Invasive species are a subset of non-native (or alien) species, and knowing what species are non-native to a region is a first step to managing invasive species. People have been compiling non-native and invasive species lists ever since these species started causing harm, yet national non-native species lists are neither universal, nor common. Non-native species lists serve diverse purposes: watch lists for preventing invasions, inventory and monitoring lists for research and modeling, regulatory lists for species control, and nonregulatory lists for raising awareness. This diversity of purpose and the lists’ variation in geographic scope make compiling comprehensive lists of established (or naturalized) species for large regions difficult. However, listing what species are non-native in an area helps measure Essential Biodiversity Variables for invasive species monitoring and mount an effective response to established non-native species. In total, 1,166 authoritative sources were reviewed to compile the first comprehensive non-native species list for three large regions of the United States: Alaska, Hawaii, and the conterminous United States (lower 48 States). The list contains 11,344 unique names: 598 taxa for Alaska, 5,848 taxa for Hawaii, and 6,675 taxa for the conterminous United States. The list is available to the public from U.S. Geological Survey ScienceBase (https://doi.org/10.5066/P9E5K160), and the intent, though not a guarantee, is to update the list as non-native species become established in, or are eliminated from, the United States. The list has been used to annotate non-native species occurrence records in the U.S. Geological Survey all-taxa mapping application, Biodiversity Information Serving Our Nation (BISON, https://bison.usgs.gov).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181156","collaboration":" ","usgsCitation":"Simpson, A., and Eyler, M.C., 2018, First comprehensive list of non-native species established in three major regions of the United States: U.S. Geological Survey Open-File Report 2018-1156, 15 p., https://doi.org/10.3133/ofr20181156.","productDescription":"v; 15 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090660","costCenters":[{"id":38106,"text":"Science Analytics and Synthesis Program ","active":true,"usgs":true}],"links":[{"id":437693,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E5K160","text":"USGS data release","linkHelpText":"A comprehensive list of non-native species established in three major regions of the United States: Version 3.0"},{"id":358802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1156/coverthb.jpg"},{"id":358803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1156/ofr20181156.pdf","text":"Report","size":"1.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1156"}],"country":"United States","contact":"Director, Science Analytics Synthesis Program
U.S. Geological Survey
West 6th Avenue and Kipling Street
Lakewood, CO 80225
In 2016, the U.S. Geological Survey (USGS) Environmental Health Mission Area, initiated the Tapwater Exposure Study as part of an infrastructure project to assess human exposure to potential threats from complex mixtures of contaminants. In the pilot phase (2016), samples were collected from 11 States throughout the United States, and in the second phase (2017), the study focused on the Greater Chicago area, including North and South Chicago, Illinois, and East Chicago, Indiana. Residential tapwater samples were collected at private residences during both phases, and during the first phase, samples were collected from Federal office buildings and from one office 19-liter water-bottle source. During the second phase, raw intake and treated (pre-distributional) water samples also were collected from four drinking-water treatment facilities in the Greater Chicago area. Samples were sent to laboratories at the USGS, U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, and Colorado School of Mines Center for Environmental Risk Assessment, for potential drinking-water pathogens, chemical, and bioassay analyses. These analyses included more than 400 chemicals such as trace elements, steroid hormones, pharmaceuticals, volatile organic compounds, pesticides, per- and polyfluorinated alkyl substances, cyanotoxins, and other organic compounds. The in vitro bioassay analyses included estrogen, androgen, and glucocorticoid receptor activity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181098","collaboration":"Prepared in cooperation with the Colorado School of Mines, Center for Environmental Risk Assessment; National Institutes of Health/National Institute of Environmental Health Sciences (NIH/NIEHS), National Toxicology Program Laboratory; University of Illinois at Chicago, School of Public Health; U.S. Environmental Protection Agency, National Exposure Research Laboratory; U.S. Environmental Protection Agency, National Health and Environmental Effects Laboratory","usgsCitation":"Romanok, K.M., Kolpin, D.W., Meppelink, S.M., Argos, M., Brown, J.B., DeVito, M.J., Dietze, J.E., Givens, C.E., Gray, J.L., Higgins, C.P., Hladik, M.L., Iwanowicz, L.R., Loftin, K.A., McCleskey, R.B., McDonough, C.A., Meyer, M.T., Strynar, M.J., Weis, C.P., Wilson, V.S., and Bradley, P.M., 2018, Methods used for the collection and analysis of chemical and biological data for the Tapwater Exposure Study, United States, 2016–17: U.S. Geological Survey Open-File Report 2018–1098, 79 p., https://doi.org/10.3133/ofr20181098.","productDescription":"Report: ix, 79 p.; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094498","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":358920,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1098/coverthb.jpg"},{"id":358921,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1098/ofr20181098.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1098"},{"id":358923,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181071","text":"Open-File Report 2018-1071","linkHelpText":"- Concentrations of Lead and Other Inorganic Constituents in Samples of Raw Intake and Treated Drinking Water From the Municipal Water Filtration Plant and Residential Tapwater in Chicago, Illinois, and East Chicago, Indiana, July–December 2017"},{"id":358922,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7959GVJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Target-Chemical Concentrations, Exposure Activity Ratios, and Bioassay Results for Assessment of Mixed-Organic/Inorganic-Chemical Exposure in USA Tapwater, 2016"},{"id":359038,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70R9NN0","text":"USGS data release","description":"USGS data release","linkHelpText":"Occurrence and Concentrations of Trace Elements in Discrete Tapwater Samples Collected in Chicago, Illinois and East Chicago, Indiana, 2017"}],"country":"United States","geographicExtents":"{\n 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U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
The U.S. Geological Survey (USGS) Environmental Health Mission Area (EHMA) is providing comprehensive science on sources, movement, and transformation of contaminants and pathogens in watershed and aquifer drinking-water supplies and in built water and wastewater infrastructure (referred to as the USGS Water and Wastewater Infrastructure project) in the Greater Chicago Area and elsewhere in the United States, to fill data gaps identified by stakeholders and collaborators in drinking water and public health. EHMA Water and Wastewater Infrastructure research specifically provides insight into natural factors in the environment as well as those water-infrastructure components and processes (such as source-water corrosivity, treatment, plumbing, and so forth) that might influence human exposure to chemical and microbial contaminants at the residential tap. This infrastructure-exposure research role is fulfilled uniquely by the USGS and not by the U.S. Environmental Protection Agency (EPA), other agencies, or municipalities that focus on regulatory and policy activities and related compliance. The USGS approach to assessing the possible links between human health and chemical contaminant and pathogen exposure in drinking water is conducted in collaboration with public health experts and includes comprehensive characterization of the presence/absence and concentrations of more than 500 organic and 27 inorganic chemical constituents at the point of use (tap).
Laboratory results for lead and other inorganic contaminants in Chicago, Illinois, and East Chicago, Indiana, residential tapwater are being released to ensure the timely release of quality-assured data to participants in the study. Concentrations of lead and other inorganic constituents were assessed in drinking water at the point of use (kitchen tap or filter) in 45 residential locations and in two locations within each of the two Chicago water purification plants and the two East Chicago water filtration plants during July–December 2017. Three methods were used for analyzing lead. The most sensitive method had a reporting limit of 0.020 micrograms per liter (µg/L). When using the most sensitive analytical method, lead was detected in 39 of 45 residential tapwater samples, with concentrations ranging from less than 0.020 µg/L to 5.31 µg/L (median of the detected values = 0.481 µg/L). Concentrations of lead also were detected in Lake Michigan intake water at all water purification/filtration plant facilities at concentrations ranging from 0.083 to 0.330 µg/L, but were not detected above the reporting limit in any samples of treated, pre-distribution drinking water at any of the water purification/filtration plant facilities.
Because the USGS Water and Wastewater Infrastructure project in the Greater Chicago Area is focused on the potential human exposure to a broad suite of organic and inorganic contaminants in drinking water and is not focused specifically on lead, the sampling protocol did not include “first-draw,” stagnant sampling and samples were collected with point-of-use treatment in place, if present. Thus, the lead results reported herein are not appropriate for assessment of compliance with the EPA 1991 Lead and Copper Rule. Information resources for lead mitigation and water filtration are provided.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181071","collaboration":"Prepared in cooperation with the City of Chicago, Department of Water Management; City of East Chicago, Utilities Department; Indiana Department of Environmental Management, Drinking Water Branch; National Institutes of Health/National Institute of Environmental Health Sciences (NIH/NIEHS); University of Illinois at Chicago, School of Public Health","usgsCitation":"Romanok, K.M., Kolpin, D.W., Meppelink, S.M., Focazio, M.J., Argos, M., Hollingsworth, M.E., McCleskey, R.B., Putz, A.R., Stark, A., Weis, C.P., Zehraoui, A., and Bradley, P.M., 2018, Concentrations of lead and other inorganic constituents in samples of raw intake and treated drinking water from the municipal water filtration plant and residential tapwater in Chicago, Illinois, and East Chicago, Indiana, July–December 2017: U.S. Geological Survey Open-File Report 2018–1071, 10 p., https://doi.org/10.3133/ofr20181071.","productDescription":"Report: iv, 10 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094493","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":358915,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181098","text":"Open-File Report 2018–1098","linkHelpText":"- Methods Used for the Collection and Analysis of Chemical and Biological Data for the Tapwater Exposure Study, United States, 2016–17"},{"id":358912,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1071/coverthb.jpg"},{"id":358914,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F70R9NN0","text":"USGS data release ","description":"USGS data release ","linkHelpText":"Occurrence and Concentrations of Trace Elements in Discrete Tapwater Samples Collected in Chicago, Illinois and East Chicago, Indiana, 2017"},{"id":358913,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1071/ofr20181071.pdf","text":"Report","size":"1.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1071"}],"country":"United States","state":"Illinois, Indiana","city":"Chicago, East Chicago","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
The U.S. Geological Survey, in cooperation with the St. Johns River Water Management District, conducted a study to examine water fluxes in two small study areas in the Indian River Lagoon. Vertical arrays of temperature sensors were placed at multiple locations in the lagoon bed to measure temperature time series in the vertical profile. These data at one of the study areas, Eau Gallie, were used in two numerical models, 1DTempPro and VFLUX, to estimate seepage flux rates into the lagoon. 1DTempPro uses an inverse-modeling approach to calibrate groundwater flux to the measured temperature time series. VFLUX isolates the fundamental frequency signal in the temperature data and utilizes the resulting amplitude and phase differences between sensor locations to determine vertical water flux.
Field measurements were made during two time periods, March 23 to April 28, 2017, and June 1 to November 3, 2017. Simulating the first, drier period at one location with 1DTempPro helped determine reasonable seepage fluctuations and provided guidelines for choosing which temperature sensor pairs used in the VFLUX simulations would produce the best results. VFLUX simulations at eight locations indicated daily average seepage flux rates of less than 20 centimeters per day (cm/d) and substantial seepage flux out to a distance of at least 110 meters from shore. The spatial variation in average seepage flux rates within 40 meters of shore seemed large, ranging from about 3 to 20 cm/d.
In the VFLUX application using the June 1–November 3, 2017 data, the seepage flux has a higher magnitude and fluctuation than the first simulation period, making the isolation of the fundamental temperature frequency signal in the temperature data difficult. However, useful partial or full simulations were achieved at 6 of the 10 locations. The storm surge of Hurricane Irma on September 10, 2017, changed the depths of the sensors relative to the lagoon bed and disrupted the ability of VFLUX to compute seepage flux for the posthurricane period. The June 1 to November 3, 2017, computed seepage flux rates were higher than those for the March 24 to April 28, 2017, period and were sometimes as great as 40 cm/d, and more than 60 cm/d at one location. The seepage time-series data collected during Hurricane Irma indicates a downward seepage flux as a result of the storm surge, followed by upwelling from precipitation recharge inland. The average seepage flux rates are higher than those during the March–April period and are over 25 cm/d near the coast and about 20 cm/d 130 meters offshore.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181151","collaboration":"Prepared in cooperation with the St. Johns River Water Management District","usgsCitation":"Swain, E.D., and Prinos, S.T., 2018, Using heat as a tracer to determine groundwater seepage in the Indian River Lagoon, Florida, April–November, 2017: U.S. Geological Survey Open-File Report 2018–1151, 18 p., https://doi.org/10.3133/ofr20181151.","productDescription":"Report: vi, 18 p.; Data Releases","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-096716","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":358771,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q8JGAO","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Model data sets for 1DTempPro and VFLUX simulation experiments to determine groundwater seepage in the Indian River Lagoon, Florida"},{"id":358770,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1151/ofr20181151.pdf","text":"Report","size":"7.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1151"},{"id":358769,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1151/coverthb.jpg"},{"id":358772,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VM4B41","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Temperature data collected in the Indian River Lagoon to evaluate groundwater seepage, Brevard County, Florida, 2017–2018"}],"country":"United States","state":"Florida","otherGeospatial":"Indian River Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.91156005859375,\n 28.10832614221258\n ],\n [\n -80.452880859375,\n 28.10832614221258\n ],\n [\n -80.452880859375,\n 28.84707946871795\n ],\n [\n -80.91156005859375,\n 28.84707946871795\n ],\n [\n -80.91156005859375,\n 28.10832614221258\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Hurricane Florence made landfall as a Category 1 hurricane at Wrightsville Beach, North Carolina, shortly after dawn on September 14, 2018. Once over land, the forward motion of the hurricane slowed to about 2 to 3 miles per hour. Over the next several days, the hurricane delivered historic amounts of rainfall across North and South Carolina, causing substantial flooding in many communities across both States. For the Hurricane Florence event, a new record rainfall total of 35.93 inches was set in Elizabethtown, N.C. Many other locations throughout North Carolina set new records for rainfall, exceeding the previous State record for rainfall from a tropical system of 24.06 inches, which was set over a 4-day period in Southport, N.C., during Hurricane Floyd in 1999. In South Carolina, the highest reported total rainfall of 23.63 inches was in Loris, S.C., which was the highest total rainfall in South Carolina from a tropical cyclone, replacing the previous total of 17.45 inches associated with Tropical Storm Beryl in 1994. During the October 2015 flood in South Carolina, a 4-day total rainfall of 26.88 inches was recorded in Mount Pleasant; however, because that total rainfall was a combination of a tropical storm system and another front that was centered over the State, it is not considered the largest rainfall event from a tropical storm.
Peak streamflow and stage data at 84 U.S. Geological Survey streamflow gaging stations (referred to hereafter as streamgages) in North and South Carolina with at least 10 years of systematic record and for which the flooding following Hurricane Florence resulted in a peak in the top 5 for the period of record are included in this report. New peak streamflows of record were recorded at 18 sites in North Carolina and 10 sites in South Carolina. Another 49 streamgages recorded peak streamflows in the top 5 for their record (45 in North Carolina and 4 in South Carolina). Peak streamflow data following Hurricane Florence were not available for three additional streamgages prior to the publication of this report. Of those three streamgages, two recorded a new peak stage of record and one recorded the second highest peak stage of record. An additional four stage-only streamgages having at least 10 years of systematic record also had new peak stages (also referred to as gage height) of record. For 11 of the 28 streamgages for which the September 2018 peak streamflow was the peak of record, the October 2016 peak following Hurricane Matthew was the second largest peak, and for another four streamgages the September 1999 peak following Hurricane Floyd was the second largest peak.
For the 28 streamgages for which a new peak streamflow of record was recorded, a flood-frequency analysis was done using available systematic record through September 2017 and the peak streamflow from the Hurricane Florence event. Of the 28 streamgages analyzed, the estimated annual exceedance probability for the Hurricane Florence peak streamflow at 9 of the streamgages was less than 0.2 percent, which in terms of recurrence intervals is greater than a 500-year flood event. At three streamgages, the estimated annual exceedance probability was equal to 0.2 percent, and at six streamgages, it was between 0.2 and 1 percent (between a 500- and 100-year recurrence interval, respectively). For the remaining 10 streamgages, the estimated annual exceedance probability was between 1.5 and 7.1 percent, which in terms of recurrence intervals is approximately a 67- to 14-year event, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181172","usgsCitation":"Feaster, T.D., Weaver, J.C., Gotvald, A.J., and Kolb, K.R., 2018, Preliminary peak stage and streamflow data for selected U.S. Geological Survey streamgaging stations in North and South Carolina for flooding following Hurricane Florence, September 2018: U.S. Geological Survey Open-File Report 2018–1172, 36 p., https://doi.org/10.3133/ofr20181172.","productDescription":"iv, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102355","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":358696,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1172/ofr20181172.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Carolina\",\"nation\":\"USA \"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
The Mars Global Digital Dune Database (MGD3) is an online repository that has catalogued dune fields larger than 1 km2 located between latitudes 90° N. and 90° S. The work presented here expands upon previous MGD3 open-file reports, with a new emphasis upon characterizing dune fields through composition, stability, and thermal inertia. Included in this latest addition is a detailed compositional analysis and the associated observational data from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) for dune fields 300 km2 or larger; a near-global dune stability assessment; Mars Odyssey (MO1) Thermal Emission Imaging System (THEMIS) apparent thermal inertia values; and vertical near-surface thermophysical heterogeneities determined by fitting a two-layer thermal model to observed temperatures. These additional datasets are divided into two workbooks: equatorial and south polar regions. A detailed description for the layout of these workbooks can be found in the corresponding metadata document. The continuing goal of the MGD3 is to provide a reliable and multifaceted repository of data for Mars’ dunes, with the intention that such data be easily accessible and useful to future research.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181164","usgsCitation":"Gullikson, A.L., Hayward, R.K., Titus, T.N., Charles, H., Fenton, L.K., Hoover, R., and Putzig, N.E., 2018, Mars global digital dune database (MGD3)—Composition, stability, and thermal inertia: U.S. Geological Survey Open-File Report 2018–1164, 17 p., https://doi.org/10.3133/ofr20181164.","productDescription":"Report: vi, 17 p.; Appendix 1; Dune Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097409","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":358707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1164/coverthb.jpg"},{"id":358708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1164"},{"id":358709,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164_appendix.pdf","text":"Appendix 1","size":"603 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1164 Appendix","linkHelpText":"Graphs pertaining to the spectral glitch"},{"id":358710,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164_dunedatabase.zip","text":"Dune Database","size":"3 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1164 Database","linkHelpText":"Equatorial and South Polar Dune Databases and metadata"},{"id":358712,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20101170","text":"Open-File Report 2010–1170 —","linkHelpText":"Mars Global Digital Dune Database: MC–1"},{"id":358711,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20071158","text":"Open-File Report 2007–1158 —","linkHelpText":"Mars Global Digital Dune Database: MC2–MC29"},{"id":358713,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20121259","text":"Open-File Report 2012–1259 —","linkHelpText":"Mars Global Digital Dune Database: MC–30"}],"contact":"Contact Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The Bureau of Reclamation supports the Shasta Dam Fish Passage Evaluation (SDFPE; Yip, 2015) program, and in 2016 set out to determine the feasibility of reintroducing winter-run and spring-run Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) to tributaries upstream of Shasta Dam. Ideally, reintroduction strategy includes trapping naturally produced downstream-migrating juvenile fish at the head of Lake Shasta (upstream of Shasta Dam), or near the mouth of the tributaries where they flow into the lake. However, evaluations of a juvenile collection system in one of the target tributaries (McCloud River) was delayed because of concerns about the fish source to be used as surrogate for winter-run Chinook salmon and the location and impact of the trap-and-haul operations.
In 2017, the U.S. Geological Survey (USGS) was contracted to evaluate the reintroduction of winter-run salmon into tributaries upstream of Shasta Dam, and the McCloud River, having the most suitable spawning and rearing habitat for salmon adjacent to Shasta Reservoir (Lake) was the chosen study area. The first stage of the project was to assess the feasibility using a head-of-reservoir fish trap to collect juvenile salmon, but these efforts were delayed, so efforts were used to assess how juvenile Chinook salmon would distribute within the McCloud River and Shasta Reservoir and help determine the feasibility of collecting fish at Shasta Dam. Importantly, NOAA fisheries was also conducting an acoustic telemetry project through the Sacramento River, and they provided the additional acoustic detection data on our tagged fish to San Francisco Bay. These data were collected beyond original study goals, but added a large contribution to the findings and inferences from this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181144","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Adams, N.S., Liedtke, T.L., Plumb, J.M., Hansen, A.C., Evans, S.D., and Weiland., L.K., 2018, Emigration and transportation stress of juvenile Chinook salmon relative to their reintroduction upriver of Shasta Dam, California, 2017–18: U.S. Geological Survey Open-File Report 2018-1144, 60 p., https://doi.org/10.3133/ofr20181144.","productDescription":"vi, 60 p.","onlineOnly":"Y","ipdsId":"IP-098563","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":358642,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1144/ofr20181144.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1144"},{"id":358641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1144/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Shasta Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.684326171875,\n 37.6968609874419\n ],\n [\n -121.3604736328125,\n 37.6968609874419\n ],\n [\n -121.3604736328125,\n 41.017210578228436\n ],\n [\n -122.684326171875,\n 41.017210578228436\n ],\n [\n -122.684326171875,\n 37.6968609874419\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The purpose of this report is to provide a compilation of structural retrofits and replacements of older buildings and infrastructure in the San Francisco Bay Area that have either been completed since 1989 or that are in progress as of October 2018. For the purposes of this report, all or parts of nine Bay Area counties were included: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma. Santa Cruz County was not included. The compilation of 700 investments is presented as a table in the appendix. We consider this table as version 1, as we urge that those familiar with additional projects contact the report authors with information to update the table.
In total, we have identified \\$73 to \\$80 billion in investments to retrofit or replace structures to mitigate the impacts of future San Francisco Bay Area earthquakes. These totals represent an average investment of \\$2.5 to \\$2.8 billion per year in retrofits and replacement of structures since 1989.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181168","usgsCitation":"Brocher, T.M., Gefeke, K., Boatwright, J., and Knudsen, K.L., 2018, Reported investments in earthquake mitigation top \\$73 to \\$80 billion in the San Francisco Bay Area, California, since the 1989 Loma Prieta earthquake: U.S. Geological Survey Open-File Report 2018–1168, 18 p., https://doi.org/10.3133/ofr20181168.","productDescription":"Report: iii, 18 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-102021","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":358503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1168/coverthb.jpg"},{"id":358504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1168/ofr20181168.pdf","text":"Report","size":"1.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018–1168"},{"id":358505,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1168/ofr20181168_appendix.xlsx","text":"Appendix 1","size":"175 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Open-File Report 2018–1168 Appendix","linkHelpText":"Spreadsheet of Known Investments in Earthquake Resiliency Made in the San Francisco Bay Area Since the 1989 Loma Prieta Earthquake"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","contact":"Contact Information,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
In 2016, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, collected data on isotopes, age dating, and geochemistry including aqueous uranium concentrations of samples from 20 locations in the vicinity of the Homestake Mining Company Superfund site near Milan, New Mexico. The 20 sampled locations include 19 groundwater wells and 1 treatment plant for water used for injection into aquifers. At 6 of the 19 wells, multiple samples were collected by several different sampling methods, including passive, micropurge, and volumetric methods.
Aqueous uranium concentrations were adjusted on the basis of comparisons between three sampling methods (called sample adjustments). These adjustments were specific to passive sample results because they underestimated uranium concentrations compared with results from purge samples (micropurge and volumetric). Sample adjustments were also made on aqueous selenium concentrations from previously published data for passive sampler results following a similar procedure.
Aqueous uranium concentrations in dissolved and total form were adjusted from the original analytical values (called laboratory analytical adjustments) on the basis of a rigorous comparison to several external tests, including reruns and analysis by a different laboratory after accuracy issues were identified in data from the original laboratory. The original laboratory analytical results were found to be two to five times greater than historical concentrations at the same locations, which prompted further evaluation, as described in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181055","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Harte, P.T., Blake, J.M., and Becher, K.D., 2018, Determination of representative uranium and selenium concentrations from groundwater, 2016, Homestake Mining Company Superfund site, Milan, New Mexico: U.S. Geological Survey Open-File Report 2018–1055, 40 p., appendixes, https://doi.org/10.3133/ofr20181055.","productDescription":"Report: vii, 37 p.; Appendix; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091402","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":355297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1055/coverthb.jpg"},{"id":355299,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5RJS","text":"USGS data release","description":"USGS data release","linkHelpText":"Data Associated with Uranium Background Concentrations at Homestake Mining Company Superfund Site near Milan, New Mexico, July 2016 through October 2016 "},{"id":358281,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1055/ofr20181055_app2.csv","text":"Appendix 2","size":"12.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"Original and adjusted aqueous uranium concentrations"},{"id":355298,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1055/ofr20181055.pdf","text":"Report","size":"6.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1055"}],"country":"United States","state":"New Mexico","city":"Milan","otherGeospatial":"Homestake Mining Company Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.8917,\n 35.2083\n ],\n [\n -107.8417,\n 35.2083\n ],\n [\n -107.8417,\n 35.275\n ],\n [\n -107.8917,\n 35.275\n ],\n [\n -107.8917,\n 35.2083\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey 331
Commerce Way, Suite 2
Pembroke, NH 03275
The Red Hill Bulk Fuel Storage Facility, operated by the U.S. Navy and located in the Hālawa area, Oʻahu, Hawaiʻi, includes 20 underground storage tanks that can hold a total of 250 million gallons of fuel. In January 2014, the U.S. Navy notified the Hawaiʻi Department of Health and U.S. Environmental Protection Agency of release of an estimated 27,000 gallons of fuel from the Red Hill Bulk Fuel Storage Facility. In response to past and potential future fuel releases, data are needed to evaluate groundwater flow in the surrounding area. During July 2017–February 2018, the U.S. Geological Survey collected groundwater-level data at 24 sites near the Red Hill Bulk Fuel Storage Facility. At 14 of the 24 sites, groundwater-temperature data were also collected, and at 6 of the 24 sites, barometric-pressure data were collected. During the data-collection period, a regional aquifer test was conducted in coordination with the operators of three production wells in the area. The recorded water-level changes in response to planned withdrawal changes during December 2017–February 2018 can be used to improve understanding of the groundwater-flow system. The scope of this report is limited to a non-interpretive presentation of the data and a brief discussion of the factors affecting the water-level data.
Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Oil producers have been using enhanced oil recovery methods, including (1) thermal recovery for heavy oil and (2) carbon dioxide enhanced oil recovery (CO2-EOR) for medium or light oil, to maximize oil recovery from existing reservoirs. The CO2-EOR method is widely used for recovering additional oil after waterflood, which leaves behind a large volume of oil in the reservoir. Completing a CO2-EOR feasibility study requires values of various geologic, petrophysical, and reservoir properties, as well as production data. Most of the required data are available except for two critical parameters: (1) the oil saturation at the start of CO2-EOR and (2) the oil recovery factor. Several methods, including core analysis, open-hole and cased-hole well logging, well-to-well tracer tests, and material balance, have been deployed to determine the residual oil saturation after waterflood (at which the relative permeability to oil nears zero) or remaining oil saturation after waterflood, equal to the oil saturation at the start of CO2-EOR. This report presents the material balance approach, which is less expensive than other approaches and provides reasonably accurate values of oil saturation at the start of CO2-EOR, and therefore is more useful when assessing a large number of reservoirs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181146","usgsCitation":"Verma, M.K., 2018, Material balance approach for determining oil saturation at the start of carbon dioxide enhanced oil recovery: U.S. Geological Survey Open-File Report 2018–1146, 14 p., https://doi.org/10.3133/ofr20181146.","productDescription":"v, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091063","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":358130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1146/coverthb.jpg"},{"id":358131,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1146/ofr20181146.pdf","text":"Report","size":"527 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1146"}],"contact":"Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
Email: gd-energyprogram@usgs.gov
For nature reserves in urban settings, wildlife and wildlife habitats may be affected by recreational activities and intensive, adjacent development. Sustaining biodiversity in such reserves is a challenge for land and natural resource managers, but identification of core areas and key resources for wildlife species may help in planning for current and emerging threats. To help identify core areas and resources, we conducted spatial analyses and predictive modeling of vertebrate distributions for a network of nature reserves in densely populated Orange County, California. We primarily focused on bobcats (Lynx rufus), a species with a strong association with natural habitat. Bobcat space use has been correlated with broad, simple land-use categories, but relatively little is known about the influence of greater landscape complexity on habitat suitability for bobcats. To examine habitat selection by bobcats, we developed spatial data layers representing environmental factors that might influence this species, and we used previously collected Global Positioning System tracking data for 30 male and 21 female bobcats to indicate bobcat response to complex landscape factors. We examined these inputs using Resource Selection Function (RSF) modeling and developed spatially explicit models of the probability of bobcat use (selection or avoidance) of landscape characteristics. RSF models highlighted the general importance of reserve habitat for bobcats, but suggested that female bobcats were more dependent that male bobcats on habitat within designated reserves. Male bobcats, which range more widely than female bobcats, were associated with undeveloped areas both within and outside reserves. Small areas were present outside reserves that seemed to provide additional suitable habitat or movement areas for bobcats, potentially through restoration, connectivity, or reduced edge effects.
Although bobcat RSFs suggested areas of high value to this species and potentially other species, taxa can differ greatly in their resource-selection and spatial requirements. Thus, for several species of reptiles, amphibians, and birds, we adapted species distribution models based on occurrence data to examine the response of other vertebrates to the landscape. To identify potential High-Value Areas (HVAs) for single or multiple species, we then developed a step-wise filtering process that can be applied to a series of spatial data layers. We provide examples of alternative decision models for HVAs that capture different elements of biodiversity and a range of management considerations. As landscape and management challenges change, these spatial layers and decision rules can be adjusted based on new information. Our approach thus establishes a general framework for identifying high-value habitat that can be used for current management decisions and refined in the future, depending on management interests and goals and the availability of suitable quality data or adequate surrogate information.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181095","collaboration":"Prepared in cooperation with Natural Communities Coalition","usgsCitation":"Boydston, E.E., and Tracey, J.A., 2018, Modeling resource selection of bobcats (Lynx rufus) and vertebrate species distributions in Orange County, southern California, with a section on Modeling for reptile, amphibian, and bird distributions by Tracey, J.A., Preston, K.L., Rochester, C.J., Boydston, E.E., and Fisher, R.N.: U.S. Geological Survey Open-File Report 2018–1095, 65 p., https://doi.org/10.3133/ofr20181095.","productDescription":"vi, 65 p.","onlineOnly":"Y","ipdsId":"IP-086435","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":358295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1095/coverthb.jpg"},{"id":358296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1095/ofr20181095.pdf","text":"Report","size":"13.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1095"}],"country":"United States","state":"California","county":"Orange County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.95,\n 33.5\n ],\n [\n -117.5667,\n 33.5\n ],\n [\n -117.5667,\n 34\n ],\n [\n -117.95,\n 34\n ],\n [\n -117.95,\n 33.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This short course was prepared at the request of Servicio Geológico Colombiano (SGC) as a module for staff training. Prior to the short course, the SGC expressed interest in receiving training in (1) geochemistry and quality of coal; (2) geochemistry of trace elements in coal; (3) mercury and halogens in coal; (4) characterization and cycling of atmospheric mercury; (5) mercury, trace elements, and organic constituents in atmospheric fine particulate matter; (6) mercury in coal and the effect of coal quality on mercury emissions from combustion systems; (7) environmental and health effects related to coal use; and (8) related topics in coal combustion processes. A five-session short course was prepared that addressed all but the engineering aspects of coal use. In the sections that follow, topic overviews are given for the material that was presented. Brief descriptions of each slide are given in appendix 1, and the actual short course material, presented as a series of PowerPoint slides, is included in Portable Document Format (PDF) as appendix 2.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181145","collaboration":"Prepared in collaboration with Servicio Geológico Colombiano, Bogotá, Colombia","usgsCitation":"Kolker, A., 2018, Topics in coal geochemistry—Short course: U.S. Geological Survey Open-File Report 2018–1145, 31 p., https://doi.org/10.3133/ofr20181145.","productDescription":"Report: x, 31 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087688","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":358209,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1145/ofr20181145_appendix2.pdf","text":"Appendix 2","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1145 Appendix 2","linkHelpText":"Appendix 2. Short Course Slides"},{"id":358207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1145/coverthb.jpg"},{"id":358208,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1145/ofr20181145.pdf","text":"Report","size":"365 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1145"}],"contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192
https://energy.usgs.gov/
The alluvial diamond deposits of the Central African Republic (CAR) are mined almost exclusively by way of informal artisanal and small-scale mining (ASM) methods. ASM sites range in diameter from a few meters to 30 meters or more, and are typically excavated by crews of diggers using hand tools, sieves, and jigs. CAR’s reported annual production has ranged from 300,000 to 470,000 carats over the past decade. This production is significant for CAR because it accounts for a large portion of the country’s export income and employs an estimated 60,000 to 90,000 miners nationally. Diamond production has also been linked to the violent conflict and political instability which have plagued the country for decades. The most recent conflict began in 2012 and resulted in an international embargo on the export of rough diamonds from CAR. This embargo was followed by a ceasefire and a return of peace in certain zones of the country in 2015; however, political and economic instability continues to afflict many areas of the country. International efforts to restore peace in CAR have included United Nations support as well as international technical assistance in tracking, assessing, and monitoring diamond production. In 2015, the Kimberley Process (KP) developed an operational framework allowing for legitimate exports from five subprefectures in CAR that were deemed to be compliant with KP internal controls and which were also considered to be free from systematic violence or control of armed groups.
The goal of this study was to address information gaps regarding the location and extent of diamond occurrences and mining activity through the integration of geologic research with remote sensing, geographic information systems analysis, and fieldwork. Effective and efficient monitoring of diamond mining activity using satellite imagery requires detailed understanding of the geographic distribution of diamond sources and mining activities.
A two-phase methodology was developed to address the knowledge gaps. The first phase consisted of the creation of a comprehensive geospatial catalogue of diamond mining and occurrence locations from archival records such as historical maps, mining reports, academic publications, and field data. Building upon this locational database, the second phase consisted of the creation of a geospatial dataset cataloguing current mining activity locations through manual interpretation of recently acquired satellite imagery. The accuracy of this second geospatial dataset was then assessed using field observations made between 2016 and 2017 by the U.S. Agency for International Development’s Property Rights and Artisanal Diamond Development II project. This report presents a two-part geodatabase: part 1 contains the locations of diamond mine sites and occurrences from archival sources, and part 2 indicates areas of current or recent mining activity. This geodatabase is unique in its temporal and spatial extent and may be used to analyze the geographic distribution of CAR’s known diamond resources, to assess the effect of recent violent conflicts and KP actions on diamond produc-tion, to provide decision makers with information regarding small-scale diamond mining, and to improve the monitoring of mining in regions of the country prone to conflict.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181088","collaboration":"Prepared in cooperation with the U.S. Agency for International Development under the auspices of the U.S. Department of State","usgsCitation":"DeWitt, J.D., Chirico, P.G., Bergstresser, S.E., and Clark, I.E., 2018, The Central African Republic Diamond Database—A geodatabase of archival diamond occurrences and areas of recent artisanal and small-scale diamond mining: U.S. Geological Survey Open-File Report 2018–1088, 28 p., 1 pl., https://doi.org/10.3133/ofr20181088.","productDescription":"Report: iv, 28 p.; Plate: 40.0 x 27.0 inches; Databases; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087222","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":357657,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1088/ofr20181088_metadata-for-all-gisfiles.zip","size":"2.60 GB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Text formatted metadata for all data release files"},{"id":357991,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1088/ofr20181088_hydrologically-corrected-dem.tif.zip","size":"1.31 GB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Data release of hydrologically corrected digital elevation model (DEM) and hillshade model"},{"id":357272,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2018/1088/ofr20181088_plate.pdf","text":"Surficial and Bedrock Geology, Placer Diamond Deposits, and Mineral Occurrences of the Central African Republic","size":"62.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":357270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1088/coverthb1.jpg"},{"id":357271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1088/ofr20181088.pdf","text":"Report","size":"6.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1088"},{"id":357656,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1088/ofr20181088_map-database.zip","size":"17.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"Data Files","linkHelpText":"- Data release of mapped vector data (mining locations, rivers, geology, and geomorphology)"}],"country":"Central African Republic","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[15.27946,7.42192],[16.10623,7.49709],[16.29056,7.75431],[16.45618,7.73477],[16.70599,7.50833],[17.96493,7.89091],[18.38955,8.2813],[18.91102,8.63089],[18.81201,8.98291],[19.09401,9.07485],[20.05969,9.01271],[21.00087,9.47599],[21.72382,10.56706],[22.23113,10.97189],[22.86417,11.1424],[22.97754,10.71446],[23.5543,10.08926],[23.55725,9.68122],[23.39478,9.26507],[23.45901,8.95429],[23.80581,8.66632],[24.56737,8.22919],[25.11493,7.8251],[25.12413,7.50009],[25.79665,6.97932],[26.21342,6.5466],[26.46591,5.94672],[27.21341,5.55095],[27.37423,5.23394],[27.04407,5.12785],[26.40276,5.15087],[25.65046,5.25609],[25.2788,5.17041],[25.12883,4.92724],[24.80503,4.89725],[24.41053,5.10878],[23.29721,4.60969],[22.84148,4.71013],[22.70412,4.63305],[22.40512,4.02916],[21.65912,4.22434],[20.92759,4.32279],[20.29068,4.69168],[19.46778,5.03153],[18.93231,4.70951],[18.54298,4.20179],[18.45307,3.50439],[17.8099,3.5602],[17.13304,3.7282],[16.53706,3.19825],[16.01285,2.26764],[15.90738,2.55739],[15.86273,3.01354],[15.4054,3.3353],[15.03622,3.85137],[14.95095,4.21039],[14.47837,4.73261],[14.55894,5.0306],[14.45941,5.45176],[14.53656,6.22696],[14.77655,6.4085],[15.27946,7.42192]]]},\"properties\":{\"name\":\"Central African Republic\"}}]}","contact":"Director, Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
National Center, MS 926A
12201 Sunrise Valley Drive
Reston, VA 20192
The August 24, 2014, moment magnitude (Mw) 6.0 South Napa earthquake caused an estimated $400 million in structural damage to the City of Napa, California. In 2015, we acquired high-resolution P- and S-wave seismic data near three strong-motion recording stations in Napa and Solano Counties where high peak ground accelerations (PGAs) were recorded during the South Napa earthquake. In this report, we present results from three sites—Lovall Valley Loop Road in Napa County (Northern California Seismic Network station, NCSN N019B) and Broadway Street and Sereno Drive (California Geological Survey station, CGS 68294) and Vallejo Fire Station (National Strong Motion Project station, NSMP 1759) in the City of Vallejo, California. To characterize the recording sites in terms of shallow-depth, shear-wave velocities (VS), we used both surface waves (Rayleigh and Love) and body waves (S-wave) to evaluate the time-averaged VS in the upper 30 meters of the subsurface (VS30). We used two-dimensional (2D) multichannel analysis of surface waves (MASW) to evaluate VS from surface waves, and a refraction tomography inversion algorithm, developed by Hole in 1992, to evaluate VS from the body waves. As determined by the tomography and MASW analysis for Love waves, we found VS30 near the strong-motion recording stations at Lovall Valley Loop Road, Broadway Street and Sereno Drive, and the Vallejo Fire Station to be from 711 meters per second (m/s) to 767 m/s, 455 to 673 m/s, and 490 to 583 m/s, respectively. We found that VS30 determined from Love waves were higher than those determined from Rayleigh waves at the Lovall Valley Loop Road recording site (221 m/s higher) and at the Vallejo Fire Station site (62 and 48 m/s higher); however, VS30 from Love waves was lower than those from Rayleigh waves at the Broadway Street and Sereno Drive site (78 m/s lower). We also found that VS30 varied depending on the number of shot points used in our MASW analysis for both Love and Rayleigh waves. Furthermore, VS30 values determined from S-wave refraction tomography are generally closer to those determined from MASW using Love waves than those determined using Rayleigh waves.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181162","usgsCitation":"Chan, J.H., Catchings, R.D., Goldman, M.R., and Criley, C.J., 2018, VS30 at three strong-motion recording stations in Napa and Solano Counties, California — Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station — Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love): U.S. Geological Survey Open-File Report 2018–1162, 62 p., https://doi.org/10.3133/ofr20181162.","productDescription":"Report: viii, 62 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096908","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":358151,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F4IAAL","text":"USGS data release","description":"USGS data release","linkHelpText":"2015 high resolution seismic data recorded at six strong motion seismograph sites in Napa and Solano counties, California"},{"id":358150,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181161","text":"Open-File Report 2018-1161","linkHelpText":"- VS30 at Three Strong-Motion Recording Stations in Napa and Napa County, California—Main Street in Downtown Napa, Napa Fire Station Number 3, and Kreuzer Lane—Calculations Determined From S-wave Refraction Tomography and Multichannel Analysis of Surface Waves (Rayleigh and Love)"},{"id":358149,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1162/ofr20181162.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1162"},{"id":358148,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1162/coverthb.jpg"}],"country":"United States","state":"California","county":"Napa County, Solano County","city":"Vallejo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.41713722595051,\n 38.31876308218918\n ],\n [\n -122.41713722595051,\n 38.293376084062544\n ],\n [\n -122.3791235695102,\n 38.293376084062544\n ],\n [\n -122.3791235695102,\n 38.31876308218918\n ],\n [\n -122.41713722595051,\n 38.31876308218918\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.27260163802902,\n 38.14045873726971\n ],\n [\n -122.27260163802902,\n 38.09368883459186\n ],\n [\n -122.23175717738528,\n 38.09368883459186\n ],\n [\n -122.23175717738528,\n 38.14045873726971\n ],\n [\n -122.27260163802902,\n 38.14045873726971\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
The August 24, 2014, moment magnitude (Mw) 6.0 South Napa earthquake caused an estimated $400 million in structural damage to the City of Napa, California. In 2015, we acquired high-resolution P- and S-wave seismic data near three strong-motion recording stations in Napa County where high peak ground accelerations (PGAs) were recorded during the South Napa earthquake. In this report, we present results from three sites—Main Street in Downtown Napa (Northern California Seismic Network station, NCSN N016), Napa Fire Station Number 3 (National Strong Motion Project station, NSMP 1765), and Kreuzer Lane (station KRE, temporary deployment). To characterize the recording sites in terms of shallow-depth shear-wave velocities (VS), we used both surface waves (Rayleigh and Love) and body waves (S-wave) to evaluate the time-averaged VS in the upper 30 meters of the subsurface (VS30). We used two-dimensional multichannel analysis of surface waves (MASW) to evaluate VS from the surface waves, and a refraction tomography inversion algorithm, developed by Hole in 1992, to evaluate VS from the body waves. As determined by the various methods, we found VS30 near the strong-motion recording stations on Main Street in Downtown Napa, Napa Fire Station Number 3, and on Kreuzer Lane to be from 281 meters per second (m/s) to 286 m/s, 297 to 371 m/s, and 885 to 916 m/s, respectively. The VS30 calculated from Love waves were slightly lower (10 m/s) than those calculated from Rayleigh waves at the Downtown Napa location and at Napa Fire Station Number 3 (4 m/s); however, VS30 calculated from Love waves was higher (190 m/s) than those calculated from Rayleigh waves at Kreuzer Lane. We also found that VS30 determined from MASW for both Love and Rayleigh waves varied depending on the number of shots along the profiles, and VS30 was not systematic based on the number of shots used in the analysis. Furthermore, VS30 calculated from S-wave refraction tomography are closer to those determined from MASW calculated from Love waves than from using Rayleigh waves.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181161","usgsCitation":"Chan, J.H., Catchings, R.D., Goldman, M.R., and Criley, C.J., 2018, VS30 at three strong-motion recording stations in Napa and Napa County, California — Main Street in downtown Napa, Napa fire station number 3, and Kreuzer Lane — Calculations determined from s-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love): U.S. Geological Survey Open-File Report 2018–1161, 47 p., https://doi.org/10.3133/ofr20181161.","productDescription":"Report: vii, 47 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-091224","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":358146,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F4IAAL","text":"USGS data release","description":"USGS data release","linkHelpText":"2015 high resolution seismic data recorded at six strong motion seismograph sites in Napa and Solano counties, California"},{"id":358144,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1161/ofr20181161.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1161"},{"id":358143,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1161/coverthb.jpg"},{"id":358145,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181162","text":"Open-File Report 2018-1162","linkHelpText":"- VS30 at three strong-motion recording stations in Napa and Solano Counties, California—Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station—Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love)"}],"country":"United States","state":"California","county":"Napa County","city":"Napa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.33231191016716,\n 38.340761964883995\n ],\n [\n -122.33231191016716,\n 38.28175275852939\n ],\n [\n -122.22277030151793,\n 38.28175275852939\n ],\n [\n -122.22277030151793,\n 38.340761964883995\n ],\n [\n -122.33231191016716,\n 38.340761964883995\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
The U.S. Geological Survey (USGS), along with partner organizations, has developed an earthquake early warning (EEW) system called ShakeAlert for the highest risk areas of the United States: namely, California, Oregon, and Washington. The purpose of the system is to reduce the impact of earthquakes and save lives and property by providing alerts to institutional users and the public. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Alerts can then be sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking.
ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System. However, these networks were not originally designed for EEW; old equipment needs to be updated and new stations must be added to construct EEW-capable networks. The ShakeAlert data-processing infrastructure includes redundant servers that are geographically distributed at monitoring centers in Seattle, Washington, as well as Menlo Park, Berkeley, and Pasadena in California. Three data-processing layers collect raw ground-motion data from field stations (data layer), analyze these data to estimate the area and intensity of the resulting shaking (production layer), and publish alert products as appropriate for end users (alert layer). The alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission, infrastructure, or expertise to perform public notifications and is therefore recruiting technology enablers from the private sector. Additionally, ShakeAlert will coordinate with both public and private partners to accomplish consistent and ongoing public communication, education, and outreach.
The estimated cost of completing the ShakeAlert infrastructure and sensor networks is \\$39.4 million and has an estimated annual operation and maintenance cost of \\$28.6 million per year. Building a highly reliable data telemetry infrastructure would cost another \\$20.5 million and operating this telemetry system would add \\$49.8 million per year; however, these costs could be reduced if project partners provide bandwidth on existing systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181155","usgsCitation":"Given, D.D., Allen, R.M., Baltay, A.S., Bodin, P., Cochran, E.S., Creager, K., de Groot, R.M., Gee, L.S., Hauksson, E., Heaton, T.H., Hellweg, M., Murray, J.R., Thomas, V.I., Toomey, D., and Yelin, T.S., 2018, Revised technical implementation plan for the ShakeAlert system—An earthquake early warning system for the West Coast of the United States: U.S. Geological Survey Open-File Report 2018–1155, 42 p., https://doi.org/10.3133/ofr20181155. 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\"}}]}","contact":"Earthquake Science Center-Pasadena Field Office
U.S. Geological Survey
525 South Wilson Ave.
Pasadena, CA 91106-3212
The Allegheny Portage Railroad National Historic Site (ALPO) in Blair and Cambria Counties, Pennsylvania, protects historic features of the first railroad portage over the Allegheny Front and the first railroad tunnel in the United States. This report, which was completed by the U.S. Geological Survey in cooperation with the National Park Service, summarizes water resources in the headwaters of the Blair Gap Run and Bradley Run watersheds at the ALPO Summit area during 2014–16. These new baseline data fill an existing gap in knowledge and may be helpful to evaluate potential changes in the hydrologic characteristics of streams and associated wetlands at the Summit area.
Results of synoptic water-quality surveys and continuous stage records at two streamgages near the headwaters of Blair Gap Run and Bradley Run indicate that the headwater streams of the ALPO Summit area are perennial but have different water-quality characteristics. The water sampled in the headwaters of Blair Gap Run had pH that ranged from acidic to near neutral, combined with elevated concentrations of dissolved solids, mainly sulfate, chloride, and sodium. These characteristics can be attributed to drainage from legacy coal mines and runoff from nearby roads treated with deicing salt. More than once during the study, the chloride and associated contaminant concentrations in tributaries of Blair Gap Run exceeded chronic thresholds for protection of freshwater aquatic organisms. In contrast, the water quality at tributaries of Bradley Run in the Summit area was characterized by near-neutral pH and relatively low concentrations of dissolved constituents, which met criteria for protection of freshwater aquatic life. By comparison, the deep groundwater discharged as abandoned mine drainage to Sugar Run from the Argyle Stone Bridge Mine, which underlies the Summit area, had acidic pH and elevated concentrations of sulfate and metals, which exceeded chronic and acute thresholds for aquatic life.
Data on shallow groundwater levels in piezometers at two wetlands in the Summit area, which were monitored during spring through fall of 2016, indicate downward hydraulic gradients (higher water level in shallow piezometer than in deeper piezometer) and potential for local groundwater recharge during rainfall events, particularly in the summer and fall seasons. The wetlands in the upland area (wetland 3, at altitude 2,370 feet NAVD 88) near the divide between Blair Gap Run and Bradley Run between the Lemon House and Picnic Area, exhibited a consistent downward gradient from spring through fall of 2016. The associated surface seepage at wetland 3 dried up in the summer of 2016. In contrast, the wetlands in the adjoining valley (wetland 6, at altitude 2,198 feet NAVD 88) in the northwestern Summit area exhibited upward hydraulic gradients in the spring and produced continuous seepage. Despite downward gradients during summer and fall, the seepage associated with wetland 6 sustained perennial conditions in the Bradley Run drainage through the summer of 2016.
Differences in groundwater altitudes and associated water quality among the surface water, shallow groundwater, and deep groundwater in the Summit area imply that the surface water and shallow groundwater in the Summit area could recharge the groundwater of the underlying coal mines. Seasonally upward and downward vertical gradients in the near-surface soil and bedrock at wetland 6, and unimpaired water quality in the Bradley Run headwaters, are consistent with a perched water table and local hydrology that is influenced by local recharge. Persistent downward gradients and impaired water quality at wetland 3 and the adjacent headwaters seeps and tributaries of Blair Gap Run could be attributed to subsidence and drainage from shallow coalbeds (Upper Freeport, seam E) and associated mine workings in that area; however, the underlying deep coal mine pool (Lower Kittanning, seam B), which is hundreds of feet below the surface, does not appear to affect the hydrologic characteristics of the headwater streams and wetlands in the Summit area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181125","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Cravotta, C.A., III, Galeone, D.G., and Penrod, K.A., 2018, Hydrologic characteristics and water quality of headwater streams and wetlands at the Allegheny Portage Railroad National Historic Site, Summit area, Blair and Cambria Counties, Pennsylvania, 2014–16 (ver. 1.1, December 2018): U.S. Geological Survey Open-File Report 2018–1125, 21 p., https://doi.org/10.3133/ofr20181125.","productDescription":"Report: vi, 21 p.; Table; Appendix; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098767","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":357980,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1125/coverthb2.jpg"},{"id":357981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1125/ofr20181125.pdf","text":"Report","size":"5.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1125"},{"id":357982,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1125/ofr20181125_appendixes.xlsx","size":"1.65 MB","linkFileType":{"id":3,"text":"xlsx"}},{"id":357984,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YWMMHG","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrologic data collected by the U.S. Geological Survey and National Park Service at the Allegheny Portage Railroad National Historic Site, Summit Area, Blair and Cambria Counties, Pennsylvania, April 2014-December 2016"},{"id":357983,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2018/1125/ofr20181125_tables.xlsx","size":"1.12 MB","linkFileType":{"id":3,"text":"xlsx"}},{"id":360331,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2018/1125/versionHist.txt","text":"Version History","size":"1.27 KB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Pennsylvania","county":"Blair County, Cambria County","otherGeospatial":"Allegheny Portage Railroad National Historic Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.56268,\n 40.45209\n ],\n [\n -78.5237,\n 40.45209\n ],\n [\n -78.5237,\n 40.47688\n ],\n [\n -78.56268,\n 40.47688\n ],\n [\n -78.56268,\n 40.45209\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: December 2018; Version 1.0: October 2018","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
As part of local wellhead protection area programs, areas
contributing water to production wells need to be periodically
updated because groundwater-flow paths depend in part on
the stresses to the groundwater-flow system. A steady-state
groundwater-flow model that was constructed in 2009 was
updated to reflect recent (2017) pumping conditions in the
Lansing and East Lansing area in the Tri-County region, Michigan.
For this current (2017) study, withdrawals from selected
production wells were updated, and the existing model calibration
under the new pumping conditions was checked. Results
of flow simulations indicate that 10-year time-of-travel areas
cover approximately 25 square miles and 40-year time-oftravel
areas cover approximately 51 square miles.
Director, Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way Suite 5
Lansing, MI 48911
We present numeric grids containing estimates of the thickness of unconsolidated sediments and depth to the pre-Cenozoic
basement for the western United States. Values for these grids were combined and integrated from previous studies or derived
directly from gravity analyses. The grids are provided with 1-kilometer grid-node spacing in ScienceBase (https://www.sciencebase.gov).
These layers may be updated as results from new studies become available.
Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
In 2016, the U.S. Geological Survey (USGS) completed an updated assessment of undiscovered, technically recoverable oil and gas resources in the Upper Jurassic Haynesville Formation of the onshore U.S. Gulf Coast Province (Paxton and others, 2017). The Haynesville Formation was assessed using both the standard continuous (unconventional) and conventional methodologies established by the USGS for four assessment units (AUs): (1) Haynesville Western Shelf Carbonate Gas and Oil AU, (2) Haynesville Eastern Shelf Sandstone and Carbonate Oil and Gas AU, (3) Haynesville Shale Continuous Gas AU, and (4) Haynesville Shale Peripheral Continuous Gas AU. The revised assessment resulted in total estimated mean resources of 1.1 billion barrels of oil, 195.8 trillion cubic feet of gas, and 866 million barrels of natural gas liquids. The purpose of this report is to provide supplemental documentation of the input parameters used in the USGS 2016 Haynesville Formation assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181130","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2018, U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Haynesville Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1130, 62 p., https://doi.org/10.3133/ofr20181130.","productDescription":"iii, 62 p.","onlineOnly":"Y","ipdsId":"IP-098784","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357710,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1130/ofr20181130.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1130"},{"id":357709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1130/coverthb.jpg"}],"otherGeospatial":"Upper Jurassic Haynesville Formation","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The U.S. Geological Survey completed a geology-based assessment of undiscovered, technically recoverable oil and gas resources in the Haynesville and Bossier Formations of the onshore and State waters portion of the U.S. Gulf Coast region. Haynesville Formation conventional oil and gas production began in the late 1930s, whereas Bossier Formation production began in the early 1970s. Production of continuous gas resources from both formations began in 2006–7. Most of the current activity is focused on natural gas production from Haynesville and Bossier shales using horizontal wells and hydraulic fracturing. In 2016, the U.S. Geological Survey assessed technically recoverable mean resources of 4 billion barrels of oil and 304.4 trillion cubic feet of gas in the Haynesville and Bossier Formations of the onshore and State waters portion of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181135","usgsCitation":"Paxton, S.T., 2018, Assessment of oil and gas resources in the Upper Jurassic Haynesville and Bossier Formations, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1135, 13 p., https://doi.org/10.3133/ofr20181135.","productDescription":"ii, 13 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-098785","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357757,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1135/ofr20181135.pdf","text":"Report","size":"9.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1135"},{"id":357756,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1135/coverthb.jpg"}],"otherGeospatial":"Upper Jurassic Haynesville and Bossier Formations","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
In 2016, the U.S. Geological Survey (USGS) completed an updated assessment of undiscovered, technically recoverable oil and gas resources in the Upper Jurassic Bossier Formation of the onshore U.S. Gulf Coast Province (Paxton and others, 2017). The Bossier Formation was assessed using both the standard continuous (unconventional) and conventional methodologies established by the USGS for three assessment units (AUs): (1) Bossier Eastern Shelf Sandstone Gas and Oil AU, (2) Bossier Western Shelf Sandstone Gas AU, and (3) Bossier Shale Continuous Gas AU. A fourth assessment unit, the Upper Jurassic Downdip Continuous Gas AU, was also defined but was not quantitatively assessed because of limited well data within the extent of the AU. The revised assessment resulted in total estimated mean resources of 2.9 billion barrels of oil, 108.6 trillion cubic feet of gas, and 1.1 billion barrels of natural gas liquids. The purpose of this report is to provide supplemental documentation of the input parameters used in the USGS 2016 Bossier Formation assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181134","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2018, U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Bossier Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1134, 48 p., https://doi.org/10.3133/ofr20181134.","productDescription":"iii, 48 p.","onlineOnly":"Y","ipdsId":"IP-098783","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1134/coverthb.jpg"},{"id":357712,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1134/ofr20181134.pdf","text":"Report","size":"960 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1134"}],"otherGeospatial":"Upper Jurassic Bossier Formation","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
On March 22, 2018, the Seattle Department of Construction and Inspections (SDCI) and the U.S. Geological Survey (USGS) convened a workshop of engineers and seismologists to provide guidance on incorporating sedimentary basin response into the design of tall buildings in Seattle. This workshop provided recommendations that build on those from a March 2013 workshop (Chang and others, 2014), primarily based on new results from 3-D simulations of magnitude (M) 9 Cascadia earthquakes (The M9 Project). Susan Chang, a geotechnical engineer with the Seattle Department of Construction and Inspections, organized and led the workshop; Art Frankel (USGS) assisted in constructing the agenda.
The workshop agenda and attendees are provided in the appendix. The attendees represented a wide range of expertise, including seismologists with expertise in ground motions and basin response, geotechnical engineers, and structural engineers. Their professional experience included working on local projects related to the design of long-period structures; peer reviewing ground motions for performance-based design of high-rises in Seattle; researching basin response in academic, government and industry settings; developing ground motion models; and representing local and national structural engineering organizations. In this report, we summarize the technical presentations, key discussion points, and recommendations from the workshop.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181149","usgsCitation":"Wirth, E.A., Chang, S.W., and Frankel, A.D., 2018, 2018 report on incorporating sedimentary basin response into the design of tall buildings in Seattle, Washington: U.S. Geological Survey Open-File Report 2018–1149, 19 p., https://doi.org/10.3133/ofr20181149.","productDescription":"iv, 19 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-099788","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":357679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1149/ofr20181149.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1149"},{"id":357678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1149/coverthb.jpg"}],"country":"United States","state":"Washington","city":"Seattle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5,\n 47.5\n ],\n [\n -122.2,\n 47.5\n ],\n [\n -122.2,\n 47.8\n ],\n [\n -122.5,\n 47.8\n ],\n [\n -122.5,\n 47.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center, Seattle Field Office
U.S. Geological Survey
University of Washington, Dept. of Earth and Space Sciences
Box 351310
Seattle, WA 98195