophage genes, and identified similarities to strains from other parts of the world with a transposable element (tr1). We also tested for genetic differences in ankyrin motifs (ank2 and pk1) which have been used to classify wPip strains into five worldwide groups (wPip1–wPip5) that vary in compatibility with each other based on experimental crosses. We found a mixture of both widely distributed and site specific genotypes based on presence or absence of WO prophage and transposable element markers on Hawai‘i Island (Volcano, Pu‘u Wa‘awa‘a, Laupāhoehoe, Kaumana, Kahuku, Nīnole, and Maulua Gulch), Kaua‘i Island (Kawaikōī, Mōhihi, Kalāheo, Lāwa‘i and Hanapepe) and Midway Atoll. Genotypes from American Samoa were unique and formed their own clade. Based on analysis of ankyrin motifs, wPip strains from Hawai‘i, Kaua‘i, and Midway Atoll were most similar to wPip5 strains of Australasian origin. By contrast, Wolbachia strains from Culex quinquefasciatus collected in American Samoa were most similar to wPip3 strains of American origin. We detected a single Culex mosquito from Pu‘u Wa‘awa‘a on Hawai‘i Island that was infected with a unique wPip3 genotype. This discovery, plus a rarefaction analysis of genotypes from Kaua‘i and Hawai‘i Islands suggests that limited sampling may have underestimated diversity of wPip in our study. Mosquitoes infected with wPip5 and wPip3 are bidirectionally compatible with each other based on prior studies, which would support their ability to coexist within the same population on Hawai‘i Island. Available evidence from prior studies suggests that genotype wPip4 from Africa, the Middle East, Europe, and Asia is bidirectionally incompatible with genotype wPip5 and varies in compatibility with genotype wPip3 depending on geographic origin. Since wPip5 appears to be the most common compatibility group in Hawai‘i based on limited sampling, logical next steps are to 1) expand the current survey to include additional islands and localities, 2) infect a laboratory colony of Hawaiian Culex with wPip4 through tetracycline treatment of Hawaiian mosquitoes and backcross with Culex from Europe, North Africa, and the Middle East that are naturally infected with wPip4, 3) conduct cage trials to confirm bidirectional incompatibilities between Hawaiian Culex infected with wPip4 and wPip5, and 4) conduct field trials to evaluate whether release of incompatible males can be applied at small scales to suppress local populations.
","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, Hi","collaboration":"This product was prepared under Cooperative Agreement G15AC00191 for the Pacific Island Ecosystems Research Center of the U.S. Geological Survey.","usgsCitation":"Atkinson, C.T., Watcher-Weatherwax, W., and Lapointe, D., 2016, Genetic diversity of Wolbachia endosymbionts in Culex quinquefasciatus from Hawai`i, Midway Atoll, and Samoa: Technical Report HCSU-074, Report: iv, 33 p.","productDescription":"Report: iv, 33 p.","startPage":"1","endPage":"33","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073512","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328011,"type":{"id":15,"text":"Index 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Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Are brown trout replacing or displacing bull trout populations in a changing climate?","docAbstract":"Understanding how climate change may facilitate species turnover is an important step in identifying potential conservation strategies. We used data from 33 sites in western Montana to quantify climate associations with native bull trout (Salvelinus confluentus) and non-native brown trout (Salmo trutta) abundance and population growth rates (λ). We estimated λ using exponential growth state space models and delineated study sites based on bull trout use for either Spawning and Rearing (SR) or Foraging, Migrating, and Overwintering (FMO) habitat. Bull trout abundance was negatively associated with mean August stream temperatures within SR habitat (r = -0.75). Brown trout abundance was generally highest at temperatures between 12 and 14°C. We found bull trout λ were generally stable at sites with mean August temperature below 10°C but significantly decreasing, rare, or extirpated at 58% of the sites with temperatures exceeding 10°C. Brown trout λ were highest in SR and sites with temperatures exceeding 12°C. Declining bull trout λs at sites where brown trout were absent suggests brown trout are likely replacing bull trout in a warming climate.
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2016 - Ecoregions of California","interactions":[],"lastModifiedDate":"2025-05-14T18:41:14.173917","indexId":"ofr20161021","displayToPublicDate":"2016-02-23T17:00:00","publicationYear":"2016","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":"2016-1021","title":"Ecoregions of California","docAbstract":"Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000).
The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014).
California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014).
The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities.
The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.
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\"}}]}","contact":"Western Geographic Science Center
U.S. Geological Survey
345 Middlefield Road, MS 531
Menlo Park, CA 94025
http://geography.wr.usgs.gov/
Tritium–helium-3 groundwater ages of the Edwards aquifer in south-central Texas were determined as part of a long-term study of groundwater flow and recharge in the Edwards and Trinity aquifers. These ages help to define groundwater residence times and to provide constraints for calibration of groundwater flow models. A suite of 17 samples from public and private supply wells within Uvalde County were collected for active and noble gases, and for tritium–helium-3 analyses from the confined and unconfined parts of the Edwards aquifer. Samples were collected from monitoring wells at discrete depths in open boreholes as well as from integrated pumped well-head samples. The data indicate a fairly uniform groundwater flow system within an otherwise structurally complex geologic environment comprised of regionally and locally faulted rock units, igneous intrusions, and karst features within carbonate rocks. Apparent ages show moderate, downward average, linear velocities in the Uvalde area with increasing age to the east along a regional groundwater flow path. Though the apparent age data show a fairly consistent distribution across the study area, many apparent ages indicate mixing of both modern (less than 60 years) and premodern (greater than 60 years) waters. This mixing is most evident along the “bad water” line, an arbitrary delineation of 1,000 milligrams per liter dissolved solids that separates the freshwater zone of the Edwards aquifer from the downdip saline water zone. Mixing of modern and premodern waters also is indicated within the unconfined zone of the aquifer by high excess helium concentrations in young waters. Excess helium anomalies in the unconfined aquifer are consistent with possible subsurface discharge of premodern groundwater from the underlying Trinity aquifer into the younger groundwater of the Edwards aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155163","usgsCitation":"Hunt, A.G., Landis, G.P., and Faith, J.R., 2016, Groundwater ages from the freshwater zone of the Edwards Aquifer, Uvalde County, Texas—Insights into groundwater flow and recharge: U.S. Geological Survey Scientific Investigations Report 2015–5163, 28 p., https://dx.doi.org/10.3133/sir20155163.","productDescription":"viii, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065915","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":318180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5163/coverthb.jpg"},{"id":318181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5163/sir20155163.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5163"}],"country":"United States","state":"Texas","county":"Uvalde County","otherGeospatial":"Edwards Aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.4132,29.6253],[-99.4107,29.087],[-99.6813,29.0872],[-100.1119,29.0844],[-100.1112,29.3486],[-100.111,29.6236],[-100.0145,29.6237],[-99.6173,29.6257],[-99.6033,29.6257],[-99.4132,29.6253]]]},\"properties\":{\"name\":\"Uvalde\",\"state\":\"TX\"}}]}","contact":"Center Director, USGS Crustal Geophysics and Geochemistry Science Center
Box 25046, Mail Stop 964
Denver, CO 80225
In 2013, the U.S. Geological Survey and the Miami Conservancy District investigated the effectiveness of methods used to remove arsenic from drinking water at 11 homes in southwestern and central Ohio. The untreated (raw) ground-water had arsenic concentrations of 7.7–382 micrograms per liter (µg/L), and the median concentration was 30 µg/L. The pH was neutral to slightly alkaline, and redox conditions were strongly reducing, as indicated by high concentrations of iron. The predominant arsenic species was arsenite (As3+), which is difficult to treat because it exists in water as an uncharged compound (H3AsO3).
The water-treatment systems included (1) seven single-tap reverse-osmosis systems, (2) two whole-house oxidation/filtration systems, and (3) two systems that included wholehouse anion exchange and single-tap reverse osmosis. All but one system included pretreatment by a water softener, and two systems included preoxidation to convert arsenite (As3+) to arsenate (As5+) before treatment by anion exchange.
None of the treatment systems removed all of the arsenic from the drinking water. About one-half of the systems decreased the arsenic concentration to less than the maximum contamination level of 10 µg/L. The effectiveness of the systems varied widely; the percentage of arsenic removed ranged from 2 to 90 percent, and the median was 65 percent.
At some sites, the low effectiveness of arsenic removal may have been related to system maintenance and(or) operation issues. At two sites, homeowners acknowledged that the treatment systems had not been maintained for several years. At two other sites, the treatment systems were being maintained, but the water-quality data indicated that one of the components was not working, unbeknownst to the homeowner. EPA research at a small number of sites in Ohio indicated that operation and maintenance of some arsenic-treatment systems was not always simple.
Another factor that affected system effectiveness was the quality of the raw water. In general, the treatment systems were less effective at treating higher concentrations of arsenic. For five sites with raw-water arsenic concentrations of 10–30 µg/L, the systems removed 65–81 percent of the arsenic, and the final concentrations were less than the maximum contamination level. For three sites with higher raw-water arsenic concentrations (50–75 µg/L), the systems removed 22–34 percent of the arsenic; and the final concentrations were 4–5 times more than the maximum contamination level. Other characteristics of the raw water may have affected the performance of treatment systems; in general, raw water with the higher arsenic concentrations also had higher pH, higher concentrations of organic carbon and ammonia, and more reducing (methanogenic) redox conditions.
For sites with raw-water arsenic concentrations of 10–30 µg/L, two types of systems (reverse osmosis and oxidation/filtration) removed similar amounts of arsenic, but the quality of the treated water differed in other respects. Reverse osmosis caused substantial decreases in pH, alkalinity, and concentrations of most ions. On the other hand, oxidation/filtration using manganese-based media caused a large increase of manganese concentrations, from less than 50 µg/L in raw water to more than 700 µg/L in outflow from the oxidation filtration units.
It is not known if the results of this study are widely applicable; the number of systems sampled was relatively small, and each system was sampled only once. Further study may be warranted to investigate whether available methods of arsenic removal are effective/practical for residential use in areas like Ohio, were groundwater with elevated arsenic concentrations is strongly reducing, and the predominant arsenic species is arsenite (As3+).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155156","isbn":"978-1-4113-4006-0","collaboration":"Prepared in cooperation with Miami Conservancy District","usgsCitation":"Thomas, M.A., and Ekberg, Mike, 2016, The effectiveness of water-treatment systems for arsenic used in 11 homes in Southwestern and Central Ohio, 2013: U.S. Geological Survey Scientific Investigations Report 2015–5156, 26 p., https://dx.doi.org/10.3133/sir20155156.","productDescription":"Report: vi, 26 p.; Table","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065490","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":318264,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5156/sir20155156_table2.xlsx","text":"Table 2. Water-quality results from 11 domestic wells in southwestern and central Ohio, 2013","size":"36.0 kb","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5156 Table 2"},{"id":318263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5156/sir20155156.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5156"},{"id":318262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5156/coverthb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.825439453125,\n 39.24927084622338\n ],\n [\n -84.825439453125,\n 40.43858586704328\n ],\n [\n -81.815185546875,\n 40.43858586704328\n ],\n [\n -81.815185546875,\n 39.24927084622338\n ],\n [\n -84.825439453125,\n 39.24927084622338\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Ohio Water Science Center
6480 Doubletree Ave
Columbus, OH 43229-1111
","tableOfContents":"
The U.S. Geological Survey (USGS) assessed the undiscovered, technically recoverable oil and gas resources of Armenia in 2013. A Paleozoic and a Cenozoic total petroleum system (TPS) were identified within the country of Armenia. The postulated petroleum system elements are uncertain, resulting in low geologic probabilities for significant oil an gas resources. Two assessment units (AU) were delineated in each TPS—a Paleozoic-Sourced Conventional Reservoirs AU and a Permian Shale Gas AU in the Paleozoic Composite TPS and a Paleogene-Sourced Conventional Reservoirs AU and a Cenozoic Coalbed Gas AU in the Cenozoic Composite TPS. The TPS elements are largely uncertain and risked, and so only the Paleogene-Sourced Conventional Reservoirs AU was quantitatively assessed because the geologic probability is more than the threshold of 10 percent (that is, the probability of at least one conventional oil or gas accumulation of 5 million barrels of oil equivalent or greater based on postulated petroleum-system elements). The USGS estimated fully risked mean volumes of about 1 million barrels of oil (MMBO), about 6 billion cubic feet of natural gas (BCFG), and less than 1 million barrels of natural gas liquids (MMBNGL).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69PP","usgsCitation":"Klett, T.R., 2016, Geology and assessment of undiscovered, technically recoverable petroleum resources of Armenia, 2013: U.S. Geological Survey Digital Data Series 69–PP, 21 p., https://dx.doi.org/10.3133/ds69PP.","productDescription":"Report: vi, 21 p.; Figure","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063804","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-pp/dds69pp.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DDS-69-PP Report"},{"id":318113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-pp/coverthb.jpg"},{"id":318154,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-pp/figure09.pdf","text":"Figure 9, lithostratigraphic column","size":"424 kb","linkFileType":{"id":1,"text":"pdf"},"description":"DDS-69-PP Figure 9"}],"country":"Armenia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[43.58275,41.09214],[44.97248,41.24813],[45.1795,40.98535],[45.56035,40.81229],[45.35917,40.5615],[45.89191,40.21848],[45.61001,39.89999],[46.03453,39.62802],[46.4835,39.46415],[46.50572,38.77061],[46.14362,38.7412],[45.73538,39.31972],[45.73998,39.474],[45.29814,39.47175],[45.00199,39.74],[44.79399,39.713],[44.40001,40.005],[43.65644,40.25356],[43.75266,40.7402],[43.58275,41.09214]]]},\"properties\":{\"name\":\"Armenia\"}}]}","contact":"Center Director, USGS Central Energy Resources Science Center
Box 25046, Mail Stop 939
Denver, CO 80225
Arsenic concentrations were measured in samples from 168 domestic wells in Licking County, Ohio, to document arsenic concentrations in a wide variety of wells and to identify hydrogeologic factors associated with arsenic concentrations in groundwater. Elevated concentrations of arsenic (greater than 10.0 micrograms per liter [µg/L]) were detected in 12 percent of the wells (about 1 in 8). The maximum arsenic concentration of about 44 µg/L was detected in two wells in the same township.
A subset of 102 wells was also sampled for iron, sulfate, manganese, and nitrate, which were used to estimate redox conditions of the groundwater. Elevated arsenic concentrations were detected only in strongly reducing groundwater. Almost 20 percent of the samples with iron concentrations high enough to produce iron staining (greater than 300 µg/L) also had elevated concentrations of arsenic.
In groundwater, arsenic primarily occurs as two inorganic species—arsenite and arsenate. Arsenic speciation was determined for a subset of nine samples, and arsenite was the predominant species. Of the two species, arsenite is more difficult to remove from water, and is generally considered to be more toxic to humans.
Aquifer and well-construction characteristics were compiled from 99 well logs. Elevated concentrations of arsenic (and iron) were detected in glacial and bedrock aquifers but were more prevalent in glacial aquifers. The reason may be that the glacial deposits typically contain more organic carbon than the Paleozoic bedrock. Organic carbon plays a role in the redox reactions that cause arsenic (and iron) to be released from the aquifer matrix. Arsenic concentrations were not significantly different for different types of bedrock (sandstone, shale, sandstone/shale, or other). However, arsenic concentrations in bedrock wells were correlated with two well-construction characteristics; higher arsenic concentrations in bedrock wells were associated with (1) shorter open intervals and (2) deeper open intervals, relative to the water level.
The spatial distribution of arsenic concentrations was compared to hydrogeologic characteristics of Licking County. Elevated concentrations of arsenic (and iron) were associated with areas of flat topography and thick (greater than 100 feet),clay-rich glacial deposits. These characteristics are conducive to development of strongly reducing redox conditions, which can cause arsenic associated with iron oxyhydroxides in the aquifer matrix to be released to the groundwater.
Hydrogeologic characteristics conducive to the development of strongly reducing groundwater are relatively wide-spread in the western part of Licking County, which is part of the Central Lowland physiographic province. In this area, a thick layer of clay-rich glacial deposits obscures the bedrock surface and creates flat to gently rolling landscape with poorly developed drainage networks. In the eastern part of the county, which is part of the Appalachian Plateaus physiographic province, the landscape includes steep-sided valleys and bedrock uplands. In this area, elevated arsenic concentrations were detected in buried valleys but not in the bedrock uplands, where glacial deposits are thin or absent. The observation that elevated concentrations of arsenic (and iron) were more prevalent in the western part of Licking County is true for both glacial and bedrock aquifers.
In Licking County, thick, clay-rich glacial deposits (and elevated concentrations of arsenic) are associated with two hydrogeologic settings—buried valley and complex thick drift. Most wells in the buried-valley setting had low arsenic concentrations, but a few samples had very high concentrations (30–44 µg/L) and very reducing redox conditions (methanogenic and near-methanogenic). For wells in the complex-thick-drift setting, elevated arsenic concentrations are more prevalent, but the maximum concentration was lower (about 21 µg/L). Similar observations were made about arsenic concentrations in parts of southwestern Ohio.
The hydrogeologic settings and characteristics associated with arsenic in Licking County also exist in other parts of Ohio. The statewide extent of these characteristics roughly corresponds to areas where elevated concentrations of arsenic are known to exist. This preliminary conceptual model can be tested and revised as additional wells are sampled for arsenic.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155148","isbn":"978-1-4113-4008-4","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Thomas, M.A., 2016, Arsenic in groundwater of Licking County, Ohio, 2012—Occurrence and relation to hydrogeology:\nU.S. Geological Survey Scientific Investigations Report 2015–5148, 38 p., https://dx.doi.org/10.3133/sir20155148.","productDescription":"Report: vii, 38 p.; Table","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065867","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":318250,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5148/sir20155148_table2.xlsx","text":"Table 2. Water-quality and hydrogeologic data for 168 domestic wells in Licking County, Ohio, 2012.","size":"108 kb","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5148 Table 2."},{"id":318247,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5148/coverthb.jpg"},{"id":318248,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5148/sir20155148.pdf","text":"Report","size":"9.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5148"}],"country":"United States","state":"Ohio","county":"Licking County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.96875,\n 39.95185892663003\n ],\n [\n -82.96875,\n 40.50544628405211\n ],\n [\n -81.89208984375,\n 40.50544628405211\n ],\n [\n -81.89208984375,\n 39.95185892663003\n ],\n [\n -82.96875,\n 39.95185892663003\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Ohio Water Science Center
6480 Doubletree Ave
Columbus, OH 43229-1111
This study analyzes the active tectonics within the northwestern and southeastern extensions of the Pambak-Sevan-Syunik fault (PSSF), a major right-lateral strike-slip fault cutting through Armenia. Quantifying the deformations in terms of geometry, kinematics, slip rates and earthquake activity, using cosmogenic 3He, OSL/IRSL and radiocarbon dating techniques, reveal different behaviors between the two regions. Within the northwestern extension, in the region of Amasia, the PSSF bends to the west and splits into two main WNW–ESE trending reverse faults defining a compressional pop-up structure. We estimate an uplift rate and a shortening rate of 0.5 ± 0.1 mm/y and 1.4 ± 0.6 mm/y, respectively. This suggests that most of the ∼2 mm/y right lateral movement of the PSSF seems to be absorbed within the Amasia pop-structure. Within the southeastern extension, the PSSF shows signs of dying out within the Tsghuk Volcano region at the southernmost tip of the Syunik graben. There, the tectonic activity is characterized by a very slow NS trending normal faulting associated with a slight right-lateral movement. Slip rates analyses (i.e. vertical slip rate, EW stretching rate at 90° to the fault, and right-lateral slip rate of ∼0.2 mm/y, ∼0.1 mm/y and ∼0.05 mm/y, respectively) lead to the conclusion that the right lateral movement observed further north along the PSSF is mainly transferred within other active faults further west within the Karabagh (Hagari fault or other structures further northwestwards). Comparing our slip rates with those estimated from GPS data suggests that most of the deformation is localized and seismic, at least within the Tsghuk region. The geometrical and kinematic pattern observed within the two terminations of the PSSF suggests that the fault and its surrounding crustal blocks are presently rotating anticlockwise, as also observed within the GPS velocity field. This is consistent with the recent kinematic models proposed for the Caucasus-Kura-South Caspian region and brings a new insight into the present geodynamics of Armenia.
\n","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Quaternary International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Pergamon","publisherLocation":"Oxford","doi":"10.1016/j.quaint.2015.05.021","collaboration":"Geosciences Montpellier, UMR CNRS 5243, University of Montpellier II, France; Institute of Geological Sciences, National Academy of Sciences of Armenia, Armenia; Research Institute for Earth Sciences, Geological Survey of Iran, Iran; CRPG, UMR 7358, CNRS, Université de Lorraine, Vandoeuvre-lès-Nancy, France; Laboratoire Préhistoire et Quaternaire, Université de Lille 1, France; US Geological Survey, Denver Federal Center, Denver, Colorado, USA; Department of Earth and Atmospheric Sciences, University of Québec, Montréal, Canada","usgsCitation":"Ritz, J., Avagyan, A., Mkrtchyan, M., Nazari, H., Blard, P., Karakhanian, A., Philip, H., Balescu, S., Mahan, S.A., Huot, S., Munch, P., and Lamothe, M., 2016, Active tectonics within the NW and SE extensions of the Pambak-Sevan-Syunik fault: Implications for the present geodynamics of Armenia: Quaternary International, v. 395, p. 61-78, https://doi.org/10.1016/j.quaint.2015.05.021.","productDescription":"18 p.","startPage":"61","endPage":"78","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065629","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":318395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Armenia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 45,\n 41.31082388091818\n ],\n [\n 44.769287109375,\n 41.29431726315258\n ],\n [\n 44.6923828125,\n 41.244772343082076\n ],\n [\n 44.439697265625,\n 41.21172151054787\n ],\n [\n 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