The distribution of groundwater salinity was mapped for 31 oil fields and adjacent aquifers and summarized by 8 subregions across major oil-producing areas of central and southern California. The objectives of this study were to describe the distribution of groundwater near oil fields having total dissolved solids less than 10,000 milligrams per liter (mg/L) based on available data and to document where data gaps exist. Salinity was represented by the measured or calculated concentration of total dissolved solids (TDS) in samples of produced water obtained from petroleum wells and groundwater obtained from water wells. The water chemistry data were used to estimate the minimum depths of TDS greater than 3,000 mg/L and greater than 10,000 mg/L in areas near selected oil fields using historical water-chemistry data coupled with available well-location and construction information.
The 10,000 mg/L threshold, representing the highest level of TDS concentration of water that could be considered as a potential source of drinking water, was present in all but 4 (Jasmin, Kern Bluff, Kern Front, and Mount Poso) of the 31 individual oil fields. Among petroleum wells, the median TDS concentration of produced water ranged from 500 mg/L for the Jasmin field to 32,636 mg/L for the Elk Hills field. Among water wells, median TDS concentrations, either reported or calculated from specific conductance, ranged from 151 mg/L for wells within 2 miles of the Ten Section field to 9,750 mg/L for wells within 2 miles of the combined North and South Belridge fields.
In general, TDS across the eight geographic subregions increased with depth, but the relation of TDS with depth varied regionally. The most pronounced increases in TDS with depth were across the West Kern Valley Floor and West Kern Valley Margin subregions on the west side of the San Joaquin Valley, and in the vicinity of the Wilmington field in the Los Angeles Basin subregion; in these areas, relatively high TDS concentrations greater than 10,000 mg/L were present within the upper few hundred to several thousand feet of land surface. Total dissolved solids concentrations increased more gradually with depth in the Middle Kern Valley Floor subregion, in the South Kern Valley Margin subregion, in the vicinity of the Montebello and Santa Fe Springs fields in the Los Angeles Basin subregion, and in the Central Coast Basin subregion. The Kern Sierran Foothills and East Kern Valley Floor subregions, on the east side of the San Joaquin Valley, had the most gradual increases in TDS with depth. Fields in the East Kern Valley Floor subregion generally had groundwater and produced water with TDS less than 10,000 mg/L that extended to a large depth compared to most other subregions.
Overall, the west side of the San Joaquin Valley in Kern County and the Wilmington field in Los Angeles County generally have the highest TDS values and the shallowest depths to high TDS. High TDS at relatively shallow depths on the west side of the San Joaquin Valley may be because of a combination of natural conditions and anthropogenic factors. In the vicinity of the Wilmington field in the Los Angeles Basin subregion, high TDS at relatively shallow depths is attributable at least in part to seawater intrusion. Fields on the east side of the San Joaquin Valley in Kern County have the lowest TDS and greatest depths to TDS greater than 10,000 mg/L because of their geologic setting adjacent to Sierra Nevada recharge areas.
Reconnaissance salinity mapping was limited by several factors. The primary limitation was the lack of well-construction data for a significant number of water wells. Bottom perforation, well depth, or hole depth were not available for 35 percent of wells used for salinity mapping. A second limitation was variability in data quality. Total dissolved solids and specific conductance data were compiled from different data sources with varying degrees of documentation that ranged from comprehensive to very little or none. As a result, it was not always possible to assess the quality of the provided data with respect to either conditions at each well during sampling or the methodology used for sample collection and analysis. A third limitation was the lack of wells, either petroleum or water, and associated TDS data over large vertical intervals for some fields. As a result, the distribution of salinity and the depths at which TDS concentration exceeds the 3,000 and 10,000 mg/L thresholds could not always be precisely determined. This analysis highlights key gaps that need to be filled with additional analysis of other sources of information, such as borehole geophysical logs and new water sample or geophysical data collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185082","collaboration":"Prepared in cooperation with the California State Water Resources Control Board and the Bureau of Land Management","usgsCitation":"Metzger, L.F., and Landon, M.K., 2018, Preliminary groundwater salinity mapping near selected oil fields using historical water-sample data, central and southern California: U.S. Geological Survey Scientific Investigations Report 2018–5082, 54 p., https://doi.org/10.3133/sir20185082.","productDescription":"Report: vi, 54 p.; Data release","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-075027","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355849,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RN373C","linkHelpText":"Water and petroleum well data used for preliminary regional groundwater salinity mapping near selected oil fields in central and southern California"},{"id":355613,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5082/sir20185082_.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5082"},{"id":355612,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5082/coverthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.75622558593749,\n 33.280027811732154\n ],\n [\n -118,\n 33.280027811732154\n ],\n [\n -118,\n 36.5\n ],\n [\n -120.75622558593749,\n 36.5\n ],\n [\n -120.75622558593749,\n 33.280027811732154\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"We operated a bird banding station on the Naval Base Coronado, Remote Training Site, Warner Springs (RTSWS), in northeastern San Diego County, California, during the bird breeding season (spring/summer) from 2013 to 2017 and during migration (fall) from 2013 to 2016. The station was established in spring 2013 as part of the Monitoring Avian Productivity and Survivorship (MAPS) program and continued into the fall for the first 4 years as part of a long-term monitoring program for neotropical migratory birds.
We captured 705 individuals of 58 species during the MAPS/breeding season from 2013 to 2017 (12–13 days each year in April through August), 79 percent of which were newly banded during the MAPS season (555), 8 percent of which were recaptures banded in previous years (57), and 13 percent of which we released unbanded (64 hummingbirds and 29 other birds that were released or escaped prior to banding). Sixty individuals were captured more than once within a year during MAPS. Bird capture rate averaged 19 ± 1 captures per 100 net-hours (range 17–20) across 5 years. Annual species richness ranged from 28 (2017) to 42 (2014). The average species richness per day was highest in 2014 (9 ± 3) and lowest in 2016 (6 ± 2). Bushtit (Psaltriparus minimus) was the most abundant breeding species captured, followed by Spotted Towhee (Pipilo maculatus), Oak Titmouse (Baeolophus inornatus), Anna’s Hummingbird (Calypte anna), House Wren (Troglodytes aedon), Ash-throated Flycatcher (Myiarchus cinerascens), California Scrub-jay (Aphelocoma californica), Bewick’s Wren (Thryomanes bewickii), Acorn Woodpecker (Melanerpes formicivorus), California Towhee (Melozone crissalis), and Western Bluebird (Sialia mexicana). Each of these 11 breeding species accounted for at least 5 percent of captures in any 1 year. Fifty-seven percent of known-sex captures were female and 43 percent were male. Thirty-three percent of known-age captures were juveniles. Peaks in number of birds captured were in the first and last weeks of April, and the greatest number of species was captured in early May.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181112","usgsCitation":"Lynn, S., Hall, K.A., Madden, M.C., and Kus, B.E., 2018, Monitoring breeding and migration of neotropical migratory birds at Naval Base Coronado, Remote Training Site, Warner Springs, San Diego County, California, 5-year summary, 2013–17: U.S. Geological Survey Open-File Report 2018–1112, 98 p., https://doi.org/10.3133/ofr20181112.","productDescription":"viii, 98 p.","onlineOnly":"Y","ipdsId":"IP-096573","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":355910,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1112/coverthb.jpg"},{"id":355911,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1112/ofr20181112.pdf","text":"Report","size":"8.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1112"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Naval Base Coronado, Remote Training Site","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The Bureau of Reclamation (Reclamation) and the Washington State Department of Ecology (Ecology), working with the Yakima River Basin Water Enhancement Project Workgroup (composed of representatives of the Yakama Nation; Federal, State, county, and city governments; environmental organizations; and irrigation districts), developed the Yakima Basin Integrated Plan (Integrated Plan). The Integrated Plan identifies a comprehensive approach to water resources and ecosystem restoration improvements in the Yakima Basin to be implemented over a 30-year period. The Integrated Plan includes seven elements:
The first listed element, reservoir fish passage, will be expensive and take many years to accomplish. Reclamation and Ecology decided to look at new and innovative means to provide passage that could help reduce project cost and construction timing while maintaining survival rates of traditional upstream passage facilities. Reclamation contracted with the U.S. Geological Survey to do a study to evaluate the outcome of passage through one innovative fish-passage system at Cle Elum Dam, the first Integrated Plan reservoir fish-passage project being implemented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181116","collaboration":"Prepared in cooperation with the Yakama Nation, Bureau of Reclamation, and Washington State Department of Ecology","usgsCitation":"Kock, T.J., Evans, S.D., Hansen, A.C., Perry, R.W., Hansel, H.C., Haner, P.V., and Tomka, R.G., 2018, Evaluation of sockeye salmon after passage through an innovative upstream fish-passage system at Cle Elum Dam, Washington, 2017: U.S. Geological Survey Open-File Report 2018-1116, 30 p., https://doi.org/10.3133/ofr20181116.","productDescription":"vi, 30 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-096396","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":355935,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1116/coverthb.jpg"},{"id":355936,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1116/ofr20181116.pdf","text":"Report","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1116"}],"country":"United States","state":"Washington","otherGeospatial":"Cle Elum Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.13800048828125,\n 46.71256084516054\n ],\n [\n -120.42663574218749,\n 46.71256084516054\n ],\n [\n -120.42663574218749,\n 47.352780247239586\n ],\n [\n -121.13800048828125,\n 47.352780247239586\n ],\n [\n -121.13800048828125,\n 46.71256084516054\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
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Seattle, Washington 98115
Regional regression is a common tool used to estimate daily flow-duration curves (FDCs) at ungaged locations. In this report, several refinements to a particular implementation of the regional regression method for estimating FDCs are evaluated by consideration of different methodological options through a leave-one-out cross-validation procedure in the 19 major river basins of the conterminous United States. Regression analyses in this report are based on streamflow data from water years 1981–2013 (October 1, 1980 to September 30, 2013) from 1,378 mostly undisturbed watersheds. Linear regression using selected basin characteristics at 27 quantiles with nonexceedance probabilities ranging from 0.02 to 99.98 percent was applied. The regression computations were primarily by weighted least squares, with left-censored Gaussian regression solved by maximum likelihood in the presence of zero-valued quantiles.
The regional regression method as applied to the FDC estimation problem includes several methodological options that require determination of the better of two or more choices. The options considered in this report include (1) the setting of the maximum number of basin characteristics considered in the regression models for each region, (2) the method of placing the quantiles into groups (“flow regimes”) having the same basin characteristics used as independent variables, (3) the maximum number of candidate models retained from regressions at the single-quantile level that are retained for testing of the best model at the flow-regime scale, and (4) whether drainage area should be forced into the models. In all, 5 binary options were considered for most regions, resulting in 32 methodological combinations. Leave-one-out cross-validation predictions of FDC quantiles at each streamgage used in the study were used to evaluate compared options. Various performance measures were computed based on the predicted quantiles; these were combined by region and the methods were ranked for each measure.
Based on examination of the ranked methods compared across the measures, the following treatments produced the more accurate results: (1) using fewer basin characteristics (of the two options considered), (2) utilizing a variance of the unit FDC-based method of determining the flow regimes rather than fixed regimes, (3) retaining more models from the quantile-level regressions regime-wide consideration, and (4) forcing drainage area into the regression models. Results of analyses also indicate that performance varies more by region than by methodological option, with FDCs in arid regions and those with a large value of a measure of intraregional FDC heterogeneity being harder to predict, particularly with respect to the low-flow quantiles.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185072","collaboration":"Water Availability and Use Science Program","usgsCitation":"Over, T.M., Farmer, W.H., and Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States: U.S. Geological Survey Scientific Investigations Report 2018–5072, 34 p., https://doi.org/10.3133/sir20185072.","productDescription":"Report: vi, 34 p.; Appendixes 1–3; Data Release","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085859","costCenters":[{"id":344,"text":"Illinois Water Science 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\"}}]}\n\n\n","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin Ave.
Urbana, Illinois 61801
Juvenile Chinook salmon (Oncorhynchus tshawytscha) migrating through California's Sacramento-San Joaquin River Delta toward the Pacific Ocean face numerous challenges to their survival. The Yolo Bypass is a broad floodplain of the Sacramento River that floods in about 70 percent of years in response to large, uncontrolled runoff events. As one of the routes juvenile salmon may utilize, the Yolo Bypass has recently received attention for having potential benefit to rearing and migrating salmon. Consideration is being given to a plan to build a cut or “notch” in the Fremont Weir to increase juvenile salmon access to the Yolo Bypass. To help provide information about the potential benefit of such a plan, we analyzed data from a telemetry study conducted in February and March 2016 by the U.S. Geological Survey and California Department of Water Resources to estimate entrainment into and distribution of juvenile Chinook salmon within the Yolo Bypass, and to compare survival and travel time through the Yolo Bypass to other routes in the Delta. We also estimated juvenile Chinook salmon survival through three short reaches of the Sacramento River where the proposed California WaterFix North Delta Diversion intakes would divert water to export facilities to provide baseline information against which any effects of those intakes could be measured in the future.
We found that entrainment into the Yolo Bypass varied widely and was quite high only at the peak of the March 2016 flood. Spatial distribution of juvenile Chinook salmon within the Yolo Bypass was fairly even for fish entering the Yolo Bypass over the Fremont Weir, but increasingly skewed toward the east bank for fish released within the Yolo Bypass. Survival within Yolo Bypass was not significantly different for fish based on spatial distribution. Survival through the Delta for fish migrating through the Yolo Bypass was generally on par with the weighted survival through the Delta of fish migrating through all other routes. Survival was highest for fish remaining in the Sacramento River and lowest for those entrained into the Interior Delta via Georgiana Slough. Survival through the short section of the Sacramento River near the proposed North Delta Diversion intakes was high.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181118","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Pope, A.C., Perry, R.W., Hance, D.J., and Hansel, H.C., 2018, Survival, travel time, and utilization of Yolo Bypass, California, by outmigrating acoustic-tagged late-fall Chinook salmon: U.S. Geological Survey Open-File Report 2018-1118, 33 p., https://doi.org/10.3133/ofr20181118.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-097769","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":355940,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1118/ofr20181118.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1118"},{"id":355939,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1118/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yolo Bypass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 38\n ],\n [\n -121.4,\n 38\n ],\n [\n -121.4,\n 38.8\n ],\n [\n -122,\n 38.8\n ],\n [\n -122,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Two Donax obesulus and two Protothaca asperrima shells collected prior to the nuclear testing of the 1950's were micromilled at sub-seasonal resolution to yield new reservoir effect (ΔR) estimates for the coast of Peru. Shells from northern (4°40′S to 8°14′S) and central (13°52′S) Peru produced ΔR values of 123 ± 50 and 110 ± 49 years respectively. We found such values statistically indistinguishable from each other while reporting intra-annual ΔR variability along shells ontogeny in agreement with previously published regional ΔR values. This similarity suggests radiocarbon dating of short-lived (<1.5 years) mollusks shells is a useful tool for comparing marine radiocarbon signals. Additionally, our analysis of ΔR and δ18O changes along shells' ontogeny found a tenuous relationship between them. We are not the first one to report these phenomena in Peruvian upwelling, but we are the first to suggest that fast Lagrangian water mixing as a mechanism behind it.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2018.07.001","usgsCitation":"Etayo-Cadavid, M.F., Andrus, C.F., Jones, K.B., and Hodgins, G.W., 2018, Subseasonal variations in marine reservoir age from pre-bomb Donax obesulus and Protothaca asperrima shell carbonate: Chemical Geology, v. 526, p. 110-116, https://doi.org/10.1016/j.chemgeo.2018.07.001.","productDescription":"7 p.","startPage":"110","endPage":"116","ipdsId":"IP-022729","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468570,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2018.07.001","text":"Publisher Index Page"},{"id":357866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"526","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fcbe4b0fc368eb53982","contributors":{"authors":[{"text":"Etayo-Cadavid, Miguel F.","contributorId":16296,"corporation":false,"usgs":true,"family":"Etayo-Cadavid","given":"Miguel","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":746574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrus, C. Fred T.","contributorId":80568,"corporation":false,"usgs":true,"family":"Andrus","given":"C.","email":"","middleInitial":"Fred T.","affiliations":[],"preferred":false,"id":746575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Kevin B. 0000-0002-6386-2623 kevinjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6386-2623","contributorId":565,"corporation":false,"usgs":true,"family":"Jones","given":"Kevin","email":"kevinjones@usgs.gov","middleInitial":"B.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":746576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hodgins, Gregory W. L.","contributorId":67787,"corporation":false,"usgs":false,"family":"Hodgins","given":"Gregory","email":"","middleInitial":"W. L.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":746577,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196254,"text":"fs20183020 - 2018 - U.S. Geological Survey response to white-nose syndrome in bats","interactions":[],"lastModifiedDate":"2018-07-24T09:24:23","indexId":"fs20183020","displayToPublicDate":"2018-07-20T15:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3020","title":"U.S. Geological Survey response to white-nose syndrome in bats","docAbstract":"Since its discovery in 2007, the fungal disease known as white-nose syndrome (WNS) has killed more than six million bats. Ten of 47 bat species have been affected by WNS across 32 States and 5 Canadian Provinces. The cold-growing fungus (Pseudogymnoascus destructans) that causes WNS infects skin covering the muzzle, ears, and wings of hibernating bats. The fungus erodes deep into the vitally important skin of bat wings and fatally disrupts hibernation of bats through physical damage and energy depletion as they try to cope with infection.
U.S. Geological Survey (USGS) science has been critical in identifying the causal fungus, characterizing the effects of WNS, and tracking the fungus as it rapidly spreads through many populations of bats in North America. Early USGS research enhanced our understanding of how WNS affects individual bats and how the fungus persists in the environment. Today, USGS scientists are engaged in a nationwide response to WNS, in close coordination with our partners at the U.S. Fish and Wildlife Service (USFWS), National Park Service (NPS), and U.S. Forest Service (USFS).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183020","usgsCitation":"Hopkins, M.C., and Soileau, S.C., 2018, U.S. Geological Survey response to white-nose syndrome in bats: U.S. Geological Survey Fact Sheet 2018–3020,Associate Director, Ecosystems
U.S. Geological Suvey
12201 Sunrise Valley Drive
Mail Stop 300
Reston, VA 20192
Seismic rate increases often precede eruptions at volcanoes worldwide. However, many eruptions occur without such precursors. Additionally, identifying seismic rate increases near volcanoes with high levels of background seismicity is non-trivial and many periods of elevated seismicity occur without ensuing eruptions, limiting their usefulness for forecasting in some cases. Although these issues are commonly known, efforts to quantify them are limited. In this study, we consistently apply a common statistical tool, the β-statistic, to seismically monitored eruptions in Alaska of various styles to determine the overall prevalence of seismic rate anomalies immediately preceding eruptions. We find that 6 out of 20 (30%) eruptions have statistically significant precursory seismic rate increases. Of these 6 eruptions, 3 of them occur at volcanoes with relatively felsic compositions, repose periods >15 years, and VEI ≥ 3. Overall, our results confirm that seismic rate increases are common prior to larger eruptions at long dormant, “closed-system” volcanoes, but uncommon preceding smaller eruptions at more frequently active, “open-system” volcanoes with more mafic magmas. We also explore the rate of other anomalies not precursory to eruptions and investigate their origins. Some of these non-eruptive anomalies can be explained by aftershocks of regional seismic events, magmatic activity that did not lead to eruption, or unrest at other nearby volcanoes. Some open-system volcanoes have high non-eruptive anomaly rates and low pre-eruptive anomaly rates and are thus not amenable to forecasting based on earthquake catalogs. In this study, we find that 31% of anomalies lead to eruption. With continued calibration at more volcanoes, the β-statistic that we apply may be used more broadly to analyze future periods of seismic unrest at other volcanoes, properly placing such episodes into the context of the long-term background rate. These results may be useful for informing future eruption forecasts around the world, and the statistical tool may aid volcano observatories in identifying future seismic rate anomalies under changing network conditions.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2018.00100","usgsCitation":"Pesicek, J.D., Wellik, J., Prejean, S., and Ogburn, S.E., 2018, Prevalence of seismic rate anomalies preceding volcanic eruptions in Alaska: Frontiers in Earth Science, v. 6, 100, 15 p., https://doi.org/10.3389/feart.2018.00100.","productDescription":"100, 15 p.","ipdsId":"IP-096007","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":460875,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00100","text":"Publisher Index Page"},{"id":383077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.2265625,\n 60.261617082844616\n ],\n [\n -150.29296875,\n 61.52269494598361\n ],\n [\n -148.5791015625,\n 65.164578884019\n ],\n [\n -166.1572265625,\n 66.10716955858042\n ],\n [\n -172.3095703125,\n 63.68524808030715\n ],\n [\n -173.759765625,\n 60.326947742998414\n ],\n [\n -175.166015625,\n 51.699799849741936\n ],\n [\n -165.8056640625,\n 52.9883372533954\n ],\n [\n -153.4130859375,\n 58.37867853932655\n ],\n [\n -152.138671875,\n 60.174306261926034\n ],\n [\n -152.2265625,\n 60.261617082844616\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Pesicek, Jeremy D. 0000-0001-7964-5845","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":202042,"corporation":false,"usgs":true,"family":"Pesicek","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wellik, John 0000-0002-8099-5794","orcid":"https://orcid.org/0000-0002-8099-5794","contributorId":204753,"corporation":false,"usgs":true,"family":"Wellik","given":"John","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prejean, Stephanie 0000-0003-0510-1989 sprejean@usgs.gov","orcid":"https://orcid.org/0000-0003-0510-1989","contributorId":172404,"corporation":false,"usgs":true,"family":"Prejean","given":"Stephanie","email":"sprejean@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogburn, Sarah E. 0000-0002-4734-2118","orcid":"https://orcid.org/0000-0002-4734-2118","contributorId":204751,"corporation":false,"usgs":true,"family":"Ogburn","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809912,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198430,"text":"70198430 - 2018 - The influence of different deep-sea coral habitats on sediment macrofaunal community structure and function","interactions":[],"lastModifiedDate":"2018-08-06T14:35:24","indexId":"70198430","displayToPublicDate":"2018-07-20T14:35:17","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"The influence of different deep-sea coral habitats on sediment macrofaunal community structure and function","docAbstract":"Deep-sea corals can create a highly complex, three-dimensional structure that facilitates sediment accumulation and influences adjacent sediment environments through altered hydrodynamic regimes. Infaunal communities adjacent to different coral types, including reef-building scleractinian corals and individual colonies of octocorals, are known to exhibit higher macrofaunal densities and distinct community structure when compared to non-coral soft-sediment communities. However, the coral types have different morphologies, which may modify the adjacent sediment communities in discrete ways. Here we address: (1) how infaunal communities and their associated sediment geochemistry compare among deep-sea coral types (Lophelia pertusa, Madrepora oculata, and octocorals) and (2) do infaunal communities adjacent to coral habitats exhibit typical regional and depth-related patterns observed in the Gulf of Mexico (GOM). Sediment push cores were collected to assess diversity, composition, numerical abundance, and functional traits of macrofauna (>300 µm) across 450 kilometers in the GOM at depths ranging from 263–1,095 m. Macrofaunal density was highest in L. pertusa habitats, but similar between M. oculata and octocorals habitats. Density overall exhibited a unimodal relationship with depth, with maximum densities between 600 and 800 m. Diversity and evenness were highest in octocoral habitats; however, there was no relationship between diversity and depth. Infaunal assemblages and functional traits differed among coral habitats, with L. pertusa habitats the most distinct from both M. oculata and octocorals. These patterns could relate to differences in sediment geochemistry as L. pertusa habitats contained high organic carbon content but low proportions of mud compared to both M. oculata and octocoral habitats. Distance-based linear modeling revealed depth, mud content, and organic carbon as the primary factors in driving coral infaunal community structure, while geographic location (longitude) was the primary factor in functional trait composition, highlighting both the location and ecological differences of L. pertusa habitats from other coral habitats. Enhanced habitat structural complexity associated with L. pertusa and differences in localized hydrodynamic flow may contribute to the dissimilarities in the communities found among the coral types. Our results suggest a decoupling for infaunal coral communities from the typical depth-related density and diversity patterns present throughout soft-sediment habitats in the GOM, highlighting the importance of deep-sea corals in structuring unique communities in the nearby benthos.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.5276","usgsCitation":"Bourque, J.R., and Demopoulos, A.W., 2018, The influence of different deep-sea coral habitats on sediment macrofaunal community structure and function: PeerJ, v. 6, p. 1-32, https://doi.org/10.7717/peerj.5276.","productDescription":"e5276; 32 p.","startPage":"1","endPage":"32","ipdsId":"IP-094605","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468571,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.5276","text":"Publisher Index Page"},{"id":437820,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8KXD","text":"USGS data release","linkHelpText":"Sediment macrofaunal composition, sediment grain size, and taxa functional traits of multiple deep-sea coral habitats in the Gulf of Mexico, 2009-2014"},{"id":356203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.5,\n 27\n ],\n [\n -87.5,\n 27\n ],\n [\n -87.5,\n 30\n ],\n [\n -90.5,\n 30\n ],\n [\n -90.5,\n 27\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3f5e4b0f5d57878e97f","contributors":{"authors":[{"text":"Bourque, Jill R. 0000-0003-3809-2601 jbourque@usgs.gov","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":5452,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","email":"jbourque@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":741401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":196216,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":741402,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216334,"text":"70216334 - 2018 - Discontinuities and functional resilience of large river fish assemblages","interactions":[],"lastModifiedDate":"2020-11-12T14:50:43.846922","indexId":"70216334","displayToPublicDate":"2018-07-20T08:43:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Discontinuities and functional resilience of large river fish assemblages","docAbstract":"Functional composition of communities across scales is increasingly used to infer resilience of biotic communities to environmental change. To assess the relevance of these concepts to management of large rivers, analyses were applied to fish community data of the Upper Mississippi River. First, to evaluate whether there was evidence for structural patterns in fish size distributions, a discontinuity analysis was performed. Using long‐term fish data, consistent discontinuities were identified across 14 reaches, suggesting similar structuring processes occur throughout the nearly 1300 river kilometers represented by those reaches. Increased variability in species abundance in relation to proximity to edges of body size aggregations supports the discontinuity hypothesis that body size aggregations are structured by key processes. Functional richness and redundancy were quantified within and across identified scales for each of 14 river reaches. Diversity of trophic and spawning guilds was generally greater in the upstream reaches in comparison with downstream reaches, with the exception of the diversity of large‐bodied spawning guilds. Evidence of functional shifts in the composition of fishes occurred, but differed by size aggregations, likely reflecting scale‐specific resource availability. Redundancy of spawning and trophic groups across body size aggregations suggested downstream reaches of this system may be less resilient to disturbances and were weakly associated with reduced habitat diversity. These findings suggest that discontinuities in large river fish assemblages do occur and may provide indication of shifting resource availability. Further investigation of the underlying processes and scales that support resource availability will be critical to managing for resilience in large river ecosystems.
As the Nation’s principal earth-science information agency, the U.S. Geological Survey (USGS) is depended upon to collect accurate data and produce factual and impartial interpretive reports. Methods for data collection and analysis that were developed by the USGS have become standard techniques used by numerous Federal, State, and local agencies and by private enterprises. The USGS has implemented a program designed to ensure that all scientific work done by or for USGS Water Science Centers is done in accordance with a quality-assurance plan. The implementation of a groundwater quality-assurance plan will enhance groundwater data collected by the USGS. This report is a quality-assurance plan for groundwater activities conducted by the USGS Dakota Water Science Center and is meant to complement qualityassurance plans for surface-water and water-quality activities and similar plans for the Dakota Water Science Center and general project activities throughout the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181103","usgsCitation":"Valder, J.F., Carter, J.M., Robinson, S.M., Laveau, C.D., and Petersen, J.A., 2018, Quality-assurance plan for groundwater activities, U.S. Geological Survey Dakota Water Science Center: U.S. Geological Survey Open-File Report 2018–1103, 28 p., https://doi.org/10.3133/ofr20181103.","productDescription":"v, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-097126","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":355869,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1103/ofr20181103.pdf","text":"Report","size":"1.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1103"},{"id":355868,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1103/coverthb.jpg"}],"contact":"Director, Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
The giant gartersnake (Thamnophis gigas) is a semi-aquatic species of snake precinctive to the Central Valley of California. Because the Central Valley has experienced a substantial loss of wetland habitat, giant gartersnake populations are largely found in aquatic habitats associated with rice agriculture. In dry years, less water may be available for rice agriculture, resulting in less aquatic habitat, which could have cascading effects on giant gartersnake populations. We present 2 years of data intended to examine how the demography of giant gartersnakes is affected by the availability of aquatic habitat on the landscape (2016–17), along with 2 years of (sparse) preliminary data (2014–15) collected as part of an earlier radio-telemetry study on giant gartersnake movement behavior. We sampled agricultural canals near rice fields for giant gartersnakes at 8 sites distributed throughout the Sacramento Valley. Five sites were sampled from 2014–17, and 3 sites were sampled from 2015–17. In total, we made 2,995 captures of 1,011 snakes from 2014–17. We used these capture data to fit a multi-site Jolly-Seber model to estimate the abundance of giant gartersnakes as well as the daily and annual probability of capture at each site. We used remotely sensed Landsat data to characterize the extent of flooded rice fields surrounding each site in each year. In addition, we collected 175 females from 2014–17 and delivered them to the Sacramento Zoo for health assessments and reproductive exams.
The abundance of giant gartersnakes varied among sites, and abundance estimates were more precise in 2016 and 2017 when sampling effort was greatest. The probability of a giant gartersnake being captured at least once in a year was higher in 2016 and 2017 than 2014 and 2015, and recaptures of snakes marked the previous year were highest in 2016 and 2017 as well. Mean annual apparent survival was estimated to be 0.40 but varied among sites from a low of 0.14 to a high of 0.63. Five sites had diverse size distributions that included abundant sub-adult and large adult female snakes. One site had a truncated size distribution with few large adult female snakes, and 2 sites had mostly large adult-sized snakes and few small individuals. Both the probability a female was gravid and a female’s litter size were positively related to the female’s snout-vent length. Somatic growth rates varied more among years than among sites, and females grew faster (in millimeters per day) than male snakes.
The proportion of the landscape around each site under active rice cultivation fluctuated over time (generally between 60–90 percent of the landscape was active rice growing, although this proportion was lower for some sites in some years), and variation in rice growing was asynchronous among sites. This study demonstrates that intensive demographic sampling enables estimation of several key demographic variables at each study site. Continued sampling would allow for investigating potential relationships between the amount of rice growing at a site and demographic parameters such as growth, survival, and reproduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181114","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Rose, J.P., Ersan, J.S.M., Reyes, G.A., Gustafson, K.B., Fulton, A.M., Fouts, K.J., Wack, R.F., Wylie, G.D., Casazza, M.L., and Halstead, B.J., 2018, Findings from a preliminary investigation of the effects of aquatic habitat (water) availability on giant gartersnake (Thamnophis gigas) demography in the Sacramento Valley, California, 2014–17: U.S. Geological Survey Open-File Report 2018–1114, 48 p., https://doi.org/10.3133/ofr20181114.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-097068","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":355890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1114/coverthb.jpg"},{"id":355891,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1114/ofr20181114.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1114"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33,\n 38.8333\n ],\n [\n -121.5833,\n 38.8333\n ],\n [\n -121.5833,\n 39.6667\n ],\n [\n -122.33,\n 39.6667\n ],\n [\n -122.33,\n 38.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The California State Water Resources Control Board initiated a regional monitoring program in July 2015 to determine where and to what degree groundwater quality may be adversely impacted by oil and gas development activities. A key issue in the implementation of the regional groundwater monitoring program is that each year, detailed characterization work can be done in only a few of California’s 487 onshore oil and gas fields. The first step in monitoring groundwater near petroleum development is to prioritize oil and gas fields using consistent statewide analysis of available data that indicate potential risk of groundwater to oil and gas development.
The U.S. Geological Survey compiled data for four factors that characterize the intensity of petroleum resource development and proximity to groundwater resources: petroleum-well density, volume of water injected in oil fields, vertical proximity of groundwater resources to oil and gas resource development, and water-well density. An overall priority ranking for each field was determined by computing summary metrics, analyzing statewide distributions of summary metrics for all oil and gas fields, using those distributions to define relative categories of potential risk for each factor, and combining relative risk rankings for different factors into an overall priority ranking. This preliminary assessment does not represent an evaluation of groundwater risk to oil and gas development, which needs to be based on detailed analysis and data related to development activities including well stimulation, well integrity issues, produced water ponds, and underground injection.
Based on the prioritization analysis, 22 percent (107 fields) of the total number of oil and gas fields in California were ranked as high priority, 23 percent (114 fields) as moderate priority, and 55 percent (266 fields) as low priority. These results indicate that between 100 and 200 oil fields are principal candidates for the next steps in the regional monitoring program. The land area of fields that ranked high priority accounted for 41 percent of the total field area (3,392 square miles). More than half of the high priority fields were in the southern San Joaquin Valley and the Los Angeles Basin. Some of the larger fields tended to have higher rankings because of greater intensity of petroleum development, sometimes coupled with proximity to groundwater resources.
The U.S. Geological Survey, in collaboration with the California State Water Resources Control Board and other agencies, has begun regional groundwater monitoring near oil and gas fields selected for study through the California Oil, Gas, and Groundwater cooperative program. Groundwater monitoring includes compiling, analyzing, and developing three-dimensional visualizations of existing data, including geological frameworks, salinity mapping, identification of surface features that could potentially affect groundwater quality, locations and depths of oil/gas and water wells, cataloging well-construction integrity issues, and evaluating the directions of groundwater flow. These analyses are required to determine where existing wells should be monitored and where new monitoring wells may need to be drilled.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185065","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Davis, T.A., Landon, M.K., and Bennett, G.L., 2018, Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources: U.S. Geological Survey Scientific Investigations Report 2018–5065, 115 p.,\nhttps://doi.org/10.3133/sir20185065.","productDescription":"Report: viii, 115 p.; Tables 1-6; Appendix Tables 1-7","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073272","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437823,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2DV3","text":"USGS data 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\"}}]}","contact":"Streams within the Coeur d’Alene River drainage basin in northern Idaho have been extensively affected by historical mining activities and are subject to ongoing remedial actions as part of the Bunker Hill Mining & Metallurgical Complex Superfund Site. The U.S. Geological Survey (USGS) operates 12 real-time streamgages and collects surface-water-quality samples two to four times annually at 20 sites in the Spokane River and Coeur d’Alene River drainage basins. These data are used by the U.S. Environmental Protection Agency (USEPA) to monitor cleanup progress and to support decisions related to implementing remedial actions throughout the basin. USGS data collection highlights from water year 2017 include: • A rain-on-snow event in March 2017 produced high streamflows and flooding in the basin. • The March event mobilized high concentrations of total metals (cadmium, lead, zinc, and others) in the Coeur d’Alene River near Cataldo, at Rose Lake, and near Harrison; these concentrations were among the highest that have been measured at these sites during flood events sampled by the USGS. • Total lead and dissolved zinc and cadmium concentrations decreased in Canyon Creek in 2017 when compared with water years 2007–16; in contrast, concentrations of dissolved zi
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181113","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Zinsser, L.M., 2018, Coeur d’Alene Basin Environmental Monitoring Program, surface water, northern Idaho—Annual data summary, water year 2017: U.S. Geological Survey Open-File Report 2018-1113, 15 p., https://doi.org/10.3133/ofr20181113.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-098458","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":355896,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1113/ofr20181113.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1113"},{"id":355895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1113/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur d’Alene Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 47.25\n ],\n [\n -115.5,\n 47.25\n ],\n [\n -115.5,\n 47.75\n ],\n [\n -117,\n 47.75\n ],\n [\n -117,\n 47.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
Maps of extreme value, horizontal component geoelectric field amplitude are constructed for the Pacific Northwest United States (and parts of neighboring Canada). Multidecade long geoelectric field time series are calculated by convolving Earth surface impedance tensors from 71 discrete magnetotelluric survey sites across the region with historical 1‐min (2‐min Nyquist) geomagnetic variation time series obtained from two nearby observatories. After fitting statistical models to 1‐min geoelectric amplitudes realized during magnetic storms, extrapolations are made to estimate threshold amplitudes that are only exceeded, on average, once per century. One hundred‐year geoelectric exceedance amplitudes range from 0.06 V/km at a survey site in western Washington State to 9.47 V/km at a site in southeast British Columbia; 100‐year geoelectric exceedance amplitudes equal 7.10 V/km at a site north of Seattle and 2.28 V/km at a site north of Portland. Systematic and random errors are estimated to be less than 20%, much less than site‐to‐site differences in geoelectric amplitude that arise from site‐to‐site differences in surface impedance. Maps of 100‐year exceedance amplitudes are compared with the peak geoelectric amplitudes realized during the March 1989 magnetic superstorm; it is noted that some storms of relatively modest intensity can generate localized geoelectric fields of relatively high amplitude. The geography of geoelectric hazard across the Pacific Northwest is closely related to known geologic and tectonic structures.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018SW001844","usgsCitation":"Love, J.J., Lucas, G.M., Kelbert, A., and Bedrosian, P.A., 2018, Geoelectric hazard maps for the Pacific Northwest: Space Weather, v. 16, no. 8, p. 1114-1127, https://doi.org/10.1029/2018SW001844.","productDescription":"13 p.","startPage":"1114","endPage":"1127","ipdsId":"IP-097864 ","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468573,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018sw001844","text":"Publisher Index Page"},{"id":359152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Pacific Northwest","volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","scienceBaseUri":"5be16511e4b0b3fc5cf3ffbc","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":750774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":202808,"corporation":false,"usgs":true,"family":"Lucas","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":750775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":750776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":750777,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226824,"text":"70226824 - 2018 - Linking the Ukinrek 1977 maar-eruption observations to the tephra deposits: New insights into maar depositional processes","interactions":[],"lastModifiedDate":"2021-12-14T12:44:30.908574","indexId":"70226824","displayToPublicDate":"2018-07-19T06:39:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Linking the Ukinrek 1977 maar-eruption observations to the tephra deposits: New insights into maar depositional processes","docAbstract":"The Ukinrek Maars erupted 30 March to 9 April 1977, forming two maars, a line of small pit craters and a tephra blanket extending to ~2 km from the vents. We combine photographic and written observations with stratigraphic analysis to reconstruct the eruption. The eruption began with very low (a few meters high) fountaining from small craters above an inferred east-west-trending dike, creating local scoria/spatter agglomerate ramparts with a sandy matrix. The eruption very quickly (in minutes to hours) centered on the West Maar. The West Maar eruption lasted 1–2 days, starting and ending with phreatomagmatic explosions with weak phreato-Strombolian activity in between. Initial explosions formed a 30-m-wide crater, enlarged by crater-wall collapse, and columns as high as 6500 m. Phreato-Strombolian activity produced ~72% of the erupted volume, including a small spatter cone and a scoria blanket around the vent. A final explosion series emplaced a lithic-rich breccia as ballistic blocks, possibly as the northern half of the final crater collapsed into the southern vent area. The East Maar formed over the last nine days of the eruption and represents ~93% of the total volume (4.6 × 106 m3) of the Ukinrek eruption. Initial explosions were probably shallower than 10–20 m but most of the eruption occurred from explosions at 50–60 m below the pre-eruptive surface, with evidence of explosions to 90 m depth only at the very end of the eruption. The East Maar eruption mostly produced columns of lapilli, ash, and steam and the deposits are mostly fallout. Winds blew fallout mostly to the north for the first 5–6 days and to the south for the last three days of the eruption. Wind-directed pyroclastic density currents collapsed from the column, producing fines-rich layers within the coarser fallout. Sporadic explosions produced weak density currents in the first few days and lithic-and juvenile-block-rich breccias in the last few days of the eruption. We interpret that collapse of the crater walls made a slurry that in part provided the water for phreatomagmatic interaction. Explosions came from depths <90 m below the pre-eruptive surface except for a few explosions at the end of the eruption, with most occurring at <70 m depth. The East Maar crater was open to 40–60 m depth throughout most of the eruption, so the explosions were rarely, if ever, deeper than 30 m below the crater floor. Thus, we infer there is no classic, well-formed diatreme structure below the maar. Collapse of the East Maar crater walls provided a supply of water-saturated sediment for much of the phreatomagmatic activity, which came from two vents that did not migrate much, if at all, during the eruption. The Ukinrek Maars deposits were nearly entirely emplaced by fallout, rather than density currents, from explosions and low columns.
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2017 to December 2017. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2017 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
Significant reductions in silver and copper concentrations in sediment and M. petalum occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above silver (Ag) or near copper (Cu) regional background concentrations. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2017, concentrations of silver and copper in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.
Analyses of the benthic community structure of a mudflat in south San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2017), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2017. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2017. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like M. petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or anoxia. The reproductive mode of most species that were present in 2017 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2017 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181107","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Barasch, D., Slabic, A., and Luoma, S.N., 2018, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017: U.S. Geological Survey Open-File Report 2018–1107, 71 p., https://doi.org/10.3133/ofr20181107.","productDescription":"vi, 71 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-098497","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":416196,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416195,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416197,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416194,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":416193,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":355780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1107/ofr20181107_.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1107"},{"id":355779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1107/coverthb.jpg"}],"country":"United States","state":"California","city":"Palo Alto","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.27371215820312,\n 37.315567502511044\n ],\n [\n -121.827392578125,\n 37.315567502511044\n ],\n [\n -121.827392578125,\n 37.655557695625056\n ],\n [\n -122.27371215820312,\n 37.655557695625056\n ],\n [\n -122.27371215820312,\n 37.315567502511044\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Hydro-Eco Interactions Branch
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
National Research Program
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape-based regressions are also used to understand macroscale variability of lake nutrients, clarity, and productivity (hereafter referred to as nutrient-productivity). Predictions from both models are used to inform eutrophication management globally. To date, these two classes of models are generally conducted separately, which ignores the known dependencies among nutrient-productivity variables. We present a statistical model that integrates nutrient-productivity and landscape-based regressions—where lake nutrients, productivity, and clarity variables are modeled jointly. We fitted a joint nutrient-productivity model to over 7000 lakes with three nutrients (total phosphorus, total nitrogen, nitrate concentrations), chlorophyll a concentrations, and Secchi disk depth as response variables and landscape features as predictor variables. Because lakes in different regions respond to landscape features differently, we focused our analysis on two subregions with different dominant land uses, the agricultural Midwest and the forested Northeast U.S. Predictive performance was enhanced by modeling nutrient-productivity variables jointly. We also found strong evidence that nutrient-productivity variables were coupled, and that only nitrate may be decoupled from other nutrient-productivity variables in the forested region. We speculate that these regional differences may be related to differences in the strength of biogeochemical cycles and stoichiometric controls between these regions. Jointly modeling nutrient-productivity variables in lakes effectively integrates the two dominant approaches for studying lakes nutrient-productivity relationships and provides novel insight into macroscale patterns of the coupling of nutrients, chlorophyll, and water clarity in lakes.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.10944","usgsCitation":"Wagner, T., and Schliep, E.M., 2018, Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales: Limnology and Oceanography, v. 63, no. 6, p. 2372-2383, https://doi.org/10.1002/lno.10944.","productDescription":"12 p.","startPage":"2372","endPage":"2383","ipdsId":"IP-093432","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468575,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10944","text":"Publisher Index Page"},{"id":395248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schliep, Erin M.","contributorId":171525,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":832536,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206816,"text":"70206816 - 2018 - Cadmium isotope fractionation during coal combustion: Insights from two U.S. coal-fired power plants","interactions":[],"lastModifiedDate":"2019-11-22T15:17:13","indexId":"70206816","displayToPublicDate":"2018-07-18T15:07:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Cadmium isotope fractionation during coal combustion: Insights from two U.S. coal-fired power plants","docAbstract":"Coal combustion, one of the principal energy sources of electricity in the United States, produces over 100 million tons of coal combustion products (CCPs) per year in the U.S. The reuse and disposal of CCPs has the potential to release toxic trace elements, including cadmium (Cd), into the environment. In this study, we investigated CCPs, including bottom ash (BA), economizer fly ash (EFA), and fly ash (FA), as well as feed coal (FC) and pulverized coal (PC) collected from two U.S. coal-fired power plants in New Mexico and Ohio with different coal supplies. The New Mexico plant uses high volatile C bituminous, low-sulfur coals mined from the San Juan Basin (Cretaceous Fruitland Formation) and the Ohio plant uses high volatile A bituminous, high-sulfur central Appalachian Basin coals (Upper Pennsylvanian Monongahela Formation). Mineralogical and elemental analysis showed that these CCP samples consist of ∼70% amorphous Al-Si-rich glasses and ∼30% mineral phases of quartz (SiO2) and mullite (Ai6Si2O13). The Cd isotope compositions (δ114Cd, normalized to NIST Cd standard 3108) of FA and EFA samples (ranging from −0.51 to +0.47‰) are distinctively heavier than those of BA samples (−0.75 to −0.52‰) in both power plants. We interpret this Cd isotope difference as a result of Cd condensation from the gas phase during flue gas cooling, instead of evaporation of Cd phase during coal combustion. Cd condensation is the main process to generate the isotopically heavy Cd signatures that preferentially partition on the fine FA particles. We also investigated Cd isotope compositions in different leachate products from a series of batch-leaching experiments with these CCPs, using diluted acetic acid, hydroxyl ammonium chloride, hydrogen peroxide followed by ammonium acetate, and 5% nitric acid, as a possible means to identify CCP-released Cd in the environment. Unusually and significantly heavier Cd isotope compositions were observed in each leachate of FA samples (+1.10 to +7.09‰), which fall far outside from the range of Cd isotope ratios observed in natural soils and rocks, but less so for the EFA samples (−0.43 to +1.18‰). Such an observation is consistent with the interpretation that isotopically heavy Cd preferentially partitions on the fine FA particles after coal combustion and is readily to be released during these leaching experiments. This study demonstrates that high-temperature coal combustion can lead to a very large degree of fractionation of Cd isotopes that can be used as a unique tracer for identifying anthropogenic metal inputs in the environment. The major Cd isotope fractionation process occurs as the Cd gas phase condenses on fine FA particles during the flue gas cooling stage after coal combustion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2018.06.007","usgsCitation":"Fouskas, F., Lin, M., Engle, M.A., Ruppert, L.F., Geboy, N., and Costa, M.A., 2018, Cadmium isotope fractionation during coal combustion: Insights from two U.S. coal-fired power plants: Applied Geochemistry, v. 96, p. 100-112, https://doi.org/10.1016/j.apgeochem.2018.06.007.","productDescription":"13 p.","startPage":"100","endPage":"112","ipdsId":"IP-087791","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2018.06.007","text":"Publisher Index Page"},{"id":369496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Ohio","volume":"96","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fouskas, Fotio","contributorId":220837,"corporation":false,"usgs":false,"family":"Fouskas","given":"Fotio","email":"","affiliations":[],"preferred":false,"id":775910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Ma","contributorId":57896,"corporation":false,"usgs":true,"family":"Lin","given":"Ma","email":"","affiliations":[],"preferred":false,"id":775911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geboy, Nicholas J. ngeboy@usgs.gov","contributorId":3860,"corporation":false,"usgs":true,"family":"Geboy","given":"Nicholas J.","email":"ngeboy@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costa, Matthew A.","contributorId":220838,"corporation":false,"usgs":false,"family":"Costa","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":775915,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197647,"text":"sir20185077 - 2018 - Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","interactions":[],"lastModifiedDate":"2018-07-20T10:23:35","indexId":"sir20185077","displayToPublicDate":"2018-07-18T12:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5077","displayTitle":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","title":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","docAbstract":"As the population of the Triangle area in central North Carolina increases, the demand for good quality drinking water from streams and lakes within the upper Neuse and upper Cape Fear River Basins also increases. The Triangle area includes Raleigh, Cary, Research Triangle Park, Durham, Chapel Hill, and the surrounding communities. The U.S. Geological Survey examined temporal trends in water quality for 13 stream and 8 reservoir sites in the two basins on the basis of data collected during 1989–2013. Trends were analyzed using a fitted time-series model that accommodated for shifting trends and variations in streamflow at multiple time scales. Seventeen water-quality properties and constituents were evaluated, including specific conductance and major ions, nutrients, and organic carbon. Suspended solids and suspended sediment were examined at stream sites; chlorophyll a and Secchi transparency were examined at lake sites.
The investigation identified considerable changes in population, land cover, streamflow, and selected water-quality characteristics in the study area over the 25-year period. Specific conductance and concentrations of calcium, magnesium, potassium, sodium, and chloride tended to increase throughout the study area. Area-wide increases were also observed for organic nitrogen. Trends for other water-quality constituents varied on a more site-specific basis because of local watershed influences such as changes to wastewater-treatment processes and substantial shifts from rural to urban land use. Water quality is influenced by multiple, often confounding factors, and thus may change in a non-uniform manner over time. Long-term monitoring is critical for tracking these trends and ensuring resiliency of water supplies for the future. Results from this study may promote the understanding of water-quality response to a growing population and land-cover changes and can assist water-resource managers in the Triangle area in tracking progress toward water-quality goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185077","collaboration":"Prepared in cooperation with the Triangle Area Water Supply Monitoring Project Steering Committee","usgsCitation":"Giorgino, M.J., Cuffney, T.F., Harden, S.L., and Feaster, T.D., 2018, Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013: U.S. Geological Survey Scientific Investigations Report 2018–5077, 67 p., https://doi.org/10.3133/sir20185077.","productDescription":"Report: viii, 67 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095343","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":355697,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5077/coverthb.jpg"},{"id":355698,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5077/sir20185077.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5077"},{"id":355835,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MS3S17","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets for trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989-2013"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Fear River basin, Neuse River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.79919433593749,\n 35.02099970111467\n ],\n [\n -77.84912109375,\n 35.02099970111467\n ],\n [\n -77.84912109375,\n 36.32397712011264\n ],\n [\n -79.79919433593749,\n 36.32397712011264\n ],\n [\n -79.79919433593749,\n 35.02099970111467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
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Columbia, SC 29210
The purpose of this study was to evaluate the effects of irrigation and cover crops as conservation practices on water quality in groundwater and streams. Bucks Branch, a stream in the Nanticoke River watershed in southwestern Delaware, was identified as having one of the highest concentrations of nitrate in all surface-water sites sampled by the Delaware Department of Natural Resources and Environmental Control (DNREC). The study site is on two adjacent fields bordering Bucks Branch, one that has used irrigation since 2000 and one with dryland farming; both under conservation tillage and long-term rotation of corn, soybean, and small grain crops. A streamgage was installed near the study site fields to measure streamflow and water quality. The study area is typical of farming practices and environmental conditions throughout much of the intensively farmed agricultural land of the Coastal Plain of Delaware and surrounding parts of Maryland. Monitoring was conducted from January 2014 through June 2016. Corn was grown on both fields during the two growing seasons of the study period, and cover crops were planted before or shortly after harvest on both fields. During the second year of data collection, the effects of radish and rye grass cover crops on nutrient transport were studied.
The combined results from data collected for this study show that water and nitrate moved below the root zone year round when soil moisture was high, especially after significant rainfall and frequently after irrigation. Soil water sampled 2 to 3 weeks after nutrients were applied had nitrate concentrations greater than 50 milligrams per liter as nitrogen (mg/L as N) and may be a significant source of nitrate to groundwater. Whereas recharge containing elevated nitrate concentrations also occurred under the dryland field, it was less frequent and of lower concentration than recharge under the irrigated field.
Nitrate was present in all groundwater samples from these sites. Groundwater estimated to have recharged within 10 years or less had higher median concentrations of nitrate than in older water samples. The oldest groundwater encountered was over 30 years old, and had traveled along the longest, deep flowpaths from upland fields to the stream. The median nitrate concentration was 18 mg/L as N in younger water (less than 10 years old) beneath the irrigated field, compared to about 10 mg/L as N in younger water beneath the dryland field. Samples from the shallow upland wells in both study fields showed little, if any, evidence of denitrification. Several samples from deeper wells and from wells near forested riparian zone wetlands that border both fields did show partial denitrification.
A mixing model estimated that between 12 and 22 percent of the nitrate discharging to the stream was lost through uptake and denitrification upstream of the streamgage on Bucks Branch. Continuous data collected at this site and evidence of denitrification in the surface-water samples showed a greater potential for loss of nitrate during the warmer months than the colder months. This pattern was similar to that seen below the streamgage at the most downstream site in the watershed.
A mixed cover crop of radishes and rye was planted prior to removal (radishes) and just after harvest (rye) of the corn crop on the irrigated field. Rye grass was planted shortly after crop harvest on the dryland field. Cover crop biomass samples collected while radishes were growing and after they were killed by freezing temperatures indicates that the early planted radish crop effectively scavenged available nitrogen from the soil. Whereas radish biomass initially held more nitrogen than rye, at 55 to 8 pounds per acre, respectively, leaching of inorganic nitrate following radish die-off was minimal. Soil-water nitrate concentrations during the cover-crop growing period were lower than during the growing season prior to planting of the cover crop. There also was an increase in soil fertility and dissolved organic nitrate in samples of soil water that was likely related to increased soil microbial metabolism. Results indicate that cover crops stored plant nutrients over the winter and did not increase shallow groundwater concentrations of nitrate.
Although conservation practices such as cover crops and nutrient management have been applied to these fields, there was still significant leaching of nitrate to groundwater, especially under the irrigated field. This will likely continue to be a challenge in this area and other parts of the Coastal Plain where soil moisture capacity is relatively low and managing irrigation around rainfall is difficult. Cover crops, when planted in standing corn, are one practice that can effectively pull nitrate from below the root zone to the top layer of soil, thus limiting the amount of potential nitrate leaching to groundwater. Irrigation management that would lower average soil moisture conditions during the growing season also could potentially limit nitrogen transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185020","collaboration":"Prepared in cooperation with the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey","usgsCitation":"Denver, J.M., Soroka, A.M., Reyes, B., Lester, T.R., Bringman, D.A., and Brownley, M.S., 2018, Monitoring the water-quality response of agricultural conservation practices in the Bucks Branch watershed, Sussex County, Delaware, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5020, 43 p., https://doi.org/10.3133/sir20185020.","productDescription":"ix, 43 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088518","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":355731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5020/sir20185020.pdf","text":"Report","size":"8.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5020"},{"id":355732,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77H1HK5","text":"USGS data release","description":"USGS data release","linkHelpText":"Chemistry analysis results for groundwater, soil-pore water, soil and plant material collected from two agricultural sites in the Nanticoke and Chester River watersheds on the Delmarva Peninsula from 2013 to 2016"},{"id":355730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5020/coverthb.jpg"}],"country":"United States","state":"Delaware","county":"Sussex County","otherGeospatial":"Bucks Branch Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.6833,\n 38.6833\n ],\n [\n -75.6167,\n 38.6833\n ],\n [\n -75.6167,\n 38.7333\n ],\n [\n -75.6833,\n 38.7333\n ],\n [\n -75.6833,\n 38.6833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228