The U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management have cooperated to map approximately 185 square kilometers of the inner continental shelf south of Martha’s Vineyard and north of Nantucket, Massachusetts. This report contains geophysical data collected by the U.S. Geological Survey during a survey in 2013. The geophysical data include (1) swath bathymetry collected by using interferometric sonar, (2) acoustic backscatter from the interferometric sonar, and (3) seismic-reflection profiles from a chirp subbottom profiler. These spatial data support research on the Quaternary evolution of coastal Massachusetts, the influence of sea-level change and sediment supply on coastal evolution, and efforts to understand the type, distribution, and quality of subtidal marine habitats in the coastal ocean of Massachusetts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161168","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Ackerman, S.D., Brothers, L.L., Foster, D.S., Andrews, B.D., Baldwin, W.E., and Schwab, W.C., 2016, High-resolution geophysical data from the inner continental shelf—South of Martha’s Vineyard and north of Nantucket, Massachusetts: U.S. Geological Survey Open-File Report 2016–1168, 21 p., https://dx.doi.org/10.3133/ofr20161168.","productDescription":"Report: vi, 21 p.; HTML Document","startPage":"1","endPage":"21","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069726","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":330433,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1168/index.html","text":"Report HTML","description":"Report HTML"},{"id":330432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1168/images/coverthb.jpg"},{"id":330434,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1168/ofr20161168.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1168"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Martha's Vineyard, Nantucket","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.7904052734375,\n 41.15384235711447\n ],\n [\n -70.7904052734375,\n 41.38711263243966\n ],\n [\n -70.02960205078125,\n 41.38711263243966\n ],\n [\n -70.02960205078125,\n 41.15384235711447\n ],\n [\n -70.7904052734375,\n 41.15384235711447\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
http://woodshole.er.usgs.gov/
With growing climate change concerns and energy constraints, there is an increasing need for renewable energy sources within the United States and globally. Looking forward, offshore wind-energy infrastructure (OWEI) has the potential to produce a significant proportion of the power needed to reach our Nation’s renewable energy goal. Offshore wind-energy sites can capitalize open areas within Federal waters that have persistent, high winds with large energy production potential. Although there are few locations in the California Current System (CCS) where it would be acceptable to build pile-mounted wind turbines in waters less than 50 m deep, the development of technology able to support deep-water OWEI (>200 m depth) could enable wind-energy production in the CCS. As with all human-use of the marine environment, understanding the potential impacts of wind-energy infrastructure on the marine ecosystem is an integral part of offshore wind-energy research and planning. Herein, we present a comprehensive database to quantify marine bird vulnerability to potential OWEI in the CCS (see https://doi.org/10.5066/F79C6VJ0). These data were used to quantify marine bird vulnerabilities at the population level. For 81 marine bird species present in the CCS, we created three vulnerability indices: Population Vulnerability, Collision Vulnerability, and Displacement Vulnerability. Population Vulnerability was used as a scaling factor to generate two comprehensive indicies: Population Collision Vulnerability (PCV) and Population Displacement Vulnerability (PDV). Within the CCS, pelicans, terns (Forster’s [Sterna forsteri], Caspian [Hydroprogne caspia], Elegant [Thalasseus elegans], and Least Tern [Sternula antillarum]), gulls (Western [Larus occidentalis] and Bonaparte’s Gull [Chroicocephalus philadelphia]), South Polar Skua (Stercorarius maccormicki), and Brandt’s Cormorant (Phalacrocorax penicillatus) had the greatest PCV scores. Brown Pelican (Pelicanus occidentalis) had the greatest overall PCV score. Some alcids (Scripps’s Murrelet [Synthliboramphus scrippsi], Marbled Murrelet [Brachyramphus marmoratus], and Tufted Puffin [Fratercula cirrhata]), terns (Elegant and Least Lern), and loons (Yellow-billed [Gavia adamsii] and Common Loon [G. immer]) had the greatest PDV scores. Ashy Storm-Petrel (Oceanodroma homochroa) had the greatest overall PDV score. To help inform decisions that will impact seabird conservation, vulnerability assessment results can now be combined with recent marine bird at-sea distribution and abundance data for the CCS to evaluate vulnerability areas where OWEI development is being considered. Lastly, it is important to note that as new information about seabird behavior and populations in the CCS becomes available, this database can be easily updated and modified.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161154","collaboration":"Prepared in cooperation with Bureau of Ocean Energy Management (OCS Study, BOEM 2016-043)","usgsCitation":"Adams, J., Kelsey, E.C., Felis, J.J., and Pereksta, D.M., 2017, Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure (ver. 1.1, July 2017): U.S. Geological Survey Open-File Report 2016-1154, 116 p., https://doi.org/10.3133/ofr20161154.","productDescription":"Report: vi, 116 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-071912","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438527,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79C6VJ0","text":"USGS data release","linkHelpText":"Data for calculating population, collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure (ver. 2.0, June 2017)"},{"id":341751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1154/coverthb.jpg"},{"id":344436,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1154/ofr20161154.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1154"},{"id":344437,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1154/ofr20161154_revision history.docx","size":"153 KB docx","description":"OFR 2016-1154 Revision History"}],"edition":"Version 1.0: Originally posted October 27, 2016; Version 1.1: July 2017","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Managed aquifer recharge is used to augment natural recharge to aquifers. It can be used to replenish aquifers depleted by pumping or to store water during wetter years for withdrawal during drier years. Infiltration from ponds is a commonly used, inexpensive approach for managed aquifer recharge.
At some managed aquifer-recharge sites, the time when infiltrated water arrives at the water table is not always clearly shown by water-level data. As part of site characterization and operation, it can be desirable to track downward movement of infiltrated water through the unsaturated zone to identify when it arrives at the water table.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161180","collaboration":"Prepared in cooperation with the Antelope Valley-East Kern Water Agency","usgsCitation":"Nawikas, J.M, O’Leary, D.R., Izbicki, J.A., and Burgess, M.K., 2016, Selected techniques for monitoring water movement through unsaturated alluvium during managed aquifer recharge: U.S. Geological Survey Open-File Report 2016–5105, 8 p., https://dx.doi.org/10.3133/ofr20161180.","productDescription":"8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-060596","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":329775,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1180/coverthb.jpg"},{"id":329776,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1180/ofr20161180.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1180"}],"country":"United States","state":"California","otherGeospatial":"Antelope Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.795166015625,\n 34.474863669009004\n ],\n [\n -117.20214843749999,\n 34.474863669009004\n ],\n [\n -117.20214843749999,\n 35.106428057364255\n ],\n [\n -118.795166015625,\n 35.106428057364255\n ],\n [\n -118.795166015625,\n 34.474863669009004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Joseph Nawikas
4165 Spruance Road, Suite 200
San Diego, CA 92101
(619) 225-6148
jnawika@usgs.gov
Every two years, scientists, natural resource managers, outreach specialists, and a variety of other interested parties get together for the biennial meeting of the Yellowstone Volcano Observatory (YVO). Each time, the theme varies. In past years, we have focused the meeting around topics including monitoring plans, emergency response, geodesy, and outreach. This year, we spent the first half-day devoted to recent research results, plans for upcoming studies, and geothermal monitoring. On the second day, our focus switched to eruption precursors, particularly as they apply to large caldera systems.
Very few large explosive eruptions from caldera systems have taken place in recorded history. Therefore, there are few empirical data with which to characterize the nature of volcanic unrest that might precede eruptions with volcano explosivity index (VEI) of six or greater. For this reason, we set up a series of talks that explore what we know and don’t know about large eruptions. We performed an informal expert elicitation (a frequently used method to characterize expert opinion) with a small number of our colleagues, which served as the basis for a productive discussion session.
This short volume of abstracts and extended abstracts provides a summary of the presentations made at the YVO meeting held in Mammoth Hot Springs, Wyoming, on May 10–11, 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161104","usgsCitation":"Lowenstern, J.B., ed., 2016, Abstract volume for the 2016 biennial meeting of the Yellowstone Volcano Observatory: U.S. Geological Survey Open-File Report 2016–1104, 46 p., https://www.dx.doi.org/10.3133/ofr20161104","productDescription":"iii, 46 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-076807","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":329774,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1104/ofr20161104.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1104"},{"id":329773,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1104/coverthb.jpg"}],"contact":"Contact YVO
Volcano Science Center, Yellowstone Volcano Observatory
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
http://volcanoes.usgs.gov/yvo/
Water samples were collected and analyzed for arsenic and radon from 36 private, mostly domestic wells that tap the Rancocas aquifer in southern New Castle and northern Kent Counties, Delaware, during the summer of 2015. Both arsenic and radon are from natural mineral sources, in particular glauconitic and other marine-derived sediments, which are important components of the geologic formations comprising the Rancocas aquifer. Routine testing of domestic wells is not required in Delaware; as a result, many homeowners are not aware of potential water-quality problems with these chemicals in their well water. Arsenic has previously been detected at levels of potential concern for human health in this aquifer in adjacent parts of Maryland where it is referred to as the Aquia aquifer. Arsenic and radon also have previously been detected in several Rancocas aquifer wells in Delaware. The Delaware Department of Natural Resources and Environmental Control intends to use the data from this project to better identify areas with potential for levels of concern for domestic well owners. This report includes chemical results and maps showing the distribution of sampled wells and concentrations of arsenic and radon. All data collected for this study also are available in the U.S. Geological Survey’s National Water Information System database.
Arsenic was detected above the minimum reporting limit of 0.1 micrograms per liter (µg/L) in 34 of the 36 wells sampled with concentrations ranging from about 0.11 to 27 µg/L. In 15 of the samples, arsenic concentrations were at or above the U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level (MCL) of 10 µg/L for public wells. Most of the higher concentrations are clustered along a band running from the southwest to northeast in the southern part of the study area.
Radon, which is an inert gas derived from radium, was detected in all water samples with concentrations ranging from 85 to 1,870 picocuries per liter (pCi/L). Currently, the EPA has not set a MCL for radon in public water systems. There were no samples where radon was detected at a concentration exceeding the proposed alternative MCL of 4,000 pCi/L. Samples from 16 of 36 wells were above the lower proposed MCL of 300 pCi/L. Most of these samples were from wells greater than 200 feet deep located in a similar part of the aquifer as the higher concentrations of arsenic along an east-northeasterly line in the southern part of the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161143","isbn":"978-1-4113 4086-2","collaboration":"Prepared in cooperation with the Delaware Department of Natural Resources and Environmental Control (DNREC) Water Supply Section, Groundwater Protection Branch","usgsCitation":"Denver, J.M., 2016, Occurrence and distribution of arsenic and radon in water from private wells in the Rancocas aquifer, southern New Castle and northern Kent Counties, Delaware, 2015: U.S. Geological Survey Open-File Report 2016–1143, 15 p., https://dx.doi.org/10.3133/ofr20161143. ","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"N","ipdsId":"IP-076094","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":329414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1143/ofr20161143.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1143"},{"id":329413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1143/coverthb.jpg"}],"country":"United States","state":"Delaware","county":"Kent County, New Castle County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.43624877929688,\n 39.310925412127155\n ],\n [\n -75.76034545898438,\n 39.298705113102244\n ],\n [\n -75.77888488769531,\n 39.50827899034114\n ],\n [\n -75.57220458984375,\n 39.51834388059882\n ],\n [\n -75.43624877929688,\n 39.310925412127155\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Or visit our Web site at:
http://md.water.usgs.gov
The Alaskan breeding population of Steller’s eiders (Polysticta stelleri) was listed as threatened under the Endangered Species Act in 1997 in response to perceived declines in abundance throughout their breeding and nesting range. Aerial surveys suggest the breeding population is small and highly variable in number, with zero birds counted in 5 of the last 25 years. Research was conducted to evaluate competing population process models of Alaskan-breeding Steller’s eiders through comparison of model projections to aerial survey data. To evaluate model efficacy and estimate demographic parameters, a Bayesian state-space modeling framework was used and each model was fit to counts from the annual aerial surveys, using sequential importance sampling and resampling. The results strongly support that the Alaskan breeding population experiences population level nonbreeding events and is open to exchange with the larger Russian-Pacific breeding population. Current recovery criteria for the Alaskan breeding population rely heavily on the ability to estimate population viability. The results of this investigation provide an informative model of the population process that can be used to examine future population states and assess the population in terms of the current recovery and reclassification criteria.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161062","usgsCitation":"Dunham, Kylee, and Grand, J.B., 2016, Evaluating models of population process in a threatened population of Steller’s eiders—A retrospective approach: U.S. Geological Survey Open-File Report 2016–1062, 14 p., https://dx.doi.org/10.3133/ofr20161062.","productDescription":"vi, 14 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074896","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":329250,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/preview/ofr20161084","text":"Open-File Report 2016–1084","description":"Open-File Report 2016–1084","linkHelpText":"- Viability of the Alaskan Breeding Population of Steller’s Eiders"},{"id":329247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1062/ofr20161062.pdf","text":"Report","size":"355 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1062"},{"id":329246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1062/coverthb.jpg"}],"contact":"Chief, Cooperative Research Units
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192-0002
https://www.usgs.gov/science/mission-areas/ecosystems
The U.S. Fish and Wildlife Service is tasked with setting objective and measurable criteria for delisting species or populations listed under the Endangered Species Act. Determining the acceptable threshold for extinction risk for any species or population is a challenging task, particularly when facing marked uncertainty. The Alaskan breeding population of Steller’s eiders (Polysticta stelleri) was listed as threatened under the Endangered Species Act in 1997 because of a perceived decline in abundance throughout their nesting range and geographic isolation from the Russian breeding population. Previous genetic studies and modeling efforts, however, suggest that there may be dispersal from the Russian breeding population. Additionally, evidence exists of population level nonbreeding events. Research was conducted to estimate population viability of the Alaskan breeding population of Steller’s eiders, using both an open and closed model of population process for this threatened population. Projections under a closed population model suggest this population has a 100 percent probability of extinction within 42 years. Projections under an open population model suggest that with immigration there is no probability of permanent extinction. Because of random immigration process and nonbreeding behavior, however, it is likely that this population will continue to be present in low and highly variable numbers on the breeding grounds in Alaska. Monitoring the winter population, which includes both Russian and Alaskan breeding birds, may offer a more comprehensive indication of population viability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161084","usgsCitation":"Dunham, Kylee, and Grand, J.B., 2016, Viability of the Alaskan breeding population of Steller’s eiders: U.S. Geological Survey Open-File Report 2016–1084, 8 p., https://dx.doi.org/10.3133/ofr20161084.","productDescription":"v, 8 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074532","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":329251,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/preview/ofr20161062","text":"Open-File Report 2016–1062","description":"Open-File Report 2016–1062","linkHelpText":"- Evaluating Models of Population Process in a Threatened Population of Steller’s Eiders: A Retrospective Approach"},{"id":329249,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1084/ofr20161084.pdf","text":"Report","size":"232 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1084"},{"id":329248,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1084/coverthb.jpg"}],"contact":"Chief, Cooperative Research Units
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192-0002
https://www.usgs.gov/science/mission-areas/ecosystems
The U.S. Geological Survey developed the Massachusetts Reservoir Simulation Tool to examine the effects of reservoirs on natural streamflows in Massachusetts by simulating the daily water balance of reservoirs. The simulation tool was developed to assist environmental managers to better manage water withdrawals in reservoirs and to preserve downstream aquatic habitats.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161136","usgsCitation":"Levin, S.B., 2016, Massachusetts reservoir simulation tool—User’s manual: U.S. Geological Survey Open-File Report 2016–1136, 22 p., https://dx.doi.org/10.3133/ofr20161136.","productDescription":"Report: iv, 22 p.; Software or Model Page","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073794","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":329305,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165123","text":"Scientific Investigations Report 2016–5123","description":"Scientific Investigations Report 2016–5123","linkHelpText":"- Effects of Water-Supply Reservoirs on Streamflow in Massachusetts"},{"id":329300,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1136/ofr20161136.pdf","text":"Report","size":"4.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1136"},{"id":329306,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://newengland.water.usgs.gov/dev/sl1/rst/ ","text":"Software or Model Page","description":"Software or Model Page","linkHelpText":"- The Massachusetts Reservoir Simulation Tool"},{"id":329299,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1136/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Massachusetts Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.116667,\n 42.311111\n ],\n [\n -72.116667,\n 42.270833\n ],\n [\n -72.045833,\n 42.270833\n ],\n [\n -72.045833,\n 42.311111\n ],\n [\n -72.116667,\n 42.311111\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov/
During 2015, the U.S. Geological Survey, in cooperation with the City of Ithaca, New York, and the New York State Department of State, conducted a bathymetric survey of the lower Sixmile Creek reservoir in Tompkins County, New York. A former water-supply reservoir for the City of Ithaca, the reservoir is no longer a functional component of Ithaca’s water-supply system, having been replaced by a larger reservoir less than a mile upstream in 1911. Excessive sedimentation has substantially reduced the reservoir’s water-storage capacity and made the discharge gate at the base of the 30-foot dam, which creates the reservoir, inoperable. U.S. Geological Survey personnel collected bathymetric data by using an acoustic Doppler current profiler. Across more than half of the approximately 14-acre reservoir, depths were manually measured because of interference from aquatic vegetation with the acoustic Doppler current profiler. City of Ithaca personnel created a bottom-elevation surface from these depth data. A second surface was created from depths that were manually measured by City of Ithaca personnel during 1938. Surface areas and storage capacities were computed at 1-foot increments of elevation for both bathymetric surveys. The results indicate that the current storage capacity of the reservoir at its normal water-surface elevation is about 84 acre-feet and that sediment accumulated between 1938 and 2015 has decreased the reservoir’s capacity by about 68 acre-feet. This sediment load is attributed to annual inputs from the watershed above the reservoir, as well as from an episodic landslide that filled a large part of the reservoir along its northern edge in 1949.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161157","collaboration":"Prepared in cooperation with the City of Ithaca, New York, and the New York State Department of State","usgsCitation":"Wernly, J.F., Zajd, H.J., Jr., and Coon, W.F., 2016, Bathymetric survey and estimation of storage capacity of lower Sixmile Creek reservoir, Ithaca, New York: U.S. Geological Survey Open-File Report 2016–1157, 13 p., https://dx.doi.org/10.3133/ofr20161157.","productDescription":"Report: vii, 13 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074656","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":438539,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G15Z0S","text":"USGS data release","linkHelpText":"Geospatial data set of bathymetric survey of lower Sixmile Creek Reservoir, Ithaca, New York, 2015"},{"id":329057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1157/coverthb.jpg"},{"id":329058,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1157/ofr20161157.pdf","text":"Report","size":"7.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1157"},{"id":329059,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7G15Z0S","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial Dataset of Bathymetric Survey of Lower Sixmile Creek Reservoir, Ithaca, New York, 2015"}],"country":"United States","state":"New York","city":"Ithaca","otherGeospatial":"Lower Sixmile Creek Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.47645235061646,\n 42.42269621215634\n ],\n [\n -76.47645235061646,\n 42.42519885057981\n ],\n [\n -76.47053003311157,\n 42.42519885057981\n ],\n [\n -76.47053003311157,\n 42.42269621215634\n ],\n [\n -76.47645235061646,\n 42.42269621215634\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
30 Brown Road
Ithaca, NY 14850
Information requests:
(518) 285-5602
or visit our Web site at:
http://ny.water.usgs.gov
Restoration of tidal flows to formerly diked marshland can alter land-to-sea fluxes and patterns of accumulation of terrestrial sediment and organic matter, and these tidal flows can also affect existing nearshore habitats. Dikes were removed from 308 hectares (ha) of the Nisqually National Wildlife Refuge on the Nisqually River Delta in south Puget Sound, Washington, in fall 2009 to improve habitat for wildlife, such as juvenile salmon. Ecologically important intertidal and subtidal eelgrass (Zostera marina) beds grow on the north and west margins of the delta. The goal of this study was to understand long-term changes in eelgrass habitat and their relation to dike removal. Sediment and eelgrass properties were monitored annually in May from 2010 to 2014 at two sites on the west side of the Nisqually River Delta along McAllister Creek, a spring-fed creek near two restored tidal channels. In May 2014, the mean canopy height of eelgrass was the same as in previous years in an 8-ha bed extending to the Nisqually River Delta front, but mean canopy height was 20 percent lower in a 0.3-ha eelgrass bed closer to the restored marsh when compared to mean canopy height of eelgrass in May 2010, 6 months after dike removal was completed. Over 5 years, the amount of eelgrass leaf area per square meter (m2) in the 8-ha bed increased slightly, and surface-sediment grain size became finer. In contrast, in the 0.3-ha bed, eelgrass leaf area per m2 decreased by 45 percent, and surface sediment coarsened. Other potential stressors, including sediment pore water reduction-oxidation potential (redox) and hydrogen sulfide (H2S) concentration in the eelgrass rhizosphere, or root zone, were below levels that negatively affect eelgrass growth and therefore did not appear to be environmental stressors on plants. Eelgrass biomass partitioning, though less favorable in the 8-ha eelgrass bed compared to the 0.3-ha one, was well above the critical above-ground to below-ground biomass ratio of 2:1 for Z. marina, an indication that these plants were not at risk of a carbon deficit during low-light conditions. After 5 years, nearshore changes associated with the restoration of tidal flows to formerly diked marshes of the Nisqually River Delta appeared to have little impact on the large eelgrass bed extending from Luhr Beach to the Nisqually River Delta front; however, restoration appears to be contributing to the decline of a small eelgrass bed closer to the restoration area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161169","usgsCitation":"Takesue, R.K., 2016, Environmental and eelgrass response to dike removal: Nisqually River Delta (2010–14): U.S. Geological Survey Open-File Report 2016–1169, 17 p., https://dx.doi.org/10.3133/ofr20161169.","productDescription":"vi, 17 p.","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-064121","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":329008,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1169/ofr20161169.pdf","text":"Report","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1169"},{"id":329007,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1169/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":" Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73556709289551,\n 47.06760800518024\n ],\n [\n -122.73556709289551,\n 47.10997630516621\n ],\n [\n -122.68183708190917,\n 47.10997630516621\n ],\n [\n -122.68183708190917,\n 47.06760800518024\n ],\n [\n -122.73556709289551,\n 47.06760800518024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
The Design Analysis Associates (DAA) DAA H-3613i radar water-level sensor (DAA H-3613i), manufactured by Xylem Incorporated, was evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to manufacturer’s accuracy specifications for measuring a distance throughout the sensor’s operating temperature range, for measuring distances from 3 to 15 feet at ambient temperatures, and for compliance with the SDI-12 serial-to-digital interface at 1200-baud communication standard. The DAA H-3613i is a noncontact water-level sensor that uses pulsed radar to measure the distance between the radar and the water surface from 0.75 to 131 feet over a temperature range of −40 to 60 degrees Celsius (°C). Manufacturer accuracy specifications that were evaluated, the test procedures that followed, and the results obtained are described in this report. The sensor’s accuracy specification of ± 0.01 feet (± 3 millimeters) meets USGS requirements for a primary water-stage sensor used in the operation of a streamgage. The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during temperature testing at a distance of 8 feet from the target over its temperature-compensated operating range of −40 to 60 °C, except at 60 °C. At 60 °C, about half the measurements exceeded the manufacturer’s accuracy specification by not more than 0.005 feet.The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during distance-accuracy testing at the tested distances from 3 to 15 feet above the water surface at the HIF.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161124","usgsCitation":"Carnley, M.V., 2016, Laboratory evaluation of the Design Analysis Associates DAA H-3613i radar water-level sensor—Results of temperature, distance, and SDI-12 tests: U.S. Geological Survey Open-File Report 2016–1124, 7 p., https://dx.doi.org/10.3133/ofr20161124. ","productDescription":"iii, 7 p.","numberOfPages":"16","onlineOnly":"Y","ipdsId":"IP-071442","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":329212,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1124/coverthb.jpg"},{"id":329213,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1124/ofr20161124.pdf","text":"Report","size":"2.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1124"}],"contact":"Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
In the 1970s and 1980s, C.S. Venable Barclay conducted geologic mapping of areas primarily underlain by Cretaceous coals in the eastern part of the Little Snake River coal field (LSR) in Carbon County, southwest Wyoming. With some exceptions, most of the mapping data were never published. Subsequently, after his retirement from the U.S. Geological Survey (USGS), his field maps and field notebooks were archived in the USGS Field Records. Due to a pending USGS coal assessment of the Little Snake River coal field area and planned geological mapping to be conducted by the Wyoming State Geological Survey, Barclay’s mapping data needed to be published to support these efforts. Subsequently, geologic maps were scanned and georeferenced into a geographic information system, and project and field notes were scanned into Portable Document Format (PDF) files. Data for seventeen 7½-minute quadrangles are presented in this report. This publication is solely intended to compile the mapping data as it was last worked on by Barclay and provides no interpretation or modification of his work.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161170","usgsCitation":"Haacke, J.E., Barclay, C.S.V., and Hettinger, R.D., 2016, Preliminary geologic mapping of Cretaceous and Tertiary formations in the eastern part of the Little Snake River coal field, Carbon County, Wyoming: U.S. Geological Survey Open-File Report 2016–1170, 9 p., https://dx.doi.org/10.3133/ofr20161170.","productDescription":"Report: iii, 9 p.; Field Notes; Metadata; Read Me; Spatial Data","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-070800","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":329139,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_Field Notes.zip","text":"Field Notes","size":"444 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1170 Field Notes"},{"id":329143,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_Readme.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1170 Read Me"},{"id":329138,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170.pdf","text":"Report","size":"7.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1170"},{"id":329137,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1170/coverthb.jpg"},{"id":329142,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_Metadata.zip","text":"Metadata","size":"32.0 kB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1170 Metadata"},{"id":329141,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_GIS.zip","text":"Spatial Data","size":"2.45 GB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1170 Spatial Data"}],"country":"United States","state":"Wyoming","county":"Carbon County","otherGeospatial":"Little Snake River Coal 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Director, USGS Central Energy Resources Science Center
Box 25046, Mail Stop 939
Denver, CO 80225
In the spring of 2009, the U.S. Geological Survey, in cooperation with the San Bernardino Valley Municipal Water District, began working on a gravity survey in the Yucaipa area to explore the three-dimensional shape of the sedimentary fill (alluvial deposits) and the surface of the underlying crystalline basement rocks. As water use has increased in pace with rapid urbanization, water managers have need for better information about the subsurface geometry and the boundaries of groundwater subbasins in the Yucaipa area. The large density contrast between alluvial deposits and the crystalline basement complex permits using modeling of gravity data to estimate the thickness of alluvial deposits. The bottom of the alluvial deposits is considered to be the top of crystalline basement rocks. The gravity data, integrated with geologic information from surface outcrops and 51 subsurface borings (15 of which penetrated basement rock), indicated a complex basin configuration where steep slopes coincide with mapped faults―such as the Crafton Hills Fault and the eastern section of the Banning Fault―and concealed ridges separate hydrologically defined subbasins.
Gravity measurements and well logs were the primary data sets used to define the thickness and structure of the groundwater basin. Gravity measurements were collected at 256 new locations along profiles that totaled approximately 104.6 km (65 mi) in length; these data supplemented previously collected gravity measurements. Gravity data were reduced to isostatic anomalies and separated into an anomaly field representing the valley fill. The ‘valley-fill-deposits gravity anomaly’ was converted to thickness by using an assumed, depth-varying density contrast between the alluvial deposits and the underlying bedrock.
To help visualize the basin geometry, an animation of the elevation of the top of the basement-rocks was prepared. The animation “flies over” the Yucaipa groundwater basin, viewing the land surface, geology, faults, and ridges and valleys of the shaded-relief elevation of the top of the basement complex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161127","collaboration":"Prepared in cooperation with the San Bernardino Valley Municipal Water District","usgsCitation":"Mendez, G.O., Langenheim, V.E., Morita, Andrew, and Danskin, W.R., 2016, Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California: U.S. Geological Survey Open-File Report 2016–1127, 22 p., https://dx.doi.org/10.3133/ofr20161127.","productDescription":"Report: vii, 23 p.; Video Animation","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077241","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":329070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1127"},{"id":329071,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127_gravity.mp4","text":"Video animation","size":"47.3 MB mp4","description":"OFR 2016-1127 Video Animation","linkHelpText":"Land surface, geology, faults, wells, and elevation of the basement rocks in the Yucaipa area, California."},{"id":329069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1127/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County, Riverside County","otherGeospatial":"Yucaipa Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.15888977050781,\n 33.96842016198477\n ],\n [\n -117.15888977050781,\n 34.08962997133382\n ],\n [\n -116.97212219238281,\n 34.08962997133382\n ],\n [\n -116.97212219238281,\n 33.96842016198477\n ],\n [\n -117.15888977050781,\n 33.96842016198477\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
The effects of earthquake shaking on the population and infrastructure across the State of Hawaii could be catastrophic, and the high seismic hazard in the region emphasizes the likelihood of such an event. Earthquake early warning (EEW) has the potential to give several seconds of warning before strong shaking starts, and thus reduce loss of life and damage to property. The two approaches to EEW are (1) a network approach (such as ShakeAlert or ElarmS) where the regional seismic network is used to detect the earthquake and distribute the alarm and (2) a local approach where a critical facility has a single seismometer (or small array) and a warning system on the premises.
The network approach, also referred to here as ShakeAlert or ElarmS, uses the closest stations within a regional seismic network to detect and characterize an earthquake. Most parameters used for a network approach require observations on multiple stations (typically 3 or 4), which slows down the alarm time slightly, but the alarms are generally more reliable than with single-station EEW approaches. The network approach also benefits from having stations closer to the source of any potentially damaging earthquake, so that alarms can be sent ahead to anyone who subscribes to receive the notification. Thus, a fully implemented ShakeAlert system can provide seconds of warning for both critical facilities and general populations ahead of damaging earthquake shaking.
The cost to implement and maintain a fully operational ShakeAlert system is high compared to a local approach or single-station solution, but the benefits of a ShakeAlert system would be felt statewide—the warning times for strong shaking are potentially longer for most sources at most locations.
The local approach, referred to herein as “single station,” uses measurements from a single seismometer to assess whether strong earthquake shaking can be expected. Because of the reliance on a single station, false alarms are more common than when using a regional network of seismometers. Given the current network, a single-station approach provides more warning for damaging earthquakes that occur close to the station, but it would have limited benefit compared to a fully implemented ShakeAlert system. For Honolulu, for example, the single-station approach provides an advantage over ShakeAlert only for earthquakes that occur in a narrow zone extending northeast and southwest of O‘ahu. Instrumentation and alarms associated with the single-station approach are typically maintained and assessed within the target facility, and thus no outside connectivity is required. A single-station approach, then, is unlikely to help broader populations beyond the individuals at the target facility, but they have the benefit of being commercially available for relatively little cost.
The USGS Hawaiian Volcano Observatory (HVO) is the Advanced National Seismic System (ANSS) regional seismic network responsible for locating and characterizing earthquakes across the State of Hawaii. During 2014 and 2015, HVO tested a network-based EEW algorithm within the current seismic network in order to assess the suitability for building a full EEW system. Using the current seismic instrumentation and processing setup at HVO, it is possible for a network approach to release an alarm a little more than 3 seconds after the earthquake is recorded on the fourth seismometer. Presently, earthquakes having M≥3 detected with the ElarmS algorithm have an average location error of approximately 4.5 km and an average magnitude error of -0.3 compared to the reviewed catalog locations from the HVO. Additional stations and upgrades to existing seismic stations would serve to improve solution precision and warning times and additional staffing would be required to provide support for a robust, network-based EEW system.
For a critical facility on the Island of Hawaiʻi, such as the telescopes atop Mauna Kea, one phased approach to mitigate losses could be to immediately install a single station system to establish some level of warning. Subsequently, supporting the implementation of a full network-based EEW system on the Island of Hawaiʻi would provide additional benefit in the form of improved warning times once the system is fully installed and operational, which may take several years.
Distributed populations across the Hawaiian Islands, including those outside the major cities and far from the likely earthquake source areas, would likely only benefit from a network approach such as ShakeAlert to provide warnings of strong shaking.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161172","usgsCitation":"Thelen, W.A., Hotovec-Ellis, A.J., Bodin, P., 2016, Feasibility study of earthquake early warning (EEW) in Hawaii: U.S. Geological Survey Open-File Report 2016–1172, 33 p., https://dx.doi.org/10.3133/ofr20161172.","productDescription":"iii, 30 p.","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-079231","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":329083,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1172/ofr20161172.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1172"},{"id":329082,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1172/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Contact HVO
Volcano Science Center, Hawaiian Volcano Observatory
U.S. Geological Survey
P.O. Box 51, 1 Crater Rim Road
Hawaiʻi Volcanoes National Park, HI 96718-0051
http://hvo.wr.usgs.gov/
Multiple sampling trips during calendar years 2013 through 2015 were coordinated to provide measurements of interdependent benthic processes that potentially affect contaminant transport in Upper Klamath Lake (UKL), Oregon. The measurements were motivated by recognition that such internal processes (for example, solute benthic flux, bioturbation and solute efflux by benthic invertebrates, and physical groundwater-surface water interactions) were not integrated into existing management models for UKL. Up until 2013, all of the benthic-flux studies generally had been limited spatially to a number of sites in the northern part of UKL and limited temporally to 2–3 samplings per year. All of the benthic invertebrate studies also had been limited to the northern part of the lake; however, intensive temporal (weekly) studies had previously been completed independent of benthic-flux studies. Therefore, knowledge of both the spatial and temporal variability in benthic flux and benthic invertebrate distributions for the entire lake was lacking. To address these limitations, we completed a lakewide spatial study during 2013 and a coordinated temporal study with weekly sampling of benthic flux and benthic invertebrates during 2014. Field design of the spatially focused study in 2013 involved 21 sites sampled three times as the summer cyanobacterial bloom developed (that is, May 23, June 13, and July 3, 2013). Results of the 27-week, temporally focused study of one site in 2014 were summarized and partitioned into three periods (referred to herein as pre-bloom, bloom and post-bloom periods), each period involving 9 weeks of profiler deployments, water column and benthic sampling. Partitioning of the pre-bloom, bloom, and post-bloom periods were based on water-column chlorophyll concentrations and involved the following date intervals, respectively: April 15 through June 10, June 17 through August 13, and August 20 through October 16, 2014.
To examine dissolved-solute (0.2-micrometer [μm] filtered) benthic flux, sets of nonmetallic pore-water profilers (U.S. Patent 8,051,727 B1) were deployed. In 2013, the deployment of profilers at 21 UKL sites occurred at the beginning of the annual cyanobacterial bloom of Aphanizomenon flos–aquae (AFA), in the middle of the bloom period, and at the peak of the bloom. Coordinated benthic invertebrate collections also were made. Based on results from 2013, weekly deployments of profilers and collection of benthic invertebrate samples from late spring to early autumn were used to estimate temporal trends in solute flux and benthic invertebrate densities. Estimates of nutrient efflux by benthic invertebrates were determined in the spring and autumn from 2011 through 2013 and three times (spring, summer, and autumn) in 2015. This work extends UKL studies that began in 2006 to quantify the importance of benthic solute sources in the lake. In 2015, piezometers and thermistor sets were deployed to quantify potential groundwater exchange with the lake water column.
Analysis of the 2013 soluble reactive phosphorus (SRP) benthic flux indicated no effect of location (lake region), habitat, or sampling period, and the average lakewide flux values were consistent with earlier studies that had been confined to the northern region of UKL and adjacent wetlands. The 2014 study therefore focused on estimating temporal trends at a site within Ball Bay. During both 2013 and 2014 field studies, fluxes of macronutrients (soluble reactive phosphorus (SRP) and ammonia) and micronutrients (iron [Fe] and manganese [Mn]) were consistently positive and increased prior to the initial AFA bloom, varied or lagged with water-column chlorophyll during the summer bloom period, then decreased after the cyanobacterial blooms, only to rebound toward pre-bloom conditions in the final weeks of sampling. These four solutes exhibited benthic loads greater than maximum riverine loads estimated during the spring and early summers of 2013 and 2014. However, consistently detectable concentrations for all four solutes provide no evidence that they consistently serve as the limiting nutrient for primary production in the lake. In contrast to the four solutes (SRP, ammonia, Fe, and Mn), benthic fluxes of dissolved arsenic (As) were both negative and positive (that is, the lakebed currently serves as both a source and a sink for dissolved As, depending on season). In a further contrast with SRP, ammonia, dissolved Fe, and Mn, dissolved-As riverine loads to UKL were of similar magnitude to benthic loads. A negative relationship between dissolved-As flux and water-column As over the 2014 temporal study provides a potential advantage for the management of water-quality in contrast to solutes, like SRP or ammonia, with consistently positive flux.
The mean total benthic invertebrate density during 2013 was 12,610 individuals per square meter (n=63). Although benthic invertebrate density did not change over the study period, it was higher in littoral habitats than open-lake or trench habitats and higher in the northern region compared to the central or southern regions of UKL. Mean total benthic invertebrate density during 2014 was 19,726 individuals m−2 (n=27). Density during the pre-bloom and bloom periods of April 15 to August 13, 2014 (the first two thirds of the 2014 sampling period), were similar to 2013. However, benthic invertebrate density more than doubled during the latter one-third of the study, that is, the post-bloom period between August 20 to October 16, 2014. Oligochaeta, Chironomidae and Hirudinea represented well over 90 percent of the benthic fauna; Oligochaeta were twice as abundant as Chironomidae or Hirudinea, the latter two of which were similar in density.
Benthic invertebrates may enhance dissolved-nutrient (or toxicant) transport across the sediment-water interface by (1) modifying diffusion-layer thicknesses and permeability through bioturbation, (2) enhancing advective flow across the interface through bioirrigation, and (3) excreting or expelling dissolved or particulate solutes directly into the overlying water column (Boudreau and Jorgensen, 2001). We evaluated SRP efflux via excretion for approximately 15 different major taxa in UKL. Once these measures were scaled, it was evident that benthic invertebrates potentially contribute approximately 1.5 times the amount of SRP to the water column of Upper Klamath Lake as diffusive SRP flux alone, measured in profiler deployments.
Sets of piezometers and temperature loggers were deployed in UKL to obtain estimates of vertical advective solute flux. The pressure transducer installations, within the piezometers, did not perform as designed, rendering the head gradient data unreliable. However, in terms of future research, this field work did demonstrate the feasibility of collecting vertical gradient data with piezometer deployments. Advective flux estimates herein are based solely on heat-flow modeling based on temperature data from four lake sites, without use of transducer data. Given the magnitudes (both positive or negative) of the heat-transfer fluxes for SRP, relative to diffusive-flux and macroinvertebrate efflux measurements (all positive but spanning the same orders of magnitude), further examination of solute advective flux is recommended as a potential transport process to integrate into existing water-quality (for example, Total Maximum Daily Load [TMDL]) models.
As a complement to the biogeochemical focus of this study, initial analyses of suspended-particle (floc) characteristics and settling velocities from the water column were derived near the surface and lakebed at two UKL sites. To better understand changing particle characteristics during the AFA-bloom period, suspended particles were examined in 2015 using a LabSFLOC (LF), which is a Laboratory Spectral Flocculation Characteristics version of an In-Situ Settling Velocity instrument (INSSEV-LF). Particle characteristics and settling velocities were analyzed from the water column near the surface (sample dp_10) and lakebed (sample dp_90) at two lake sites (open-lake site ML and littoral site LS01). The term “floc” refers herein to suspended particles that may aggregate or disaggregate to change in size, composition, and settling velocity.
During pre-bloom (May) conditions, where maximum suspended particulate matter concentration (SPMC) was 140 milligrams per liter (mg L−1) was now observed at site LS01 in close proximity to the bed, where Dmean peaked at 305 μm, and the corresponding Wsmean was 3.9 millimeters per second (mm s−1). The high near-bed SPMC (828 mg L−1) experienced during post-bloom October 2015 at LS01 formed a benthic nepheloid layer (BNL) above the lake’s bed. Numerous low density, fast settling macrofloc-sized organic aggregates (D >160 μm) were observed (some up to 1 mm in size) near bed at LS01 both during the bloom and post-bloom conditions; many of these flocs displayed fibrous organic structures. In terms of mass settling fluxes, the post-bloom BNL produced a total MSF of 4,139 milligrams per square meter per second (mg m−2 s−1) (92.1 percent of MSF credited to the macrofloc-sized organic aggregates/cyanobacterial colonies); that was nearly three times the corresponding near-bed settling flux observed during the July 2015 bloom and 360 times greater than the pre-bloom conditions from May 2015 (98.8 percent and 14 percent of MSF credited to the macrofloc-sized fractions for those respective months). Such changes in the near-bed settling flux demonstrate the highly significant seasonal effects that the AFA bloom has on the floc depositional fluxes in UKL and highlights the importance of seasonal monitoring of these conditions in order to correctly parameterize the wide range in depositional characteristics and floc properties measured throughout UKL.
Collectively, floc populations observed within UKL demonstrated a wide range in settling velocity (Ws) for a given particle size, D. Similarly, a given settling velocity was not associated with a specific particle size. This variability in particle characteristics and properties indicates the influence of varying floc effective density and its effect on mass and mass settling fluxes (MSF). The use of instruments, such as the INSSEV-LF, enables measuring the variability of settling velocity and its relation to particle density and size.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161175","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Kuwabara, J.S., Topping, B.R., Carter, J.L., Carlson, R.A., Parchaso, F., Fend, S.V., Stauffer-Olsen, N., Manning, A.J., Land, J.M., 2016, Benthic processes affecting contaminant transport in Upper Klamath Lake, Oregon (ver. 1.1, October 2016): U.S. Geological Survey Open-File Report 2016–1175, 103 p., https://dx.doi.org/10.3133/ofr20161175. ","productDescription":"Report: viii, 103 p.; 2 Tables","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":329222,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1175/coverthb.jpg"},{"id":329223,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1175"},{"id":329224,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175_table4.xlsx","text":"Table 4","size":"96 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1175 Table 4"},{"id":329425,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1175/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1175 Version History"},{"id":329424,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175_table19.xlsx","text":"Table 19","size":"18 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1175 Table 19"}],"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 -122.09793090820311,\n 42.231567925608616\n ],\n [\n -122.09793090820311,\n 42.70464124398721\n ],\n [\n -121.79992675781249,\n 42.70464124398721\n ],\n [\n -121.79992675781249,\n 42.231567925608616\n ],\n [\n -122.09793090820311,\n 42.231567925608616\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted September 30, 2016; Version 1.1: October 11, 2016","contact":"NRP staff
Water Resources National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
National Research Program
The generation of Everglades Depth Estimation Network (EDEN) daily water-level and water-depth maps is dependent on high quality real-time data from over 240 water-level stations. To increase the accuracy of the daily water-surface maps, the Automated Data Assurance and Management (ADAM) tool was created by the U.S. Geological Survey as part of Greater Everglades Priority Ecosystems Science. The ADAM tool is used to provide accurate quality-assurance review of the real-time data from the EDEN network and allows estimation or replacement of missing or erroneous data. This user’s manual describes how to install and operate the ADAM software. File structure and operation of the ADAM software is explained using examples.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161116","collaboration":"Greater Everglades Priority Ecosystems Science","usgsCitation":"Petkewich, M.D., Daamen, R.C., Roehl, E.A., and Conrads, P.A., 2016, User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data: U.S. Geological Survey Open-File Report 2016–1116, 28 p., https://dx.doi.org/10.3133/ofr20161116.","productDescription":"Report: vi, 28 p.; Companion File","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-076311","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329016,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165094","text":"Scientific Investigations Report 2016–5094","description":"Scientific Investigations Report 2016–5094","linkHelpText":"- Using Inferential Sensors for Quality Control of Everglades Depth Estimation Network Water-Level Data"},{"id":328990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1116/ofr20161116.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1116"},{"id":328989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1116/coverthb.jpg"},{"id":329002,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2016/1116/downloads","text":"Executable files for Automated Data Assurance and Management application","description":"OFR 2016-1116"}],"contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
Stephenson Center, Suite 129
Gracern Road
Columbia, SC 29210
https://www2.usgs.gov/water/southatlantic
The Bi-State distinct population segment (DPS) of greater sage-grouse (Centrocercus urophasianus) that occurs along the Nevada–California border was proposed for listing as threatened under the Endangered Species Act (ESA) by the U.S. Fish and Wildlife Service (FWS) in October 2013. However, in April 2015, the FWS determined that the Bi-State DPS no longer required protection under the ESA and withdrew the proposed rule to list the Bi-State DPS (U.S. Fish and Wildlife Service, 2015). The Bi-State DPS occupies portions of Alpine, Mono, and Inyo Counties in California, and Douglas, Esmeralda, Lyon, Carson City, and Mineral Counties in Nevada. Unique threats facing this population include geographic isolation, expansion of single-leaf pinyon (Pinus monophylla) and Utah juniper (Juniperus osteosperma), anthropogenic activities, and recent changes in predator communities. Estimating population vital rates, identifying seasonal habitat, quantifying threats, and identifying movement patterns are important first steps in developing effective sage-grouse management and conservation plans. During 2011–15, we radio- and Global Positioning System (GPS)-marked (2012–14 only) 44, 47, 17, 9, and 3 sage-grouse, respectively, for a total of 120, in the Pine Nut Mountains Population Management Unit (PMU). No change in lek attendance was detected at Mill Canyon (maximum=18 males) between 2011 and 2012; however, 1 male was observed in 2014 and no males were observed in 2013 and 2015. Males were observed near Bald Mountain in 2013, making it the first year this lek was observed to be active during the study period. Males were observed at a new site in the Buckskin Range in 2014 during trapping efforts and again observed during surveys in 2015. Findings indicate that pinyon-juniper is avoided by sage-grouse during every life stage. Nesting females selected increased sagebrush cover, sagebrush height, and understory horizontal cover, and brood-rearing females selected similar areas, but also preferred increased perennial forb abundance. Using maximum likelihood estimation, nest survival for the Pine Nut Mountains PMU during 2011–14 was 23.8 percent (95-percent confidence interval [CI]=0.3–40.6 percent) and appeared lower in comparison to the average 42 percent nest success for sage-grouse range-wide.
Brood survival for 50-day brood-rearing phase in the Pine Nut Mountains PMU during 2011–14 was 53.8 percent (95-percent CI=30.0–73.4 percent). Adult survival during 2011–15 was 67.4 percent (95-percent CI=56.1–76.5 percent). During 2011–14, 696 raptor/raven surveys were completed and results indicate a greater number of raven detections (n=464) in the Pine Nut Mountains PMU than at other study areas in Nevada. These data will be used to develop a predator index. We conducted a more minimal monitoring effort of sage-grouse populations during the 2015 field season, which included trapping efforts, general telemetry, brood monitoring, and GPS monitoring. Nest monitoring, microhabitat sampling, and raptor/raven surveys were not conducted in the 2015 season. Deployment of GPS transmitters has expanded our knowledge of movement corridors and fine-scale movement patterns by sage-grouse in the Pine Nut Mountains PMU. Movement corridors between seasonal habitats were identified with one sage-grouse traveling greater than 100 kilometers south to the Bodie Mountains in California for the winter season. The use of GPS technology to monitor movements in conjunction with intensive field efforts will be important in developing habitat models and maps for the Pine Nut Mountains PMU.
Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
Cyanobacterial harmful algal blooms (CyanoHABs) are increasingly a global concern because CyanoHABs pose a threat to human and aquatic ecosystem health and cause economic damages. Despite advances in scientific understanding of cyanobacteria and associated compounds, many unanswered questions remain about occurrence, environmental triggers for toxicity, and the ability to predict the timing, duration, and toxicity of CyanoHABs. U.S. Geological Survey (USGS) scientists are leading a diverse range of studies to address CyanoHAB issues in water bodies throughout the United States, using a combination of traditional methods and emerging technologies, and in collaboration with numerous partners. By providing practical applications of cutting edge CyanoHAB research, USGS studies have advanced scientific understanding, enabling the development of approaches to help protect ecological and human health.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
This is the eighth annual report highlighting U.S. Geological Survey (USGS) science and decision-support activities conducted for the Wyoming Landscape Conservation Initiative (WLCI). The activities address specific management needs identified by WLCI partner agencies. In 2015, USGS scientists continued 24 WLCI projects in 5 categories: (1) acquiring and analyzing resource-condition data to form a foundation for understanding and monitoring landscape conditions and projecting changes; (2) using new technologies to improve the scope and accuracy of landscape-scale monitoring and assessments, and applying them to monitor indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms that drive wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them to use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. Of the 24 projects, 21 were ongoing, including those that entered new phases or more in-depth lines of inquiry, 2 were new, and 1 was completed.
A highlight of 2015 was the WLCI science conference sponsored by the USGS, Bureau of Land Management, and National Park Service in coordination with the Wyoming chapter of The Wildlife Society. Of 260 participants, 41 were USGS professionals representing 13 USGS science centers, field offices, and Cooperative Wildlife Research Units. Major themes of USGS presentations included using new technologies for developing more efficient research protocols for modeling and monitoring natural resources, researching effects of energy development and other land uses on wildlife species and habitats of concern, and modeling species distributions, population trends, habitat use, and effects of land-use changes. There was also a special session on the effectiveness of Wyoming’s Sage-Grouse Executive Order. Combined, USGS presentations provided WLCI partners with a wealth of information and conservation tools.
The project completed in 2015 yielded an index of important agricultural lands in the WLCI region. The index improves upon existing measures of agricultural productivity and provides planners and managers with additional values to consider when making decisions about land use and conservation actions. The two new projects include an analysis of satellite imagery to quantify sagebrush productivity and mortality, and an evaluation of how groundwater and small streams interact in the upper Green River Basin. Initiated in response to concern among WLCI partners that large areas of sagebrush appear to have died recently, the sagebrush study objectives are to assess effects of these mortality events on overall sagebrush ecosystem productivity, evaluate the feasibility of using satellite imagery to detect patterns in sagebrush mortality over time, and identify factors driving these mortality events. The groundwater-streamflow interaction study is being conducted by hydrologists and fish ecologists to better understand how groundwater-streamflow interactions are affected by energy-resource development and how native fish communities are affected by these factors. Expected outcomes of both new projects will provide WLCI partners with additional information and decision-support tools.
Highlights of ongoing science foundation activities included simulations of nine alternative build-out scenarios for oil and gas development and an associated online fact sheet that explains how the simulations were conducted, with an applied example for the Atlantic Rim. Also completed in 2015 was an update of the USGS online inventory of mineral resources data, and publication of a USGS uranium resource survey for the WLCI region. Combined, the outcomes of this work provide decisionmakers and managers with important baseline information for existing and (or) future planning and monitoring efforts.
Terrestrial monitoring activities in 2015 emphasized the use of satellite data in combination with other technologies and field data to monitor, assess, and (or) forecast distribution patterns and (or) trends in sagebrush ecosystems, seasonal and migration stopover habitats used by mule deer and elk, and semi-arid aspen woodlands. Several professional papers detailing new monitoring models and results have been published. Combined, this and related work will help managers understand distribution patterns and trends among priority habitats, identify areas in need of restoration or conservation, and monitor the effectiveness of habitat-management actions.
Aquatic monitoring activities entailed not only the new groundwater-streamflow interaction study already mentioned, but also continued monitoring with streamgages paired with nearby wells in the Green River Basin to assess groundwater effects on streamflow and surface water temperatures. A map that portrays groundwater levels and general direction of flow in the Green River Basin was published as well. Overall, outcomes of USGS hydrological research and monitoring will inform WLCI partners about water resources in the WLCI region and help to explain fish-community responses to energy-resource development.
In 2015, USGS terrestrial wildlife ecologists continued to make crucial strides towards better understanding wildlife species responses to energy-resource development and other land-use changes. This body of research includes six taxa that require or heavily depend on sagebrush habitats: sage-grouse, pygmy rabbits, 3 songbird species, and mule deer. Native fish communities are also being evaluated. Approaches include modeling and mapping wildlife species distributions, abundances, and trends; using satellite and other technologies to track wildlife seasonal movements; conducting successive phases of research that build on the knowledge gained through prior phases to reveal the specific factors or thresholds that drive population- or individual-level responses to changes; and conducting population viability analyses. Additionally, wildlife habitat association models for pygmy rabbit and sage-grouse were combined with the oil and gas build-out scenarios to project species responses to alternative energy development scenarios. Outcomes of the wildlife response research are helping decisionmakers and managers identify specific factors that contribute to species population trends, the potential for spatial overlap between important wildlife habitats and proposed energy-resource development, locations of priority habitats for restoration and conservation, and more.
Data and WLCI Web site management highlights of 2015 included not only ongoing software upgrades, but also an update of the datasets displayed in two of the online products developed for the WLCI effort: (1) a map of 15,532 oil and natural gas well pad scars and other features associated with oil and gas extraction, and (2) a map of oil and gas, oil shale, uranium, and solar energy production, both for southwestern Wyoming. In addition, a map viewer was developed for a previously published map of coal and wind production in relation to sage-grouse distribution and core management areas in southwestern Wyoming. Combined, these maps place valuable decision-support tools in the hands of WLCI partners.
The USGS coordination efforts on behalf of the WLCI in 2015 included significant work on planning and executing the WLCI science conference. They also included ongoing efforts to support Local Project Development Teams and the WLCI Coordination Team (CT) with developing conservation priorities and strategies, identifying priority areas for future conservation actions, supporting the evaluation and ranking of conservation projects, and evaluating the ways in which proposed habitat projects relate to WLCI priorities. In 2015, the USGS also assisted the WLCI CT with updating the WLCI Conservation Action Plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161141","usgsCitation":"Bowen, Z.H., Aldridge, C.L., Anderson, P.J., Assal, T.J., Bartos, T.T., Chalfoun, A.D., Chong, G.W., Dematatis, M.K., Eddy-Miller, C.A., Garman, S.L., Germaine, S.S., Homer, C.G., Huber, C.C., Kauffman, M.J., Manier, D.J., Melcher, C.P., Miller, K.A., Norkin, Tamar, Sanders, L.E., Walters, A.W., Wilson, A.B., and Wyckoff, T.B., 2016, U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2015 annual report: U.S. Geological Survey Open-File Report 2016–1141, 59 p., https://dx.doi.org/10.3133/ofr20161141.","productDescription":"viii, 59 p.","onlineOnly":"Y","ipdsId":"IP-075182","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":329020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1141/coverthb.jpg"},{"id":329021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1141/ofr20161141.pdf","text":"Report","size":"36.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1141"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.07177734375,\n 43.40504748787035\n ],\n [\n -111.0498046875,\n 41\n ],\n [\n -105.99609375,\n 41\n ],\n [\n -105.99609375,\n 41.80407814427234\n ],\n [\n -105.35888671875,\n 41.82045509614034\n ],\n [\n -105.380859375,\n 42.47209690919285\n ],\n [\n -106.5673828125,\n 42.52069952914966\n ],\n [\n -107.20458984375,\n 42.48830197960227\n ],\n [\n -107.70996093749999,\n 42.53689200787315\n ],\n [\n -108.5009765625,\n 42.779275360241904\n ],\n [\n -108.80859375,\n 42.98857645832184\n ],\n [\n -109.22607421875,\n 43.229195113965005\n ],\n [\n -109.3798828125,\n 43.42100882994726\n ],\n [\n -109.79736328125,\n 43.5326204268101\n ],\n [\n -110.41259765625,\n 43.56447158721811\n ],\n [\n -111.07177734375,\n 43.40504748787035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
In 2009, the U.S. Department of the Interior (DOI) Secretary Ken Salazar established a network of eight regional Climate Science Centers (CSCs) that, along with the Landscape Conservation Cooperatives (LCCs), would help define and implement the Department's climate adaptation response. The Southeast Climate Science Center (SE CSC) was established at North Carolina State University (NCSU) in Raleigh, North Carolina, in 2010, under a 5-year cooperative agreement with the U.S. Geological Survey (USGS), to identify and address the regional challenges presented by climate change and variability in the Southeastern United States. All eight regional CSC hosts, including NCSU, were selected through a competitive process.
Since its opening, the focus of the SE CSC has been on working with partners in the identification and development of research-based information that can assist managers, including cultural and natural resource managers, in adapting to global change processes, such as climate and land use change, that operate at local to global scales and affect resources important to the DOI mission. The SE CSC was organized to accomplish three goals:
This report provides an overview of the SE CSC and the projects developed by the SE CSC since its inception. An important goal of this report is to provide a framework for understanding the evolution of the SE CSC science agenda, which has evolved over the first 5 years of the Center’s operation.
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Southeast Climate Science Center
North Carolina State University
Campus Box 7617
Raleigh, NC 27695-7617
https://www.doi.gov/csc/southeast/
https://globalchange.ncsu.edu/secsc/
Warm Mineral Springs, located in southern Sarasota County, Florida, is a warm, highly mineralized, inland spring. Since 1946, a bathing spa has been in operation at the spring, attracting vacationers and health enthusiasts. During the winter months, the warm water attracts manatees to the adjoining spring run and provides vital habitat for these mammals. Well-preserved late Pleistocene to early Holocene-age human and animal bones, artifacts, and plant remains have been found in and around the spring, and indicate the surrounding sinkhole formed more than 12,000 years ago. The spring is a multiuse resource of hydrologic importance, ecological and archeological significance, and economic value to the community.
The pool of Warm Mineral Springs has a circular shape that reflects its origin as a sinkhole. The pool measures about 240 feet in diameter at the surface and has a maximum depth of about 205 feet. The sinkhole developed in the sand, clay, and dolostone of the Arcadia Formation of the Miocene-age to Oligocene-age Hawthorn Group. Underlying the Hawthorn Group are Oligocene-age to Eocene-age limestones and dolostones, including the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. Mineralized groundwater, under artesian pressure in the underlying aquifers, fills the remnant sink, and the overflow discharges into Warm Mineral Springs Creek, to Salt Creek, and subsequently into the Myakka River. Aquifers described in the vicinity of Warm Mineral Springs include the surficial aquifer system, the intermediate aquifer system within the Hawthorn Group, and the Upper Floridan aquifer in the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. The Hawthorn Group acts as an upper confining unit of the Upper Floridan aquifer.
Groundwater flow paths are inferred from the configuration of the potentiometric surface of the Upper Floridan aquifer for September 2010. Groundwater flow models indicate the downward flow of water into the Upper Floridan aquifer in inland areas, and upward flow toward the surface in coastal areas, such as at Warm Mineral Springs. Warm Mineral Springs is located in a discharge area. Changes in water use in the region have affected the potentiometric surface of the Upper Floridan aquifer. Historical increase in groundwater withdrawals resulted in a 10- to 20-foot regional decline in the potentiometric surface of the Upper Floridan aquifer by May 1975 relative to predevelopment levels and remained at approximately that level in May 2007 in the area of Warm Mineral Springs. Discharge measurements at Warm Mineral Springs (1942–2014) decreased from about 11–12 cubic feet per second in the 1940s to about 6–9 cubic feet per second in the 1970s and remained at about that level for the remainder of the period of record. Similarity of changes in regional water use and discharge at Warm Mineral Springs indicates that basin-scale changes to the groundwater system have affected discharge at Warm Mineral Springs. Water temperature had no significant trend in temperature over the period of record, 1943–2015, and outliers were identified in the data that might indicate inconsistencies in measurement methods or locations.
Within the regional groundwater basin, Warm Mineral Springs is influenced by deep Upper Floridan aquifer flow paths that discharge toward the coast. Associated with these flow paths, the groundwater temperatures increase with depth and toward the coast. Multiple lines of evidence indicate that a source of warm groundwater to Warm Mineral Springs is likely the permeable zone of the Avon Park Formation within the Upper Floridan aquifer at a depth of about 1,400 to 1,600 feet, or deeper sources. The permeable zone contains saline groundwater with water temperatures of at least 95 degrees Fahrenheit.
The water quality of Warm Mineral Springs, when compared with other springs in Florida had the highest temperature and the greatest mineralized content. Warm Mineral Springs water is characterized by a slight-green color, with varying water clarity, low dissolved oxygen (indicative of deep groundwater), and a hydrogen sulfide odor. Water-quality samples detected ammonium-nitrogen and nitrates, but at low concentrations. The drinking water standard for nitrate adopted by the U.S. Environmental Protection Agency is 10 milligrams per liter, measured as nitrogen. Water samples collected at spring vents by divers on April 29, 2015, had concentrations of 0.9 milligram per liter nitrate-nitrogen at vent A and 0.04–0.05 milligram per liter at vents B, C, and D. Typically, the water clarity is highest in the morning (about 30 feet Secchi depth) and often decreases throughout the day.
Analysis of existing data provided some insight into the hydrologic processes affecting Warm Mineral Springs; however, data have been sparsely and discontinuously collected since the 1940s. Continuous monitoring of hydrologic characteristics such as discharge, water temperature, specific conductance, and water-quality indicators, such as nitrate and turbidity (water clarity), would be valuable for monitoring and development of models of spring discharge and water quality. In addition, water samples could be analyzed for isotopic tracers, such as strontium, and the results used to identify and quantify the sources of groundwater that discharge at Warm Mineral Springs. Groundwater flow/transport models could be used to evaluate the sensitivity of the quality and quantity of water flowing from Warm Mineral Springs to changes in climate, aquifer levels, and water use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161166","collaboration":"Prepared in cooperation with the City of North Port and Sarasota County ","usgsCitation":"Metz, P.A., 2016, Discharge, water temperature, and water quality of Warm Mineral Springs, Sarasota County, Florida: A retrospective analysis: U.S. Geological Survey Open-File Report 2016–1166, 31 p., https://dx.doi.org/10.3133/ofr20161166.","productDescription":"vi, 31 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-066216","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":328877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1166/coverthb2.jpg"},{"id":328878,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1166/ofr20161166.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1166"}],"country":"United States","state":"Florida","county":"Sarasota County","otherGeospatial":"Warm Mineral Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.26177334785461,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.058867814427533\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
(813) 498-5000
Or visit the Caribbean-Florida Water Science Center Web page at
http://fl.water.usgs.gov
This study provides an independent estimate of the areal and volumetric extent of groundwater contaminant plumes which are affected by waste disposal in the 100-K and 100-N Areas (study area) along the Columbia River Corridor of the Hanford Site. The Hanford Natural Resource Trustee Council requested that the U.S. Geological Survey perform this interpolation to assess the accuracy of delineations previously conducted by the U.S. Department of Energy and its contractors, in order to assure that the Natural Resource Damage Assessment could rely on these analyses. This study is based on previously existing chemical (or radionuclide) sampling and analysis data downloaded from publicly available Hanford Site Internet sources, geostatistically selected and interpreted as representative of current (from 2009 through part of 2012) but average conditions for groundwater contamination in the study area. The study is limited in scope to five contaminants—hexavalent chromium, tritium, nitrate, strontium-90, and carbon-14, all detected at concentrations greater than regulatory limits in the past.
All recent analytical concentrations (or activities) for each contaminant, adjusted for radioactive decay, non-detections, and co-located wells, were converted to log-normal distributions and these transformed values were averaged for each well location. The log-normally linearized well averages were spatially interpolated on a 50 × 50-meter (m) grid extending across the combined 100-N and 100-K Areas study area but limited to avoid unrepresentative extrapolation, using the minimum curvature geostatistical interpolation method provided by SURFER®data analysis software. Plume extents were interpreted by interpolating the log-normally transformed data, again using SURFER®, along lines of equal contaminant concentration at an appropriate established regulatory concentration . Total areas for each plume were calculated as an indicator of relative environmental damage. These plume extents are shown graphically and in tabular form for comparison to previous estimates. Plume data also were interpolated to a finer grid (10 × 10 m) for some processing, particularly to estimate volumes of contaminated groundwater. However, hydrogeologic transport modeling was not considered for the interpolation. The compilation of plume extents for each contaminant also allowed estimates of overlap of the plumes or areas with more than one contaminant above regulatory standards.
A mapping of saturated aquifer thickness also was derived across the 100-K and 100–N study area, based on the vertical difference between the groundwater level (water table) at the top and the altitude of the top of the Ringold Upper Mud geologic unit, considered the bottom of the uppermost unconfined aquifer. Saturated thickness was calculated for each cell in the finer (10 × 10 m) grid. The summation of the cells’ saturated thickness values within each polygon of plume regulatory exceedance provided an estimate of the total volume of contaminated aquifer, and the results also were checked using a SURFER® volumetric integration procedure. The total volume of contaminated groundwater in each plume was derived by multiplying the aquifer saturated thickness volume by a locally representative value of porosity (0.3).
Estimates of the uncertainty of the plume delineation also are presented. “Upper limit” plume delineations were calculated for each contaminant using the same procedure as the “average” plume extent except with values at each well that are set at a 95-percent upper confidence limit around the log-normally transformed mean concentrations, based on the standard error for the distribution of the mean value in that well; “lower limit” plumes are calculated at a 5-percent confidence limit around the geometric mean. These upper- and lower-limit estimates are considered unrealistic because the statistics were increased or decreased at each well simultaneously and were not adjusted for correlation among the well distributions (i.e., it is not realistic that all wells would be high simultaneously). Sources of the variability in the distributions used in the upper- and lower-extent maps include time varying concentrations and analytical errors.
The plume delineations developed in this study are similar to the previous plume descriptions developed by U.S. Department of Energy and its contractors. The differences are primarily due to data selection and interpolation methodology. The differences in delineated plumes are not sufficient to result in the Hanford Natural Resource Trustee Council adjusting its understandings of contaminant impact or remediation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161161","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Hanford Natural Resource Trustee Council","usgsCitation":"Johnson, K.H., 2016, Groundwater contaminant plume maps and volumes, 100-K and 100–N Areas, Hanford Site, Washington: U.S. Geological Survey Open-File Report 2016–1161, 64 p., https://dx.doi.org/10.3133/ofr20161161.","productDescription":"Report: vi, 64 p.; Appendix A","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-071546","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1161/coverthb.jpg"},{"id":329029,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1161/ofr20161161.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1161"},{"id":329030,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1161/ofr20161161_appendixa.xlsx","text":"Appendix A","size":"2.1 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1161 Appendix A"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.83886718750001,\n 46.25204849722291\n ],\n [\n -119.83886718750001,\n 46.82637528602131\n ],\n [\n -119.19616699218749,\n 46.82637528602131\n ],\n [\n -119.19616699218749,\n 46.25204849722291\n ],\n [\n -119.83886718750001,\n 46.25204849722291\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Scientists and technical support staff from the U.S. Geological Survey measured suspended-sediment concentrations, currents, pressure, and water temperature in two tidal creeks, Reedy Creek and Dinner Creek, in Barnegat Bay, New Jersey, from August 11, 2014, to July 10, 2015 as part of the Estuarine Physical Response to Storms project (GS2–2D). The oceanographic and water-quality data quantify suspended-sediment transport in Reedy Creek and Dinner Creek, which are part of a tidal marsh wetland complex in the Edwin B. Forsythe National Wildlife Refuge. All deployed instruments were removed between January 7, 2015, and April 14, 2015, to avoid damage by ice.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161149","usgsCitation":"Suttles, S.E., Ganju, N.K, Montgomery, E.T., Dickhudt, P.J., Borden, Jonathan., Brosnahan, S.M., and Martini, M.A., 2016, Summary of oceanographic and water-quality measurements in Barnegat Bay, New Jersey, 2014–15: U.S. Geological Survey Open-File Report 2016–1149, 22 p., https://dx.doi.org/10.3133/ofr20161149.","productDescription":"Report: vii, 22 p.; Appendix: 1-2","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076598","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328800,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1149/appendix/downloads/adcptransects","text":"Appendix 2 ","description":"OFR 2016-1149","linkHelpText":"- Acoustic Doppler Current Profiler Transect Data, August 2014 and May 2015 for Reedy and Dinner Creeks"},{"id":328792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1149/coverthb.jpg"},{"id":328793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1149/ofr20161149.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1149"},{"id":328794,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1149/appendix/downloads/watersamples/ofr20161149_appendix1.zip","text":"Appendix 1","size":"40.4 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1149","linkHelpText":"- Water Sample Data, August 2014 to January 2015 and April to July 2015"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.55184936523438,\n 39.36190883564925\n ],\n [\n -74.55184936523438,\n 40.08752795413118\n ],\n [\n -74.02450561523438,\n 40.08752795413118\n ],\n [\n -74.02450561523438,\n 39.36190883564925\n ],\n [\n -74.55184936523438,\n 39.36190883564925\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
http://woodshole.er.usgs.gov/
MODPATH is a particle-tracking post-processing program designed to work with MODFLOW, the U.S. Geological Survey (USGS) finite-difference groundwater flow model. MODPATH version 7 is the fourth major release since its original publication. Previous versions were documented in USGS Open-File Reports 89–381 and 94–464 and in USGS Techniques and Methods 6–A41.
MODPATH version 7 works with MODFLOW-2005 and MODFLOW–USG. Support for unstructured grids in MODFLOW–USG is limited to smoothed, rectangular-based quadtree and quadpatch grids.
A software distribution package containing the computer program and supporting documentation, such as input instructions, output file descriptions, and example problems, is available from the USGS over the Internet (http://water.usgs.gov/ogw/modpath/).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161086","usgsCitation":"Pollock, D.W., 2016, User guide for MODPATH Version 7—A particle-tracking model for MODFLOW: U.S. Geological Survey Open-File Report 2016–1086, 35 p., https://dx.doi.org/10.3133/ofr20161086. ","productDescription":"v, 35 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073899","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":325509,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr94464","text":"Open-File Report 1994-464","description":"ofr 2016-1086","linkHelpText":"- User's guide for MODPATH/MODPATH-PLOT, Version 3; a particle tracking post-processing package for MODFLOW, the U.S. Geological Survey finite-difference ground-water flow model"},{"id":325510,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A41","text":"Techniques and Methods 6-A41","linkFileType":{"id":5,"text":"html"},"description":"ofr 2016-1086","linkHelpText":"- User guide for MODPATH Version 6 - A particle-tracking model for MODFLOW"},{"id":325508,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr89381","text":"Open-File Report 1989-381","description":"ofr 2016-1086","linkHelpText":"- Documentation of computer programs to compute and display pathlines using results from the U.S. Geological Survey modular three-dimensional finite-difference ground-water flow model"},{"id":325506,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1086/coverthb.jpg"},{"id":325507,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1086/ofr20161086.pdf","text":"Report","size":"3.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"ofr 2016-1086"},{"id":328711,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://water.usgs.gov/ogw/modpath/","text":"MODPATH Version 7","description":"ofr 2016-1086","linkHelpText":"- MODPATH: A Particle-Tracking Model for MODFLOW"}],"contact":"Office of Groundwater
U.S. Geological Survey
Mail Stop 411
12201 Sunrise Valley Drive
Reston, VA 20192
http://water.usgs.gov/ogw/
Melting occurred during stick-slip faulting of granite blocks sheared at room-dry, room-temperature conditions in a triaxial apparatus at 200–400 megapascals (MPa) confining pressure. Petrographic examinations of melt textures focused largely on the 400-MPa run products. This report presents an overview of the petrographic data collected on those samples, followed by brief descriptions of annotated versions of all the images.
Scanning electron microscope (SEM) images of the starting materials and the three examined 400-MPa samples are presented in this report. Secondary-electron (SE) and backscattered-electron (BSE) imaging techniques were used on different samples. The SE images look down on the sawcut surfaces, yielding topographic and three-dimensional textural information. The BSE imaging was done on samples cut to provide cross-sectional views of the glass-filled shear band (or zone) that developed along the sawcut. Brightness in the BSE images increases with increasing mean atomic number of the material. Additional chemical information about the quenched melt and adjoining minerals was obtained using the energy dispersive system of the SEM during BSE examinations. However, the very narrow shear-band thicknesses and common occurrence of very fine lamellar compositional layering limited the usefulness of this technique for estimating melt chemistry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161059","usgsCitation":"Moore, D.E., Lockner, D.A., Kilgore, B.D., and Beeler, N.M., 2016, Gallery of melt textures developed in Westerly Granite during high-pressure triaxial friction experiments: U.S. Geological Survey Open-File Report 2016–1059, 75 p., https://dx.doi.org/10.3133/ofr20161059.","productDescription":"iv, 75 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-073957","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":328890,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1059/ofr20161059.pdf","text":"Report","size":"81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1059"},{"id":328889,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1059/coverthb.jpg"}],"contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/