Hydrocarbon reserves and technically recoverable undiscovered resources in continuous accumulations are present in Upper Ordovician strata in the Appalachian Basin Province. The province includes parts of New York, Pennsylvania, Ohio, Maryland, West Virginia, Virginia, Kentucky, Tennessee, Georgia, and Alabama. The Upper Ordovician strata are part of the previously defined Utica-Lower Paleozoic Total Petroleum System (TPS) that extends from New York and southern Canada to Tennessee. This publication presents a revision to the hydrocarbon source rocks in the TPS, a change to the name of the TPS, and changes to the geographic extent of the Utica-Lower Paleozoic TPS. The revision to the TPS recognizes the Upper Ordovician Point Pleasant Formation as a major hydrocarbon source rock in this TPS. Consequently, the name of the TPS is changed to Ordovician Point Pleasant/Utica-Lower Paleozoic TPS. The most significant modification to the boundary of the newly defined Ordovician Point Pleasant/Utica-Lower Paleozoic TPS is a westward extension in the southwesterly portion of the TPS, adding areas in Ohio, Indiana, Kentucky, and Tennessee in order to include Ordovician strata, including potential petroleum source rocks, from the subsurface to their near-surface exposure. Also, portions of the former Utica-Lower Paleozoic TPS are now excluded from the newly defined TPS in a portion of northwestern Ohio and adjacent States to eliminate overlap with the Ordovician to Devonian Composite TPS in the Michigan basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195025","collaboration":" ","usgsCitation":"Enomoto, C.B., Trippi, M.H., and Higley, D.K., 2019, Ordovician Point Pleasant/Utica-Lower Paleozoic Total Petroleum System—Revisions to the Utica-Lower Paleozoic Total Petroleum System in the Appalachian Basin Province: U.S. Geological Survey Scientific Investigations Report 2019–5025, \n6 p., https://doi.org/10.3133/sir20195025. ","productDescription":"Report: iii, 14 p.; 1 Figure","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099699","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":363034,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5025/sir20195025.pdf","text":"Report","size":"3.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5025"},{"id":363033,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5025/coverthb.jpg"},{"id":363035,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2019/5025/sir20195025_fig2.pdf","text":"Figure 2","size":"345 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Correlation chart of the stratigraphic units in the Ordovician Point Pleasant/Utica-Lower Paleozoic Total Petroleum System"}],"country":"United States","otherGeospatial":"Appalachian Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86,\n 36\n ],\n [\n -74,\n 36\n ],\n [\n -74,\n 43\n ],\n [\n -86,\n 43\n ],\n [\n -86,\n 36\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Energy Resources Science Center
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954 National Center
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The use of single nucleotide polymorphism (SNP) arrays to generate large SNP datasets for comparison purposes have recently become an attractive alternative to other genotyping methods. Although most SNP arrays were originally developed for domestic organisms, they can be effectively applied to wild relatives to obtain large panels of SNPs. In this study, we tested the cross-species application of the Affymetrix 600K Chicken SNP array in five species of North American prairie grouse (Centrocercus and Tympanuchus genera). Two individuals were genotyped per species for a total of ten samples. A high proportion (91%) of the total 580 961 SNPs were genotyped in at least one individual (73–76% SNPs genotyped per species). Principal component analysis with autosomal SNPs separated the two genera, but failed to clearly distinguish species within genera. Gene ontology analysis identified a set of genes related to morphogenesis and development (including genes involved in feather development), which may be primarily responsible for large phenotypic differences between Centrocercus and Tympanuchus grouse. Our study provided evidence for successful cross-species application of the chicken SNP array in grouse which diverged ca. 37 mya from the chicken lineage. As far as we are aware, this is the first reported application of a SNP array in non-passerine birds, and it demonstrates the feasibility of using commercial SNP arrays in research on non-model bird species.
Tidal wetland fluxes of particulate organic matter and carbon (POM, POC) are important terms in global budgets but remain poorly constrained. Given the link between sediment fluxes and wetland stability, POM and POC fluxes should also be related to stability. We measured POM and POC fluxes in eight microtidal salt marsh channels, with net POM fluxes ranging between −121 ± 33 (export) and 102 ± 28 (import) g OM·m−2·year−1 and net POC fluxes ranging between −52 ± 14 and 43 ± 12 g C·m−2·year−1. A regression employing two measures of stability, the unvegetated‐vegetated marsh ratio (UVVR) and elevation, explained >95% of the variation in net fluxes. The regression indicates that marshes with lower elevation and UVVR import POM and POC while higher elevation marshes with high UVVR export POM and POC. We applied these relationships to marsh units within Barnegat Bay, New Jersey, USA, finding a net POM import of 2,355 ± 1,570 Mg OM/year (15 ± 10 g OM·m−2·year−1) and a net POC import of 1,263 ± 632 Mg C/year (8 ± 4 g C·m−2·year−1). The magnitude of this import was similar to an estimate of POM and POC export due to edge erosion (−2,535 Mg OM/year and − 1,291 Mg C/year), suggesting that this system may be neutral from a POM and POC perspective. In terms of a net budget, a disintegrating wetland should release organic material, while a stable wetland should trap material. This study quantifies that concept and demonstrates a linkage between POM/POC flux and geomorphic stability.
The Cornwall and Devon vein- and greisen-type copper and tin deposits of southwest England are spatially and genetically related to shallow-seated granitic intrusions. These late Variscan intrusions, collectively known as the Cornubian Batholith, extend over 200 km and form a continuous granitic spine from the Isles of Scilly Granite in the west to the Dartmoor Granite in the east. The granitic plutons of the Cornubian Batholith were intruded from ~ 295 to 270 Ma without a major hiatus. Twelve samples of cassiterite (SnO2) were obtained from tin deposits associated with seven different plutons within the Cornubian Batholith for in situ LA-ICPMS U–Pb dating. This study of cassiterite was undertaken to obtain the first results of direct dating of ore mineral to refine the geochronology of tin mineralization in this region. Of the cassiterite samples analyzed, the oldest ages were determined within the Kit Hill and Hingston–Gunnislake Granites in the central part of the Cornubian Batholith. The Hingston–Gunnislake cassiterite, from Drakewalls Mine, was the oldest sample dated at 291.8 ± 3.4 Ma. The next oldest dates, 290.5 ± 2.8 and 288.5 ± 2.9 Ma, were from two cassiterite samples extracted from the adjacent Kit Hill Consolidated Mines within the Kit Hill Granite. At the eastern end of the study area, two cassiterite samples within the Dartmoor Granite produced ages of 286.0 ± 1.8 and 284.1 ± 1.3 Ma. The youngest sample from this study, 275.4 ± 1.6 Ma, is from the Balleswidden Mine within the westernmost Land’s End Granite. The cassiterite dates do not reveal any readily observable relationship between ore ages and geographic relationship from west to east throughout the Cornubian Batholith. Incorporating the associated errors, the geochronology does indicate continuous mineralization within the granites for ~ 21 million years, from ca. 295 to 274 Ma. This span falls within the established period of granitic magmatism of ca. 295 to 270 Ma for the Cornubian Batholith and further confirms the reliability of in situ LA-ICPMS U–Pb dating of cassiterite.
","language":"English","publisher":"Springer","doi":"10.1007/s00126-019-00870-y","usgsCitation":"Moscati, R.J., and Neymark, L., 2019, U-Pb geochronology of tin deposits associated with the Cornubian Batholith of southwest England: Direct dating of cassiterite by in situ LA-ICPMS: Mineralium Deposita, v. 55, p. 1-20, https://doi.org/10.1007/s00126-019-00870-y.","productDescription":"20 p.","startPage":"1","endPage":"20","ipdsId":"IP-102427","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":363209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"England","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -3.399367930011948,\n 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rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":761521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neymark, Leonid A. 0000-0003-4190-0278 lneymark@usgs.gov","orcid":"https://orcid.org/0000-0003-4190-0278","contributorId":140338,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid A.","email":"lneymark@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":761522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202671,"text":"ofr20191026 - 2019 - Adaptive management of flows from R.L. Harris Dam (Tallapoosa River, Alabama)—Stakeholder process and use of biological monitoring data for decision making","interactions":[],"lastModifiedDate":"2019-11-22T06:49:08","indexId":"ofr20191026","displayToPublicDate":"2019-04-22T14:42:09","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1026","displayTitle":"Adaptive Management of Flows from R.L. Harris Dam (Tallapoosa River, Alabama)—Stakeholder Process and Use of Biological Monitoring Data for Decision Making","title":"Adaptive management of flows from R.L. Harris Dam (Tallapoosa River, Alabama)—Stakeholder process and use of biological monitoring data for decision making","docAbstract":"Adaptive management has been applied to problems with multiple conflicting objectives in various natural resources settings to learn how management actions affect divergent values regarding system response. Hydropower applications have only recently begun to emerge in the field, yet in the specific example reported herein, stakeholders invested in determining the best management alternatives for attainment of a suite of objectives outlined in a long-term adaptive management program below R.L. Harris Dam, a large, privately owned dam in Alabama. Stakeholders convened an objective-setting workshop to engage a governance structure and developed a decision support model to determine appropriate actions that optimized stakeholder values. The process led to implemented change in dam operation inclusive of incorporating hypothetical responses in system parameters to management. To account for the iterative loop of adaptive management, yearly monitoring of state variables that approximated many stakeholder objectives was performed from 2005 to 2016 and data collected were incorporated into the decision model. Specific analysis of fish and macroinvertebrate population responses indicated a less than satisfactory response for some stakeholders to the flow-management changes at the dam. Uncertainty regarding the best management to provide adequate hydrologic and thermal habitats for fauna and boatable days for recreationists still exists. The project led to a Federal Energy Regulatory Commission process for renewing the license to operate the dam (beginning in 2018); adaptive management could be a viable path forward to ensure stakeholder satisfaction related to new management options.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191026","collaboration":"Prepared in cooperation with the Alabama Department of Conservation and Natural Resources, Alabama Power Company, U.S. Fish and Wildlife Service, and R.L. Harris Dam Adaptive Management Stakeholders","usgsCitation":"Irwin, E.R., ed., 2019, Adaptive management of flows from R.L. Harris Dam (Tallapoosa River, Alabama)—Stakeholder process and use of biological monitoring data for decision making: U.S. Geological Survey Open-File Report 2019–1026, 93 p., https://doi.org/10.3133/ofr20191026.","productDescription":"Report: x, 93 p.; 4 Appendixes; 1 Table","numberOfPages":"108","onlineOnly":"Y","ipdsId":"IP-096592","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":363058,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_A2.pdf","text":"Appendix A2","size":"302 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix A2","linkHelpText":"– Initial Bayesian Belief Network (2005), Training Cases and Learned Networks (2005–16)"},{"id":363057,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_A1.pdf","text":"Appendix A1","size":"1.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix A1","linkHelpText":"– Transcripts from the Adaptive Management Workshop, April 30–May 1, 2003"},{"id":363061,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_table_C2.1.pdf","text":"Table C2.1","size":"198 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Table C2.1","linkHelpText":"– Sum of total observations for each macroinvertebrate taxon at all sites, listed alphabetically by class, order, family and taxon"},{"id":363060,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_B.pdf","text":"Appendix B","size":"296 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix B","linkHelpText":"– R code used to conduct metapopulation analyses"},{"id":363056,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026.pdf","text":"Report","size":"5.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026"},{"id":363053,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1026/coverthb3.jpg"},{"id":363059,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_A3.pdf","text":"Appendix A3","size":"112 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix A3","linkHelpText":"– Charter of the R.L. Harris Stakeholders Board"}],"country":"United States","state":"Alabama","otherGeospatial":"Tallapoosa River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.7208251953125,\n 32.93953889877841\n ],\n [\n -85.48324584960936,\n 32.93953889877841\n ],\n [\n -85.48324584960936,\n 33.6283419913718\n ],\n [\n -85.7208251953125,\n 33.6283419913718\n ],\n [\n -85.7208251953125,\n 32.93953889877841\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alabama Cooperative Fish and Wildlife Research Unit
School of Forestry and Wildlife Sciences
Auburn University
602 Duncan Dr.
Auburn, AL 36849–5418
A binational study was initiated to update statistical equations that are used to estimate the magnitude and frequency of peak flows on streams in Manitoba and Ontario, Canada, and Minnesota that are contained within the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada. Hydraulic engineers use peak streamflow data to inform designs of bridges, culverts, and dams, and water managers use peak streamflow data to inform regulation and planning activities. However, long-term streamflow measurements are available at few locations along the more than 20,000 miles of stream/ditch networks within the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada.
Estimates of peak-flow magnitudes for 66.7-, 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities equivalent to annual flood-frequency recurrence intervals of 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals, respectively, are presented for 49 streamgages in Minnesota and adjacent areas in the Province of Ontario, Canada, based on data collected through water year 2013. Peak-flow frequency information was subsequently used in regression analyses to develop equations relating peak flows for selected recurrence intervals to various basin and climatic characteristics.
The study area includes 49 streamgages located in the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada, and is represented by southern portions of the Canadian Provinces of Manitoba (2 percent) and Ontario (56 percent) and the northern portion of the U.S. State of Minnesota (42 percent). The study area was represented by three regions that were defined in previous studies in the U.S. State of Minnesota and another in the Canadian Province of Ontario. The two Minnesota regions A and B were developed using a multiple regression method and hydrologic landscape units were used to validate regions in Minnesota. The Ontario region A was developed using a multiple regression method and standardized residuals from the 100-year recurrence intervals.
Canadian maximum instantaneous peak-flow data were converted from a calendar year to a water year (October 1 to September 30) and where the annual maximum instantaneous peak-flow value was not available in HYDAT, the Sangal method was applied to known average daily flow values to estimate an annual maximum instantaneous peak-flow value. Geographic information system software was used to calculate eight characteristics investigated as potential explanatory variables in the regression analyses.
The procedure for estimating peak-flow frequency for selected exceedance probabilities for a specific ungaged site depends on whether the site is near a streamgage on the same stream or is on an ungaged stream. For an ungaged site near a streamgage on the same stream, the drainage-area ratio method can be used. For an ungaged site on an ungaged stream, the regional regression equations developed for this study should be used.
All equations presented in this study will be incorporated into StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey. StreamStats allows users to obtain streamflow statistics, basin characteristics, and other information for user-selected locations on streams through an interactive map.
Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
The dynamic, multiscale nature of stream systems makes it challenging to establish basic ecological principles to guide stream fish conservation and management. For example, finer-scale instream habitat is often constrained by coarser-scale characteristics driving observed species distributions. Additionally, instream environmental variability can result in patchy species distributions within general upstream–downstream occurrence patterns (i.e., variation around a common theme). Groundwater contribution, an often-overlooked habitat characteristic in warmwater systems, has numerous influences on the instream environment and can play a role in fish habitat-use patterns and assemblage structure. We identified multiscale instream habitat characteristics associated with the occurrence probability of 20 Ozark Highland stream fishes. Fishes were surveyed using tow-barge electrofishing in 76 channel unit complexes (i.e., riffle-to-riffle habitat sequences) nested in 20 reaches of northwest Oklahoma and southwest Missouri. We used a multiscale, multispecies generalized linear mixed model to identify relationships between fish occurrence and both channel unit complex- and reach-scale variables. Stream fishes were more likely to occur in larger or deeper channel unit complexes. Fish occurrence was also associated with different levels of reach-scale groundwater contribution, bankfull width-to-depth ratio, and percent instream cover. Ten fishes, typically associated with warmer water temperatures, had lower occurrence probabilities in reaches with higher groundwater contribution, whereas Banded Sculpin Cottus carolinae and Creek Chub Semotilus atromaculatus occurrence probabilities were higher. There was no relationship between occurrence probabilities and instream cover for 11 fishes. The occurrence probabilities in relation to varying amounts of instream cover for the other nine stream fishes was dependent on bankfull width-to-depth ratio, where the direction and magnitude of the relationships varied among stream fishes. The variation in occurrence relationships can be attributed to thermal preferences, environmental interactions, and the use of multiple habitat types. Our findings demonstrate the multiscale nature of fish occurrence relationships and how conservation and management may benefit from considering this complexity when developing holistic instream habitat enhancement strategies.
","language":"English","publisher":"American Society of Ichthyologists and Herpetologists","doi":"10.1643/CE-18-099","usgsCitation":"Mollenhauer, R., Zhou, Y., and Brewer, S.K., 2019, Multiscale habitat factors explain variability in stream fish occurrence in the Ozark Highlands ecoregion, USA: Copeia, v. 107, no. 2, p. 219-231, https://doi.org/10.1643/CE-18-099.","productDescription":"13 p.","startPage":"219","endPage":"231","ipdsId":"IP-099822","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Ozark Highlands ecoregion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.1910400390625,\n 36.465471886798134\n ],\n [\n -93.9935302734375,\n 36.465471886798134\n ],\n [\n -93.9935302734375,\n 36.99816565700228\n ],\n [\n -95.1910400390625,\n 36.99816565700228\n ],\n [\n -95.1910400390625,\n 36.465471886798134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mollenhauer, Robert","contributorId":274327,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Yan","contributorId":274328,"corporation":false,"usgs":false,"family":"Zhou","given":"Yan","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832909,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203128,"text":"70203128 - 2019 - Adaptive Management and Monitoring","interactions":[],"lastModifiedDate":"2019-04-25T08:33:30","indexId":"70203128","displayToPublicDate":"2019-04-22T10:19:14","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Adaptive Management and Monitoring","docAbstract":"This is a chapter in a technical report that is the second of two works describing longer-term actions to implement policies and strategies for preventing and suppressing rangeland fire and restoring rangeland landscapes affected by fire in the Western United States. The first part, Chambers et al 2017, \"Science Framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions. Part 1. Science basis and applications\" provides information and decision support tools. This part 2 describes application and use of part 1 to resource managers.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Science framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions. Part 2. Management applications","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Forest Service","usgsCitation":"Wiechman, L.A., Pyke, D.A., Crist, M., Munson, S., Brooks, M., Chambers, J.C., Rowland, M.M., Kachergis, E.J., and Davidson, Z., 2019, Adaptive Management and Monitoring, 13 p.","productDescription":"13 p.","startPage":"19","endPage":"31","ipdsId":"IP-096061","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":363178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363120,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/treesearch/pubs/57911"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wiechman, Lief A. 0000-0002-3804-4426","orcid":"https://orcid.org/0000-0002-3804-4426","contributorId":184047,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","email":"","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":761295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crist, Michele R.","contributorId":178453,"corporation":false,"usgs":false,"family":"Crist","given":"Michele R.","affiliations":[],"preferred":false,"id":761296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth","contributorId":214953,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":761297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooks, Matthew 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":214954,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":761298,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chambers, Jeanne C.","contributorId":178256,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":761299,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rowland, Mary M.","contributorId":173292,"corporation":false,"usgs":false,"family":"Rowland","given":"Mary","email":"","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":761300,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kachergis, Emily J","contributorId":214955,"corporation":false,"usgs":false,"family":"Kachergis","given":"Emily","email":"","middleInitial":"J","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":761301,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davidson, Zoe","contributorId":214956,"corporation":false,"usgs":false,"family":"Davidson","given":"Zoe","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":761302,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70215404,"text":"70215404 - 2019 - Aluminum mobility in mildly acidic mine drainage: Interactions between hydrobasaluminite, silica and trace metals from the nano to the meso-scale","interactions":[],"lastModifiedDate":"2020-10-18T15:23:00.83267","indexId":"70215404","displayToPublicDate":"2019-04-22T10:15:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Aluminum mobility in mildly acidic mine drainage: Interactions between hydrobasaluminite, silica and trace metals from the nano to the meso-scale","docAbstract":"Aluminum precipitates control the hydrochemistry and mineralogy of a broad variety of environments on Earth (e.g., acid mine drainage, AMD, coastal wetlands, boreal and alpine streams, tropical acid sulfate soils, laterites and bauxites, …). However, the geochemical and mineralogical processes controlling Al (and other associated metals and metalloids) transport and removal in those environments are not fully understood. The geochemical system of Paradise Portal (Colorado, USA) comprises sulfate-rich mildly acidic waters, the hydrochemistry of which is directly controlled by the massive precipitation of hydrobasaluminite Al4(SO4)(OH)10·12-36H2O. Three connected but discernible aluminum precipitation stages were identified and described: 1) nanoparticle formation and size decrease along the creek, 2) hydrobasaluminite neoformation on the riverbed, and 3) precipitate accretion and accumulation on the riverbed leading to Al and Fe banded formations. The co-occurrence of Al and Si in the system was observed, recording significant amounts of Si accompanying the three different components of the system (i.e., nanoparticles and fresh and aged Al-precipitates). Also, abrupt and minor changes in the sedimentary record were described and proposed to be the response of the system to seasonal and interannual changes in AMD chemistry. Concerning the mobility of other metals and metalloids, P, Th, V, W, Ti and B showed a tendency to be preferentially incorporated into hydrobasaluminite, while others like Be, As, Se or Ba tend to remain dissolved in the water.
The quantity and character of dissolved organic matter (DOM) can change rapidly during storm events, affecting key biogeochemical processes, carbon bioavailability, metal pollutant transport, and disinfection byproduct formation during drinking water treatment. We used in situ ultraviolet–visible spectrophotometers to concurrently measure dissolved organic carbon (DOC) concentration and spectral slope ratio, a proxy for DOM molecular weight. Measurements were made at 15-minute intervals over three years in three streams draining primarily agricultural, urban, and forested watersheds. We describe storm event dynamics by calculating hysteresis indices for DOC concentration and spectral slope ratio for 220 storms and present a novel analytical framework that can be used to interpret these metrics together. DOC concentration and spectral slope ratio differed significantly among sites, and individual storm DOM dynamics were remarkably variable at each site and among the three sites. Distinct patterns emerged for storm DOM dynamics depending on land use/land cover (LULC) of each watershed. In agricultural and forested streams, DOC concentration increased after the time of peak discharge, and spectral slope ratio dynamics indicate that this delayed flux was of relatively higher molecular weight material compared to the beginning of each storm. In contrast, DOM character during storms at the urban stream generally shifted to lower molecular weight while DOC concentration increased on the falling limb, indicating either the introduction of lower molecular weight DOM, the exhaustion of a higher molecular weight DOM sources, or a combination of these factors. We show that the combination of high-frequency DOM character and quantity metrics have the potential to provide new insight into short-timescale DOM dynamics and can reveal previously unknown effects of LULC on the chemical nature, source, and timing of DOM export during storms.
Paleohydrologic reconstructions of water-year streamflow for 105 sites across the western United States (West) were used to compute the likelihood (risk) of regime (wet/dry state) shifts given the length of time in a specific regime and for a specified time in the future. The spatial variability of risks was examined and indicates that regime shift risks are variable across the West. The Pacific-Northwest region is associated with low risks of regime shifts, indicating persistence controlled by prevalent low frequency variability in flow (periods above 64 years). Other areas in the West indicate higher risks compared to the Pacific-Northwest due to flow variability in the mid-to-high frequencies (periods of 32 to 16 years). Understanding risks of regime shifts provides critical information for improved management of water supplies, particularly during periods of extended low flows. The method presented here has global applicability as a decision-making framework for risk-based planning and management.
The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO).
This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes.
During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes.
The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without.
A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point:
During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191033","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration, FourBridges, European Space Agency, and European Association of Remote Sensing Companies","usgsCitation":"Pearlman, F., Lawrence, C.B., Pindilli, E.J., Geppi, D., Shapiro, C.D., Grasso, M., Pearlman, J., Adkins, J., Sawyer, G., and Tassa, A., 2019, Demonstrating the value of Earth observations—Methods, practical applications, and solutions—Group on Earth Observations side event proceedings: U.S. Geological Survey Open-File Report 2019–1033, 33 p., https://doi.org/10.3133/ofr20191033.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102614","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":363044,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1033/coverthb.jpg"},{"id":363045,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1033/ofr20191033.pdf","text":"Report","size":"1.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1033"}],"contact":"Science and Decisions Center
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Email: gs_emeh_sdc@usgs.gov
The tropics are a region encircling the equator, delineated to the north by the Tropic of Cancer (23°26′14.0″N) and to the south by the Tropic of Capricorn (23°26′14.0″S). While we often think of the tropics as consistently warm and wet throughout the year, in reality, the tropics maintain a myriad of climates. Of the 116 Holdridge life zones (a global bioclimatic classification scheme), the tropics contain more life zones than the sum of all the planet's other geographic regions combined (Holdridge, 1967). In addition to high climatic diversity, the tropics support a wide range of parent materials, landforms, geomorphic characteristics, and soil ages, and maintain all 12 soil types of the USDA soil taxonomy system (Palm et al., 2007; Porder et al., 2007; Quesada et al., 2010; Richter and Babbar, 1991; Sanchez, 1977; Soil Survey Staff, 2006; Townsend et al., 2008). Accordingly, there is no single representative tropical ecosystem. Given the diversity of tropical biomes, this chapter will focus specifically on tropical forested ecosystems and their responses to warming because of their global importance, potential sensitivity to change, and the fact that an improved understanding of how these ecosystems may respond to warmer climate conditions is of significant importance to ecology and society. Furthermore, while generally considering all tropical forest types, emphasis in this chapter is on the humid tropics for which we have most data.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecosystem consequences of soil warming: Microbes, vegetation, fauna and soil biogeochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-813493-1.00015-6","usgsCitation":"Wood, T.E., Cavaleri, M., Giardina, C.P., Khan, S., Mohan, J., Nottingham, A.T., Reed, S., and Slot, M., 2019, Soil warming effects on tropical forests with highly weathered soils, chap. 14 of Ecosystem consequences of soil warming: Microbes, vegetation, fauna and soil biogeochemistry, p. 385-439, https://doi.org/10.1016/B978-0-12-813493-1.00015-6.","productDescription":"55 p.","startPage":"385","endPage":"439","ipdsId":"IP-102016","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":389955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Tana E.","contributorId":197805,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","middleInitial":"E.","affiliations":[],"preferred":false,"id":824198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cavaleri, Molly A.","contributorId":67381,"corporation":false,"usgs":true,"family":"Cavaleri","given":"Molly A.","affiliations":[],"preferred":false,"id":824199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giardina, Christian P. 0000-0002-3431-5073","orcid":"https://orcid.org/0000-0002-3431-5073","contributorId":182695,"corporation":false,"usgs":false,"family":"Giardina","given":"Christian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":824200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khan, Shafkat","contributorId":266048,"corporation":false,"usgs":false,"family":"Khan","given":"Shafkat","email":"","affiliations":[],"preferred":false,"id":824201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohan, Jacqueline","contributorId":62924,"corporation":false,"usgs":true,"family":"Mohan","given":"Jacqueline","email":"","affiliations":[],"preferred":false,"id":824202,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nottingham, Andrew T.","contributorId":266049,"corporation":false,"usgs":false,"family":"Nottingham","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":824203,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824204,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Slot, Martijn","contributorId":266050,"corporation":false,"usgs":false,"family":"Slot","given":"Martijn","email":"","affiliations":[],"preferred":false,"id":824205,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203199,"text":"70203199 - 2019 - Evaluating and using existing models to map probable suitable habitat for rare plants to inform management of multiple-use public lands in the California desert","interactions":[],"lastModifiedDate":"2019-04-29T08:53:31","indexId":"70203199","displayToPublicDate":"2019-04-19T08:53:00","publicationYear":"2019","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":"Evaluating and using existing models to map probable suitable habitat for rare plants to inform management of multiple-use public lands in the California desert","docAbstract":"Multiple-use public lands require balancing diverse resource uses and values across landscapes. In the California desert, there is strong interest in renewable energy development and important conservation concerns. The Bureau of Land Management recently completed a land-use plan for the area that provides protection for modeled suitable habitat for multiple rare plants. Three sets of habitat models were commissioned for plants of conservation concern as part of the planning effort. The Bureau of Land Management then needed to determine which model or combination of models to use to implement plan requirements. Our goals were to: 1) develop a process for evaluating the existing habitat models and 2) use the evaluation results to map probable and potential suitable habitat. We developed a method for evaluating the construction (input data and methods) and performance of existing models and applied it to 88 habitat models for 43 rare plant species. We also developed a process for mapping probable and potential suitable habitat based on the existing models; potential habitat maps are intended only to guide future field surveys. We were able to map probable suitable habitat for 26 of the 43 species and potential suitable habitat for 41 species. Forty percent of the project area contains probable suitable habitat for at least one species (43,338 km2), with much of that habitat (43%) occurring on lands managed by the Bureau of Land Management. Lands prioritized for renewable energy development contain 3% of the habitat modeled as suitable for at least one species. Our products can be used by agencies to review proposed projects and plan future plant surveys and by developers to target sites likely to minimize conflicts with rare plant conservation goals. Our methods can be broadly applied to understand and quantify the defensibility of models used in conservation and regulatory contexts.","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0214099","usgsCitation":"Reese, G., Carter, S.K., Lunch, C., and Walterscheid, S., 2019, Evaluating and using existing models to map probable suitable habitat for rare plants to inform management of multiple-use public lands in the California desert: PLoS ONE, v. 14, no. 4, 26 p., https://doi.org/10.1371/journal.pone.0214099.","productDescription":"26 p.","ipdsId":"IP-099792","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467685,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0214099","text":"Publisher Index Page"},{"id":437493,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NDA9YC","text":"USGS data release","linkHelpText":"Probable and potential suitable habitat for 43 rare plant species in the California desert"},{"id":363287,"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 -122.27783203125,\n 31.87755764334002\n ],\n [\n -113.88427734374999,\n 31.87755764334002\n ],\n [\n -113.88427734374999,\n 38.22091976683121\n ],\n [\n -122.27783203125,\n 38.22091976683121\n ],\n [\n -122.27783203125,\n 31.87755764334002\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Reese, Gordon 0000-0002-5191-7770 greese@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-7770","contributorId":215093,"corporation":false,"usgs":true,"family":"Reese","given":"Gordon","email":"greese@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lunch, Christina","contributorId":215094,"corporation":false,"usgs":false,"family":"Lunch","given":"Christina","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":761614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walterscheid, Steve","contributorId":215095,"corporation":false,"usgs":false,"family":"Walterscheid","given":"Steve","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":761615,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202389,"text":"sir20185170 - 2019 - Drinking water health standards comparison and chemical analysis of groundwater for 72 domestic wells in Bradford County, Pennsylvania, 2016","interactions":[],"lastModifiedDate":"2019-06-12T10:00:24","indexId":"sir20185170","displayToPublicDate":"2019-04-19T08:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5170","displayTitle":"Drinking Water Health Standards Comparison and Chemical Analysis of Groundwater for 72 Domestic Wells in Bradford County, Pennsylvania, 2016","title":"Drinking water health standards comparison and chemical analysis of groundwater for 72 domestic wells in Bradford County, Pennsylvania, 2016","docAbstract":"Pennsylvania has the second highest number of residential wells of any state in the Nation with approximately 2.4 million residents that depend on groundwater for their domestic water supply. Despite the widespread reliance on groundwater in rural areas of the state, publicly available data to characterize the quality of private well water are limited. In Bradford County, more than half of the residents use groundwater from private domestic-supply wells as their primary drinking source. The quality of private well water is influenced by the regional and local setting, including the surrounding soil, geology, land use, household plumbing, and well construction. The groundwater used for domestic water supply in Bradford County is obtained primarily from shallow bedrock and from unconsolidated (glacial) deposits that overlie the bedrock. Historical land use has been predominately forested, agricultural, and residential, but more recently unconventional oil/gas development has been distributed throughout the landscape. Pennsylvania is one of only two states in the Nation without statewide water-well construction standards.
To better assess the quality of groundwater used for drinking water supply in Bradford County, data for 72 domestic wells were collected and analyzed for a wide range of constituents that could be evaluated in relation to drinking water health standards, geology, land use, and other environmental factors. Groundwater samples were collected from May through August 2016 and analyzed for physical and chemical properties, including major ions, nutrients, trace elements, volatile organic compounds, ethylene and propylene glycol, alcohols, gross-alpha/beta-particle activity, uranium, radon-222, and dissolved gases. A subset of samples was analyzed for radium isotopes (radium-226 and -228) and for the isotopic composition of methane. This study was conducted by the U.S. Geological Survey in cooperation with the Northern Tier Regional Planning and Development Commission and is part of a regional effort to characterize groundwater in rural areas of Pennsylvania.
Results of the 2016 study show that groundwater quality generally met most drinking-water standards. However, a percentage of samples failed to meet maximum contaminant levels (MCLs) for total coliform bacteria (49.3 percent), Escherichia coli (8.5 percent), barium (2.8 percent), and arsenic (2.8 percent); and secondary maximum contaminant levels (SMCL) for sodium (48.6 percent), manganese (30.6 percent), gross alpha and beta activity (16.7 percent), iron (11.1 percent), pH (8.3 percent), total dissolved solids (5.6 percent), chloride (1.4 percent), and aluminum (1.4 percent). Radon-222 activities exceeded the proposed drinking-water standard of 300 picocuries per liter (pCi/L) in 70.4 percent of the samples. There were no exceedances of drinking water health standards for any volatile organic compounds, and the only detections were for three trihalomethanes in one sample.
The pH of the groundwater had a large influence on chemical characteristics and ranged from 6.18 to 9.31. Generally, the higher pH samples had higher potential for elevated concentrations of several constituents, including total dissolved solids, sodium, lithium, chloride, fluoride, boron, arsenic, and methane. For the Bradford County well-water samples, calcium/bicarbonate type waters were most abundant, with others classified as sodium/bicarbonate or mixed water types including calcium-sodium/bicarbonate, calcium-sodium/bicarbonate-chloride, sodium/bicarbonate-chloride, sodium/bicarbonate-sulfate, or sodium/chloride types. Six principal components (pH, redox, hardness, chloride-bromide, strontium-barium, and molybdenum-arsenic) explained nearly 78.3 percent of the variance in the groundwater dataset.
Groundwater from 12.5 percent of the wells had concentrations of methane greater than the Pennsylvania action level of 7 milligrams per liter (mg/L); detectable methane concentrations ranged from 0.01 to 77 mg/L. In addition, low levels of ethane (as much as 0.13 mg/L) were present in seven samples with the highest methane concentrations. The isotopic composition of methane in five of these groundwater samples was consistent with the isotopic compositions reported for mud-gas logging samples from these geologic units and a thermogenic source. Isotopic composition from a sixth sample suggested the methane in that sample may be of microbial origin. Well-water samples with the higher methane concentrations also had higher pH values and elevated concentrations of sodium, lithium, boron, fluoride, arsenic, and bromide. Relatively elevated concentrations of some other constituents, such as barium and chloride, commonly were present in, but not limited to, those well-water samples with elevated methane.
Four of the six groundwater samples with the highest methane concentrations had chloride/bromide ratios that indicate mixing with a small amount of brine (0.02 percent or less) similar in composition to those reported for gas and oil well brines in Pennsylvania. In several other eastern Pennsylvania counties where gas drilling is absent, groundwater with comparable chloride/bromide ratios and chloride concentrations have been reported, implying a potential natural source of brine. Most of Bradford County well-water samples have chloride concentrations less than 20 mg/L, and those with higher chloride concentrations have chloride/bromide ratios that indicate anthropogenic sources (such as road-deicing salt and septic effluent) or brine. Brines that are naturally present may originate from deeper parts of the aquifer system, whereas anthropogenic sources are more likely to affect shallow groundwater because they occur on or near the land surface.
The available data for this study indicate that no one physical factor, such as the topographic setting, well depth, or altitude at the bottom of the well, was particularly useful for predicting those well locations with an elevated dissolved concentration of methane. The 2016 assessment of groundwater quality in Bradford County shows groundwater is generally of good quality, but methane and some constituents that occur in high concentration in naturally occurring brine and also in produced waters may be present at low to moderate concentrations in groundwater in various parts of the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185170","collaboration":"Prepared in cooperation with the Northern Tier Regional Planning and Development Commission","usgsCitation":"Clune, J.W., and Cravotta, C.A., III, 2019, Drinking water health standards comparison and chemical analysis of groundwater for 72 domestic wells in Bradford County, Pennsylvania, 2016 (ver 1.2, May 30, 2019): U.S. Geological Survey Scientific Investigations Report 2018–5170, 66 p., https://doi.org/10.3133/sir20185170.","productDescription":"Report: vi, 66 p.; Data Release","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098593","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":363039,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5170/coverthb4.jpg"},{"id":363132,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5170/versionHist.txt","text":"Version History","size":"1.24 KB","linkFileType":{"id":2,"text":"txt"}},{"id":363047,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VRV6US","text":"USGS data release","description":"USGS data release","linkHelpText":"Compilation of Data Not Available in the National Water Information System for Domestic Wells Sampled by the U.S. Geological Survey in Bradford County, Pennsylvania, May-August 2016"},{"id":363040,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5170/sir20185170.pdf","text":"Report","size":"8.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5170"}],"country":"United States","state":"Pennsylvania","county":"Bradford County ","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-76.9291,42.0024],[-76.9095,42.0025],[-76.8966,42.0026],[-76.6476,42.0019],[-76.6334,42.0017],[-76.5964,42.0013],[-76.5618,42.0009],[-76.5531,42.0008],[-76.5229,42.0005],[-76.466,41.9999],[-76.3826,41.9989],[-76.1467,41.9991],[-76.1382,41.898],[-76.1336,41.8467],[-76.1285,41.7935],[-76.1258,41.773],[-76.1219,41.7217],[-76.1171,41.6531],[-76.1959,41.648],[-76.1996,41.6467],[-76.2015,41.6435],[-76.2015,41.6426],[-76.2015,41.6408],[-76.2016,41.6353],[-76.2016,41.6344],[-76.2023,41.6335],[-76.2029,41.6322],[-76.2063,41.6145],[-76.209,41.6004],[-76.2091,41.5982],[-76.2184,41.5579],[-76.2217,41.5447],[-76.2383,41.5458],[-76.2432,41.5463],[-76.2487,41.5468],[-76.3277,41.5526],[-76.4454,41.5608],[-76.5,41.5649],[-76.5975,41.5715],[-76.6367,41.5745],[-76.6478,41.5755],[-76.6619,41.5765],[-76.679,41.578],[-76.6938,41.579],[-76.6993,41.5795],[-76.7496,41.5834],[-76.7569,41.5839],[-76.787,41.5872],[-76.7949,41.5882],[-76.8005,41.5887],[-76.8103,41.5896],[-76.8133,41.5901],[-76.8219,41.5911],[-76.8379,41.593],[-76.8747,41.5968],[-76.8747,41.599],[-76.8805,41.6363],[-76.8833,41.6681],[-76.8838,41.6717],[-76.885,41.6781],[-76.8873,41.6999],[-76.8907,41.7267],[-76.8936,41.7503],[-76.8976,41.783],[-76.8987,41.8007],[-76.8993,41.808],[-76.9022,41.8248],[-76.9022,41.8257],[-76.9051,41.8466],[-76.9162,41.918],[-76.9209,41.9507],[-76.9238,41.9711],[-76.9291,42.0024]]]},\"properties\":{\"name\":\"Bradford\",\"state\":\"PA\"}}]}","edition":"Version 1.2: May 30, 2019; Version 1.1: April 23, 2019; Version 1.0: April 19, 2019","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070