This report presents selected photographic images taken by the author during U.S. Geological Survey (USGS) research into paleoclimatology and geochemistry in Devils Hole cavern during 1984 to 1993 in cooperation with the National Park Service. The unaltered suite of photographs was prepared by the USGS dive team as an aid to assist nondiving scientists with a visual perspective of the environment where earth-science samples were collected and subsequently analyzed for chemical and isotopic composition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171058","usgsCitation":"Hoffman, R.J., 2017, Devils Hole, Nevada—A photographic story of a restricted subaqueous environment: U.S. Geological Survey Open-File Report 2017–1058, 34 p., https://doi.org/10.3133/ofr20171058.","productDescription":"iv, 34 p. ","startPage":"1","endPage":"34","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-085250","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":343076,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1058/ofr20171058.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1058"},{"id":343075,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1058/coverthb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Devil's Hole ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.30109786987303,\n 36.41838163154906\n ],\n [\n -116.28710746765137,\n 36.41838163154906\n ],\n [\n -116.28710746765137,\n 36.43177971506432\n ],\n [\n -116.30109786987303,\n 36.43177971506432\n ],\n [\n -116.30109786987303,\n 36.41838163154906\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, National Research Program, Eastern Branch
U.S. Geological Survey
12201 Sunrise Valley Drive
432 National Center
Reston, VA 20192
In this study, we combined two 1 km actual evapotranspiration datasets (ET), one obtained from a root zone water balance model and another from an energy balance model, to partition annual ET into green (rainfall-based) and blue (surface water/groundwater) sources. Time series maps of green water ET (GWET) and blue water ET (BWET) are produced for the conterminous United States (CONUS) over 2001–2015. Our results indicate that average green and blue water for all land cover types in CONUS accounts for nearly 70% and 30% of the total ET, respectively. The ET in the eastern US arises mostly from GWET, and in the western US, it is mostly BWET. Analysis of the BWET in the 16 irrigated areas in CONUS revealed interesting results. While the magnitude of the BWET gradually showed a decline from west to east, the increase in coefficient of variation from west to east confirmed greater use of supplemental irrigation in the central and eastern US. We also established relationships between different hydro-climatology zones and their blue water requirements. This study provides insights on the relative contributions and the spatiotemporal dynamics of GWET and BWET, which could lead to improved water resources management.
Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (LRS; Deltistes luxatus) and shortnose suckers (SNS; Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2015 were incorporated into capture-recapture analyses of population dynamics. Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Separate analyses were done for each species and also for each subpopulation of LRS. Shortnose suckers and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake. Characteristics of the spawning migrations in 2015, such as the effects of temperature on the timing of the migrations, were similar to past years.
Capture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for 13,617 individuals, and analyses for the subpopulation that spawns in the rivers included 39,321 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (greater than or equal to 0.86) between 1999 and 2013. Survival was notably lower for males from the rivers in 2000, 2006, and 2012. Survival probabilities were lower for males from the shoreline areas in 2002. Between 2001 and 2014, the abundance of males in the lakeshore spawning subpopulation decreased by at least 59 percent and the abundance of females decreased by at least 53 percent. By combining information from capture-recapture models and size composition data, we concluded that the abundance of both sexes in the river spawning subpopulation of LRS likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation between 2002 and 2014. Capture-recapture analyses for SNS included encounter histories for 20,981 individuals. Most annual survival estimates between 2005 and 2009 were high (greater than 0.88), but both sexes of SNS experienced lower and more variable survival in 2001–04 and 2010–13. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 77 percent and the abundance of females decreased by 74 percent between 2001 and 2014. Decreases in abundance for both sexes likely are greater than these estimates indicate. Despite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. The status of the endangered sucker populations in Upper Klamath Lake remains worrisome, especially for SNS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171059","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2017, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2015: U.S. Geological Survey Open-File Report 2017–1059, 38 p., https://doi.org/10.3133/ofr20171059.","productDescription":"iv, 38 p.","onlineOnly":"Y","ipdsId":"IP-081967","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":344162,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1059/ofr20171059.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1059"},{"id":344161,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1059/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.17,\n 42.2\n ],\n [\n -121.75,\n 42.2\n ],\n [\n -121.75,\n 42.62\n ],\n [\n -122.17,\n 42.62\n ],\n [\n -122.17,\n 42.2\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 increasing demands on groundwater for water supply in desert areas in California and the western United States have resulted in the need to better understand groundwater sources, availability, and sustainability. This is true for a 650-square-mile area that encompasses the Antelope Valley, El Mirage Valley, and Upper Mojave River Valley groundwater basins, about 50 miles northeast of Los Angeles, California, in the western part of the Mojave Desert. These basins have been adjudicated to ensure that groundwater rights are allocated according to legal judgments. In an effort to assess if the boundary between the Antelope Valley and El Mirage Valley groundwater basins could be better defined, the U.S. Geological Survey began a cooperative study in 2014 with the Mojave Water Agency to better understand the hydrogeology in the area and investigate potential controls on groundwater flow and availability, including basement topography.
Recharge is sporadic and primarily from small ephemeral washes and streams that originate in the San Gabriel Mountains to the south; estimates range from about 400 to 1,940 acre-feet per year. Lateral underflow from adjacent basins has been considered minor in previous studies; underflow from the Antelope Valley to the El Mirage Valley groundwater basin has been estimated to be between 100 and 1,900 acre-feet per year. Groundwater discharge is primarily from pumping, mostly by municipal supply wells. Between October 2013 and September 2014, the municipal pumpage in the Antelope Valley and El Mirage Valley groundwater basins was reported to be about 800 and 2,080 acre-feet, respectively.
This study was motivated by the results from a previously completed regional gravity study, which suggested a northeast-trending subsurface basement ridge and saddle approximately 3.5 miles west of the boundary between the Antelope Valley and El Mirage Valley groundwater basins that might influence groundwater flow. To better define potential basement structures that could affect groundwater flow between the groundwater basins in the study area, gravity data were collected using more closely spaced measurements in September 2014. Groundwater-level data was gathered and collected from March 2014 through March 2015 to determine depth to water and direction of groundwater flow. The gravity and groundwater-level data showed that the saturated thickness of the alluvium was about 2,000 feet thick to the east and about 130 feet thick above the northward-trending basement ridge near Llano, California. Although it was uncertain whether the basement ridge affects the groundwater system, a potential barrier to groundwater flow could be created if the water table fell below the altitude of the basement ridge, effectively causing the area to the west of the basement ridge to become hydraulically isolated from the area to the east. In addition, the direction of regional-groundwater flow likely will be influenced by future changes in the number and distribution of pumping wells and the thickness of the saturated alluvium from which water is withdrawn. Three-dimensional animations were created to help visualize the relation between the basins’ basement topography and the groundwater system in the area. Further studies that could help to more accurately define the basins and evaluate the groundwater-flow system include exploratory drilling of multi-depth monitoring wells; collection of depth-dependent water-quality samples; and linking together existing, but separate, groundwater-flow models from the Antelope Valley and El Mirage Valley groundwater basins into a single, calibrated groundwater-flow model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175065","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Stamos, C.L., Christensen, A.H., and Langenheim, V.E., 2017, Preliminary hydrogeologic assessment near the boundary of the Antelope Valley and El Mirage Valley groundwater basins, California: U.S. Geological Survey Scientific Investigations Report 2017–5065, 44 p., https://doi.org/10.3133/sir20175065.","productDescription":"Report: vii, 44 p.; 2 Figures","onlineOnly":"Y","ipdsId":"IP-064470","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343370,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2017/5065/sir20175065_fig14_dewatering.mp4","text":"Figure 14.","size":"18 MB","description":"SIR 2017-5065 Animation","linkHelpText":"- Animation showing the potential dewatering of the saturated alluvium starting with the 2014–15 water-table altitude and assuming an incremental 16.4 feet (5 meter) drop per frame of the water table, near Piñon Hills, California."},{"id":343369,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2017/5065/sir20175065_fig13_gravity.mp4","text":"Figure 13.","size":"11 MB","description":"SIR 2017-5065 Animation","linkHelpText":"- Animation showing the altitude of the top of the basement rocks based on the gravity data and altitude of the water table in 2014–15, near Piñon Hills, California. "},{"id":343217,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5065/sir20175065.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5065"},{"id":343216,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5065/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Antelope Valley groundwater basin, El Mirage Valley groundwater basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.033333,\n 34.366667\n ],\n [\n -117.5,\n 34.366667\n ],\n [\n -117.5,\n 34.75\n ],\n [\n -118.033333,\n 34.75\n ],\n [\n -118.033333,\n 34.366667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
The Energy Independence and Security Act of 2007 authorized the U.S. Geological Survey (USGS) to conduct a national assessment of geologic storage resources for carbon dioxide (CO2) and requested the USGS to estimate the “potential volumes of oil and gas recoverable by injection and sequestration of industrial carbon dioxide in potential sequestration formations” (42 U.S.C. 17271(b)(4)). Geologic CO2 sequestration associated with enhanced oil recovery (EOR) using CO2 in existing hydrocarbon reservoirs has the potential to increase the U.S. hydrocarbon recoverable resource. The objective of this report is to provide detailed information on three approaches that can be used to calculate the incremental recovery factors for CO2-EOR. Therefore, the contents of this report could form an integral part of an assessment methodology that can be used to assess the sedimentary basins of the United States for the hydrocarbon recovery potential using CO2-EOR methods in conventional oil reservoirs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175062","usgsCitation":"Verma, M.K., ed., 2017, Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062–A–E, variously paged, https://doi.org/10.3133/sir20175062.","productDescription":"88 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068432","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":342892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/sir20175062.pdf","text":"Report","size":"1.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062"},{"id":342891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/coverthb.jpg"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Oil and Gas Journal’s enhanced oil recovery (EOR) survey for 2014 (Koottungal, 2014) showed that gas injection is the most frequently applied method of EOR in the United States and that carbon dioxide (CO2 ) is the most commonly used injection fluid for miscible operations. The CO2-EOR process typically follows primary and secondary (waterflood) phases of oil reservoir development. The common objective of implementing a CO2-EOR program is to produce oil that remains after the economic limit of waterflood recovery is reached. Under conditions of miscibility or multicontact miscibility, the injected CO2 partitions between the gas and liquid CO2 phases, swells the oil, and reduces the viscosity of the residual oil so that the lighter fractions of the oil vaporize and mix with the CO2 gas phase (Teletzke and others, 2005). Miscibility occurs when the reservoir pressure is at least at the minimum miscibility pressure (MMP). The MMP depends, in turn, on oil composition, impurities of the CO2 injection stream, and reservoir temperature. At pressures below the MMP, component partitioning, oil swelling, and viscosity reduction occur, but the efficiency is increasingly reduced as the pressure falls farther below the MMP.
CO2-EOR processes are applied at the reservoir level, where a reservoir is defined as an underground formation containing an individual and separate pool of producible hydrocarbons that is confined by impermeable rock or water barriers and is characterized by a single natural pressure system. A field may consist of a single reservoir or multiple reservoirs that are not in communication but which may be associated with or related to a single structural or stratigraphic feature (U.S. Energy Information Administration [EIA], 2000).
The purpose of modeling the CO2-EOR process is discussed along with the potential CO2-EOR predictive models. The data demands of models and the scope of the assessments require tradeoffs between reservoir-specific data that can be assembled and simplifying assumptions that allow assignment of default values for some reservoir parameters. These issues are discussed in the context of the CO2 Prophet EOR model, and their resolution is demonstrated with the computation of recovery-factor estimates for CO2-EOR of 143 reservoirs in the Powder River Basin Province in southeastern Montana and northeastern Wyoming.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery (Scientific Investigations Report 2017–5062)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175062B","usgsCitation":"Attanasi, E.D., 2017, Using CO2 Prophet to estimate recovery factors for carbon dioxide enhanced oil recovery, chap. B of Verma, M.K., ed., Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062, p. B1–B10, https://doi.org/10.3133/sir20175062B.","productDescription":"iii, 10 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343112,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/b/sir20175062_chapb.pdf","text":"Report","size":"377 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062B"},{"id":343111,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/b/coverthb.jpg"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The need to increase the efficiency of oil recovery and environmental concerns are bringing to prominence the use of carbon dioxide (CO2) as a tertiary recovery agent. Assessment of the impact of flooding with CO2 all eligible reservoirs in the United States not yet undergoing enhanced oil recovery (EOR) requires making the best possible use of the experience gained in 40 years of applications. Review of the publicly available literature has located relevant CO2-EOR information for 53 units (fields, reservoirs, pilot areas) in the United States and 17 abroad.
As the world simultaneously faces an increasing concentration of CO2 in the atmosphere and a higher demand for fossil fuels, the CO2-EOR process continues to gain popularity for its efficiency as a tertiary recovery agent and for the potential for having some CO2 trapped in the subsurface as an unintended consequence of the enhanced production (Advanced Resources International and Melzer Consulting, 2009). More extensive application of CO2-EOR worldwide, however, is not making it significantly easier to predict the exact outcome of the CO2 flooding in new reservoirs. The standard approach to examine and manage risks is to analyze the intended target by conducting laboratory work, running simulation models, and, finally, gaining field experience with a pilot test. This approach, though, is not always possible. For example, assessment of the potential of CO2-EOR at the national level in a vast country such as the United States requires making forecasts based on information already available.
Although many studies are proprietary, the published literature has provided reviews of CO2-EOR projects. Yet, there is always interest in updating reports and analyzing the information under new perspectives. Brock and Bryan (1989) described results obtained during the earlier days of CO2-EOR from 1972 to 1987. Most of the recovery predictions, however, were based on intended injections of 30 percent the size of the reservoir’s hydrocarbon pore volume (HCPV), and the predictions in most cases badly missed the actual recoveries because of the embryonic state of tertiary recovery in general and CO2 flooding in particular at the time. Brock and Bryan (1989), for example, reported for the Weber Sandstone in the Rangely oil field in Colorado, an expected recovery of 7.5 percent of the original oil in place (OOIP) after injecting a volume of CO2 equivalent to 30 percent of the HCPV, but Clark (2012) reported that after injecting a volume of CO2 equivalent to 46 percent of the HCPV, the actual recovery was 4.8 percent of the OOIP. Decades later, the numbers by Brock and Bryan (1989) continue to be cited as part of expanded reviews, such as the one by Kuuskraa and Koperna (2006). Other comprehensive reviews including recovery factors are those of Christensen and others (2001) and Lake and Walsh (2008). The Oil and Gas Journal (O&GJ) periodically reports on active CO2-EOR operations worldwide, but those releases do not include recovery factors. The monograph by Jarrell and others (2002) remains the most technically comprehensive publication on CO2 flooding, but it does not cover recovery factors either.
This chapter is a review of the literature found in a search for information about CO2-EOR. It has been prepared as part of a project by the U.S. Geological Survey (USGS) to assess the incremental oil production that would be technically feasible by CO2 flooding of all suitable oil reservoirs in the country not yet undergoing tertiary recovery.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery (Scientific Investigations Report 2017–5062)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Virginia","doi":"10.3133/sir20175062D","usgsCitation":"Olea, R.A., 2017, Carbon dioxide enhanced oil recovery performance according to the literature, chap. D of Verma, M.K., ed., Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062, p. D1–D21, https://doi.org/10.3133/sir20175062D.","productDescription":"iii, 21 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343121,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/d/coverthb.jpg"},{"id":343122,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/d/sir20175062_chapd.pdf","text":"Report","size":"570 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062D"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
We produce a one‐year 2017 seismic‐hazard forecast for the central and eastern United States from induced and natural earthquakes that updates the 2016 one‐year forecast; this map is intended to provide information to the public and to facilitate the development of induced seismicity forecasting models, methods, and data. The 2017 hazard model applies the same methodology and input logic tree as the 2016 forecast, but with an updated earthquake catalog. We also evaluate the 2016 seismic‐hazard forecast to improve future assessments. The 2016 forecast indicated high seismic hazard (greater than 1% probability of potentially damaging ground shaking in one year) in five focus areas: Oklahoma–Kansas, the Raton basin (Colorado/New Mexico border), north Texas, north Arkansas, and the New Madrid Seismic Zone. During 2016, several damaging induced earthquakes occurred in Oklahoma within the highest hazard region of the 2016 forecast; all of the 21 moment magnitude (M) ≥4 and 3 M≥5 earthquakes occurred within the highest hazard area in the 2016 forecast. Outside the Oklahoma–Kansas focus area, two earthquakes with M≥4 occurred near Trinidad, Colorado (in the Raton basin focus area), but no earthquakes with M≥2.7 were observed in the north Texas or north Arkansas focus areas. Several observations of damaging ground‐shaking levels were also recorded in the highest hazard region of Oklahoma. The 2017 forecasted seismic rates are lower in regions of induced activity due to lower rates of earthquakes in 2016 compared with 2015, which may be related to decreased wastewater injection caused by regulatory actions or by a decrease in unconventional oil and gas production. Nevertheless, the 2017 forecasted hazard is still significantly elevated in Oklahoma compared to the hazard calculated from seismicity before 2009.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170005","usgsCitation":"Petersen, M.D., Mueller, C., Moschetti, M.P., Hoover, S.M., Shumway, A., McNamara, D.E., Williams, R., Llenos, A.L., Ellsworth, W., Rubinstein, J.L., McGarr, A.F., and Rukstales, K.S., 2017, 2017 One‐year seismic‐hazard forecast for the central and eastern United States from induced and natural earthquakes: Seismological Research Letters, v. 88, no. 3, p. 772-783, https://doi.org/10.1785/0220170005.","productDescription":"12 p.","startPage":"772","endPage":"783","ipdsId":"IP-083989","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438266,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KP80B9","text":"USGS data release","linkHelpText":"Earthquake catalogs for the 2017 Central and Eastern U.S. short-term seismic hazard model"},{"id":438265,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RV0KWR","text":"USGS data release","linkHelpText":"2017 One-Year Seismic Hazard Forecast for the Central and Eastern United States from Induced and Natural Earthquakes"},{"id":343937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-01","publicationStatus":"PW","scienceBaseUri":"596dcca1e4b0d1f9f062754e","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shumway, Allison M. 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705088,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705089,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Robert 0000-0002-2973-8493 rawilliams@usgs.gov","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":140741,"corporation":false,"usgs":true,"family":"Williams","given":"Robert","email":"rawilliams@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705090,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705091,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ellsworth, William L. 0000-0001-8378-4979","orcid":"https://orcid.org/0000-0001-8378-4979","contributorId":194691,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William L.","affiliations":[],"preferred":false,"id":705092,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705093,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705094,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705095,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70189457,"text":"70189457 - 2017 - Sand ridge morphology and bedform migration patterns derived from bathymetry and backscatter on the inner-continental shelf offshore of Assateague Island, USA","interactions":[],"lastModifiedDate":"2017-07-13T11:12:25","indexId":"70189457","displayToPublicDate":"2017-07-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Sand ridge morphology and bedform migration patterns derived from bathymetry and backscatter on the inner-continental shelf offshore of Assateague Island, USA","docAbstract":"The U.S. Geological Survey and the National Oceanographic and Atmospheric Administration conducted\r\ngeophysical and hydrographic surveys, respectively, along the inner-continental shelf of Fenwick and\r\nAssateague Islands, Maryland and Virginia over the last 40 years. High resolution bathymetry and backscatter\r\ndata derived from surveys over the last decade are used to describe the morphology and presence of sand ridges\r\non the inner-continental shelf and measure the change in the position of smaller-scale (10–100 s of meters)\r\nseafloor features. Bathymetric surveys from the last 30 years link decadal-scale sand ridge migration patterns to\r\nthe high-resolution measurements of smaller-scale bedform features. Sand ridge morphology on the inner-shelf\r\nchanges across-shore and alongshore. Areas of similar sand ridge morphology are separated alongshore by\r\nzones where ridges are less pronounced or completely transected by transverse dunes. Seafloor-change analyses\r\nderived from backscatter data over a 4–7 year period show that southerly dune migration increases in\r\nmagnitude from north to south, and the east-west pattern of bedform migration changes ~ 10 km north of the\r\nMaryland-Virginia state line. Sand ridge morphology and occurrence and bedform migration changes may be\r\nconnected to observed changes in geologic framework including topographic highs, deflated zones, and sand\r\navailability. Additionally, changes in sand ridge occurrence and morphology may help explain changes in the\r\nlong-term shoreline trends along Fenwick and Assateague Islands. Although the data presented here cannot\r\nquantitatively link sand ridges to sediment transport and shoreline change, it does present a compelling\r\nrelationship between inner-shelf sand availability and movement, sand ridge occurrence and morphology,\r\ngeologic framework, and shoreline behavior.","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2017.06.021","usgsCitation":"Pendleton, E.A., Brothers, L.L., Thieler, E.R., and Sweeney, E., 2017, Sand ridge morphology and bedform migration patterns derived from bathymetry and backscatter on the inner-continental shelf offshore of Assateague Island, USA: Continental Shelf Research, v. 144, p. 80-97, https://doi.org/10.1016/j.csr.2017.06.021.","productDescription":"18 p. ","startPage":"80","endPage":"97","ipdsId":"IP-077828","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.06.021","text":"Publisher Index Page"},{"id":343788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States ","otherGeospatial":"Assateague Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.6630859375,\n 39.05758374935667\n ],\n [\n -76.4263916015625,\n 38.9807627650163\n ],\n [\n -76.4044189453125,\n 38.47939467327645\n ],\n [\n -76.256103515625,\n 38.28993659801203\n ],\n [\n -76.1517333984375,\n 38.151837403006766\n ],\n [\n -76.102294921875,\n 37.931200459333716\n ],\n [\n -76.036376953125,\n 37.76637243960179\n ],\n [\n -75.9210205078125,\n 37.80978395301097\n ],\n [\n -75.8331298828125,\n 37.9051994823157\n ],\n [\n -75.772705078125,\n 37.91820111976663\n ],\n [\n -75.87158203125,\n 37.77071473849609\n ],\n [\n -76.102294921875,\n 37.37888785004527\n ],\n [\n -75.992431640625,\n 36.954281585675965\n ],\n [\n -75.55847167968749,\n 37.35269280367274\n ],\n [\n -75.07507324218749,\n 38.11727165830543\n ],\n [\n -74.8223876953125,\n 38.64261790634527\n ],\n [\n -74.6630859375,\n 39.05758374935667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5968869be4b0d1f9f05f595a","contributors":{"authors":[{"text":"Pendleton, Elizabeth A. 0000-0002-1224-4892 ependleton@usgs.gov","orcid":"https://orcid.org/0000-0002-1224-4892","contributorId":174845,"corporation":false,"usgs":true,"family":"Pendleton","given":"Elizabeth","email":"ependleton@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Laura L. 0000-0003-2986-5166 lbrothers@usgs.gov","orcid":"https://orcid.org/0000-0003-2986-5166","contributorId":176698,"corporation":false,"usgs":true,"family":"Brothers","given":"Laura","email":"lbrothers@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sweeney, Edward 0000-0003-4458-4493 emsweeney@usgs.gov","orcid":"https://orcid.org/0000-0003-4458-4493","contributorId":152121,"corporation":false,"usgs":true,"family":"Sweeney","given":"Edward","email":"emsweeney@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704650,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189381,"text":"70189381 - 2017 - Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer","interactions":[],"lastModifiedDate":"2023-06-30T14:46:42.911615","indexId":"70189381","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer","title":"Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer","docAbstract":"Bats occupying hibernacula during summer are exposed to Pseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome (WNS), and may contribute to its dispersal. Furthermore, equipment and clothing exposed to cave environments are a potential source for human-assisted spread of Pd. To explore dispersal hazards for Pd during the nonhibernal season, we tested samples that were collected from bats, the environment, and equipment at hibernacula in the eastern US between 18 July–22 August 2012. Study sites included six hibernacula known to harbor bats with Pd with varying winter-count impacts from WNS and two hibernacula (control sites) without prior history of WNS. Nucleic acid from Pd was detected from wing-skin swabs or guano from 40 of 617 bats (7% prevalence), including males and females of five species at five sites where WNS had previously been confirmed as well as from one control site. Analysis of guano collected during summer demonstrated a higher apparent prevalence of Pd among bats (17%, 37/223) than did analysis of wing-skin swabs (1%, 4/617). Viable Pd cultured from wing skin (2%, 1/56) and low recapture rates at all sites suggested bats harboring Pd during summer could contribute to pathogen dispersal. Additionally, Pd DNA was detected on clothing and trapping equipment used inside and near hibernacula, and Pd was detected in sediment more readily than in swabs of hibernaculum walls. Statistically significant differences in environmental abundance of Pd were not detected among sites, but prevalence of Pd differed between sites and among bat species. Overall, bats using hibernacula in summer can harbor Pd on their skin and in their guano, and demonstration of Pd on clothing, traps, and other equipment used at hibernacula during summertime within the WNS-affected region indicates risk for pathogen dispersal during the nonhibernal season.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2016-09-206","usgsCitation":"Ballmann, A., Torkelson, M.R., Bohuski, E.A., Russell, R.E., and Blehert, D.S., 2017, Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer: Journal of Wildlife Diseases, v. 53, no. 4, p. 725-735, https://doi.org/10.7589/2016-09-206.","productDescription":"11 p.","startPage":"725","endPage":"735","ipdsId":"IP-079434","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":469685,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/2016-09-206","text":"Publisher Index Page"},{"id":343641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418656,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F78P5XRX","text":"USGS data release","description":"USGS data release","linkHelpText":"WNS Summer Surveillance: DATA"}],"country":"United States","state":"Indiana, Kentucky, Ohio, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.13232421875,\n 36.13787471840729\n ],\n [\n -82.0458984375,\n 36.13787471840729\n ],\n [\n -82.0458984375,\n 39.2832938689385\n ],\n [\n -88.13232421875,\n 39.2832938689385\n ],\n [\n -88.13232421875,\n 36.13787471840729\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5967353ee4b0d1f9f05dd7c1","contributors":{"authors":[{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torkelson, Miranda R.","contributorId":194524,"corporation":false,"usgs":false,"family":"Torkelson","given":"Miranda","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":704439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bohuski, Elizabeth A. 0000-0001-8061-2151 ebohuski@usgs.gov","orcid":"https://orcid.org/0000-0001-8061-2151","contributorId":5890,"corporation":false,"usgs":true,"family":"Bohuski","given":"Elizabeth","email":"ebohuski@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704442,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187574,"text":"sim3380 - 2017 - Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016","interactions":[],"lastModifiedDate":"2017-07-11T16:39:14","indexId":"sim3380","displayToPublicDate":"2017-07-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3380","title":"Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016","docAbstract":"The inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, was mapped in 2011. Since that time, the saltwater interface has continued to move inland. The interface is near several active well fields; therefore, an updated approximation of the inland extent of saltwater and an improved understanding of the rate of movement of the saltwater interface are necessary. A geographic information system was used to create a map using the data collected by the organizations that monitor water salinity in this area. An average rate of saltwater interface movement of 140 meters per year was estimated by dividing the distance between two monitoring wells (TPGW-7L and Sec34-MW-02-FS) by the travel time. The travel time was determined by estimating the dates of arrival of the saltwater interface at the wells and computing the difference. This estimate assumes that the interface is traveling east to west between the two monitoring wells. Although monitoring is spatially limited in this area and some of the wells are not ideally designed for salinity monitoring, the monitoring network in this area is improving in spatial distribution and most of the new wells are well designed for salinity monitoring. The approximation of the inland extent of the saltwater interface and the estimated rate of movement of the interface are dependent on existing data. Improved estimates could be obtained by installing uniformly designed monitoring wells in systematic transects extending landward of the advancing saltwater interface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3380","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., 2017, Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016: U.S. Geological Survey Scientific Investigations Map 3380, 8-p. pamphlet, 1 sheet, https://doi.org/10.3133/sim3380.","productDescription":"Pamphlet: vi, 8 p.; Sheet: 20.00 x 19.64 inches; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080722","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":343395,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R78CF8","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data pertaining to mapping the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016"},{"id":343258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3380/coverthb.jpg"},{"id":343259,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3380/sim3380.pdf","text":"Map","size":"867 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380"},{"id":343260,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3380/sim3380_pamphlet.pdf","text":"Pamphlet","size":"503 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380 Pamphlet"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Biscayne Aquifer, Model Land Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.595703125,\n 25.243453810607868\n ],\n [\n -80.25787353515625,\n 25.243453810607868\n ],\n [\n -80.25787353515625,\n 25.58456258101669\n ],\n [\n -80.595703125,\n 25.58456258101669\n ],\n [\n -80.595703125,\n 25.243453810607868\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Laurel Hill Creek is considered one of the most pristine waterways in southwestern Pennsylvania and has high recreational value as a high-quality cold-water fishery; however, the upper parts of the basin have documented water-quality impairments. Groundwater and surface water are withdrawn for public water supply and the basin has been identified as a Critical Water Planning Area (CWPA) under the State Water Plan. The U.S. Geological Survey, in cooperation with the Somerset County Conservation District, collected data and developed modeling tools to support the assessment of water-quality and water-quantity issues for a basin designated as a CWPA. Streams, springs, and groundwater wells were sampled for water quality in 2007. Streamflows were measured concurrent with water-quality sampling at main-stem sites on Laurel Hill Creek and tributaries in 2007. Stream temperatures were monitored continuously at five main-stem sites from 2007 to 2010. Water usage in the basin was summarized for 2003 and 2009 and a Water-Analysis Screening Tool (WAST) developed for the Pennsylvania State Water Plan was implemented to determine whether the water use in the basin exceeded the “safe yield” or “the amount of water that can be withdrawn from a water resource over a period of time without impairing the long-term utility of a water resource.” A groundwater and surface-water flow (GSFLOW) model was developed for Laurel Hill Creek and calibrated to the measured daily streamflow from 1991 to 2007 for the streamflow-gaging station near the outlet of the basin at Ursina, Pa. The CWPA designation requires an assessment of current and future water use. The calibrated GSFLOW model can be used to assess the hydrologic effects of future changes in water use and land use in the basin.
Analyses of samples collected for surface-water quality during base-flow conditions indicate that the highest nutrient concentrations in the main stem of Laurel Hill Creek were at sites in the northeastern part of the basin where agricultural activity is prominent. All of the total nitrogen (N) and a majority of the total phosphorus (P) concentrations in the main stem exceeded regional nutrient criteria levels of 0.31 and 0.01 milligrams per liter (mg/L), respectively. The highest total N and total P concentrations in the main stem were 1.42 and 0.06 mg/L, respectively. Tributary sites with the highest nutrient concentrations are in subbasins where treated wastewater is discharged, such as Kooser Run and Lost Creek. The highest total N and total P concentrations in subbasins were 3.45 and 0.11 mg/L, respectively. Dissolved chloride and sodium concentrations were highest in the upper part of the basin downstream from Interstate 76 because of road deicing salts. The mean base-flow concentrations of dissolved chloride and sodium were 117 and 77 mg/L, respectively, in samples from the main stem just below Interstate 76, and the mean concentrations in Clear Run were 210 and 118 mg/L, compared to concentrations less than 15 mg/L in tributaries that were not affected by highway runoff. Water quality in forested tributary subbasins underlain by the Allegheny and Pottsville Formations was influenced by acidic precipitation and, to a lesser extent, the underlying geology as indicated by pH values less than 5.0 and corresponding specific conductance ranging from 26 to 288 microsiemens per centimeter at 25 degrees Celsius for some samples; in contrast, pH values for main stem sites ranged from 6.6 to 8.5. Manganese (Mn) was the only dissolved constituent in the surface-water samples that exceeded the secondary maximum contaminant level (SMCL). More than one-half the samples from the main stem had Mn concentrations exceeding the SMCL level of 50 micrograms per liter (μg/L), whereas only 19 percent of samples from tributaries exceeded the SMCL for Mn.
Stream temperatures along the main stem of Laurel Hill Creek became higher moving downstream. During the summer months of June through August, the daily mean temperatures at the five sites exceeded the limit of 18.9 degrees Celsius (°C) for a cold-water fishery. The maximum instantaneous values for each site ranged from 27.2 to 32.8 °C.
Water-quality samples collected at groundwater sites (wells and springs) indicate that wells developed within the Mauch Chunk Formation had the best water quality, whereas wells developed within the Allegheny and Pottsville Formations yielded the poorest water quality. Waters from the Mauch Chunk Formation had the highest median pH (7.6) and alkalinity (80 mg/L calcium carbonate) values. The lowest pH and alkalinity median values were in waters from the Allegheny and Pottsville Formations. Groundwater samples collected from wells in the Allegheny and Pottsville Formations also had the highest concentrations of dissolved iron (Fe) and dissolved Mn. Seventy-eight percent of the groundwater samples collected from the Allegheny Formation exceeded the SMCL of 300 μg/L for Fe and 50 μg/L for Mn. Forty-three and 62 percent of the groundwater samples collected from the Pottsville Formation exceeded the SMCL for iron and Mn, respectively. The highest Fe and Mn concentrations for surface waters were measured for tributaries draining the Pottsville Formation. The highest median Fe concentration for tributaries was in samples from streams draining the Allegheny Formation.
During base-flow conditions, the streamflow per unit area along the main stem of Laurel Hill Creek was lowest in the upper parts of the basin [farthest upstream site 0.07 cubic foot per second per square mile (ft3/s/mi2)] and highest (two sites averaging about 0.20 (ft3/s/mi2) immediately downstream from Laurel Hill Lake in the center of the basin. Tributaries with the highest streamflow per unit area were those subbasins that drain the western ridge of the Laurel Hill Creek Basin. The mean streamflow per unit area for tributaries draining areas that extend into the western ridge and draining eastern or central sections was 0.24 and 0.05 ft3/s/mi2, respectively. In general, as the drainage area increased for tributary basins, the streamflow per unit area increased.
Criteria established by the Pennsylvania Department of Environmental Protection indicate that the safe yield of water withdrawals from the Laurel Hill Creek Basin is 1.43 million gallons per day (Mgal/d). Water-use data for 2009 indicate that net (water withdrawals subtracted by water discharges) water withdrawals from groundwater and surface-water sources in the basin were approximately 1.93 Mgal/d. Water withdrawals were concentrated in the upper part of the basin with approximately 80 percent of the withdrawals occurring in the upper 36 mi2 of the basin. Three subbasins—Allen Creek, Kooser Run, and Shafer Run— in the upper part were affected the most by water withdrawals such that safe yields were exceeded by more than 1,000 percent in the first two and more than 500 percent in the other. In the subbasin of Shafer Run, intermittent streamflow characterizes sections that historically have been perennial.
The GSFLOW model of the Laurel Hill Creek Basin is a simple one-layer representation of the groundwater flow system. The GSFLOW model was primarily calibrated to reduce the error term associated with base-flow periods. The total amount of observed streamflow at the Laurel Hill Creek at Ursina, Pa. streamflow-gaging station and the simulated streamflow were within 0.1 percent over the entire modeled period; however, annual differences between simulated and observed streamflow showed a range of -27 to 24 percent from 1992 to 2007 with nine of the years having less than a 10-percent difference. The primary source of simulated streamflow in the GSFLOW model was the subsurface (interflow; 62 percent), followed by groundwater (25 percent) and surface runoff (13 percent). Most of the simulated subsurface flow that reached the stream was in the form of slow flow as opposed to preferential (fast) interflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165082","collaboration":"Prepared in cooperation with the Somerset County Conservation District","usgsCitation":"Galeone, D.G., Risser, D.W., Eicholtz, L.W., and Hoffman, S.A., 2017, Water quality and quantity and simulated surface-water and groundwater flow in the Laurel Hill Creek Basin, southwestern Pennsylvania, 1991–2007: U.S. Geological Survey Scientific Investigations Report 2016–5082, 85 p., https://doi.org/10.3133/sir20165082.","productDescription":"Report: vii, 85 p.; Appendices 1, 4","startPage":"1","endPage":"85","numberOfPages":"97","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-006526","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":343501,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5082/sir20165082_appendix4.xlsx","text":"Appendix 4","linkHelpText":"- Concentrations of selected water-quality constituents and values of selected physical characteristics in groundwater samples collected in the Laurel Hill Creek Basin, southwestern, Pennsylvania, summer and fall 2007"},{"id":343499,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5082/sir20165082.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5082"},{"id":343498,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5082/coverthb.jpg"},{"id":343500,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5082/sir20165082_appendix1.xlsx","text":"Appendix 1","linkHelpText":"- Concentrations of selected water-quality constituents and values of selected physical characteristics in surface-water samples collected during low-flow conditions in the Laurel Hill Creek Basin, southwestern, Pennsylvania, June and September 2007"}],"country":"United 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The northern White Hills map area lies within the Kingman Uplift, a regional structural high in which Tertiary rocks lie directly on Proterozoic rocks as a result of Cretaceous orogenic uplift and erosional stripping of Paleozoic and Mesozoic strata. The Miocene Salt Spring Fault forms the major structural boundary in the map area. This low-angle normal fault separates a footwall (lower plate) of Proterozoic gneisses on the east and south from a hanging wall (upper plate) of faulted middle Miocene volcanic and sedimentary rocks and their Proterozoic substrate. The fault is part of the South Virgin–White Hills Detachment Fault, which records significant tectonic extension that decreases from north to south. Along most of its trace, the Salt Spring Fault dips gently westward, but it also has north-dipping segments along salients. A dissected, domelike landscape on the eroded footwall, which contains antiformal salients and synformal reentrants, extends through the map area from Salt Spring Bay southward to the Golden Rule Peak area. The “Lost Basin Range” represents an upthrown block of the footwall, raised on the steeper Lost Basin Range Fault.
The Salt Spring Fault, as well as the normal faults that segment its hanging wall, deform rocks that are about 16 to 10 Ma, and younger deposits overlie the faults. Rhyodacitic welded tuff about 15 Ma underlies a succession of geochemically intermediate to progressively more mafic lavas (including alkali basalt) that range from about 14.7 to 8 Ma, interfingered with sedimentary rocks and breccias in the western part of the map area. Upper Miocene strata record further filling of the extension-formed continental basins. Basins that are still present in the modern landscape reflect the youngest stages of extensional-basin formation, expressed as the downfaulted Detrital Valley and Hualapai Wash basins in the western and eastern parts of the map area, respectively, as well as the north-centrally located, northward-sagged Temple Basin. Pliocene fluvial and piedmont alluvial fan deposits record postextensional basin incision, refilling, and reincision driven by the inception and evolution of the westward-flowing Colorado River, centered north of the map area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3372","usgsCitation":"Howard, K.A., Priest, S.S., Lundstrom, S.C., and Block, D.L., 2017, Geologic map of the northern White Hills, Mohave County, Arizona: U.S. Geological Survey Scientific Investigations Map 3372, pamphlet 31 p., scale 1:50,000, https://doi.org/10.3133/sim3372.","productDescription":"Pamphlet: iii, 31 p.; Sheet: 30.34 x 31.40 inches; Database; Metadata","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066011","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":343328,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_database.zip","text":"Database","size":"11.5 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3372 Database"},{"id":343318,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_pamphlet.pdf","text":"Pamphlet","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3372 Pamphlet"},{"id":343329,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_metadata.zip","text":"Metadata","size":"50 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3372 Pamphlet"},{"id":343240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3372/coverthb2.jpg"},{"id":343241,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_map.pdf","text":"Map","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3372 Sheet"}],"country":"United States","state":"Arizona","county":"Mohave County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.5,\n 35.75\n ],\n [\n -114,\n 35.75\n ],\n [\n -114,\n 36\n ],\n [\n -114.5,\n 36\n ],\n [\n -114.5,\n 35.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
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Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables (ECVs), including information about burned area. In this paper, we present an algorithm that identifies burned areas in dense time-series of Landsat data to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm uses gradient boosted regression models to generate burn probability surfaces using band values and spectral indices from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Burn classifications are generated from the burn probability surfaces using pixel-level thresholding in combination with a region growing process. The algorithm can be applied anywhere Landsat and training data are available. For this study, BAECV products were generated for the conterminous United States from 1984 through 2015. These products consist of pixel-level burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability and a burn classification. We compared the BAECV burn classification products to the existing Global Fire Emissions Database (GFED; 1997–2015) and Monitoring Trends in Burn Severity (MTBS; 1984–2013) data. We found that the BAECV products mapped 36% more burned area than the GFED and 116% more burned area than MTBS. Differences between the BAECV products and the GFED were especially high in the West and East where the BAECV products mapped 32% and 88% more burned area, respectively. However, the BAECV products found less burned area than the GFED in regions with frequent agricultural fires. Compared to the MTBS data, the BAECV products identified 31% more burned area in the West, 312% more in the Great Plains, and 233% more in the East. Most pixels in the MTBS data were detected by the BAECV, regardless of burn severity. The BAECV products document patterns of fire similar to those in the GFED but also showed patterns of fire that are not well characterized by the existing MTBS data. We anticipate the BAECV products will be useful to studies that seek to understand past patterns of fire occurrence, the drivers that created them, and the impacts fires have on natural and human systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.06.027","usgsCitation":"Hawbaker, T., Vanderhoof, M.K., Beal, Y.G., Takacs, J., Schmidt, G.L., Falgout, J.T., Williams, B., Brunner, N.M., Caldwell, M., Picotte, J.J., Howard, S.M., Stitt, S., and Dwyer, J.L., 2017, Mapping burned areas using dense time-series of Landsat data: Remote Sensing of Environment, v. 198, p. 504-522, https://doi.org/10.1016/j.rse.2017.06.027.","productDescription":"19 p.","startPage":"504","endPage":"522","ipdsId":"IP-077532","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469690,"rank":1,"type":{"id":40,"text":"Open Access Publisher 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nbrunner@usgs.gov","orcid":"https://orcid.org/0000-0001-9657-2860","contributorId":5323,"corporation":false,"usgs":true,"family":"Brunner","given":"Nicole","email":"nbrunner@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":703876,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Caldwell, Megan K. 0000-0003-0759-2793","orcid":"https://orcid.org/0000-0003-0759-2793","contributorId":194382,"corporation":false,"usgs":false,"family":"Caldwell","given":"Megan K.","affiliations":[],"preferred":false,"id":703877,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":703878,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howard, Stephen M. 0000-0001-5255-5882 smhoward@usgs.gov","orcid":"https://orcid.org/0000-0001-5255-5882","contributorId":3483,"corporation":false,"usgs":true,"family":"Howard","given":"Stephen","email":"smhoward@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":703879,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stitt, Susan 0000-0002-0663-2696","orcid":"https://orcid.org/0000-0002-0663-2696","contributorId":194383,"corporation":false,"usgs":false,"family":"Stitt","given":"Susan","affiliations":[],"preferred":false,"id":703880,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":703881,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70200982,"text":"70200982 - 2017 - The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA","interactions":[],"lastModifiedDate":"2018-11-20T10:46:43","indexId":"70200982","displayToPublicDate":"2017-07-06T10:46:25","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA","docAbstract":"A synthesis of field, biostratigraphic, detrital zircon geochronologic, and remote sensing data across north-central Nevada, United States, defines a thick, regionally extensive sheet of Middle–Upper Ordovician Valmy Formation quartzite that structurally overlies deformed early Paleozoic units of the Roberts Mountains allochthon. Late Paleozoic regional unconformities that record tectonic disruptions have been recognized in the foreland of central and eastern Nevada and locally within the Roberts Mountains allochthon; these identify multiple, regional tectonic events between the Devonian–Mississippian initiation of the Antler orogeny and the Permian–Triassic Sonoma orogeny. However, few studies have documented the regional kinematic history of the Robert Mountains allochthon sensu stricto. In the Independence Mountains of northern Nevada, emplacement of the Roberts Mountains allochthon is restricted to the Mississippian. In the Tuscarora Mountains, the range west and southwest of the Independence Mountains, several deformation events have been identified, and emplacement of the thrust sheet containing the Valmy Formation is restricted to the Late Pennsylvanian–Early Permian. These structural and temporal relations, reflected in the Antler foreland basin adjacent to the Roberts Mountains allochthon and overlap sequences, suggest that the Roberts Mountains allochthon is a composite stratigraphic terrane assembled along the Cordilleran margin during two or more late Paleozoic contractional events.
Valmy Formation deposits likely represent the development of coalescing submarine fans below or within bypass channels in a deep slope or rise environment. Petrographic characteristics, biostratigraphy, and detrital zircon U-Pb age populations of the Valmy Formation link it to coeval slope and rise turbidites of the Vinini Formation and shelfal Eureka Quartzite; Valmy Formation detrital zircon age populations are dissimilar to the rift-to-drift facies of the Neoproterozoic–Cambrian Prospect Mountain Quartzite. Throughout north-central Nevada, the Valmy Formation is in fault contact with units of the Roberts Mountains allochthon, including the Devonian–Mississippian Slaven Chert, Silurian–Devonian Elder Sandstone, and Cambrian(?)–Ordovician Vinini Formation, which were deformed prior to, or during, emplacement of the thrust sheet containing Valmy Formation quartzite. Our mapping and data synthesis, guided by regional quartz maps based on remote sensing (Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER]) data, delineate similar structural relationships discontinuously for >200 km along strike of the Roberts Mountains allochthon.
Exploration for concealed gold deposits within reach of drilling requires knowledge of the relative thicknesses of the Roberts Mountains allochthon and the Valmy Formation. Overall thicknesses of deformed Roberts Mountains allochthon units between the Valmy Formation and underlying carbonate rocks, which host large, world-class Carlin-type gold deposits, vary by hundreds of meters, but are generally less than 700 m in three of the areas studied here. Recognition of windows through and klippen of the Roberts Mountains allochthon is essential for identification of areas where deposits may be at or near the surface. Correspondingly, most ongoing exploration for Carlin-type gold deposits subjacent to the Roberts Mountains allochthon targets concealed deposits. The model proposed in this study is applicable to determining depth to rocks prospective for undiscovered deposits.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31491.1","usgsCitation":"Holm-Denoma, C.S., Hofstra, A.H., Rockwell, B., and Noble, P.J., 2017, The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA: GSA Bulletin, v. 129, no. 11-12, p. 1521-1536, https://doi.org/10.1130/B31491.1.","productDescription":"16 p.","startPage":"1521","endPage":"1536","ipdsId":"IP-077542","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":359600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 40\n ],\n [\n -115.5,\n 40\n ],\n [\n -115.5,\n 42\n ],\n [\n -117,\n 42\n ],\n [\n -117,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"129","issue":"11-12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-06","publicationStatus":"PW","scienceBaseUri":"5bf52b6ae4b045bfcae28010","contributors":{"authors":[{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440 cholm-denoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":2442,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher","email":"cholm-denoma@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":203924,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Paula J.","contributorId":40455,"corporation":false,"usgs":true,"family":"Noble","given":"Paula","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":751548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189018,"text":"sir20175022C - 2017 - Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington","interactions":[{"subject":{"id":70189018,"text":"sir20175022C - 2017 - Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington","indexId":"sir20175022C","publicationYear":"2017","noYear":false,"chapter":"C","title":"Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington"},"predicate":"IS_PART_OF","object":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"id":1}],"isPartOf":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"lastModifiedDate":"2017-07-27T12:28:33","indexId":"sir20175022C","displayToPublicDate":"2017-07-05T00:00:00","publicationYear":"2017","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":"2017-5022","chapter":"C","title":"Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington","docAbstract":"Pyroclastic density currents (PDCs) are one of the most dangerous phenomena associated with explosive volcanism. To help constrain damage potential, a combination of field studies, laboratory experiments, and numerical modeling are used to establish conditions that influence PDC dynamics and depositional processes, including runout distance. The objective of this field trip is to explore field relations that may constrain PDCs at the time of emplacement.
The PDC deposits from the May 18, 1980, eruption of Mount St. Helens are well exposed along the steep flanks (10–30° slopes) and across the pumice plain (5–12° slopes) as far as 8 km north of the volcano. The pumice plain deposits represent deposition from a series of concentrated PDCs and are primarily thick (3–12 m), massive, and poorly sorted. In contrast, the steep east-flank deposits are stratified to cross-stratified, suggesting deposition from PDCs where turbulence strongly influenced transport and depositional processes.
The PDCs that descended the west flank were largely nondepositional; they maintained a higher flow energy and carrying capacity than PDCs funneled through the main breach, as evidenced by the higher concentration of large blocks in their deposits. The PDC from the west flank collided with PDCs funneled through the breach at various points along the pumice plain. Evidence for flow collision will be explored and debated throughout the field trip.
Evidence for substrate erosion and entrainment is found (1) along the steep eastern flank of the volcano, which has a higher degree of rough, irregular topography relative to the west flanks where PDCs were likely nonerosive, (2) where PDCs encountered debris-avalanche hummocks across the pumice plain, and (3) where PDCs eroded and entrained material deposited by PDCs produced during earlier phases of the eruption. Two features interpreted as large-scale (tens of meters wide) levees and a large (~200 m wide) channel scour-and-fill feature provide the first evidence of self-channelization within PDCs sustained for minutes to tens of minutes (total volume of deposits is ~0.12 km3; area covered is ~15.5 km2; Rowley and others, 1981).
Our ability to interpret the deposits of PDCs is critical for understanding transport and depositional processes that control PDC dynamics. The results of extensive work on the May 18, 1980, PDC deposits show that slope and irregular topography strongly influence PDC flow path, dynamics, criticality (for example, supercritical versus subcritical), carrying capacity, and erosive capacity. However, the influence of these conditions on ultimate flow runout and damage potential warrants further exploration through the combination of field, experimental, and numerical approaches.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022C","usgsCitation":"Brand, B.D., Pollock, Nicholas, Sarocchi, Damiano, Dufek, Josef, and Clynne, M.A., 2017, Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington: U.S. Geological Survey Scientific Investigations Report 2017–5022–C, 34 p., https://doi.org/10.3133/sir20175022C.","productDescription":"ix, 34 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-075876","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":343226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/c/coverthb.jpg"},{"id":343227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/c/sir20175022c.pdf","text":"Report","size":"22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-C"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.21328735351562,\n 46.1408312087306\n ],\n [\n -121.9647216796875,\n 46.1408312087306\n ],\n [\n -121.9647216796875,\n 46.33175800051563\n ],\n [\n -122.21328735351562,\n 46.33175800051563\n ],\n [\n -122.21328735351562,\n 46.1408312087306\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Gas analyses from northeastern New Mexico, USA indicate that previous interpretations of the location of gas charge into the northeastern portion of Bravo Dome are likely correct, and that there may be multiple migration pathways from the same source for different regions in northeastern New Mexico.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.egypro.2017.03.1428","usgsCitation":"Brennan, S.T., 2017, Chemical and isotopic evidence for CO2 charge and migration within Bravo Dome and potential CO2 leakage to the southwest: Energy Procedia, v. 114, p. 2996-3005, https://doi.org/10.1016/j.egypro.2017.03.1428.","productDescription":"10 p.","startPage":"2996","endPage":"3005","ipdsId":"IP-079898","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":461455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.egypro.2017.03.1428","text":"Publisher Index Page"},{"id":361246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Bravo Dome","volume":"114","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brennan, Sean T. 0000-0002-7102-9359 sbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":559,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean","email":"sbrennan@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":705917,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70192631,"text":"70192631 - 2017 - Fine particle retention within stream storage areas at base flow and in response to a storm event","interactions":[],"lastModifiedDate":"2017-11-06T12:31:21","indexId":"70192631","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Fine particle retention within stream storage areas at base flow and in response to a storm event","docAbstract":"Fine particles (1–100 µm), including particulate organic carbon (POC) and fine sediment, influence stream ecological functioning because they may contain or have a high affinity to sorb nitrogen and phosphorus. These particles are immobilized within stream storage areas, especially hyporheic sediments and benthic biofilms. However, fine particles are also known to remobilize under all flow conditions. This combination of downstream transport and transient retention, influenced by stream geomorphology, controls the distribution of residence times over which fine particles influence stream ecosystems. The main objective of this study was to quantify immobilization and remobilization rates of fine particles in a third-order sand-and-gravel bed stream (Difficult Run, Virginia, USA) within different geomorphic units of the stream (i.e., pool, lateral cavity, and thalweg). During our field injection experiment, a thunderstorm-driven spate allowed us to observe fine particle dynamics during both base flow and in response to increased flow. Solute and fine particles were measured within stream surface waters, pore waters, sediment cores, and biofilms on cobbles. Measurements were taken at four different subsurface locations with varying geomorphology and at multiple depths. Approximately 68% of injected fine particles were retained during base flow until the onset of the spate. Retention was evident even after the spate, with 15.4% of the fine particles deposited during base flow still retained within benthic biofilms on cobbles and 14.9% within hyporheic sediment after the spate. Thus, through the combination of short-term remobilization and long-term retention, fine particles can serve as sources of carbon and nutrients to downstream ecosystems over a range of time scales.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR020202","usgsCitation":"Drummond, J.D., Larsen, L.G., González-Pinzón, R., Packman, A.I., and Harvey, J., 2017, Fine particle retention within stream storage areas at base flow and in response to a storm event: Water Resources Research, v. 53, no. 7, p. 5690-5705, https://doi.org/10.1002/2016WR020202.","productDescription":"16 p.","startPage":"5690","endPage":"5705","ipdsId":"IP-085237","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469725,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr020202","text":"Publisher Index Page"},{"id":348266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Difficult Run","volume":"53","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-16","publicationStatus":"PW","scienceBaseUri":"5a07e8b9e4b09af898c8cba9","contributors":{"authors":[{"text":"Drummond, J. D.","contributorId":198633,"corporation":false,"usgs":false,"family":"Drummond","given":"J.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":716597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larsen, L. G.","contributorId":198634,"corporation":false,"usgs":false,"family":"Larsen","given":"L.","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":716598,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"González-Pinzón, R.","contributorId":198635,"corporation":false,"usgs":false,"family":"González-Pinzón","given":"R.","affiliations":[],"preferred":false,"id":716599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Packman, A. I.","contributorId":198636,"corporation":false,"usgs":false,"family":"Packman","given":"A.","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":716600,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harvey, Judson 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":140228,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":716596,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193447,"text":"70193447 - 2017 - Evaluating population expansion of black bears using spatial capture-recapture","interactions":[],"lastModifiedDate":"2017-11-10T12:25:46","indexId":"70193447","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating population expansion of black bears using spatial capture-recapture","docAbstract":"The population of American black bears (Ursus americanus) in southern New York, USA has been growing and expanding in range since the 1990s. This has motivated a need to anticipate future patterns of range expansion. We conducted a non-invasive, genetic, spatial capture-recapture (SCR) study to estimate black bear density and identify spatial patterns of population density that are potentially associated with range expansion. We collected hair samples in a 2,519-km2 study area in southern New York with barbed-wire hair snares and identified individuals and measured genetic diversity using 7 microsatellite loci and 1 sex-linked marker. We estimated a mean density of black bears in the region of 13.7 bears/100 km2, and detected a slight latitudinal gradient in density consistent with the documented range expansion. However, elevation and the amounts of forest, crop, and developed landcover types did not influence density, suggesting that bears are using a diversity of resources in this heterogeneous landscape outside their previously described distribution. These results provide the first robust baseline estimates for population density and distribution associated with different landcover types in the expanded bear range. Further, genetic diversity was comparable to that of non-expanding black bear populations in the eastern United States, and in combination with the latitudinal density gradient, suggest that the study area is not at the colonizing front of the range expansion. In addition, the diversity of landcover types used by bears in the study area implies a possible lack of constraints for further northern expansion of the black bear range. Our non-invasive, genetic, spatial capture-recapture approach has utility for studying populations of other species that may be expanding in range because SCR allows for the testing of explicit, spatial ecological hypotheses.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21248","usgsCitation":"Sun, C.C., Fuller, A.K., Hare, M.P., and Hurst, J.E., 2017, Evaluating population expansion of black bears using spatial capture-recapture: Journal of Wildlife Management, v. 81, no. 5, p. 814-823, https://doi.org/10.1002/jwmg.21248.","productDescription":"10 p.","startPage":"814","endPage":"823","ipdsId":"IP-060611","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","volume":"81","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-29","publicationStatus":"PW","scienceBaseUri":"5a06c8cce4b09af898c8611a","contributors":{"authors":[{"text":"Sun, Catherine C.","contributorId":70274,"corporation":false,"usgs":false,"family":"Sun","given":"Catherine","email":"","middleInitial":"C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":719081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hare, Matthew P.","contributorId":171454,"corporation":false,"usgs":false,"family":"Hare","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":719082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurst, Jeremy E.","contributorId":177504,"corporation":false,"usgs":false,"family":"Hurst","given":"Jeremy","email":"","middleInitial":"E.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":719083,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190050,"text":"70190050 - 2017 - Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA)","interactions":[],"lastModifiedDate":"2018-03-28T14:27:13","indexId":"70190050","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2821,"text":"Natural Areas Journal","active":true,"publicationSubtype":{"id":10}},"title":"Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA)","docAbstract":"Many eastern forest communities depend on fire for regeneration or are enhanced by fire as a restoration practice. However, the use of prescribed fire in the mesic forested environments and the densely populated regions of the eastern United States has been limited. The objective of our research was to develop a science-based approach to prioritizing the use of prescribed fire in appropriate forest types in the eastern United States based on a set of desired management outcomes. Through a process of expert elicitation and data analysis, we assessed and integrated recent vegetation community mapping results along with other available spatial data layers into a spatial prioritization tool for prescribed fire planning at Shenandoah National Park (Virginia, USA). The integration of vegetation spatial data allowed for development of per-pixel priority rankings and exclusion areas enabling precise targeting of fire management activities on the ground, as well as a park-wide ranking of fire planning compartments. We demonstrate the use and evaluation of this approach through implementation and monitoring of a prescribed burn and show that progress is being made toward desired conditions. Integration of spatial data into the fire planning process has served as a collaborative tool for the implementation of prescribed fire projects, which assures projects will be planned in the most appropriate areas to meet objectives that are supported by current science.
","language":"English","publisher":"Natural Areas Association","doi":"10.3375/043.037.0312","usgsCitation":"Young, J.A., Mahan, C.G., and Forder, M., 2017, Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA): Natural Areas Journal, v. 37, no. 3, p. 394-405, https://doi.org/10.3375/043.037.0312.","productDescription":"12 p.","startPage":"394","endPage":"405","ipdsId":"IP-066214","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":352864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","volume":"37","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee854e4b0da30c1bfc426","contributors":{"authors":[{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":707326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahan, Carolyn G.","contributorId":146582,"corporation":false,"usgs":false,"family":"Mahan","given":"Carolyn","email":"","middleInitial":"G.","affiliations":[{"id":12754,"text":"Penn State University Altoona","active":true,"usgs":false}],"preferred":false,"id":707327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forder, Melissa","contributorId":195517,"corporation":false,"usgs":false,"family":"Forder","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":707328,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192800,"text":"70192800 - 2017 - A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States","interactions":[],"lastModifiedDate":"2018-07-31T14:02:18","indexId":"70192800","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5215,"text":"Energy Procedia","onlineIssn":"1876-6102","active":true,"publicationSubtype":{"id":10}},"title":"A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States","docAbstract":"The U.S. Geological Survey (USGS) has developed an assessment methodology for estimating the potential incremental technically recoverable oil resources resulting from carbon dioxide-enhanced oil recovery (CO2-EOR) in reservoirs with appropriate depth, pressure, and oil composition. The methodology also includes a procedure for estimating the CO2 that remains in the reservoir after the CO2-EOR process is complete. The methodology relies on a reservoir-level database that incorporates commercially available geologic and engineering data. The mathematical calculations of this assessment methodology were tested and produced realistic results for the Permian Basin Horseshoe Atoll, Upper Pennsylvanian-Wolfcampian Play (Texas, USA). The USGS plans to use the new methodology to conduct an assessment of technically recoverable hydrocarbons and associated CO2 sequestration resulting from CO2-EOR in the United States.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.egypro.2017.03.1847","usgsCitation":"Warwick, P.D., Verma, M., Attanasi, E., Olea, R.A., Blondes, M., Freeman, P., Brennan, S.T., Merrill, M., Jahediesfanjani, H., Roueche, J., and Lohr, C., 2017, A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States: Energy Procedia, v. 114, p. 7055-7059, https://doi.org/10.1016/j.egypro.2017.03.1847.","productDescription":"5 p.","startPage":"7055","endPage":"7059","ipdsId":"IP-079968","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.egypro.2017.03.1847","text":"Publisher Index Page"},{"id":350441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb8fe4b06e28e9c2328e","contributors":{"authors":[{"text":"Warwick, Peter D. 0000-0002-3152-7783 pwarwick@usgs.gov","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":762,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter","email":"pwarwick@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":716978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verma, Mahendra K. mverma@usgs.gov","contributorId":1027,"corporation":false,"usgs":true,"family":"Verma","given":"Mahendra K.","email":"mverma@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":716979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":716980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olea, Ricardo A. 0000-0003-4308-0808 rolea@usgs.gov","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":139555,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo","email":"rolea@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":716981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":716982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freeman, Philip 0000-0002-0863-7431 pfreeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":198729,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip","email":"pfreeman@usgs.gov","affiliations":[],"preferred":false,"id":716983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brennan, Sean T. 0000-0002-7102-9359 sbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":559,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean","email":"sbrennan@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":716984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Merrill, Matthew D. 0000-0003-3766-847X mmerrill@usgs.gov","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":145534,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","email":"mmerrill@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":716985,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166 hjahediesfanjani@usgs.gov","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":193397,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","email":"hjahediesfanjani@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":716986,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roueche, Jacqueline jroueche@usgs.gov","contributorId":198730,"corporation":false,"usgs":true,"family":"Roueche","given":"Jacqueline","email":"jroueche@usgs.gov","affiliations":[],"preferred":true,"id":716987,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":716988,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70193476,"text":"70193476 - 2017 - Grassland bird productivity in warm season grass fields in southwest Wisconsin","interactions":[],"lastModifiedDate":"2017-11-10T14:51:05","indexId":"70193476","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5153,"text":"The American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Grassland bird productivity in warm season grass fields in southwest Wisconsin","docAbstract":"Surrogate grasslands established through federal set-aside programs, such as U.S. Department of Agriculture's Conservation Reserve Program (CRP), provide important habitat for grassland birds. Warm season grass CRP fields as a group have the potential for providing a continuum of habitat structure for breeding birds, depending on how the fields are managed and their floristic composition. We studied the nesting activity of four obligate grassland bird species, Bobolink (Dolichonyx oryzivorus), Eastern Meadowlark (Sturnella magna), Grasshopper Sparrow (Ammodramus savannarum), and Henslow's Sparrow (A. henslowii), in relation to vegetative composition and fire management in warm season CRP fields in southwest Wisconsin during 2009–2011. Intraspecific variation in apparent nest density was related to the number of years since the field was burned. Apparent Grasshopper Sparrow nest density was highest in the breeding season immediately following spring burns, apparent Henslow's Sparrow nest density was highest 1 y post burn, and apparent Bobolink and Eastern Meadowlark nest densities were higher in post fire years one to three. Grasshopper Sparrow nest density was highest on sites with more diverse vegetation, specifically prairie forbs, and on sites with shorter less dense vegetation. Bobolink, Eastern Meadowlark, and Henslow's Sparrow apparent nest densities were higher on sites with deeper litter; litter was the vegetative component that was most affected by spring burns. Overall nest success was 0.487 for Bobolink (22 d nesting period), 0.478 for Eastern Meadowlark (25 d nesting period), 0.507 for Grasshopper Sparrow (22 d nesting period), and 0.151 for Henslow's Sparrow (21 d nesting period). The major nest predators were grassland-associated species: thirteen-lined ground squirrel (Ictidomys tridecemlineatus), striped skunk (Mephitis mephitis), milk snake (Lampropeltis triangulum), American badger (Taxidea taxus), and western fox snake (Elaphe vulpina). Overall depredation rate was not affected by the number of years since the site had been burned. The diversity of vegetation on warm season CRP fields created by management using fire provides a continuum of structure for obligate grassland birds to use for breeding and habitat for a diversity of nest predators.
","language":"English","publisher":"University of Notre Dame","doi":"10.1674/0003-0031-178.1.47","usgsCitation":"Byers, C.M., Ribic, C., Sample, D.W., Dadisman, J.D., and Guttery, M., 2017, Grassland bird productivity in warm season grass fields in southwest Wisconsin: The American Midland Naturalist, v. 178, no. 1, p. 47-63, https://doi.org/10.1674/0003-0031-178.1.47.","productDescription":"17 p.","startPage":"47","endPage":"63","ipdsId":"IP-079728","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","volume":"178","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8cbe4b09af898c8610c","contributors":{"authors":[{"text":"Byers, Carolyn M.","contributorId":200253,"corporation":false,"usgs":false,"family":"Byers","given":"Carolyn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sample, David W.","contributorId":19484,"corporation":false,"usgs":true,"family":"Sample","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":721613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dadisman, John D.","contributorId":171934,"corporation":false,"usgs":false,"family":"Dadisman","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":721614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guttery, Michael","contributorId":191425,"corporation":false,"usgs":false,"family":"Guttery","given":"Michael","email":"","affiliations":[],"preferred":false,"id":721615,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192632,"text":"70192632 - 2017 - Complex networks of functional connectivity in a wetland reconnected to its floodplain","interactions":[],"lastModifiedDate":"2017-11-06T12:27:36","indexId":"70192632","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Complex networks of functional connectivity in a wetland reconnected to its floodplain","docAbstract":"Disturbances such as fire or flood, in addition to changing the local magnitude of ecological, hydrological, or biogeochemical processes, can also change their functional connectivity—how those processes interact in space. Complex networks offer promise for quantifying functional connectivity in watersheds. The approach resolves connections between nodes in space based on statistical similarities in perturbation signals (derived from solute time series) and is sensitive to a wider range of timescales than traditional mass-balance modeling. We use this approach to test hypotheses about how fire and flood impact ecological and biogeochemical dynamics in a wetland (Everglades, FL, USA) that was reconnected to its floodplain. Reintroduction of flow pulses after decades of separation by levees fundamentally reconfigured functional connectivity networks. The most pronounced expansion was that of the calcium network, which reflects periphyton dynamics and may represent an indirect influence of elevated nutrients, despite the comparatively smaller observed expansion of phosphorus networks. With respect to several solutes, periphyton acted as a “biotic filter,” shifting perturbations in water-quality signals to different timescales through slow but persistent transformations of the biotic community. The complex-networks approach also revealed portions of the landscape that operate in fundamentally different regimes with respect to dissolved oxygen, separated by a threshold in flow velocity of 1.2 cm/s, and suggested that complete removal of canals may be needed to restore connectivity with respect to biogeochemical processes. Fire reconfigured functional connectivity networks in a manner that reflected localized burn severity, but had a larger effect on the magnitude of solute concentrations.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2017WR020375","usgsCitation":"Larsen, L., Newman, S., Saunders, C., and Harvey, J., 2017, Complex networks of functional connectivity in a wetland reconnected to its floodplain: Water Resources Research, v. 53, no. 7, p. 6089-6108, https://doi.org/10.1002/2017WR020375.","productDescription":"10 p.","startPage":"6089","endPage":"6108","ipdsId":"IP-086967","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469703,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020375","text":"Publisher Index Page"},{"id":348265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","volume":"53","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-28","publicationStatus":"PW","scienceBaseUri":"5a07e8b9e4b09af898c8cba7","contributors":{"authors":[{"text":"Larsen, Laurel G.","contributorId":191391,"corporation":false,"usgs":false,"family":"Larsen","given":"Laurel G.","affiliations":[],"preferred":false,"id":716602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, Susan","contributorId":15308,"corporation":false,"usgs":true,"family":"Newman","given":"Susan","email":"","affiliations":[],"preferred":false,"id":716603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saunders, Colin","contributorId":73913,"corporation":false,"usgs":true,"family":"Saunders","given":"Colin","email":"","affiliations":[],"preferred":false,"id":716604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harvey, Judson 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":140228,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":716601,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194547,"text":"70194547 - 2017 - 10Be dating of late Pleistocene megafloods and Cordilleran Ice Sheet retreat in the northwestern United States","interactions":[],"lastModifiedDate":"2017-12-05T11:12:45","indexId":"70194547","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"10Be dating of late Pleistocene megafloods and Cordilleran Ice Sheet retreat in the northwestern United States","title":"10Be dating of late Pleistocene megafloods and Cordilleran Ice Sheet retreat in the northwestern United States","docAbstract":"During the late Pleistocene, multiple floods from drainage of glacial Lake Missoula further eroded a vast anastomosing network of bedrock channels, coulees, and cataracts, forming the Channeled Scabland of eastern Washington State (United States). However, the timing and exact pathways of these Missoula floods remain poorly constrained, thereby limiting our understanding of the evolution of this spectacular landscape. Here we report cosmogenic 10Be ages that directly date flood and glacial features important to understanding the flood history, the evolution of the Channeled Scabland, and relationships to the Cordilleran Ice Sheet (CIS). One of the largest floods occurred at 18.2 ± 1.5 ka, flowing down the northwestern Columbia River valley prior to blockage of this route by advance of the Okanogan lobe of the CIS, which dammed glacial Lake Columbia and diverted later Missoula floods to more eastern routes through the Channeled Scabland. The Okanogan and Purcell Trench lobes of the CIS began to retreat from their maximum extent at ca. 15.5 ka, likely in response to onset of surface warming of the northeastern Pacific Ocean. Upper Grand Coulee fully opened as a flood route after 15.6 ± 1.3 ka, becoming the primary path for later Missoula floods until the last ones from glacial Lake Missoula at 14.7 ± 1.2 ka. The youngest dated flood(s) (14.0 ± 1.4 ka to 14.4 ± 1.3 ka) came down the northwestern Columbia River valley and were likely from glacial Lake Columbia, indicating that the lake persisted for a few centuries after the last Missoula flood.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38956.1","usgsCitation":"Balbas, A.M., Barth, A.M., Clark, P.U., Clark, J., Caffee, M.A., O'Connor, J., Baker, V.R., Konrad, K., and Bjornstad, B., 2017, 10Be dating of late Pleistocene megafloods and Cordilleran Ice Sheet retreat in the northwestern United States: Geology, v. 45, no. 7, p. 583-586, https://doi.org/10.1130/G38956.1.","productDescription":"4 p.","startPage":"583","endPage":"586","ipdsId":"IP-083290","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":349682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121,\n 45.72152152227954\n ],\n [\n -115,\n 45.72152152227954\n ],\n [\n -115,\n 48.30512072140391\n ],\n [\n -121,\n 48.30512072140391\n ],\n [\n -121,\n 45.72152152227954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-08","publicationStatus":"PW","scienceBaseUri":"5a60fb8de4b06e28e9c23270","contributors":{"authors":[{"text":"Balbas, Andrea M.","contributorId":201138,"corporation":false,"usgs":false,"family":"Balbas","given":"Andrea","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Aaron M.","contributorId":201139,"corporation":false,"usgs":false,"family":"Barth","given":"Aaron","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Peter U.","contributorId":178026,"corporation":false,"usgs":false,"family":"Clark","given":"Peter","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":724419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Jorie","contributorId":201140,"corporation":false,"usgs":false,"family":"Clark","given":"Jorie","email":"","affiliations":[],"preferred":false,"id":724420,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caffee, Marc A.","contributorId":36048,"corporation":false,"usgs":false,"family":"Caffee","given":"Marc","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724421,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":724416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baker, Victor R.","contributorId":201141,"corporation":false,"usgs":false,"family":"Baker","given":"Victor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":724422,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Konrad, Kevin","contributorId":167397,"corporation":false,"usgs":false,"family":"Konrad","given":"Kevin","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":724423,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bjornstad, Bruce","contributorId":201142,"corporation":false,"usgs":false,"family":"Bjornstad","given":"Bruce","email":"","affiliations":[],"preferred":false,"id":724424,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}