Fines, defined here as grains or particles, less than 75 μm in diameter, exist nearly ubiquitously in natural sediment, even those classified as coarse. Macroscopic sediment properties, such as compressibility, which relates applied effective stress to the resulting sediment deformation, depend on the fabric of fines. Unlike coarse grains, fines have sizes and masses small enough to be more strongly influenced by electrical interparticle forces than by gravity. These electrical forces acting through pore fluids are influenced by pore fluid chemistry changes. Macroscopic property dependence on pore fluid chemistry must be accounted for in sediment studies involving subsurface flow and sediment stability analyses, as well as in engineered flow situations such as groundwater pollutant remediation, hydrocarbon migration, or other energy resource extraction applications. This study demonstrates how the liquid limit‐based electrical sensitivity index can be used to predict sediment compressibility changes due to pore fluid chemistry changes. Laboratory tests of electrical sensitivity, sedimentation, and compressibility illustrate mechanisms linking microscale and macroscale processes for selected pure, end‐member fines. A specific application considered here is methane extraction via depressurization of gas hydrate‐bearing sediment, which causes a dramatic pore water salinity drop concurrent with sediment being compressed by the imposed effective stress increase.
The Colorado River Basin (CRB) drains 246,000 square miles and includes parts of California, Colorado, Nevada, New Mexico, Utah, and Wyoming, and all of Arizona (Basin States). This report contains water-use estimates by category of use for drainage basins (Hydrologic Unit Code 8; HUC‑8) within the CRB from 1985 to 2010, at 5-year intervals. Estimates for public supply, domestic, commercial, industrial, irrigation, livestock, mining, aquaculture, hydroelectric and thermoelectric power, and wastewater returns are tabulated as (1) water withdrawals from groundwater or surface‑water sources of fresh or saline quality, (2) water delivered for domestic use, (3) wastewater returns and instream use (hydroelectric), and (4) consumptive use, or water that is consumed (USGS definition) and not available for immediate reuse. Water transported outside of the CRB (interbasin transfers) is not included as part of withdrawals and are not accounted for in any category of use within the CRB.
Total withdrawals in the CRB (excluding interbasin transfers) averaged about 17 million acre-feet (maf) from 1985 to 2010, peaked at about 17.76 maf in 2000, and reached their lowest levels of 16.43 maf in 1990. Interbasin transfers to serve mostly public-supply and irrigation needs outside of the CRB are reported for 2000, 2005, and 2010 only, and averaged 5.40 maf. More surface water was used in the CRB than groundwater, averaging about 78 percent of total withdrawals, and its use increased less than 2 percent from 1985 to 2010, while groundwater withdrawals decreased about 12 percent. From 1985 to 2010, surface water averaged 98 percent of withdrawals in the upper CRB, and about 59 percent in the lower CRB. Nearly all withdrawals were freshwater, but some saline groundwater was used for mining and self-supplied industrial.
Interbasin transfers have a large effect on flows in the Colorado River and are listed in this report separately with no explanation of how the water is used outside of the CRB. There are 34 interbasin transfers that conveyed an estimated 5.83, 5.20, and 5.18 maf out of the CRB in 2000, 2005, and 2010, respectively. The largest interbasin transfers are in the lower CRB and convey surface water (Colorado River water) to southern California; these accounted for 80 to 84 percent of total interbasin transfers in the CRB from 2000 to 2010. Intrabasin transfers are conveyances of surface water that cross drainage basin or State boundaries in the CRB, but the water does not leave the CRB. There are many intrabasin transfers in the CRB, but this report lists 11 that are mostly in the State of Colorado. The largest is the Central Arizona Project (CAP), through which more than 1.00 maf of water was provided to irrigate nearly 1 million acres in Maricopa, Pinal, and Pima Counties, as well as provide municipal water for Phoenix and Tucson, Arizona, during 2000, 2005, and 2010. In 2010, interbasin and intrabasin transfers accounted for 24 and 11 percent of the total water withdrawals in CRB, respectively, with the larger volumes being conveyed out of the lower CRB.
Total population in the CRB increased from 4.56 to 9.44 million people from 1985 to 2010. Most of those people were in the lower CRB, with 86 percent of the total in 1985, and 90 percent of the total in 2010. Total public-supply withdrawals in the CRB provided most people with their potable water, and averaged about 1.63 maf from 1985 to 2010, ranging from about 1.07 maf in 1985 to about 2.10 maf in 2010, when it peaked. Most of public-supply withdrawals occurred in the lower CRB, ranging from 87 to 91 percent of total public-supply withdrawals in the CRB over the 25 years. Total domestic use, comprised of public-supply deliveries and self-supply domestic withdrawals, increased more than 90 percent from 1985 to 2010, from about 0.80 maf to about 1.54 maf. Domestic daily per-capita use rates in the CRB ranged from about 144 (1985) to about 121 (2000) gallons (gal) per‑capita between 1985 and 2010. When comparing domestic daily per-capita rates for the upper and lower CRB, people in the lower CRB, on average, used less water for domestic purposes at 128 gal per-capita daily (1985–2010), while those in the upper CRB for the same time period averaged 133 gal per-capita daily. The trend in daily per-capita use rates for the entire CRB fluctuated between the reporting years, but decreased overall, indicating that more people used less water in 2010 than in 1985, likely due to improved infrastructure, conservation, and improvements to water using appliances in homes and businesses.
Irrigation accounted for most total withdrawals in the CRB, excluding instream use for hydroelectric power and interbasin transfers, averaging 85 percent from 1985 to 2010. Far more surface water than groundwater was used for irrigation in both the upper and lower CRB, but in the upper CRB, it accounted for an average of more than 98 percent of the total withdrawals (1985–2010), whereas in the lower CRB, surface-water withdrawals for irrigation averaged 61 percent of total withdrawals. On average, the upper CRB accounted for 56 percent of total irrigated acres, and the irrigation systems in the upper CRB trended towards more efficient sprinkler systems from 1985 to 2010. Long-term drought in the CRB substantially decreased the amount of streamflow available for irrigation. Increases in micro-irrigation acres, which can have efficiencies that exceed 90 percent and require 20–50 percent less water than sprinkler systems, likely contributed to reduced withdrawals in the lower CRB.
For thermoelectric power, total withdrawals, including the use of reclaimed wastewater, were greater in the upper CRB from 1985 through 2005. In 2010, the lower CRB exceeded the upper by only 11,000 acre-feet. On average, thermoelectric consumptive use accounted for about 80 percent of the total withdrawals; however, consumptive-use data in the upper CRB was incomplete. Surface water was the primary source in the upper CRB and groundwater was the primary source in the lower CRB. In the CRB overall, water withdrawals for thermoelectric generation has decreased since 2000, except for groundwater withdrawals in the lower CRB. Power generation at thermoelectric plants was greater in the upper CRB from 1985 to 2000, and after 2005 the difference in power generation was small; however, the upper CRB continued to have more power generation. In both the upper and lower CRB, power generation increased from 1985 to 2005.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185049","usgsCitation":"Maupin, M.A., Ivahnenko, T., and Bruce, B., 2018, Estimates of water use and trends in the Colorado River Basin, Southwestern United States, 1985–2010: U.S. Geological Survey Scientific Investigations Report 2018–5049, 61 p., https://doi.org/10.3133/sir20185049.","productDescription":"Report: ix, 61 p.; Data release","numberOfPages":"75","onlineOnly":"Y","ipdsId":"IP-074683","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":354013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5049/sir20185049.pdf","text":"Report","size":"18.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5049"},{"id":354012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5049/coverthb.jpg"},{"id":355338,"rank":3,"type":{"id":30,"text":"Data 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U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
The Cosumnes River watershed requires a 57–64 percent reduction in loads to meet the new Delta methylmercury (MeHg) total maximum daily load allocation, established by the Central Valley Regional Water Quality Control Board. Because there are no large point sources of MeHg in the watershed, the focus of MeHg load reductions will fall upon non-point sources, particularly the expansive wetlands considered to be a primary source of MeHg in the region. Few management practices have been implemented and tested in order to meet load reductions in managed wetlands, but recent efforts have shown promise. This project examines a treatment approach to reduce MeHg loads to the Sacramento-San Joaquin River Delta by creating open-water deep cells with a small footprint at the downstream end of wetlands to promote net demethylation of MeHg and to minimize MeHg and Hg loads exiting wetlands at the Cosumnes River Preserve. Specifically, the deep cells were were located immediately up gradient of the wetland’s outflow weir and were deep enough (75–91 centimeter depth) to be vegetation-free. The topographic and hydrologic structure of each treatment wetland was modified to include open-water deep cells so that the removal of aqueous MeHg might be enhanced through (1) particle settling, (2) photo-degradation, and (3) benthic microbial demethylation. These deep cells were, therefore, expected to clean MeHg from surface water prior to its discharge to the Cosumnes River and the downstream Delta.
Our goal was to test whether the implementation of the deep cells within wetlands would minimize MeHg and total Hg export. Further, we sought to test whether continuous flow-through hydrology, would lower MeHg concentrations in resident biota, compared to traditional wetland management operations. The dominant practice in seasonal wetlands management is the “fill-and-maintain” approach, in which wetlands are filled with water and the water levels maintained without substantial draining until drawdown. Our approach was to create and characterize replicate treatment wetland complexes, in conjunction with monitoring of hydrologic, biologic, and chemical indicators of MeHg exposure for two full annual cycles within winter-spring flooded seasonal wetlands. In addition to the creation of deep cells within treatment wetlands, hydrology was manipulated so that there was a constant flow-through of water, while the control wetlands utilized the fill-and-maintain approach. Specifically, the treatment wetlands were maintained in a flow-through manner, while the control wetlands were maintained in a fill-and-maintain manner from September through May, to test the hypothesis that the flow of water through the seasonal wetland can lower fish bioaccumulation through dilution of MeHg-concentrated water within the wetland by constant inflows of water into the wetland.
The major tasks of this study included: (1) field design and implementation, (2) water and wetland management, (3) hydrologic monitoring and water quality sampling, (4) MeHg export and load estimates, (5) caged fish experiments for examining MeHg bioaccumulation, (6) site and process characterization to improve understanding and transferability of results, (7) adaptive management, transferability, and outreach, and (8) reporting of results and conclusions. This report summarizes the key findings of this study, which focuses on MeHg load estimates from control and treatment wetlands, quantification of three MeHg removal mechanisms (particulate settling, benthic demethylation, and photo-demethylation) in the deep cells within the treatment wetlands, and MeHg bioaccumulation in wetland fishes.
Key findings include:
Hydro-Eco Interactions Branch
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
https://water.usgs.gov
Chemicals such as metals and organics (polychlorinated biphenyl [PCBs], polybrominated diphenyl ethers [PBDEs], polycyclic aromatic hydrocarbons [PAHs], and phthalates) continue to enter Puget Sound, western Washington, from point sources (such as industrial and municipal outfalls) and combined sewer outfalls and non-point sources (such as stormwater runoff). Runoff during storm events has been identified as a major source of contamination entering Puget Sound and has been implicated in the degradation of nearshore habitats and biota. Metals, organic chemicals, and other pollutants are known to accumulate in sediments such as those present along the shoreline of Puget Sound. In addition to chemical contaminants, small plastic particles (known as microplastics), found in marine waters of Puget Sound and suspected of being in aquatic sediments, are a potential concern because they can be ingested by animals and are suspected of transporting sorbed chemicals such as PCBs and metals.
The Stormwater Work Group of Puget Sound (SWG) (composed of State and municipal stormwater permittees, and other stakeholders) developed a strategy to address sediment conditions in the nearshore environment of Puget Sound. As part of this strategy, the SWG developed a regional stormwater monitoring strategy designed to inform monitoring requirements in National Pollutant Discharge Elimination System (NPDES) stormwater permits issued by the Washington State Department of Ecology (Ecology). The monitoring program is referred to as the Stormwater Action Monitoring (SAM).
The overall focus of the work described in this report is to address one of the goals of SAM, which is to characterize the status, spatial extent, and quality of Puget Sound sediment chemicals in the nearshore urban areas. The nearshore urban areas are defined as areas parallel to established Urban Growth Areas (UGAs) using a spatially balanced probabilistic Generalized Random Tessellation Stratified (GRTS) sampling design. One of the benefits of the GRTS sampling design used for this study is that it allows one to efficiently extrapolate from a relatively small number of sampled nearshore sites to the entire nearshore shoreline within the 2011 defined UGA boundaries of Puget Sound. In addition to characterizing nearshore sediment chemical concentrations, this study also characterized the abundance of microplastics in the nearshore sediment.
A total of 41 randomly selected sites were sampled throughout Puget Sound in summer and early autumn of 2016. All sampling sites were located at 6 feet below the Mean Lower Low Water line. The top 2–3 centimeters of sediment were collected using a boat-mounted, pre-cleaned stainless-steel box corer. All chemical samples were sieved to 2 millimeters and placed in appropriate containers for chemical analysis for PCBs, PBDEs, PAHs, phthalates, metals, total organic carbon, and grain size. Pre-sieved sediment samples were stored in glass containers for microplastic analysis. Nearshore sediment chemical concentrations were summarized using numerous statistical approaches to examine the minimum, mean, and maximum concentrations for each of the compounds analyzed and to compare the results to criteria and other nearshore and marine sediment studies.
The GRTS sampling design also allowed the authors to assess the percentage of the UGA nearshore environment that did not meet established standards or criteria for each chemical analyzed. Additionally, regression and machine learning statistical analyses were used to examine relations between measured chemical concentrations, and land cover and geologic features at multiple scales within the watersheds adjacent to sampling sites. The influence of marine hydrodynamic factors on nearshore sediment chemical concentrations was statistically evaluated with nonparametric methods by assigning each sampling site to one of five nearshore drift cell types based on its location. The Puget Sound shoreline can be divided into segments, referred to as drift cells, based on the movement of sediment along the shore by waves. Each drift cell type has a unique influence on nearshore sediment transport.
The nearshore sediment chemical concentrations for organics and metals generally were low, and in most cases less than Washington State criteria. The concentrations of some PAHs were greater than the criteria, but these exceedances were limited to one or two sites. The results of the probabilistic study design determined that, for the PAHs examined, 96 percent or more of the 1,344 km of shoreline represented by this study had concentrations less than any established criteria. For the remaining organics (PCBs and PBDEs), the probabilistic study design indicates that more than 98 percent of shoreline examined had concentrations less than criteria or proposed standards. For the metals, the results of the study indicate that 100 percent of the nearshore sediment had concentrations less than the criteria. The relations between sediment organic and metal concentrations, and adjacent watershed land cover and the particle size of the samples, were determined to be weakly related. Although weakly related, the particle size of the sediment in a sample typically explained more of the variation in metal concentrations than organics. While the measured watershed attributes adjacent to the sampling sites and sediment size of the samples were weakly related to chemical concentrations, they were significantly related to unique drift cells along the shoreline of Puget Sound known as drift cells. Each drift cell represents a long-term directional transport of sediment from its source to its depositional zone. Sediment chemical concentrations were significantly higher in drift cells with limited sediment movement compared to those with higher sediment transport energy.
Microplastics in the nearshore sediment ranged from 0.02 to 0.65 pieces per gram of sediment, with a mean of 0.19 pieces per gram of sediment, and were dominated by small fibers (355–1,000 micrometers). Like chemical concentrations, microplastics concentrations in the nearshore sediment were poorly related to watershed land cover. Although not significantly different, microplastics concentrations generally were higher in the low energy drift cells compared to the high energy drift cells.
The results of this study provide a statistically valid status assessment of current nearshore sediment chemical conditions throughout Puget Sound in those areas adjacent to defined UGAs. In addition to the study findings of relatively low concentrations of PCBs, PBDEs, PAHs, phthalates, and metals, the study design provides a statistically valid tool for evaluating changes in these compounds over time if future nearshore sediment assessments are done. Furthermore, the assessment of microplastic abundance represents the first study of its kind that can be used as a benchmark for future evaluations. The results of this study will help inform Ecology in the implementation of monitoring requirements as part of its NPDES stormwater permitting process.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185076","collaboration":"Prepared in cooperation with the Washington State Department of Ecology, Stormwater Action Monitoring (SAM) Program","usgsCitation":"Black, R.W., Barnes, A., Elliot, C., and Lanksbury, J., 2018, Nearshore sediment monitoring for the Stormwater Action Monitoring (SAM) Program, Puget Sound, western Washington: U.S. Geological Survey Scientific Investigations Report 2018-5076, 53 p., https://doi.org/10.3133/sir20185076.","productDescription":"Report: vii, 53 p.; Appendixes: 1-6","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095908","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":355365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5076/coverthb.jpg"},{"id":355367,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5076/sir20184076_appendixes01-06.xlsx","text":"Appendixes 1–6","size":"73 KB xlsx","description":"SIR 2018-5076 Appendixes 01-06"},{"id":355366,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5076/sir20185076.pdf","text":"Report","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5076"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.09033203124999,\n 46.51351558059737\n ],\n [\n -120.82763671875,\n 46.51351558059737\n ],\n [\n -120.82763671875,\n 49.993615462541136\n ],\n [\n -125.09033203124999,\n 49.993615462541136\n ],\n [\n -125.09033203124999,\n 46.51351558059737\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The North American Great Lakes are a vital natural resource that provide fish and wildlife habitat, as well as drinking water and waste assimilation services for millions of people. Tributaries to the Great Lakes receive chemical inputs from various point and nonpoint sources, and thus are expected to have complex mixtures of chemicals. However, our understanding of the co‐occurrence of specific chemicals in complex mixtures is limited. To better understand the occurrence of specific chemical mixtures in the US Great Lakes Basin, surface water from 24 US tributaries to the Laurentian Great Lakes was collected and analyzed for diverse suites of organic chemicals, primarily focused on chemicals of concern (e.g., pharmaceuticals, personal care products, fragrances). A total of 181 samples and 21 chemical classes were assessed for mixture compositions. Basin wide, 1664 mixtures occurred in at least 25% of sites. The most complex mixtures identified comprised 9 chemical classes and occurred in 58% of sampled tributaries. Pharmaceuticals typically occurred in complex mixtures, reflecting pharmaceutical‐use patterns and wastewater facility outfall influences. Fewer mixtures were identified at lake or lake‐influenced sites than at riverine sites. As mixture complexity increased, the probability of a specific mixture occurring more often than by chance greatly increased, highlighting the importance of understanding source contributions to the environment. This empirically based analysis of mixture composition and occurrence may be used to focus future sampling efforts or mixture toxicity assessments.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.4041","usgsCitation":"Elliott, S.M., Brigham, M.E., Kiesling, R.L., Schoenfuss, H.L., and Jorgenson, Z.G., 2018, Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes: Integrated Environmental Assessment and Management, v. 14, no. 4, p. 509-518, https://doi.org/10.1002/ieam.4041.","productDescription":"10 p.","startPage":"509","endPage":"518","ipdsId":"IP-087836","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":355324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92,\n 40\n ],\n [\n -74,\n 40\n ],\n [\n -74,\n 49.5\n ],\n [\n -92,\n 49.5\n ],\n [\n -92,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5b46e550e4b060350a15d0c7","contributors":{"authors":[{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":738929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jorgenson, Zachary G.","contributorId":69476,"corporation":false,"usgs":false,"family":"Jorgenson","given":"Zachary","email":"","middleInitial":"G.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":738930,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199079,"text":"70199079 - 2018 - Fungal loop transfer of nitrogen depends on biocrust constituents and nitrogen form","interactions":[],"lastModifiedDate":"2018-08-31T10:27:03","indexId":"70199079","displayToPublicDate":"2018-06-22T10:26:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Fungal loop transfer of nitrogen depends on biocrust constituents and nitrogen form","docAbstract":"Besides performing multiple ecosystem services individually and collectively, biocrust constituents may also create biological networks connecting spatially and temporally distinct processes. In the fungal loop hypothesis rainfall variability allows fungi to act as conduits and reservoirs, translocating resources between soils and host plants. To evaluate the extent to which biocrust species composition and nitrogen (N) form influence loops, we created a minor, localized rainfall event containing 15NH4+ and 15NO3−. We then measured the resulting δ15N in the surrounding dry cyanobacteria- and lichen-dominated crusts and grass, Achnatherum hymenoides, after 24 h. We also estimated the biomass of fungal constituents using quantitative PCR and characterized fungal communities by sequencing the 18S rRNA gene. We found evidence for the initiation of fungal loops in cyanobacteria-dominated crusts where 15N, from 15NH4+, moved 40 mm h−1 in biocrust soils with the δ15N of crusts decreasing as the radial distance from the water addition increased (linear mixed effects model (LMEM)): R2 = 0.67, F2,12 = 11, P = 0.002). In cyanobacteria crusts, δ15N, from 15NH4+, was diluted as Ascomycota biomass increased (LMEM: R2 = 0.63, F2,8 = 6.8, P = 0.02), Ascomycota accounted for 82 % (±2.8) of all fungal sequences, and one order, Pleosporales, comprised 66 % (±6.9) of Ascomycota. The seeming lack of loops in moss-dominated crusts may stem from the relatively large moss biomass effectively absorbing and holding N from our minor wet deposition event. The substantial movement of 15NH4+ may indicate a fungal preference for the reduced N form during amino acid transformation and translocation. We found a marginally significant enrichment of δ15N in A. hymenoides leaves but only in cyanobacteria biocrusts translocating 15N, offering evidence of links between biocrust constituents and higher plants. Our results suggest that minor rainfall events may initiate fungal loops potentially allowing constituents, like dark septate Pleosporales, to rapidly translocate N from NH4+ over NO3− through biocrust networks.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/bg-15-3831-2018","usgsCitation":"Aanderud, Z.T., Smart, T.B., Wu, N., Taylor, A.S., Zhang, Y., and Belnap, J., 2018, Fungal loop transfer of nitrogen depends on biocrust constituents and nitrogen form: Biogeosciences, v. 15, no. 12, p. 3831-3840, https://doi.org/10.5194/bg-15-3831-2018.","productDescription":"10 p.","startPage":"3831","endPage":"3840","ipdsId":"IP-091786","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468633,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-15-3831-2018","text":"Publisher Index Page"},{"id":356987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-22","publicationStatus":"PW","scienceBaseUri":"5b98a2a3e4b0702d0e842fa8","contributors":{"authors":[{"text":"Aanderud, Zachary T.","contributorId":176977,"corporation":false,"usgs":false,"family":"Aanderud","given":"Zachary","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":743959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Trevor B.","contributorId":207495,"corporation":false,"usgs":false,"family":"Smart","given":"Trevor","email":"","middleInitial":"B.","affiliations":[{"id":37545,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USA","active":true,"usgs":false}],"preferred":false,"id":743960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Nan","contributorId":207496,"corporation":false,"usgs":false,"family":"Wu","given":"Nan","email":"","affiliations":[{"id":37546,"text":"Xinjiang Institute of Ecology and Geography, Key Laboratory of Biogeography and Bioresource in Arid Land, Chinese Academy of Sciences,","active":true,"usgs":false}],"preferred":false,"id":743961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Alexander S.","contributorId":207497,"corporation":false,"usgs":false,"family":"Taylor","given":"Alexander","email":"","middleInitial":"S.","affiliations":[{"id":37545,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USA","active":true,"usgs":false}],"preferred":false,"id":743963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Yuanming","contributorId":173232,"corporation":false,"usgs":false,"family":"Zhang","given":"Yuanming","email":"","affiliations":[{"id":27200,"text":"Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China","active":true,"usgs":false}],"preferred":false,"id":743962,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743958,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196364,"text":"sir20185038 - 2018 - Extraction and development of inset models in support of groundwater age calculations for glacial aquifers","interactions":[],"lastModifiedDate":"2018-06-22T10:10:22","indexId":"sir20185038","displayToPublicDate":"2018-06-22T09:15:00","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":"2018-5038","title":"Extraction and development of inset models in support of groundwater age calculations for glacial aquifers","docAbstract":"The U.S. Geological Survey developed a regional model of Lake Michigan Basin (LMB). This report describes the construction of five MODFLOW inset models extracted from the LMB regional model and their application using the particle-tracking code MODPATH to simulate the groundwater age distribution of discharge to wells pumping from glacial deposits. The five study areas of the inset model correspond to 8-digit hydrologic unit code (HUC8) basins. Two of the basins are tributary to Lake Michigan from the east, two are tributary to the lake from the west, and one is just west of the western boundary of the Lake Michigan topographic basin. The inset models inherited many of the inputs to the parent LMB model, including the hydrostratigraphy and layering scheme, the hydraulic conductivity assigned to bedrock layers, recharge distribution, and water use in the form of pumping rates from glacial and bedrock wells. The construction of the inset models entailed modifying some inputs, most notably the grid spacing (reduced from cells 5,000 feet on a side in the parent LMB model to 500 feet on a side in the inset models). The refined grid spacing allowed for more precise location of pumped wells and more detailed simulation of groundwater/surface-water interactions. The glacial hydraulic conductivity values, the top bedrock surface elevation, and the surface-water network input to the inset models also were modified. The inset models are solved using the MODFLOW–NWT code, which allows for more robust handling of conditions in unconfined aquifers than previous versions of MODFLOW. Comparison of the MODFLOW inset models reveals that they incorporate a range of hydrogeologic conditions relative to the glacial part of the flow system, demonstrated by visualization and analysis of model inputs and outputs and reflected in the range of ages generated by MODPATH for existing and hypothetical glacial wells. Certain inputs and outputs are judged to be candidate predictors that, if treated statistically, may be capable of explaining much of the variance in the simulated age metrics. One example of a predictor that model results indicate strongly affects simulated age is the depth of the well open interval below the simulated water table. The strength of this example variable as an overall predictor of groundwater age and its relation to other predictors can be statistically tested through the metamodeling process. In this way the inset models are designed to serve as a training area for metamodels that estimate groundwater age in glacial wells, which in turn will contribute to ongoing studies, under the direction of the U.S. Geological Survey National Water Quality Assessment, of contaminant susceptibility of shallow groundwater across the glacial aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185038","usgsCitation":"Feinstein, D.T., Kauffman, L.J., Haserodt, M.J., Clark, B.R., and Juckem, P.F., 2018, Extraction and development of inset models in support of groundwater age calculations for glacial aquifers: U.S. Geological Survey Scientific Investigations Report 2018–5038, 96 p., https://doi.org/10.3133/sir20185038.","productDescription":"Report: viii, 96 p.; Data release","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081404","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":355245,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5038/sir20185038.pdf","text":"Report","size":"39.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5038"},{"id":355246,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F76D5R5V","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-NWT inset models from the regional Lake Michigan Basin Model in support of groundwater age calculations for glacial aquifers"},{"id":355244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5038/coverthb.jpg"}],"country":"United States","state":"Illinois, Indiana, Michigan, Wisconsin","otherGeospatial":"Lake Michigan Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.615234375,\n 40.413496049701955\n ],\n [\n -81.5185546875,\n 40.413496049701955\n ],\n [\n -81.5185546875,\n 46.830133640447386\n ],\n [\n -90.615234375,\n 46.830133640447386\n ],\n [\n -90.615234375,\n 40.413496049701955\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Midwest Water Science Center
8505 Research Way
Middleton, WI 53562
(608) 828–9901
We assessed hematozoa infection in Spectacled Eiders (Somateria fischeri) at two areas in Alaska. No Haemoproteus or Plasmodium species were detected. Leucocytozoon prevalence was 6.5% for adults across sites and 41.9% for juveniles sampled in the Arctic, providing evidence for local transmission. All Leucocytozoon haplotypes were previously detected in waterfowl.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-01-012","usgsCitation":"Reed, J.A., Sexson, M.G., Smith, M.M., Schmutz, J.A., and Ramey, A.M., 2018, Evidence for haemosporidian parasite infections in Spectacled Eiders (Somateria fischeri) sampled in Alaska during the breeding season: Journal of Wildlife Diseases, v. 54, no. 4, p. 877-880, https://doi.org/10.7589/2018-01-012.","productDescription":"4 p.","startPage":"877","endPage":"880","ipdsId":"IP-094145","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437847,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CDBRDC","text":"USGS data release","linkHelpText":"Blood Parasite Infection Data from Spectacled Eiders (Somateria fischeri), Alaska (USA), 2008-2012"},{"id":355316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"54","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e552e4b060350a15d0cf","contributors":{"authors":[{"text":"Reed, John A. 0000-0002-3239-6906 jareed@usgs.gov","orcid":"https://orcid.org/0000-0002-3239-6906","contributorId":127683,"corporation":false,"usgs":true,"family":"Reed","given":"John","email":"jareed@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sexson, Matthew G. 0000-0002-1078-0835 msexson@usgs.gov","orcid":"https://orcid.org/0000-0002-1078-0835","contributorId":5544,"corporation":false,"usgs":true,"family":"Sexson","given":"Matthew","email":"msexson@usgs.gov","middleInitial":"G.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":738845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":738847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":738848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197859,"text":"70197859 - 2018 - Sediment supply to San Francisco Bay, water years 1995 through 2016: Data, trends, and monitoring recommendations to support decisions about water quality, tidal wetlands, and resilience to sea level rise","interactions":[],"lastModifiedDate":"2018-06-22T10:42:50","indexId":"70197859","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Sediment supply to San Francisco Bay, water years 1995 through 2016: Data, trends, and monitoring recommendations to support decisions about water quality, tidal wetlands, and resilience to sea level rise","docAbstract":"Knowledge of the status and trends of sediment supply to San Francisco Bay is critically\nimportant for management decisions about dredging, marsh restoration, flood control,\ncontaminants, water clarity (in relation to primary production), and sea level rise. Several sitespecific\nstudies of sediment supply to San Francisco Bay have been conducted, but no synthesis\nof recent studies is available. The purpose of this report is to synthesize the best available data\nand knowledge to answer a few of the key study questions related to sediment supply to the Bay\n(listed below).\nThis synthesis report was prepared jointly by the Regional Monitoring Program for Water\nQuality in San Francisco Bay (RMP) and the U. S. Geological Survey (USGS) with funding\nfrom both organizations. The project is meant to be a step in the development of a more\ncomprehensive sediment management and monitoring strategy for the Bay.\n\nWhat are the magnitudes and sources of fine and coarse sediment transported to San Francisco Bay?\n\nNet sediment supply to San Francisco Bay from terrestrial sources during the most recent 22-\nyear period (water years [WY] 1995-2016) was 1.9+/-0.8 Mt/yr (1 Mt is one million metric\ntonnes or 1 billion kilograms). Sixty-three percent of the sediment supply was from small\ntributaries that drain directly to the Bay. Net supply from the Central Valley (measured at\nMallard Island) was 37% of the total supply. Bedload supply, after accounting for dredging,\nremovals, storage in flood control channels, and errors in measurements was indistinguishable\nfrom zero. For a 30-year “climate normal” reference period of WY 1981-2010 (a period assumed\nto be representative of current climatic conditions), we estimate the total sediment supply would\nbe 2.0 Mt/yr of which 70% would come from small tributaries. The delivery points are Mallard\nIsland for sediment from the Delta and the head of tide of each small tributary or outfall for\nsediment from the small tributaries.\nThe finding that, on average, small tributaries have supplied more sediment to the Bay than the\nDelta is important but not new (McKee et al., 2013). During the Gold Rush and perhaps through\nto the 1980s, 80% or more of the supply was estimated to be from the Central Valley\n(Porterfield, 1980). But land and water management have continued to evolve (Krone, 1996) and\nthe sediment wave associated with the Gold Rush has diminished (Schoellhamer, 2011). In\naddition, the coastal mountains of California and around the Bay are steep, tectonically active\nand composed of relatively erodible marine sedimentary and metasedimentary rocks, in contrast\nto the Central Valley watershed that is dominated by highly indurated granitic, metasedimentary,\nand metavolcanic rocks in the western-facing slopes of the Sierra Nevada Mountains\n(McKee et al., 2013). Also, water management is quite different between the Central Valley\nrivers and small tributaries. About 48% of the Central Valley watershed is upstream from dams\nthat are designed to capture, delay and diminish discharge from spring snowmelt and so\neliminate or damp many of the peak flows that are normally crucial for sediment transport.\nAnother factor contributing to the importance of small tributaries for sediment supply is the way\nthat they deliver sediment. Annual discharge from small tributaries is very small in comparison\nto the volume of the Bay (around one-fifth of a Bay volume on average), and the load that small\ntributaries supply is delivered through hundreds of channels and outfalls via wetland sloughs to\nthe mudflats on the margin of the Bay. Therefore, the majority of this sediment delivered from\nBay Area small tributaries is more likely to be trapped in these tidal channels or the margins of\nthe Bay. In contrast, supply from the Central Valley enters the Bay through one large river\nchannel at the head of the estuary (functionally adjacent to Mallard Island, near Pittsburg, CA)\nwith an average annual discharge volume that is more than twi","language":"English","publisher":"San Francisco Estuary Institute","usgsCitation":"Schoellhamer, D., McKee, L., Pearce, S., Kauhanen, P., Saloman, M., Dusterhoff, S., Grenier, J.L., Marineau, M.D., and Trowbridge, P., 2018, Sediment supply to San Francisco Bay, water years 1995 through 2016: Data, trends, and monitoring recommendations to support decisions about water quality, tidal wetlands, and resilience to sea level rise, xi, 80 p.","productDescription":"xi, 80 p.","ipdsId":"IP-091659","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355288,"type":{"id":15,"text":"Index Page"},"url":"https://www.sfei.org/documents/sediment-supply-san-francisco-bay"},{"id":355292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay-Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.64862060546875,\n 37.391981943533544\n ],\n [\n -121.74362182617188,\n 37.391981943533544\n ],\n [\n -121.74362182617188,\n 38.238180119798635\n ],\n [\n -122.64862060546875,\n 38.238180119798635\n ],\n [\n -122.64862060546875,\n 37.391981943533544\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e553e4b060350a15d0d5","contributors":{"authors":[{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKee, Lester","contributorId":205882,"corporation":false,"usgs":false,"family":"McKee","given":"Lester","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearce, Sarah","contributorId":205883,"corporation":false,"usgs":false,"family":"Pearce","given":"Sarah","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauhanen, Pete","contributorId":205884,"corporation":false,"usgs":false,"family":"Kauhanen","given":"Pete","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saloman, Micha","contributorId":205885,"corporation":false,"usgs":false,"family":"Saloman","given":"Micha","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738782,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dusterhoff, Scott","contributorId":205886,"corporation":false,"usgs":false,"family":"Dusterhoff","given":"Scott","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738783,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grenier, J. Letitia","contributorId":205887,"corporation":false,"usgs":false,"family":"Grenier","given":"J.","email":"","middleInitial":"Letitia","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738784,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738778,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trowbridge, Philip","contributorId":205888,"corporation":false,"usgs":false,"family":"Trowbridge","given":"Philip","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738785,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197861,"text":"70197861 - 2018 - Tracing enhanced oil recovery signatures in casing gases from the Lost Hills oil field using noble gases","interactions":[],"lastModifiedDate":"2018-06-22T14:25:56","indexId":"70197861","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Tracing enhanced oil recovery signatures in casing gases from the Lost Hills oil field using noble gases","docAbstract":"Enhanced oil recovery (EOR) and hydraulic fracturing practices are commonly used methods to improve hydrocarbon extraction efficiency; however the environmental impacts of such practices remain poorly understood. EOR is particularly prevalent in oil fields throughout California where water resources are in high demand and disposal of high volumes of produced water may affect groundwater quality. Consequently, it is essential to better understand the fate of injected (EOR) fluids in California and other subsurface petroleum systems, as well as any potential effect on nearby aquifer systems. Noble gases can be used as tracers to understand hydrocarbon generation, migration, and storage conditions, as well as the relative proportions of oil and water present in the subsurface. In addition, a noble gas signature diagnostic of injected (EOR) fluids can be readily identified. We report noble gas isotope and concentration data in casing gases from oil production wells in the Lost Hills oil field, northwest of Bakersfield, California, and injectate gas data from the Fruitvale oil field, located within the city of Bakersfield. Casing and injectate gas data are used to: 1) establish pristine hydrocarbon noble-gas signatures and the processes controlling noble gas distributions, 2) characterize the noble gas signature of injectate fluids, 3) trace injectate fluids in the subsurface, and 4) construct a model to estimate EOR efficiency. Noble gas results range from pristine to significantly modified by EOR, and can be best explained using a solubility exchange model between oil and connate/formation fluids, followed by gas exsolution upon production. This model is sensitive to oil-water interaction during hydrocarbon expulsion, migration, and storage at reservoir conditions, as well as any subsequent modification by EOR.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.05.028","usgsCitation":"Barry, P.H., Kulongoski, J.T., Landon, M.K., Tyne, R.L., Gillespie, J., Stephens, M.J., Hillegonds, D., Byrne, D., and Ballentine, C., 2018, Tracing enhanced oil recovery signatures in casing gases from the Lost Hills oil field using noble gases: Earth and Planetary Science Letters, v. 496, p. 57-67, https://doi.org/10.1016/j.epsl.2018.05.028.","productDescription":"11 p.","startPage":"57","endPage":"67","ipdsId":"IP-092040","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468634,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://ora.ox.ac.uk/objects/uuid:5065b220-4d22-4bf9-9f89-b0cc7e00a948","text":"Publisher Index Page"},{"id":355310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.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 -119.88693237304688,\n 35.529152854619\n ],\n [\n -119.59236145019531,\n 35.529152854619\n ],\n [\n -119.59236145019531,\n 35.72170907899236\n ],\n [\n -119.88693237304688,\n 35.72170907899236\n ],\n [\n -119.88693237304688,\n 35.529152854619\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"496","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e553e4b060350a15d0d3","contributors":{"authors":[{"text":"Barry, Peter H. 0000-0002-6960-1555","orcid":"https://orcid.org/0000-0002-6960-1555","contributorId":205890,"corporation":false,"usgs":true,"family":"Barry","given":"Peter","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738790,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tyne, R. L.","contributorId":205891,"corporation":false,"usgs":false,"family":"Tyne","given":"R.","email":"","middleInitial":"L.","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738791,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":203915,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":738792,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephens, Michael J. 0000-0001-8995-9928","orcid":"https://orcid.org/0000-0001-8995-9928","contributorId":205895,"corporation":false,"usgs":true,"family":"Stephens","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738796,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hillegonds, D.J.","contributorId":205892,"corporation":false,"usgs":false,"family":"Hillegonds","given":"D.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738793,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byrne, D.J.","contributorId":205893,"corporation":false,"usgs":false,"family":"Byrne","given":"D.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738794,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ballentine, C.J.","contributorId":205894,"corporation":false,"usgs":false,"family":"Ballentine","given":"C.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738795,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197857,"text":"70197857 - 2018 - Arsenic geochemistry of alluvial sediments and pore waters affected by mine tailings along the Belle Fourche and Cheyenne River floodplains","interactions":[],"lastModifiedDate":"2018-06-22T09:56:46","indexId":"70197857","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Arsenic geochemistry of alluvial sediments and pore waters affected by mine tailings along the Belle Fourche and Cheyenne River floodplains","docAbstract":"Gold mining operations in the northern Black Hills of South Dakota resulted in the discharge of arsenopyrite-bearing mine tailings into Whitewood Creek from 1876 to 1977. Those tailings were transported further downstream along the Belle Fourche River, the Cheyenne River, and the Missouri River. An estimated 110 million metric tons of tailings remain stored in alluvial deposits of the Belle Fourche and Cheyenne Rivers. Pore-water dialysis samplers were deployed in the channel and backwaters of the Belle Fourche and Cheyenne Rivers to determine temporal and seasonal changes in the geochemistry of groundwater in alluvial sediments. Alluvial sediment adjacent to the dialysis samplers were cored for geochemical analysis. In comparison to US Environmental Protection Agency drinking water standards and reference concentrations of alluvial sediment not containing mine tailings, the Belle Fourche River sites had elevated concentrations of arsenic in pore water (2570 μg/L compared to 10 μg/L) and sediment (1010 ppm compared to < 34 ppm), respectively. Pore water arsenic concentration was affected by dissolution of iron oxyhydroxides under reducing conditions. Sequential extraction of iron and arsenic from sediment cores indicates that substantial quantities of soluble metals were present. Dissolution of arsenic sorbed to alluvial sediment particles appears to be affected by changing groundwater levels that cause shifts in redox conditions. Bioreductive processes did not appear to be a substantial transport pathway but could affect speciation of arsenic, especially at the Cheyenne River sampling sites where microbial activity was determined to be greater than at Belle Fourche sampling sites.
","language":"English","publisher":"Springer","doi":"10.1007/s11270-018-3836-8","usgsCitation":"Pfeifle, B.D., Stamm, J.F., and Stone, J.J., 2018, Arsenic geochemistry of alluvial sediments and pore waters affected by mine tailings along the Belle Fourche and Cheyenne River floodplains: Water, Air, & Soil Pollution, v. 229, p. 1-18, https://doi.org/10.1007/s11270-018-3836-8.","productDescription":"Article 183; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-049076","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":355291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Belle Fourche River, Cheyenne River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 42.5\n ],\n [\n -101,\n 42.5\n ],\n [\n -101,\n 45\n ],\n [\n -106,\n 45\n ],\n [\n -106,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"229","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-25","publicationStatus":"PW","scienceBaseUri":"5b46e553e4b060350a15d0d7","contributors":{"authors":[{"text":"Pfeifle, Bryce D.","contributorId":205879,"corporation":false,"usgs":false,"family":"Pfeifle","given":"Bryce","email":"","middleInitial":"D.","affiliations":[{"id":37185,"text":"South Dakota School of Mines and Technology","active":true,"usgs":false}],"preferred":false,"id":738774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamm, John F. 0000-0002-3404-2933 jstamm@usgs.gov","orcid":"https://orcid.org/0000-0002-3404-2933","contributorId":149144,"corporation":false,"usgs":true,"family":"Stamm","given":"John","email":"jstamm@usgs.gov","middleInitial":"F.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":738773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, James J.","contributorId":205880,"corporation":false,"usgs":false,"family":"Stone","given":"James","email":"","middleInitial":"J.","affiliations":[{"id":37185,"text":"South Dakota School of Mines and Technology","active":true,"usgs":false}],"preferred":false,"id":738775,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197825,"text":"70197825 - 2018 - Response of mercury in an Adirondack (NY, USA) forest stream to watershed lime application","interactions":[],"lastModifiedDate":"2018-06-21T09:39:47","indexId":"70197825","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1566,"text":"Environmental Science: Processes and Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Response of mercury in an Adirondack (NY, USA) forest stream to watershed lime application","docAbstract":"Surface waters in Europe and North America previously impacted by acid deposition are recovering in conjunction with declining precursor emissions since the 1980s. Lime has been applied to some impacted watersheds to accelerate recovery. The response to liming can be considered a proxy for future recovery from acid deposition. Increases in dissolved organic carbon concentrations have been observed in surface waters in response to increased pH associated with recovery from acid deposition. Although not previously described, recovery-related increases in dissolved organic carbon could drive increases in mercury concentrations and loads because of the affinity of mercury for dissolved organic matter. We used a before–after impact-response approach to describe the response of stream mercury cycling to the application of lime to the watershed of a small stream in the Adirondack Mountains of New York, USA. Dissolved organic carbon, total mercury and methylmercury concentrations increased\nsignificantly in streamwater within two weeks of treatment, to previously unobserved oncentrations. After six months, post-treatment before–after impact-control (BACI) tests indicate that mean dissolved organic carbon concentrations and total mercury to dissolved organic carbon ratios remained significantly higher and limed site fluxes of methylmercury were lower than those at the reference stream. This pattern suggests total mercury is leaching at elevated levels from the limed watershed, but limitations in production and transport to the stream channel likely resulted in increases in methylmercury concentration that were of limited duration.","language":"English","publisher":"The Royal Society of Chemistry","doi":"10.1039/c7em00520b","usgsCitation":"Millard, G.D., Driscoll, C.T., Burns, D., Montesdeoca, M., and Riva-Murray, K., 2018, Response of mercury in an Adirondack (NY, USA) forest stream to watershed lime application: Environmental Science: Processes and Impacts, v. 20, no. 4, p. 607-620, https://doi.org/10.1039/c7em00520b.","productDescription":"14 p.","startPage":"607","endPage":"620","ipdsId":"IP-080653","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":355239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.89603042602539,\n 43.48543487611435\n ],\n [\n -74.7810173034668,\n 43.48543487611435\n ],\n [\n -74.7810173034668,\n 43.55252937447483\n ],\n [\n -74.89603042602539,\n 43.55252937447483\n ],\n [\n -74.89603042602539,\n 43.48543487611435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e554e4b060350a15d0db","contributors":{"authors":[{"text":"Millard, Geoffrey D.","contributorId":205854,"corporation":false,"usgs":false,"family":"Millard","given":"Geoffrey","email":"","middleInitial":"D.","affiliations":[{"id":37179,"text":"Research Assistant, Dept of Civil & Environmental Engineeering, Syracuse University, NY","active":true,"usgs":false}],"preferred":false,"id":738674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":738675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":738673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montesdeoca, Mario R.","contributorId":198382,"corporation":false,"usgs":false,"family":"Montesdeoca","given":"Mario R.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":738676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738677,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197822,"text":"70197822 - 2018 - Stability of mercury concentration measurements in archived soil and peat samples","interactions":[],"lastModifiedDate":"2018-06-21T09:41:40","indexId":"70197822","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Stability of mercury concentration measurements in archived soil and peat samples","docAbstract":"Archived soil samples can provide important information on the history of environmental contamination and by comparison with recently collected samples, temporal trends can be inferred. Little previous work has addressed whether mercury (Hg) concentrations in soil samples are stable with long-term storage under standard laboratory conditions. In this study, we have re-analyzed using cold vapor atomic adsorption spectroscopy a set of archived soil samples that ranged from relatively pristine mountainous sites to a polluted site near a non-ferrous metal smelter with a wide range of Hg concentrations (6 - 6485 µg kg-1). Samples included organic and mineral soils and peats with a carbon content that ranged from 0.2 to 47.7%. Soil samples were stored in polyethylene bags or bottles and held in laboratory rooms where temperature was not kept to a constant value. Mercury concentrations in four subsets of samples were originally measured in 2000, 2005, 2006 and 2007, and re-analyzed in 2017, i.e. after 17, 12, 11 and 10 years of storage. Statistical analyses of either separated or lumped data yielded no significant differences between the original and current Hg concentrations. Based on these analyses, we show that archived soil and peat samples can be used to evaluate historical soil mercury contamination.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2018.06.033","usgsCitation":"Navratil, T., Burns, D., Novakova, T., Kana, J., Rohovec, J., Roll, M., and Ettler, V., 2018, Stability of mercury concentration measurements in archived soil and peat samples: Chemosphere, v. 208, p. 707-711, https://doi.org/10.1016/j.chemosphere.2018.06.033.","productDescription":"4 p.","startPage":"707","endPage":"711","ipdsId":"IP-092247","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":355241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Czech Republic","volume":"208","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e554e4b060350a15d0dd","contributors":{"authors":[{"text":"Navratil, Tomas","contributorId":205848,"corporation":false,"usgs":false,"family":"Navratil","given":"Tomas","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":738663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Novakova, Tereza","contributorId":205849,"corporation":false,"usgs":false,"family":"Novakova","given":"Tereza","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kana, Jiri","contributorId":205850,"corporation":false,"usgs":false,"family":"Kana","given":"Jiri","email":"","affiliations":[{"id":37177,"text":"Biology Centre of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738666,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohovec, Jan","contributorId":205851,"corporation":false,"usgs":false,"family":"Rohovec","given":"Jan","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roll, Michal","contributorId":205852,"corporation":false,"usgs":false,"family":"Roll","given":"Michal","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738668,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ettler, Vojtech","contributorId":205853,"corporation":false,"usgs":false,"family":"Ettler","given":"Vojtech","email":"","affiliations":[{"id":37178,"text":"Charles University","active":true,"usgs":false}],"preferred":false,"id":738669,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196576,"text":"sir20185058 - 2018 - Shoreline erosion at selected areas along Lake Sharpe on the Lower Brule Reservation in South Dakota, 1966–2015","interactions":[],"lastModifiedDate":"2018-06-22T10:07:16","indexId":"sir20185058","displayToPublicDate":"2018-06-21T00:00:00","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":"2018-5058","title":"Shoreline erosion at selected areas along Lake Sharpe on the Lower Brule Reservation in South Dakota, 1966–2015","docAbstract":"The Lower Brule Reservation in central South Dakota is losing land because of shoreline erosion along Lake Sharpe, a reservoir on the Missouri River, which has caused detrimental effects for the Lower Brule Sioux Tribe including losses of cultural sites, recreation access points, wildlife habitat, irrigated cropland, and landmass. To better understand and quantify shoreline erosion, the Lower Brule Sioux Tribe and the U.S. Geological Survey cooperated on a series of data-collection efforts and study of shoreline erosion along Lake Sharpe. Data collected or compiled for 1966–2015 were used to describe and quantify shoreline erosion along Lake Sharpe. The progression of shoreline erosion near the community of Lower Brule, South Dakota, was tracked by comparing current or recent aerial imagery with existing historical maps. At 33 evaluation lines along a 7-mile reach of Lake Sharpe shoreline near Lower Brule, cumulative change of shoreline from 1966 to 2010 ranged from about −224 feet of deposition to 770 feet of erosion.
Photographic and location data were collected for this study to understand the processes affecting erosion and estimate erosion rates. Photographs were collected only in the 7-mile reach near Lower Brule, but locations of the bank over time were collected at the 7-mile reach and two additional reaches within the Lower Brule Reservation. Global navigation satellite system equipment was used in real-time kinematic mode to collect bank locations along three reaches of interest. Reach-length data were collected four times between November 2011 and November 2012. A small, unmanned aerial system (drone) was used to capture digital video along the shoreline of the 7-mile reach.
Water-level fluctuations contribute to the number of wet-dry cycles experienced by the soils at the shoreline or bank. The soils present under the current (2017) location of the reservoir are predominantly terrace alluvium, consisting of sand and silt. Detailed soils data for Lyman County indicate that the dominant soil type along the southern part of the shoreline in the 7-mile reach is Bullcreek clay. Weather within the study area can affect the erosion rate. Air temperature can potentially affect erosion rates by freezing and thawing water and soils. Mean hourly wind speeds vary somewhat throughout the year but averaged 13.3 miles per hour. The direction of prevailing winds near Lower Brule indicates that there are several miles of fetch to build large waves.
Annual erosion rates calculated or measured throughout this study varied by location. Long-term annual average erosion rates of the 7-mile reach, as calculated by image analysis, ranged from −5.1 feet per year (deposition) to 17.5 feet per year (erosion). Short-term annual erosion rates measured using global navigation satellite system equipment during 2010–12 ranged from about 0 to 31.7 feet per year for the 7-mile reach. Existing scour countermeasures have been effective variably. Fieldstone rip-rap seems to have stabilized the shoreline, whereas tree strips paralleling the shoreline seem to have slowed erosion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185058","collaboration":"Prepared in cooperation with the Lower Brule Sioux Tribe","usgsCitation":"Thompson, R.F., and Stamm, J.F., 2018, Shoreline erosion at selected areas along Lake Sharpe on the Lower Brule Reservation, South Dakota, 1966–2015: U.S. Geological Survey Scientific Investigations Report 2018–5058, 29 p., https://doi.org/10.3133/sir20185058.","productDescription":"Report: vi, 29 p.; Plate: 33.11 x 46.81 inches; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080051","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":355250,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2018/5058/sir20185058_plate01.pdf","text":"Plate 1 -","size":"7.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5058 Plate","linkHelpText":"Soil Type and Land Cover Interactions with Erosion Measurements near Lower Brule, South Dakota"},{"id":355251,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H130XV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data to document shoreline erosion at selected locations along Lake Sharpe on the Lower Brule Reservation in South Dakota, 1966–2015"},{"id":355249,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5058/sir20185058.pdf","text":"Report","size":"5.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5058"},{"id":355248,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5058/coverthb.jpg"}],"country":"United States","state":"South Dakota","city":"Lower Brule","otherGeospatial":"Lake Sharpe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.1678466796875,\n 43.81471121600004\n ],\n [\n -99.16259765625,\n 43.81471121600004\n ],\n [\n -99.16259765625,\n 44.38669150215206\n ],\n [\n -100.1678466796875,\n 44.38669150215206\n ],\n [\n -100.1678466796875,\n 43.81471121600004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
South Dakota Office
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Human activities on floodplains have severely disrupted the regeneration of foundation riparian shrub and tree species of the Salicaceae family (Populus and Salix spp.) throughout the Northern Hemisphere. Restoration ecologists initially tackled this problem from a terrestrial perspective that emphasized planting. More recently, floodplain restoration activities have embraced an aquatic perspective, inspired by the expanding practice of managing river flows to improve river health (environmental flows). However, riparian Salicaceae species occupy floodplain and riparian areas, which lie at the interface of both terrestrial and aquatic ecosystems along watercourses. Thus, their regeneration depends on a complex interaction of hydrologic and geomorphic processes that have shaped key life-cycle requirements for seedling establishment. Ultimately, restoration needs to integrate these concepts to succeed. However, while regeneration of Salicaceae is now reasonably well-understood, the literature reporting restoration actions on Salicaceae regeneration is sparse, and a specific theoretical framework is still missing. Here, we have reviewed 105 peer-reviewed published experiences in restoration of Salicaceae forests, including 91 projects in 10 world regions, to construct a decision tree to inform restoration planning through explicit links between the well-studied biophysical requirements of Salicaceaeregeneration and 17 specific restoration actions, the most popular being planting (in 55% of the projects), land contouring (30%), removal of competing vegetation (30%), site selection (26%), and irrigation (24%). We also identified research gaps related to Salicaceae forest restoration and discuss alternative, innovative and feasible approaches that incorporate the human component.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2018.04.069","usgsCitation":"Gonzalez, E., Martinez-Fernandez, V., Shafroth, P.B., Sher, A.A., Henry, A.L., Garofano-Gomez, V., and Corenblit, D., 2018, Regeneration of Salicaceae riparian forests in the Northern Hemisphere: A new framework and management tool: Journal of Environmental Management, v. 218, p. 374-387, https://doi.org/10.1016/j.jenvman.2018.04.069.","productDescription":"14 p.","startPage":"374","endPage":"387","ipdsId":"IP-096679","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468642,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10251/189075","text":"External Repository"},{"id":355211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"218","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e555e4b060350a15d0ef","contributors":{"authors":[{"text":"Gonzalez, Eduardo","contributorId":205798,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Eduardo","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":738525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinez-Fernandez, Vanesa","contributorId":205799,"corporation":false,"usgs":false,"family":"Martinez-Fernandez","given":"Vanesa","email":"","affiliations":[{"id":37168,"text":"Universidad Politecnica de Madrid","active":true,"usgs":false}],"preferred":false,"id":738526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":738524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sher, Anna A.","contributorId":196506,"corporation":false,"usgs":false,"family":"Sher","given":"Anna","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":738527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henry, Annie L.","contributorId":196513,"corporation":false,"usgs":false,"family":"Henry","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":12651,"text":"University of Denver","active":true,"usgs":false}],"preferred":false,"id":738528,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garofano-Gomez, Virginia","contributorId":205800,"corporation":false,"usgs":false,"family":"Garofano-Gomez","given":"Virginia","email":"","affiliations":[{"id":37169,"text":"Universitat Politecnica de Valencia","active":true,"usgs":false}],"preferred":false,"id":738529,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Corenblit, Dov","contributorId":205801,"corporation":false,"usgs":false,"family":"Corenblit","given":"Dov","email":"","affiliations":[{"id":37170,"text":"Universite Clermont Auvergne","active":true,"usgs":false}],"preferred":false,"id":738530,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197806,"text":"70197806 - 2018 - Origin of methane and sources of high concentrations in Los Angeles groundwater","interactions":[],"lastModifiedDate":"2018-06-20T16:24:11","indexId":"70197806","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Origin of methane and sources of high concentrations in Los Angeles groundwater","docAbstract":"In 2014, samples from 37 monitoring wells at 17 locations, within or near oil fields, and one site >5 km from oil fields, in the Los Angeles Basin, California, were analyzed for dissolved hydrocarbon gas isotopes and abundances. The wells sample a variety of depths of an aquifer system composed of unconsolidated and semiconsolidated sediments under various conditions of confinement. Concentrations of methane in groundwater samples ranged from 0.002 to 150 mg/L—some of the highest concentrations reported in a densely populated urban area. The δ13C and δ2H of the methane ranged from −80.8 to −45.5 per mil (‰) and −249.8 to −134.9‰, respectively, and, along with oxidation‐reduction processes, helped to identify the origin of methane as microbial methanogenesis and CO2 reduction as its main formation pathway. The distribution of methane concentrations and isotopes is consistent with the high concentrations of methane in Los Angeles Basin groundwater originating from relatively shallow microbial production in anoxic or suboxic conditions. Source of the methane is the aquifer sediments rather than the upward migration or leakage of thermogenic methane associated with oil fields in the basin.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JG004026","usgsCitation":"Kulongoski, J.T., McMahon, P.B., Land, M., Wright, M., Johnson, T., and Landon, M.K., 2018, Origin of methane and sources of high concentrations in Los Angeles groundwater: Journal of Geophysical Research: Biogeosciences, v. 123, no. 3, p. 818-831, https://doi.org/10.1002/2017JG004026.","productDescription":"14 p.","startPage":"818","endPage":"831","ipdsId":"IP-078703","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","otherGeospatial":"Los Angeles Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.46533203125,\n 33.458942753687644\n ],\n [\n -117.630615234375,\n 33.458942753687644\n ],\n [\n -117.630615234375,\n 34.97600151317588\n ],\n [\n -119.46533203125,\n 34.97600151317588\n ],\n [\n -119.46533203125,\n 33.458942753687644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-11","publicationStatus":"PW","scienceBaseUri":"5b46e555e4b060350a15d0eb","contributors":{"authors":[{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Land, Michael 0000-0001-5141-0307 mtland@usgs.gov","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":171938,"corporation":false,"usgs":true,"family":"Land","given":"Michael","email":"mtland@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Michael 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":151031,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Theodore","contributorId":205833,"corporation":false,"usgs":false,"family":"Johnson","given":"Theodore","affiliations":[{"id":37173,"text":"Water Replenishment District of Southern California","active":true,"usgs":false}],"preferred":false,"id":738600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738601,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197782,"text":"70197782 - 2018 - A simple, cost-effective emitter for controlled release of fish pheromones: development, testing, and application to management of the invasive sea lamprey","interactions":[],"lastModifiedDate":"2018-06-21T09:55:11","indexId":"70197782","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A simple, cost-effective emitter for controlled release of fish pheromones: development, testing, and application to management of the invasive sea lamprey","docAbstract":"Semiochemicals that elicit species-specific attraction or repulsion have proven useful in the management of terrestrial pests and hold considerable promise for control of nuisance aquatic species, particularly invasive fishes. Because aquatic ecosystems are typically large and open, use of a semiochemical to control a spatially dispersed invader will require the development of a cost-effective emitter that is easy to produce, environmentally benign, inexpensive, and controls the release of the semiochemical without altering its structure. We examined the release properties of five polymers, and chose polyethylene glycol (PEG) as the best alternative. In a series of laboratory and field experiments, we examined the response of the invasive sea lamprey to PEG, and to a partial sex pheromone emitted from PEG that has proven effective as a trap bait to capture migrating sea lamprey prior to spawning. Our findings confirm that the sea lamprey does not behaviorally respond to PEG, and that the attractant response to the pheromone component was conserved when emitted from PEG. Further, we deployed the pheromone-PEG emitters as trap bait during typical control operations in three Great Lakes tributaries, observing similar improvements in trap performance when compared to a previous study using mechanically pumped liquid pheromone. Finally, the polymer emitters tended to dissolve unevenly in high flow conditions. We demonstrate that housing the emitter stabilizes the dissolution rate at high water velocity. We conclude the performance characteristics of PEG emitters to achieve controlled-release of a semiochemical are sufficient to recommend its use in conservation and management activities related to native and invasive aquatic organisms.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0197569","usgsCitation":"Wagner, C., Hanson, J.E., Meckley, T.D., Johnson, N., and Bals, J.D., 2018, A simple, cost-effective emitter for controlled release of fish pheromones: development, testing, and application to management of the invasive sea lamprey: PLoS ONE, v. 13, no. 6, p. 1-17, https://doi.org/10.1371/journal.pone.0197569.","productDescription":"e0197569; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-096735","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":468641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0197569","text":"Publisher Index Page"},{"id":355197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b46e556e4b060350a15d0f3","contributors":{"authors":[{"text":"Wagner, C. Michael","contributorId":173006,"corporation":false,"usgs":false,"family":"Wagner","given":"C. Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":738478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, James E.","contributorId":198866,"corporation":false,"usgs":false,"family":"Hanson","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":738479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meckley, Trevor D.","contributorId":205787,"corporation":false,"usgs":false,"family":"Meckley","given":"Trevor","email":"","middleInitial":"D.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":738480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":738477,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bals, Jason D.","contributorId":205788,"corporation":false,"usgs":false,"family":"Bals","given":"Jason","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":738481,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197796,"text":"70197796 - 2018 - Lateral and vertical distribution of downstream migrating juvenile sea lamprey","interactions":[],"lastModifiedDate":"2018-06-20T12:29:25","indexId":"70197796","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Lateral and vertical distribution of downstream migrating juvenile sea lamprey","docAbstract":"Sea lamprey is considered an invasive and nuisance species in the Laurentian Great Lakes, Lake Champlain, and the Finger Lakes of New York and is a major focus of control efforts. Currently, management practices focus on limiting the area of infestation using barriers to block migratory adults, and lampricides to kill ammocoetes in infested tributaries. No control efforts currently target the downstream-migrating post-metamorphic life stage which could provide another management opportunity. In order to apply control methods to this life stage, a better understanding of their downstream movement patterns is needed. To quantify spatial distribution of downstream migrants, we deployed fyke and drift nets laterally and vertically across the stream channel in two tributaries of Lake Champlain. Sea lamprey was not randomly distributed across the stream width and lateral distribution showed a significant association with discharge. Results indicated that juvenile sea lamprey is most likely to be present in the thalweg and at midwater depths of the stream channel. Further, a majority of the catch occurred during high flow events, suggesting an increase in downstream movement activity when water levels are higher than base flow. Discharge and flow are strong predictors of the distribution of out-migrating sea lamprey, thus managers will need to either target capture efforts in high discharge areas of streams or develop means to guide sea lamprey away from these areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2018.03.004","usgsCitation":"Sotola, V.A., Miehls, S.M., Simard, L.G., and Marsden, J., 2018, Lateral and vertical distribution of downstream migrating juvenile sea lamprey: Journal of Great Lakes Research, v. 44, no. 3, p. 491-496, https://doi.org/10.1016/j.jglr.2018.03.004.","productDescription":"6 p.","startPage":"491","endPage":"496","ipdsId":"IP-094745","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":355210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e556e4b060350a15d0f1","contributors":{"authors":[{"text":"Sotola, V. Alex","contributorId":194906,"corporation":false,"usgs":false,"family":"Sotola","given":"V.","email":"","middleInitial":"Alex","affiliations":[],"preferred":false,"id":738521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":738520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simard, Lee G.","contributorId":194905,"corporation":false,"usgs":false,"family":"Simard","given":"Lee","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":738522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marsden, J. Ellen","contributorId":194907,"corporation":false,"usgs":false,"family":"Marsden","given":"J. Ellen","affiliations":[],"preferred":false,"id":738523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197592,"text":"fs20183035 - 2018 - Summary of estimated water use in the United States in 2015","interactions":[],"lastModifiedDate":"2018-06-19T11:42:38","indexId":"fs20183035","displayToPublicDate":"2018-06-19T10:00:00","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":"2018-3035","title":"Summary of estimated water use in the United States in 2015","docAbstract":"A total of 322 Bgal/d of water withdrawals was reported for eight categories of use in the United States in 2015, which was 9 percent less than in 2010 (354 Bgal/d), and continued a declining trend since 2005. The decline in total withdrawals in 2015 primarily was caused by significant decreases (28.8 Bgal/d) in thermoelectric power, which accounted for 89 percent of the decrease in total withdrawals. Between 2010 and 2015, withdrawals decreased in all categories except irrigation (2 percent increase), mining (1 percent increase), and livestock (no change). Fresh surface-water withdrawals (198 Bgal/d) were 14 percent less than in 2010, and fresh groundwater withdrawals (82.3 Bgal/d) were about 8 percent more than in 2010. Saline surface-water withdrawals (38.6 Bgal/d) were 14 percent less than in 2010, and saline groundwater withdrawals (2.34 Bgal/d) were 5 percent more than in 2010. Total population in the United States in 2015 (325 million) increased by 4 percent (12.4 million) from 2010, which was similar to the increase between 2005 and 2010. For the first time since 1995, consumptive use for irrigation and thermoelectric power were reported. Consumptive use accounted for 62 percent (73.2 Bgal/d) of water used for irrigation, and 3 percent (4.31 Bgal/d) of water used for thermoelectric power in 2015.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183035","usgsCitation":"Maupin, M.A., 2018, Summary of estimated water use in the United States in 2015: U.S. Geological Survey Fact Sheet 2018-3035, 2 p., https://doi.org/10.3133/fs20183035.","productDescription":"2 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096639","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":355065,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3035/coverthb.jpg"},{"id":355066,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3035/fs20183035.pdf","text":"Report","size":"117 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3035"},{"id":355067,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TB15V5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Estimated use of water in the United States county-level data for 2015"},{"id":355068,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1441","text":"Circular 1441","description":"Circular 1441"}],"country":"United States","contact":"USGS National Water-Use Science Project Team
Or USGS Water-Use Web site
Water use in the United States in 2015 was estimated to be about 322 billion gallons per day (Bgal/d), which was 9 percent less than in 2010. The 2015 estimates put total withdrawals at the lowest level since before 1970, following the same overall trend of decreasing total withdrawals observed from 2005 to 2010. Freshwater withdrawals were 281 Bgal/d, or 87 percent of total withdrawals, and saline-water withdrawals were 41.0 Bgal/d, or 13 percent of total withdrawals. Fresh surface-water withdrawals (198 Bgal/d) were 14 percent less than in 2010, and fresh groundwater withdrawals (82.3 Bgal/day) were about 8 percent greater than in 2010. Saline surface-water withdrawals were 38.6 Bgal/d, or 14 percent less than in 2010. Total saline groundwater withdrawals in 2015 were 2.34 Bgal/d, mostly for mining use.
Thermoelectric power and irrigation remained the two largest uses of water in 2015, and total withdrawals decreased for thermoelectric power but increased for irrigation. Withdrawals in 2015 for thermoelectric power were 18 percent less and withdrawals for irrigation were 2 percent greater than in 2010. Similarly, other uses showed reductions compared to 2010, specifically public supply (–7 percent), self-supplied domestic (–8 percent), self-supplied industrial (–9 percent), and aquaculture (–16 percent). In addition to irrigation (2 percent), mining (1 percent) reported larger withdrawals in 2015 than in 2010. Livestock withdrawals remained essentially the same in 2015 compared to 2010 (0 percent change). Thermoelectric power, irrigation, and public-supply withdrawals accounted for 90 percent of total withdrawals in 2015.
Withdrawals for thermoelectric power were 133 Bgal/d in 2015 and represented the lowest levels since before 1970. Surface-water withdrawals accounted for more than 99 percent of total thermoelectric-power withdrawals, and 72 percent of those surface-water withdrawals were from freshwater sources. Saline surface-water withdrawals for thermoelectric power accounted for 97 percent of total saline surface-water withdrawals for all uses. Thermoelectric-power withdrawals accounted for 41 percent of total withdrawals for all uses, and freshwater withdrawals for thermoelectric power accounted for 34 percent of the total freshwater withdrawals for all uses. Total consumptive use for thermoelectric power was 4.31 Bgal/d in 2015 or 3 percent of the total thermoelectric-power withdrawals.
Irrigation withdrawals were 118 Bgal/d in 2015, an increase of 2 percent from 2010 (116 Bgal/d), but were approximately equal to withdrawals estimated in the 1960s. Irrigation withdrawals, all freshwater, accounted for 42 percent of total freshwater withdrawals for all uses and 64 percent of total freshwater withdrawals for all uses excluding thermoelectric power. Surface-water withdrawals (60.9 Bgal/d) accounted for 52 percent of the total irrigation withdrawals, or about 8 percent less than in 2010. Groundwater withdrawals for irrigation were 57.2 Bgal/d in 2015, about 16 percent more than in 2010. About 63,500 thousand acres (or 63.5 million acres) were irrigated in 2015, an increase from 2010 of about 1,130 thousand acres (2 percent). The number of acres irrigated using sprinkler and microirrigation systems accounted for 63 percent of the total irrigated lands in 2015. Total consumptive use for irrigation was 73.2 Bgal/d in 2015 or 62 percent of the total use (withdrawals and reclaimed wastewater).
Public-supply withdrawals in 2015 were 39.0 Bgal/d, or 7 percent less than in 2010, continuing the declines observed from 2005 to 2010. Total population in the United States increased from 312.6 million people in 2010 to 325.0 million people in 2015, an increase of 4 percent. Public-supply withdrawals accounted for 14 percent of the total freshwater withdrawals for all uses and 21 percent of freshwater withdrawals for all uses, excluding thermoelectric power. The number of people that received potable water from public-supply facilities in 2015 was 283 million, or about 87 percent of the total United States population. This percentage is 1 percent greater than in 2010. Self-supplied domestic withdrawals were 3.26 Bgal/d, or 8 percent less than in 2010. More than 98 percent of the self-supplied domestic withdrawals were from groundwater sources.
Self-supplied industrial withdrawals were 14.8 Bgal/d in 2015, a 9 percent decline from 2010, continuing the downward trend since the peak of 47 Bgal/d in 1970. Total self-supplied industrial withdrawals were 5 percent of total withdrawals for all uses and 8 percent of total withdrawals for all uses, excluding thermoelectric power. Most of the total self-supplied industrial withdrawals were from surface-water sources (82 percent), and nearly all (94 percent) of those surface-water withdrawals were from freshwater sources. Nearly all of the groundwater withdrawals for self-supplied industrial use (98 percent) were from freshwater sources.
Total aquaculture withdrawals were 7.55 Bgal/d in 2015, or 16 percent less than in 2010, and surface water was the primary source (79 percent). Most of the surface-water withdrawals occurred at facilities that operated flow-through raceways, which returned the water to the source directly after use. Aquaculture withdrawals accounted for 2 percent of the total withdrawals for all uses and 4 percent of the total withdrawals for all uses, excluding thermoelectric.
Total mining withdrawals in 2015 were 4.00 Bgal/d, or about 1 percent of total withdrawals from all uses and 2 percent of total withdrawals from all uses, excluding thermoelectric. Mining withdrawals increased 1 percent from 2010 to 2015. Groundwater withdrawals accounted for 72 percent of the total mining withdrawals, and most of the groundwater was saline (65 percent). Most (77 percent) of the surface-water withdrawals for mining was freshwater.
Livestock withdrawals in 2015 were 2.00 Bgal/d, the same as in 2010. All livestock withdrawals were from freshwater sources, mostly from groundwater (62 percent). Livestock withdrawals accounted for about 1 percent of total freshwater withdrawals for all uses, excluding thermoelectric power.
In 2015, more than 50 percent of the total withdrawals in the United States were accounted for by 12 States (California, Texas, Idaho, Florida, Arkansas, New York, Illinois, Colorado, North Carolina, Michigan, Montana, and Nebraska). California accounted for almost 9 percent of the total withdrawals and 9 percent of freshwater withdrawals in the United States, predominantly for irrigation. Texas accounted for almost 7 percent of total withdrawals, predominantly for thermoelectric power, irrigation, and public supply. Florida accounted for 23 percent of the total saline-water withdrawals in the United States, mostly from surface-water sources for thermoelectric power. Texas and California accounted for 59 percent of the total saline groundwater withdrawals in the United States, mostly for mining.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1441","isbn":"978-1-4113-4233-0","collaboration":"Water Availability and Use Science Program","usgsCitation":"Dieter, C.A., Maupin, M.A., Caldwell, R.R., Harris, M.A., Ivahnenko, T.I., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2018, Estimated use of water in the United States in 2015: U.S. Geological Survey Circular 1441, 65 p., https://doi.org/10.3133/cir1441. [Supersedes USGS Open-File Report 2017–1131.]","productDescription":"v, 65 p.","numberOfPages":"76","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-090439","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":355031,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20183035","text":"Fact Sheet 2018–3035","linkHelpText":"- Summary of Estimated Water Use in the United States in 2015"},{"id":355029,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1441/circ1441.pdf","text":"Report","size":"42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIRC 1441"},{"id":355030,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TB15V5","text":"USGS data release","description":"USGS data release","linkHelpText":"Estimated Use of Water in the United States County-Level Data for 2015"},{"id":355028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1441/coverthb.jpg"}],"contact":"National Water Use Science Project Team
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
https:water.usgs.gov/watuse/
Freshwater mussels (order Unionoida) are one of the most imperiled groups of animals in the world. However, many ambient water quality criteria and other environmental guideline values do not include data for freshwater mussels, in part because mussel toxicity test methods are comparatively new and data may not have been available when criteria and guidelines were derived. The objectives of the present study were to evaluate the acute toxicity of sodium chloride (NaCl) and potassium chloride (KCl) to larvae (glochidia) and/or juveniles of a unionid mussel (fatmucket, Lampsilis siliquoidea) and to determine the potential influences of water hardness (50, 100, 200, and 300 mg/L as CaCO3) and other major ions (Ca, K, SO4, or HCO3) on the acute toxicity of NaCl to the mussels. From the KCl test, the 50% effect concentration (EC50) for fatmucket glochidia was 30 mg K/L, similar to or slightly lower than the EC50s for juvenile fatmucket (37–46 mg K/L) tested previously in our laboratory. From the NaCl tests, the EC50s for glochidia increased from 441 to 1597 mg Cl/L and the EC50s for juvenile mussels increased from 911 to 3092 mg Cl/L with increasing water hardness from 50 to 300 mg/L. Increasing K from 0.4 to 1.9 mg/L, SO4 from 13 to 40 mg/L, or HCO3 from 44 to 200 mg/L in the 50 mg/L hardness water did not substantially change the NaCl EC50s for juvenile mussels, whereas increasing Ca from 9.9 to 42 mg/L increased the EC50s by a factor of 2. The overall results indicate that glochidia were equally or more sensitive to NaCl and KCl compared with juvenile mussels and that the increased water hardness ameliorated the acute toxicity of NaCl to glochidia and juveniles. These responses rank fatmucket among the most acutely sensitive freshwater organisms to NaCl and KCl.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4206","usgsCitation":"Wang, N., Ivey, C.D., Dorman, R.A., Ingersoll, C.G., Steevens, J.A., Hammer, E.J., Bauer, C.R., and Mount, D.R., 2018, Acute toxicity of sodium chloride and potassium chloride to a unionid mussel (Lampsilis siliquoidea) in water exposures: Environmental Toxicology and Chemistry, v. 37, p. 3041-3049, https://doi.org/10.1002/etc.4206.","productDescription":"9 p.","startPage":"3041","endPage":"3049","ipdsId":"IP-094578","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":468646,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://europepmc.org/articles/pmc6693347","text":"External Repository"},{"id":437853,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HDRZM0","text":"USGS data release","linkHelpText":"Acute toxicity of sodium chloride and potassium chloride to a unionid mussel (Lampsilis siliquoidea) in water exposures-Data"},{"id":380297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","county":"Boone County","otherGeospatial":"Perche Creek, Silver Fork","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.45389938354492,\n 38.8911664375226\n ],\n [\n -92.33407974243164,\n 38.8911664375226\n ],\n [\n -92.33407974243164,\n 39.00224370106619\n ],\n [\n -92.45389938354492,\n 39.00224370106619\n ],\n [\n -92.45389938354492,\n 38.8911664375226\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","edition":"12","noUsgsAuthors":false,"publicationDate":"2018-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorman, Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804367,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804368,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hammer, Edward J.","contributorId":150723,"corporation":false,"usgs":false,"family":"Hammer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":804369,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bauer, Candice R.","contributorId":150724,"corporation":false,"usgs":false,"family":"Bauer","given":"Candice","email":"","middleInitial":"R.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":804370,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mount, David R.","contributorId":150725,"corporation":false,"usgs":false,"family":"Mount","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":18078,"text":"U. S. Environmental Protection Agency, Environmental Effects Research Laboratory, Duluth, Minnesota","active":true,"usgs":false}],"preferred":false,"id":804371,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70197625,"text":"sim3409 - 2018 - Bathymetric contour map, surface area and capacity table, and bathymetric difference map for Clearwater Lake near Piedmont, Missouri, 2017","interactions":[],"lastModifiedDate":"2018-09-25T08:04:18","indexId":"sim3409","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3409","title":"Bathymetric contour map, surface area and capacity table, and bathymetric difference map for Clearwater Lake near Piedmont, Missouri, 2017","docAbstract":"Clearwater Lake, on the Black River near Piedmont in Reynolds County, Missouri, was constructed in 1948 and is operated by the U.S. Army Corps of Engineers for flood-risk reduction, recreation, and fish and wildlife habitat. The lake area is about 1,800 acres with about 34 miles of shoreline at the conservation pool elevation of 498 feet. Since the completion of the lake in 1948, sedimentation likely has caused the storage capacity of the lake to decrease gradually. The loss of storage capacity can decrease the effectiveness of the lake to mitigate flooding, and excessive sediment accumulation also can reduce aquatic habitat in some areas of the lake. Many lakes operated by the U.S. Army Corps of Engineers have periodic bathymetric and sediment surveys to monitor the status of the lake. The U.S. Geological Survey completed one such survey of Clearwater Lake in 2008 during a period of high lake level using bathymetric surveying equipment consisting of a multibeam echosounder, a singlebeam echosounder, 1/3 arc-second National Elevation Dataset data (used outside the multibeam echosounder survey extent), and the waterline derived from 2008 aerial light detection and ranging (lidar) data. In May 2017, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, surveyed the bathymetry of Clearwater Lake to prepare an updated bathymetric map and a surface area and capacity table. The 2008 survey was contrasted with the 2017 survey to document the changes in the bathymetric surface of the lake.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3409","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Richards, J.M., and Huizinga, R.J., 2018, Bathymetric contour map, surface area and capacity table, and bathymetric difference map for Clearwater Lake near Piedmont, Missouri, 2017: U.S. Geological Survey Scientific Investigations Map 3409, 1 sheet, https://doi.org/10.3133/sim3409.","productDescription":"Sheet: 36.0 x 36.0 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095869","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":355036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3409/coverthb2.jpg"},{"id":355141,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3409/sim3409.pdf","text":"Map","size":"9.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3409"},{"id":355142,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DN44BJ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Bathymetric data for Clearwater Lake near Piedmont, Missouri, 2017"}],"country":"United States","state":"Missouri","city":"Piedmont","otherGeospatial":"Clearwater Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.9,\n 37.33\n ],\n [\n -90.67,\n 37.33\n ],\n [\n -90.67,\n 37.0833\n ],\n [\n -90.9,\n 37.0833\n ],\n [\n -90.9,\n 37.33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center, Missouri Office
U.S. Geological Survey
400 Independence Road
Rolla, MO 65401
Through integration of multiple data streams to monitor volcanic unrest scientists are able to make more robust eruption forecast and to obtain a more holistic interpretation of volcanic systems. We examined gas emission and gas geochemistry, seismic and petrologic data recorded during the 2015 unrest of Cotopaxi (Ecuador) in order to decipher the origin and temporal evolution of this eruption. Identification of families of similar seismic events and the use of seismic amplitude ratios reveals temporal changes in volcanic processes. SO2 (300 to 24000 t/d), BrO/SO2 (5-10 x10-5), SO2/HCl (5.8 ± 4.8 and 6.6 ± 3.0) and CO2/SO2 (0.6 to 2.1) measured throughout the eruption indicate a shallow magmatic source. Bulk ash and glass chemistry indicate a homogenous andesitic (SiO2 wt%=56.94 ± 0.25) magma having undergone extensive S-exsolution and degassing during ascent. These data lead us to interpret this eruption as a magma intrusion and ascend to shallow levels. The intrusion progressively interacted with the hydrothermal system, boiled off water, and produced hydromagmatic explosions. A small volume of this intrusion continued to fragment and produced episodic ash emissions until it was sufficiently degassed and rheologically stiff. Based on the 470 kt of measured SO2 we estimate that ~ 65.3 x106 m3 of magma were required to supply the emitted gases. This volume exceeds the volume of erupted juvenile material by a factor of 50. This result emphasizes the importance of careful monitoring of Cotopaxi to identify the intrusion of a new batch of magma, which could rejuvenate the non-erupted material.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GC007514","usgsCitation":"Hidalgo, S., Battaglia, J., Arellano, S., Sierra, D., Bernard, B., Parra, R., Kelly, P.J., Dinger, F., Barrington, C., and Samaniego, P., 2018, Evolution of the 2015 Cotopaxi eruption revealed by combined geochemical & seismic observations: Geochemistry, Geophysics, Geosystems, v. 19, no. 7, p. 2087-2108, https://doi.org/10.1029/2018GC007514.","productDescription":"22 p.","startPage":"2087","endPage":"2108","ipdsId":"IP-077610","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468647,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2018gc007514","text":"External Repository"},{"id":355148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-16","publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d107","contributors":{"authors":[{"text":"Hidalgo, Silvana","contributorId":205717,"corporation":false,"usgs":false,"family":"Hidalgo","given":"Silvana","email":"","affiliations":[{"id":37151,"text":"Instituto Geofísico – Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":738285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglia, Jean","contributorId":205718,"corporation":false,"usgs":false,"family":"Battaglia","given":"Jean","email":"","affiliations":[{"id":37152,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal - CNRS - IRD, OPGC, Clermont Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":738286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arellano, Santiago","contributorId":205719,"corporation":false,"usgs":false,"family":"Arellano","given":"Santiago","affiliations":[{"id":37153,"text":"Department of Earth and Space Sciences – Chalmers University of Technology, Göteborg, Sweden","active":true,"usgs":false}],"preferred":false,"id":738287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sierra, Daniel","contributorId":205720,"corporation":false,"usgs":false,"family":"Sierra","given":"Daniel","email":"","affiliations":[{"id":37151,"text":"Instituto Geofísico – Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":738288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernard, Benjamin","contributorId":178529,"corporation":false,"usgs":false,"family":"Bernard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":738290,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parra, Rene","contributorId":205721,"corporation":false,"usgs":false,"family":"Parra","given":"Rene","email":"","affiliations":[{"id":37154,"text":"Instituto de Simulación Computacional, Colegio de Ciencias e Ingenierías - Universidad San Francisco de Quito, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":738289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":738284,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dinger, Florian","contributorId":205723,"corporation":false,"usgs":false,"family":"Dinger","given":"Florian","email":"","affiliations":[{"id":37156,"text":"Max-Planck Institut for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738292,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barrington, Charlotte","contributorId":205722,"corporation":false,"usgs":false,"family":"Barrington","given":"Charlotte","email":"","affiliations":[{"id":37155,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":738291,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Samaniego, Pablo","contributorId":205724,"corporation":false,"usgs":false,"family":"Samaniego","given":"Pablo","email":"","affiliations":[{"id":37157,"text":"Université Clermont Auvergne, CNRS, IRD, OPGC, Laboratoire Magmas et Volcans, F-63000 Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":738293,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70197725,"text":"70197725 - 2018 - Sampling strategies to improve passive optical remote sensing of river bathymetry","interactions":[],"lastModifiedDate":"2018-06-19T11:36:18","indexId":"70197725","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Sampling strategies to improve passive optical remote sensing of river bathymetry","docAbstract":"Passive optical remote sensing of river bathymetry involves establishing a relation between depth and reflectance that can be applied throughout an image to produce a depth map. Building upon the Optimal Band Ratio Analysis (OBRA) framework, we introduce sampling strategies for constructing calibration data sets that lead to strong relationships between an image-derived quantity and depth across a range of depths. Progressively excluding observations that exceed a series of cutoff depths from the calibration process improved the accuracy of depth estimates and allowed the maximum detectable depth ($d_{max}$) to be inferred directly from an image. Depth retrieval in two distinct rivers also was enhanced by a stratified version of OBRA that partitions field measurements into a series of depth bins to avoid biases associated with under-representation of shallow areas in typical field data sets. In the shallower, clearer of the two rivers, including the deepest field observations in the calibration data set did not compromise depth retrieval accuracy, suggesting that $d_{max}$ was not exceeded and the reach could be mapped without gaps. Conversely, in the deeper and more turbid stream, progressive truncation of input depths yielded a plausible estimate of $d_{max}$ consistent with theoretical calculations based on field measurements of light attenuation by the water column. This result implied that the entire channel, including pools, could not be mapped remotely. However, truncation improved the accuracy of depth estimates in areas shallower than $d_{max}$, which comprise the majority of the channel and are of primary interest for many habitat-oriented applications.","language":"English","publisher":"MDPI","doi":"10.3390/rs10060935","usgsCitation":"Legleiter, C.J., Overstreet, B., and Kinzel, P.J., 2018, Sampling strategies to improve passive optical remote sensing of river bathymetry: Remote Sensing, v. 10, no. 6, e935; 24 p., https://doi.org/10.3390/rs10060935.","productDescription":"e935; 24 p.","ipdsId":"IP-092922","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":468649,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10060935","text":"Publisher Index Page"},{"id":437856,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7D50KX6","text":"USGS data release","linkHelpText":"Hyperspectral image data and field measurements used for bathymetric mapping of the Snake River in Grand Teton National Park, WY"},{"id":437855,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HT2N96","text":"USGS data release","linkHelpText":"Hyperspectral image data and field measurements used for bathymetric mapping of the Deschutes River near Bend, OR"},{"id":355153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d105","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":738300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Overstreet, Brandon 0000-0001-7845-6671 boverstreet@usgs.gov","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":169201,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"boverstreet@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":738302,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}