Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth; (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality, particularly in Upper Klamath Lake. The U.S. Geological Survey monitoring program, which began in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Juvenile sucker year-class strength and apparent survival were low in 2018 in Upper Klamath Lake. Most juvenile sucker mortality occurs within the first year of life. The Upper Klamath Lake year-class strength indices for Lost River and shortnose suckers in 2018 were the lowest they had been since the start of monitoring in 2015. The annual catch rates of shortnose sucker remained consistently low, whereas Lost River sucker catch rates varied. The capture of only four age-1 and older suckers from Upper Klamath Lake during the 2018 sampling season indicated low annual survival of the 2017 cohort.
Annual production indices of juvenile suckers in Clear Lake are highly variable and potentially affected by seasonal connections to spawning habitat in Willow Creek. A total of seven age-0 shortnose or Klamath largescale suckers (Catostomus snyderi) were captured from Clear Lake in 2018, which was a relatively wet year, indicating that a small cohort was formed or that there was a delay in the recruitment of age-0 suckers. The 2018 sampling continued to detect recruitment of juveniles from the 2015 cohort to the lake. Given the dysconnectivity between Willow Creek and Clear Lake during the 2015 spawning season, the continued recruitment of young fish of this cohort to the lake may be attributed to reproduction by resident suckers in Willow Creek. Suckers younger than age-3 in Clear Lake could be identified as either shortnose or Klamath largescale suckers. A stream resident life history, if it were occurring, is consistent with these fish being Klamath largescale suckers. Survival of all distinguishable taxa of juvenile suckers is much higher in Clear Lake than in Upper Klamath Lake, with non-trivial numbers of suckers surviving to join spawning aggregations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bart, R.J., Burdick, S.M., Hoy, M.S., and Ostberg, C.O., 2020, Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report: U.S. Geological Survey Open-File Report 2020–1064, 33 p., https://doi.org/10.3133/ofr20201064.","productDescription":"vi, 33 p.","onlineOnly":"Y","ipdsId":"IP-116680","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":375530,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1064/ofr20201064.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1064"},{"id":375529,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1064/coverthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Clear Lake Reservoir, 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 -121.25747680664064,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.789744876718984\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1075439453125,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.224449701009725\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Groundwater-level conditions, generalized groundwater potentiometric surfaces, and generalized flow directions at the decommissioned Naval Air Warfare Center in West Trenton, New Jersey, were evaluated for calendar year 2018. Groundwater levels measured continuously in five on-site wells and one nearby off-site well were plotted as hydrographs for January 1, 2018, through December 31, 2018. Groundwater levels measured in 110 wells on June 18, 2018, were contoured as generalized potentiometric surfaces on maps and sections. Generalized groundwater-flow directions inferred from the June 2018 data are shown in the maps and sections.
Groundwater levels in six monitoring wells fluctuated in response to seasonal changes, precipitation, and pumping from “pump-and-treat” (P&T) wells. Record high precipitation totals in November, combined with a shutdown of three P&T wells in November, resulted in annual high water levels in late November for five of the six wells monitored. Annual high groundwater levels that occur during the fall are uncharacteristic of the typical timing of annual high water levels, which usually occur in the spring following low evapotranspiration during the winter months, compared to annual low water levels, which usually occur in fall because of high evapotranspiration during the summer months. The annual high water levels occurred following a 3-day precipitation event totaling 3.50 inches from November 24-26, which also caused the largest 1-day water-level increase for five of the six wells in 2018.
The groundwater-level contour maps and sections include generalized flow directions. Given the heterogeneity of the site’s fractured rock aquifers, contours and associated groundwater-flow directions shown on the maps and sections should be considered as broad conceptualizations. A nearly vertical fault striking southwest to northeast separates the northwestern part of the site underlain by the Lockatong Formation from the southeastern part, which is underlain by the Stockton Formation. In the Lockatong Formation, general groundwater-flow directions were toward P&T wells. The P&T wells limited the flow of groundwater in the Lockatong Formation from the site into the adjacent areas and contained most groundwater contamination within the site. A groundwater divide bisected the site; groundwater in the western part generally flowed to P&T wells 8BR, 15BR, 20BR, 29BR, 56BR, 91BR, and BRP-2, and groundwater in the eastern part generally flowed to P&T well 48BR. A groundwater divide also was present in the Stockton Formation. Groundwater west of the divide in the Stockton Formation generally flowed toward P&T well 22BR, and groundwater east of the divide generally flowed south and southeast, away from the site. Saprolite and fill from land surface to depths of 25 feet below land surface exhibit similar properties to those of porous media, and water levels in surficial wells were contoured using a porous media aquifer approach. Water levels in these surficial wells indicate that groundwater in the saprolite and fill flowed predominantly toward Gold Run and, to a lesser extent, the West Ditch spring that drains to Gold Run. In addition, some shallow groundwater was captured by the cone of depression in the fractured bedrock and was attributed to P&T well 48BR.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201016","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., and Lacombe, P.J., 2020, Groundwater levels and generalized potentiometric surfaces, former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2020–1016, 28 p., https://doi.org/10.3133/ofr20201016.","productDescription":"Report: v, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104199","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1016/ofr20201016.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1016"},{"id":375285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1016/coverthb.jpg"},{"id":375288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98N1GWV","text":"USGS data release","linkHelpText":"Reported groundwater levels and groundwater pump-and-treat withdrawals, former Naval Air Warfare Center, West Trenton, New Jersey, 2018"}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"Former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81613278388977,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.26694411855267\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Native steelhead (anadromous form of rainbow trout [Oncorhynchus mykiss]) and bridgelip sucker (Catostomus columbianus) were historically used by the Kah-miltpah (Rock Creek) Band for sustenance, trade, and traditional practices in Rock Creek, a tributary to the Columbia River in southeastern Washington State. Rock Creek flows south to the Columbia River at river kilometer (rkm) 368 and is an intermittent stream of great significance to the Yakama Nation and to the Kah-miltpah Band in particular. Concern over declines in the abundance of these fish in Rock Creek prompted a research and monitoring program to better understand habitat conditions, population status, and limiting factors. In addition to steelhead and bridgelip sucker, coho salmon (Oncorhynchus kisutch) and resident rainbow trout are also present and monitored. Rainbow trout and steelhead will be collectively referred to as O. mykiss. Streamflow is a limiting habitat factor in this system, but steelhead and coho salmon still successfully return to spawn, rear, outmigrate, and survive over summer in many of the isolated pools that provide important refuge for juvenile rearing.
We completed a habitat survey during autumn 2018 to assess the perennial pools during low-flow conditions. In Rock Creek, the overall percentage of habitat recorded as dry was 41, non-pool wet was 42, and pool was 17. The number of pools (n=93) recorded was less than during previous years’ survey efforts (2015–17). The percentage of non-pool wet habitat was generally higher in 2018 than in previous years. This is a likely result of habitat reaches, which in the past, were considered pools but have become shallower and smaller and are now categorized as non-pool wet habitat. However, the fewer habitat reaches categorized as pools in 2018 now have an average length, area, and depth that are generally greater than in past years. In Walaluuks Creek, the percentage of habitat recorded as dry was 53, non-pool wet was 40, and pool was 7. The percentage of pool habitat was the lowest of all years surveyed since 2015.
Fish sampling occurred during autumn after habitat surveys were completed from October 1 to November 9. Fish species distribution, relative abundance, length-frequency distribution, and pool fish density were determined using backpack electrofishing in stratified, systematically selected pools. During fish sampling, 855 O. mykiss were handled and 662 were tagged with a passive integrated transponder (PIT) tag, and 718 coho salmon were handled and 567 were PIT tagged. A total of 536 bridgelip suckers and largescale suckers (Catostomus macrocheilus [n=6]) were handled and 294 were PIT tagged. In Rock Creek, pool abundance estimates were calculated for six pools for both O. mykiss age classes (age 0 and age 1 or older [age 1+]) and one additional pool for age 1+. For pools where age-0 O. mykiss were present, the average pool population abundance was 0.144 (n=6; range: 0.052–0.208) fish per square meter. For age-1+ O. mykiss, the average pool population abundance was 0.045 (n=7; range: 0.002–0.179) fish per square meter. For age-0 O. mykiss in Walaluuks Creek, the average pool abundance was 0.207 fish per square meter (n=7; range: 0.038–0.416), and for age-1+ fish, the average pool abundance was 0.382 fish per square meter (n=6; range: 0.009–0.761). In Rock Creek, coho salmon were more abundant than O. mykiss in pools except for three pools upstream from rkm 20. The average pool abundance for coho salmon was 0.256 fish per square meter (n=8; range: 0.019–0.756) in Rock Creek pools. In Walaluuks Creek, coho salmon were captured in four pools and were not captured in the upstream pools sampled. The average pool abundance for coho salmon in the four lower pools was 0.488 fish per square meter (n=4; range: 0.417–0.548). Bridgelip suckers were captured in all pools in Rock Creek except the pool sampled at rkm 21.8. The average pool abundance for bridgelip suckers was 0.552 fish per square meter (n=7; range: 0.015–1.554) in Rock Creek. Bridgelip suckers were captured in three downstream pools in Walaluuks Creek, and the average abundance was 0.044 fish per square meter (n=3; range: 0.024–0.085).
Overwinter and reach survival probabilities were estimated for O. mykiss and coho salmon using a Cormack-Jolly-Seber modeling approach. The best fit survival model for the O. mykiss and coho salmon was a reach only model. The upstream reach includes overwinter survival probability because fish are tagged and released in autumn and primarily migrate the following spring. During 2018, coho salmon (0.568, standard error [SE]=0.027) had a significantly higher probability of overwinter survival than O. mykiss (0.276, SE=0.019). The reach survival probability was higher for O. mykiss than coho salmon in the downstream migratory reaches. Survival was not modeled for bridgelip suckers. For bridgelip suckers, 147 were detected of 294, that were PIT tagged and released in the Rock Creek subbasin (50.0 percent).
Information provided in this report increases our understanding of the status and trends of these populations. It further documents how intermittent streams can support salmonid populations. It also provides insight into potential management and restoration actions that could be beneficial and timing and allocation of resources. Ongoing monitoring work of this population will inform progress towards Rock Creek species recovery goals and contribution to recovery goals for the steelhead Middle Columbia River Distinct Population Segment.
Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Cape May and Supawna Meadows National Wildlife Refuges in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 13 marsh management units within the refuges and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $785,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $785,000 included applying sediment to the marsh surface (thin layer deposition) in seven marsh management units, controlling the invasive reed Phragmites australis in four marsh management units, remediating hydrologic alterations in two marsh management units, and planting native vegetation in one marsh management unit. The management benefits were derived from expected improvements in the capacity for marsh elevation to keep pace with sea-level rise, increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and increased cover of native vegetation. The prototype presented here provides a framework for decision making at the Cape May and Supawna Meadows National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201055","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Braudis, B., and Hanlon, H., 2020, Optimization of tidal marsh management at the Cape May and Supawna Meadows National Wildlife Refuges, New Jersey, through use of structured decision making: U.S. Geological Survey Open-File Report 2020–1055, 41 p., https://doi.org/10.3133/ofr20201055.","productDescription":"vii, 41 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101980","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":375304,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1055/ofr20201055.pdf","text":"Report","size":"3.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1055"},{"id":375303,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1055/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Cape May, Supawna Meadows National Wildlife Refuges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.377197265625,\n 39.690280594818034\n ],\n [\n -75.1025390625,\n 39.95185892663005\n ],\n [\n -75.41015624999999,\n 39.9602803542957\n ],\n [\n -75.618896484375,\n 39.58029027440865\n ],\n [\n -75.3662109375,\n 39.2407625100131\n ],\n [\n -75.0146484375,\n 38.788345355085625\n ],\n [\n -74.42138671875,\n 39.07037913108751\n ],\n [\n -74.410400390625,\n 39.605688178320804\n ],\n [\n -74.77294921875,\n 39.36827914916014\n ],\n [\n -75.16845703124999,\n 39.40224434029275\n ],\n [\n -75.377197265625,\n 39.690280594818034\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708–4039
This report provides an overview of model-based climate science in a risk management context. In addition, it summarizes how the U.S. Geological Survey (USGS) will continue to follow best scientific practices and when and how the results of this research will be delivered to the U.S. Department of the Interior (DOI) and other stakeholders to inform policymaking. Climate change is a risk management challenge for society because of the uncertain consequences for natural and human systems across decades to centuries. Climate-related science activities within the USGS emphasize research on adaptation to climate change. This research helps inform adaptive management processes and planning activities within other DOI bureaus and by DOI stakeholders.
Global climate models are sophisticated numerical representations of the Earth’s climate system. Research groups from around the world regularly participate in a coordinated effort to produce a suite of climate models. This global effort provides a test bed to assess model performance and analyze projections of future change under various prescribed climate scenarios. These climate scenarios describe a plausible future outcome associated with a specific set of societal actions. Because scenarios are developed in a risk-based framework with a high degree of uncertainty about future societal developments, they are usually not assigned a formal likelihood of occurrence. Examining a range of projected climate outcomes based on multiple scenarios is a recommended best practice because it allows decision makers to better consider both short- and long-term risks and opportunities.
As part of its routine science practices, the USGS regularly reviews the state of knowledge of climate science, develops and maintains best practices in using global climate models to project climate change impacts, and provides data and interpretations of potential impacts to the DOI and other stakeholders. Management and policy decisions within the DOI will reflect different tolerances for risk, which has implications for what type of information should be considered and how that information should be used. It is suggested that a followup document be produced that would describe in more detail how these management decisions with differing risk tolerances can be made effectively and consistently in light of an uncertain future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201058","usgsCitation":"Terando, A., Reidmiller, D., Hostetler, S.W., Littell, J.S., Beard, T.D., Jr., Weiskopf, S.R., Belnap, J., and Plumlee, G.S., 2020, Using information from global climate models to inform policymaking—The role of the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2020–1058, 25 p., https://doi.org/10.3133/ofr20201058.","productDescription":"v, 25 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118715","costCenters":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"links":[{"id":375144,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1058/coverthb.jpg"},{"id":375198,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1058/ofr20201058.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1058"}],"contact":"National Climate Adaptation Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Mail Stop 516
Reston, VA 20192
https://www.usgs.gov/land-resources/
climate-adaptation-science-centers
The novel β-coronavirus, SARS-CoV-2, may pose a threat to North American bat populations if bats are exposed to the virus through interaction with humans, if the virus can subsequently infect bats and be transmitted among them, and if the virus causes morbidity or mortality in bats. Further, if SARS-CoV-2 became established in bat populations, it could possibly serve as a source for new infection in humans, domesticated animals, or other wild animals. Wildlife management agencies in the United States are concerned about these potential risks and have begun to issue guidance regarding work that brings humans into contact with bats, but decision making is difficult because of the high degree of uncertainty about many of the relevant processes that could lead to virus transmission and establishment. The risk assessment described in this report was undertaken to provide management agencies with an understanding of the likelihood that the various steps in the causal pathways would lead to SARS-CoV-2 infection of North American bats from people. This assessment focused on the active season for bats in the temperate zone of North America (April 15 through November 15), and used Myotis lucifugus (little brown bats) as a surrogate species. At the time of this work (April 2020), no empirical data about the effects of SARS-CoV-2 on North American bats were available, so a formal process of expert judgment was used to elicit estimates of the underlying parameters. Twelve experts in bat ecology, epidemiology, virology, and wildlife disease from the United States, United Kingdom, and Australia participated in the elicitation. A Monte Carlo simulation model was used to integrate the parameter estimates elicited from the experts and to predict the likelihood of exposure and infection in bats through a series of transmission pathways, with particular attention to capturing uncertainty in the predictions.
Given the current state of knowledge as expressed by the expert panel, the results of this assessment indicate that there is a non-negligible risk of transmission of SARS-CoV-2 from humans to bats. For example, if a research scientist were shedding SARS-CoV-2 virus while handling bats under the field protocols used in North America prior to the COVID-19 pandemic, the risk model indicates that 50 percent (uncertainty, 15–84 percent) of those bats could be exposed to virus, and 17 percent (uncertainty, 3–51 percent) could become infected. Use of personal protective equipment, especially a respirator, is expected to reduce the exposure risk. The expert panel estimated that exposure risk from research scientists could be reduced 94–96 percent (uncertainty, 86–99 percent) through proper use of appropriate N95 respirators (a type of mechanical filter worn over the nose and mouth), dedicated clothing (such as Tyvek coveralls), and gloves. Should any North American bats become infected with SARS-CoV-2, the expert panel estimated that there is an approximately 33-percent chance the virus could spread within a bat population.
This study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, identified several critical uncertainties that could affect the estimate of risks associated with SARS-CoV-2 entering bat populations—notably, the underlying probability that a human would be shedding virus while working with bats, the likelihood of the virus replicating in bat tissue, and the likelihood of transmission of the virus within bat populations. Ongoing empirical work during May–October 2020 may shed light on these issues. Follow-up work is needed to better understand the probability of transmission of SARS-CoV-2 to bats from the general public; the manner in which the probabilities of exposure, infection, and transmission would differ during hibernation compared to the breeding season; and the likelihood of important effects, like morbidity and mortality in bats, the possibility of zoonosis from a North American bat reservoir, and effects of and on other wildlife.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201060","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Runge, M.C., Grant, E.H.C., Coleman, J.T.H., Reichard, J.D., Gibbs, S.E.J., Cryan, P.M., Olival, K.J., Walsh, D.P., Blehert, D.S., Hopkins, M.C., and Sleeman, J.M., 2020, Assessing the risks posed by SARS-CoV-2 in and via North American bats—Decision framing and rapid risk assessment: U.S. Geological Survey Open-File Report 2020–1060, 43 p., https://doi.org/10.3133/ofr20201060.","productDescription":"vi, 43 p.","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118911","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":375248,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1060/ofr20201060.pdf","text":"Report","size":"4.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1060"},{"id":375199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1060/coverthb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.1640625,\n 13.581920900545844\n ],\n [\n -84.72656249999999,\n 19.973348786110602\n ],\n [\n -75.9375,\n 27.371767300523047\n ],\n [\n -55.8984375,\n 45.336701909968134\n ],\n [\n -48.8671875,\n 45.336701909968134\n ],\n [\n -65.0390625,\n 61.77312286453146\n ],\n [\n -58.71093750000001,\n 67.47492238478702\n ],\n [\n -84.375,\n 74.1160468394894\n ],\n [\n -125.5078125,\n 75.32002523220804\n ],\n [\n -135.703125,\n 70.95969716686398\n ],\n [\n -156.4453125,\n 71.52490903732816\n ],\n [\n -167.34375,\n 68.9110048456202\n ],\n [\n -168.046875,\n 61.60639637138628\n ],\n [\n -166.2890625,\n 53.12040528310657\n ],\n [\n -146.95312499999997,\n 57.326521225217064\n ],\n [\n -138.515625,\n 56.559482483762245\n ],\n [\n -131.484375,\n 48.922499263758255\n ],\n [\n -127.96875,\n 40.17887331434696\n ],\n [\n -116.01562499999999,\n 24.84656534821976\n ],\n [\n -98.7890625,\n 13.239945499286312\n ],\n [\n -93.1640625,\n 13.581920900545844\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
The Kansas River provides drinking water for multiple cities in northeastern Kansas and is used for recreational purposes. Thus, improving the scientific knowledge of streamflow velocities and traveltimes will greatly aid in water-treatment plans and response to critical events and threats to water supplies. Dye-tracer studies are usually done to enhance knowledge of transport characteristics, which include streamflow velocities, traveltimes, and dispersion rates, within a river system. To achieve this in the Kansas River, rhodamine water-tracing dye is planned to be injected into the Kansas River during three different flow ranges at three locations: Manhattan, Topeka, and Eudora. The primary purpose of doing a dye-tracer study in the Kansas River is to calibrate a time-of-travel model used for estimating streamflow velocities and traveltimes, which can be used by the public as well as drinking water suppliers to protect water resources and public-water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201039","collaboration":"Prepared in cooperation with the Kansas Water Office, Kansas Department of Health and Environment, The Nature Conservancy, City of Topeka, Johnson County WaterOne, City of Manhattan, and City of Olathe","usgsCitation":"Davis, C.A., Lukasz, B.S., and May, M.R., 2020, Dye-tracing plan for verifying the Kansas River time-of-travel model: U.S. Geological Survey Open-File Report 2020–1039, 10 p., https://doi.org/10.3133/ofr20201039.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-107718","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":375197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1039/ofr20201039.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1039"},{"id":375196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1039/coverthb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.1630859375,\n 38.53097889440024\n ],\n [\n -94.4384765625,\n 38.53097889440024\n ],\n [\n -94.4384765625,\n 39.926588421909436\n ],\n [\n -97.1630859375,\n 39.926588421909436\n ],\n [\n -97.1630859375,\n 38.53097889440024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The U.S. Atomic Energy Commission established the National Uranium Resources Evaluation (NURE) program in 1973 to identify uranium resources throughout the United States. Part of this program focused on the collection of stream-sediment samples and subsequent geochemical analyses of these samples for uranium, in addition to 47 other elements. As part of the original program, 18,424 stream-sediment samples were collected from Wyoming and analyzed. All original samples are stored at the U.S. Geological Survey’s (USGS) National Geochemical Sample Archive (NGSA). The Wyoming State Geological Survey (WSGS) recently selected 159 of the original Wyoming NURE stream samples to be reanalyzed using modern and standardized analytical equipment. The raw results of the reanalysis are provided with this report.
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lucke, David W.","contributorId":225587,"corporation":false,"usgs":false,"family":"Lucke","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":41168,"text":"Wyoming State Geological Survey (WSGS)","active":true,"usgs":false}],"preferred":false,"id":791760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Steven M. 0000-0003-3591-5377 smsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-3591-5377","contributorId":1460,"corporation":false,"usgs":true,"family":"Smith","given":"Steven","email":"smsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Azain, Jaime S. 0000-0002-8256-7494","orcid":"https://orcid.org/0000-0002-8256-7494","contributorId":201966,"corporation":false,"usgs":true,"family":"Azain","given":"Jaime S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingraham, Andrew David 0000-0001-7347-6171","orcid":"https://orcid.org/0000-0001-7347-6171","contributorId":225588,"corporation":false,"usgs":true,"family":"Ingraham","given":"Andrew","email":"","middleInitial":"David","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":791763,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210279,"text":"ofr20191134 - 2020 - Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water","interactions":[],"lastModifiedDate":"2020-05-29T15:12:09.612507","indexId":"ofr20191134","displayToPublicDate":"2020-05-29T09:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1134","displayTitle":"Regional Hydrostratigraphic Framework of Joint Base McGuire-Dix-Lakehurst and Vicinity, New Jersey, in the Context of Perfluoroalkyl Substances Contamination of Groundwater and Surface Water","title":"Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water","docAbstract":"A study was conducted by the U.S. Geological Survey, in cooperation with the U.S. Air Force, to describe the regional hydrostratigraphy of shallow aquifers and confining units underlying Joint Base McGuire-Dix-Lakehurst (JBMDL) and vicinity, New Jersey, in the context of contamination of groundwater and surface water by per- and polyfluoroalkyl substances (PFAS) potentially originating from JBMDL sources. The aquifers studied are two that crop out within JBMDL boundaries—the Kirkwood-Cohansey aquifer system and the Vincentown aquifer—and another aquifer near JBMDL that does not crop out at land surface—the Piney Point aquifer. The unconfined portion of the Vincentown aquifer and portions of the Kirkwood-Cohansey aquifer system that overlie the unconfined portion of the Vincentown aquifer are consolidated into, and described as, a single, separate unconfined aquifer system. Regionally extensive clay subunits that potentially create semiconfined hydrologic conditions within the mostly unconfined Kirkwood-Cohansey aquifer system also are identified. Two confining units were studied—the Manasquan-Shark River confining unit underlying the Kirkwood-Cohansey aquifer system, which includes the basal confining sediment in the Kirkwood Formation, and the Navesink-Hornerstown confining unit underlying the Vincentown aquifer. The hydrostratigraphic units are defined using available borehole geophysical logs, lithologic logs, and (or) drillers’ logs from 131 wells and are presented in a series of 8 aquifer structure maps and 12 cross sections. The framework positions JBMDL into a regional hydrostratigraphic structure for which higher-resolution delineation of the shallow aquifers can be constructed to determine potential pathways of PFAS contamination in groundwater to off-site drinking water wells in areas adjacent to JBMDL.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191134","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Fiore, A.R., 2020, Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water: U.S. Geological Survey Open-File Report 2019–1134, 42 p., https://doi.org/10.3133/ofr20191134.","productDescription":"Report: viii, 42 p.; 12 Plates: 30 x 24 inches; 2 Tables","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107327","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375120,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate06.pdf","text":"Plate 6","size":"1.87 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of the confined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375125,"rank":13,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate11.pdf","text":"Plate 11","size":"533 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections F-F’ through I-I’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1134/coverthb.jpg"},{"id":375114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134.pdf","text":"Report","size":"9.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1134"},{"id":375115,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate01.pdf","text":"Plate 1","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of well locations and outcrop areas of hydrostratigraphic units, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375116,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate02.pdf","text":"Plate 2","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375117,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate03.pdf","text":"Plate 3","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of semiconfining subunits within the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375122,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate08.pdf","text":"Plate 8","size":"1.88 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the unconfined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375123,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate09.pdf","text":"Plate 9","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the Navesink-Hornerstown confining unit, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375124,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate10.pdf","text":"Plate 10","size":"588 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections A-A’ through E-E’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375127,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_table03.xlsx","text":"Table 3","size":"23.2 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Wells used to develop a hydrostratigraphic framework, and interpreted aquifer structure points, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey (Preferred method to view file)"},{"id":375128,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_table03.csv","text":"Table 3","size":"10.2 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Wells used to develop a hydrostratigraphic framework, and interpreted aquifer structure points, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375118,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate04.pdf","text":"Plate 4","size":"1.48 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the thickness of semiconfining subunits within the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375119,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate05.pdf","text":"Plate 5","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of the Piney Point aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375121,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate07.pdf","text":"Plate 7","size":"755 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the thickness of the confined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375126,"rank":14,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate12.pdf","text":"Plate 12","size":"409 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections J-J’ through L-L’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"}],"country":"United States","state":"New Jersey","otherGeospatial":"Joint Base McGuire-Dix-Lakehurst","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.74822998046875,\n 39.886557705928475\n ],\n [\n -74.25796508789062,\n 39.886557705928475\n ],\n [\n -74.25796508789062,\n 40.11799004890473\n ],\n [\n -74.74822998046875,\n 40.11799004890473\n ],\n [\n -74.74822998046875,\n 39.886557705928475\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Bathymetric and topographic surveys performed annually along the coastlines of northern Oregon and southwestern Washington documented changes in beach and nearshore morphology between 2014 and 2019. Volume change analysis revealed measurable localized erosion and deposition throughout the study area, but significant net erosion at the regional scale (several kilometers [km]) was limited to Benson Beach, Wash., a 3-km-long stretch of coastline immediately north of the Columbia River inlet. Despite the placement of approximately 6.3 million cubic meters (Mm3) of sand dredged from the Columbia River navigational channel at nearshore placement sites located nearby, Benson Beach eroded 2.1±0.8 Mm3 over the 5-year (yr) monitoring time period (420,000 cubic meters/year [m3/yr]). A hydrodynamic and sediment transport model was applied to simulate sediment transport fluxes, and a new visualization technique was developed to evaluate the linkages between nearshore dredge placement sites and adjacent coastlines near the mouth of the Columbia River. The model results indicate the dominance of wave processes on sediment-transport patterns outside of the inlet and suggest that the current configuration of the nearshore dredge placement sites can be improved to more efficiently enhance the sediment budget of Benson Beach to reduce erosion and mitigate associated coastal change hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201045","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers Portland District and Northwest Association of Networked Ocean Observing Systems","usgsCitation":"Stevens, A.W., Elias, E., Pearson, S., Kaminsky, G.M., Ruggiero, P.R., Weiner, H.M., and Gelfenbaum, G.R., 2020, Observations of coastal change and numerical modeling of sediment-transport pathways at the mouth of the Columbia River and its adjacent littoral cell: U.S. Geological Survey Open-File Report 2020–1045, 82 p., https://doi.org//10.3133/ofr20201045.","productDescription":"Report: xii, 82 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-114630","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":375095,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1045/coverthb.jpg"},{"id":375096,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1045/ofr20201045.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":375097,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org//10.5066/P9W15JX8","linkHelpText":"Beach topography and nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon"}],"country":"United States","state":"Oregon, Washinton","otherGeospatial":"Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.07135009765625,\n 46.10180436619509\n ],\n [\n -123.57147216796875,\n 46.10180436619509\n ],\n [\n -123.57147216796875,\n 46.35261512930026\n ],\n [\n -124.07135009765625,\n 46.35261512930026\n ],\n [\n -124.07135009765625,\n 46.10180436619509\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
A 2-year radiotelemetry study was completed to monitor the movements of adult winter steelhead (Oncorhynchus mykiss) in the upper Cowlitz River Basin. A reintroduction program was established to restore healthy and harvestable populations of steelhead because volitional access to the area was blocked in the 1960s after construction of dams in the lower river. A trap-and-haul program is used to move adult steelhead and salmon (Oncorhynchus spp.) upstream, around the dams and large reservoirs, and release them in the upper basin to spawn naturally. Fish are released into Lake Scanewa, the uppermost reservoir in the system, and into the Cowlitz and Cispus Rivers. The goal of this study was to describe the behavior, movement, and tributary use of adult steelhead in the upper Cowlitz River Basin to assist in evaluating the trap-and-haul program and reintroduction program. We were specifically interested in learning more about the locations where steelhead spawn. Individual fish were assigned one of four fates, based on their location during the spawning period: Cowlitz River, Cispus River, Lake Scanewa, or fallback below the dam that impounds the reservoir. A total of 215 steelhead were tagged for the 2017–18 study. Of these, 5 fish regurgitated their transmitters before or shortly after release, so 210 tagged fish were used for analyses, including 121 fish (57.6 percent) released into the Cispus River and 89 fish (42.4 percent) released into Lake Scanewa. The Cowlitz River release site was not evaluated. Hatchery-origin (HOR) and natural-origin (NOR) steelhead were included in the study. Within the first 10 days after release, most steelhead had moved at least 2 river kilometers away from their release site. Fish released into Lake Scanewa, however, moved from their release site significantly sooner than fish released into the Cispus River, regardless of origin or sex. Most radio-tagged steelhead (93–100 percent) made no more than one trip between the reservoir and one of the rivers prior to spawning.
Steelhead were predominantly assigned fates in the river closest to where they were released, but origin also played a role. Steelhead released into the Cispus River were assigned Cispus River fates more than 80 percent of the time, including both origins and both years. About 13 percent of NOR fish had fates in the Cowlitz River, but the proportion was lower for HOR fish (0–2 percent). Fallback was the least common fate for Cispus-released steelhead (three HOR fish in 2017), followed by the reservoir fate, ranging from 5 to 9 percent in 2017, and zero in 2018. The steelhead released into Lake Scanewa were almost exclusively NOR fish, which had primarily Cowlitz River fates (55–57 percent). We released only six HOR steelhead into Lake Scanewa, and they all had Cowlitz River fates. The reservoir fate was uncommon for both release sites, and it was consistently lower in 2018 compared to 2017. Flow conditions were higher in 2017, which may have affected steelhead movement patterns or timing. The three HOR steelhead released in the Cispus River in 2017 were the only fish that fell back over Cowlitz Falls Dam, which represented 1.4 percent of the total study fish, 5.7 percent of the Cispus-released fish in 2017, and 9.4 percent of the Cispus-released HOR fish in 2017.
About 62 percent of the steelhead released in Lake Scanewa spawned in the Cowlitz River, with the remaining 38 percent in the Cispus River. Within the Cowlitz River, close to one-half (about 47 percent) of the fish spawned in the upper reach, and about 16 percent spawned in the lower reach. Steelhead released into Lake Scanewa that spawned in the Cispus River were minimal in reach 5 (4 percent) and distributed in approximately equal proportions in the middle (reach 6; 16 percent) and upper (reach 7; 18 percent) reaches. Steelhead released into the Cispus River spawned almost exclusively in the Cispus River (94 percent). The upper Cispus River reach (reach 7) was used by more fish (72 percent) than the middle Cispus reach (reach 6; 16 percent). Taken together, the upper Cowlitz River reach (reach 4) and upper Cispus River reach (reach 7) accounted for more than 71 percent of the spawning locations for radio-tagged steelhead. When the middle Cispus River reach (reach 6) is included with the upper reaches, they account for 87 percent of our described spawning sites. We described 12 tributaries in the Cowlitz River and 8 tributaries in the Cispus River where steelhead spawned. After spawning, about 53–63 percent of steelhead moved downstream as kelts, either being collected at Cowlitz Falls Dam or being detected downstream from the dam. More fish were collected from both release sites in 2018 compared to 2017. Across release sites and years, more NOR fish and females moved downstream as kelts. This study added to the understanding of the behavior and movement of adult steelhead in the upper Cowlitz River Basin, supporting the findings of previous studies in the basin and describing spawning sites in the system’s two main rivers and their tributaries. Future research efforts in this system may use additional telemetry studies, genetic analyses, and spawning ground surveys to provide further insights into the progress of the reintroduction effort.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201054","usgsCitation":"Liedtke, T.L., Kock, T.J., Hansen, A.C., Ekstrom, B.K., and Tomka, R.G., 2020, Behavior and movement of adult winter steelhead (Oncorhynchus mykiss) in the upper Cowlitz River Basin, Washington, 2017–18: U.S. Geological Survey Open-File Report 2020–1054, 35 p., https://doi.org/10.3133/ofr20201054.","productDescription":"vi, 35 p.","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-116465","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":375037,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1054/coverthb.jpg"},{"id":375038,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1054/ofr20201054.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Washington","otherGeospatial":"Upper Cowlitz River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.22265625000001,\n 45.767522962149876\n ],\n [\n -120.498046875,\n 45.767522962149876\n ],\n [\n -120.498046875,\n 46.98025235521881\n ],\n [\n -123.22265625000001,\n 46.98025235521881\n ],\n [\n -123.22265625000001,\n 45.767522962149876\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
A recent U.S. Geological Survey data compilation of stream-sediment geochemistry for Alaska contains decades of analyses collected under numerous Federal and State programs. The compiled data were determined by various analytical methods. Some samples were reanalyzed by a different analytical method than the original, resulting in some elements having concentrations reported by multiple analytical methods. Consideration of the analytical methods used to determine the elemental concentrations is an important step in a mineral prospectivity analysis. We used the compiled data to compare concentrations of barium (Ba), cobalt (Co), copper (Cu), chromium (Cr), nickel (Ni), lead (Pb), and zinc (Zn) determined by different analytical methods to show how simple data comparisons can identify bias and provide a general sense of the comparability of different analytical methods. The elements were selected because they have a range of geochemical properties that may affect the performance of different analytical procedures.
Generally, agreement between Ba, Co, Cu, Cr, Ni, Pb, and Zn concentrations is good for most quantitative methods that use a total decomposition of the sample. However, Cr concentrations typically were lower for methods using quantitative-instrumental analysis following a multi-acid dissolution technique that included hydrofluoric acid compared to those using sinter decomposition. Additionally, low- to middle-range concentrations for Co, Cr, Cu, Ni, Pb, and Zn by instrumental neutron activation (NA) and energy-dispersive x-ray spectroscopy (EDX) analyzed by the National Uranium Resource Evaluation (NURE) program have high uncertainty. Concentrations determined by methods that use partial decomposition of the sample generally correspond well to concentrations determined by methods that use a total decomposition technique, except for Ba and Cr. For Ba and Cr, partial decomposition techniques yield lower concentrations than those determined by methods that use a total decomposition technique. Comparison of Ba, Co, Cr, Cu, Ni, Pb, and Zn concentrations determined by semiquantitative visual six-step direct-current arc emission spectrography (ES_SQ) to those determined by quantitative methods using either a total or partial decomposition technique consistently show scatter that exceeds the values expected based on the range represented by the semiquantitative concentration.
The data compilation includes a best-value determination that was selected based on the analytical method from the all concentration data for that sample. Ba, Cr, Co, and Zn concentrations determined by NA usually are selected as the best-value determination. However, the NURE-NA method was designed for high throughput and the uncertainty associated with low- and mid-range concentrations is greater than that of the multi-acid method used to reanalyze many samples. Selection of the multi-acid method over the NURE-NA method for Ba, Co, and Zn could be warranted. Additionally, concentrations determined by ES_SQ usually are selected as the best-value determination over all methods that use a partial decomposition of the sample. Substitution of concentrations determined by methods that use a partial decomposition for those of ES_SQ may be warranted for Co, Cu, Ni, Pb, and Zn. Regardless of the selection of the best-value determination, the dataset remains a mixed method dataset and the uncertainty due to differences in analytical methodology must be considered when using the dataset.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201038","usgsCitation":"Wang, B, Ellefsen, K.J., Granitto, M., Kelley, K.D., Karl, S.M., Case, G.N.D., Kreiner, D.C., and Amundson, C.L., 2020, Evaluation of the analytical methods used to determine the elemental concentrations found in the stream geochemical dataset compiled for Alaska: U.S. Geological Survey Open-File Report 2020-1038, 66 p., https://doi.org/10.3133/ofr20201038.","productDescription":"xii, 66 p.","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-109726","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":375022,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1038/coverthb.jpg"},{"id":375023,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1038/ofr20201038.pdf","text":"Report","size":"8 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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Since the second half of the 20th century, there has been an increase in scientific interest, research effort, and information gathered on the geologic sedimentary character of the continental margins of the United States. Data and information from thousands of sources have increased our scientific understanding of the character of the margin surface, but rarely have those data been combined and integrated. Initially, the U.S. Geological Survey (USGS), in cooperation with the Institute of Arctic and Alpine Research at the University of Colorado Boulder, created the usSEABED database to provide surficial sea-floor-characterization data for USGS assessments of marine-based aggregates and for studies of sea-floor habitat. Since then, the USGS has continued to build up the database as a nationwide resource for many uses and applications.
Previously published data derived from the usSEABED database have been released as three USGS data series publications containing data covering the U.S. Atlantic margin, the Gulf of Mexico and Caribbean regions, and the Pacific coast. An updated USGS data release unifies the three publications, incorporates additional data and sources including data from Alaska, Hawaii, and U.S. overseas territories, and provides revised output files that fix known errors and add known or inferred sampling dates. This report accompanies the data release and contains information on the methodology and products of the usSEABED database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201046","collaboration":"Prepared in cooperation with the Institute of Arctic and Alpine Research at the University of Colorado Boulder","usgsCitation":"Buczkowski, B.J., Reid, J.A., and Jenkins, C.J., 2020, Sediments and the sea floor of the continental shelves and coastal waters of the United States—About the usSEABED integrated sea-floor-characterization database, built with the dbSEABED processing system: U.S. Geological Survey Open-File Report 2020–1046, 14 p., https://doi.org/10.3133/ofr20201046.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-107146","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science 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and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
Barrier islands, headlands, and coastal shorelines provide numerous valuable ecosystem goods and services, including storm protection and erosion control for the mainland, habitat for fish and wildlife, salinity regulation in estuaries, carbon sequestration in marshes, and areas for recreation and tourism. These coastal features are dynamic environments because of their position at the land-sea interface. Storms, wave energy, tides, currents, and relative sea-level rise are powerful forces that shape local geomorphology and habitat distribution. In order to make more informed decisions, coastal resource managers require insights into how these dynamic systems are changing through time.
In 2005, Louisiana’s Coastal Protection and Restoration Authority, in partnership with the University of New Orleans and the U.S. Geological Survey, developed the Barrier Island Comprehensive Monitoring (BICM) Program. The goal of the BICM Program is to develop long-term datasets for habitat coverage, shoreline assessments, shoreline position, topobathymetric changes, and sediment characterization to assist with planning, designing, evaluating, and maintaining current and future barrier shorelines. The overall objectives of the study described in this report were to (1) map habitats for 2008 and 2015–16 for BICM coastal reaches and (2) map habitat change between these two time periods.
This report highlights the second phase of habitat analyses for the BICM Program. This work builds on a previous habitat analysis conducted by the University of New Orleans, which included the development of habitat maps for 1996/1998, 2001, 2004, and 2005, along with habitat change maps. For this current effort, a new 15-class habitat scheme was developed from the original BICM scheme to further delineate various dune habitats, including meadow habitat found along the backslopes of dunes, to distinguish between marsh and mangrove, and to distinguish between beach and unvegetated barrier flat habitats. Additionally, a geographic object-based image analysis-based mapping framework was used to incorporate relative topography and address elevation uncertainty in light detection and ranging data to assist with mapping dune and intertidal habitats.
For the entire BICM region, the area experiencing a change in a land/water category (that is, land gain or land loss) was 3.4 percent, of which, 59.2 percent was land gain and 40.8 percent was land loss. Areal coverages of meadow, mangrove, scrub/shrub, and vegetated dune increased from 2008 to 2015–16, whereas areal coverages of beach, grassland, and intertidal decreased. The decrease in intertidal, however, was largely due to differing water levels in the orthophotography between the two time periods. Regional analyses of habitat coverage and habitat change captured the dynamic nature of these systems and the effects of restoration efforts, most notably in the Late Lafourche Delta, Modern Delta, and Chandeleur Islands regions. For instance, in the Modern Delta region there was a marked increase in unvegetated flat, meadow, mangrove, scrub/shrub, beach, unvegetated dune, and vegetated dune. As a result, this region experienced the highest percent change for land/water classes (6.6 percent) with land gain accounting for much of this change (70.8 percent). In contrast, the Acadiana Bays region had the highest relative percent loss of all regions. The region had a percent change for land/water classes of 2.8 percent, of which, 79.7 percent was land loss.
The results of this study provide information about the areal coverage and distribution of habitats for two recent time periods and change over about an 8-year period. These data can be used to evaluate changes along the Louisiana Gulf of Mexico shoreline, including gradual changes caused by coastal processes, restoration actions, and (or) episodic events, such as hurricanes and extreme storms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201030","collaboration":"Prepared in cooperation with the Louisiana Coastal Protection and Restoration Authority","usgsCitation":"Enwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030.","productDescription":"Report: ix, 57 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-114268","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":436983,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YRT54Z","text":"USGS data release","linkHelpText":"Louisiana Barrier Island Comprehensive Monitoring Program - 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U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
The Red Knot, Calidris canutus, is a highly migratory shorebird with a cosmopolitan distribution. Six subspecies have been identified, two of which occur regularly in North America (C.c. rufa and C.c. roselaari). Given their long-distance migrations through many jurisdictions and conservation status, tools are needed to reliably distinguish the subspecies when captured away from their breeding areas and to examine potential population substructure within each taxa. We used a suite of molecular approaches to develop tools to support Red Knot research and management. Although our microsatellite markers were not able to reliably distinguish C.c. rufa and C.c. roselaari, we did find evidence of population substructure within C.c. rufa.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201050","usgsCitation":"Kazyak, D., Aunins, A., and Johnson, R., 2020, Red Knot (Calidris canutus) research—Preliminary results and future opportunities: U.S. Geological Survey Open-File Report 2020–1050, 6 p., https://doi.org/10.3133/ofr20201050.","productDescription":"v, 6 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114640","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":374855,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1050/ofr20201050.pdf","text":"Report","size":"681 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":374854,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1050/coverthb.jpg"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The 2018 Kīlauea Volcano eruption lasted 107 days, and now ranks as the most destructive event at Kilauea since 1790, and as one of the most costly volcanic disasters in U.S. history. Multiple simultaneous hazard events unfolded, including sustained seismic activity leading to collapse at the summit of Halema'uma'u crater and severe damage to the HVO facility, with additional eruption of lava in the Kīlauea Lower East Rift Zone that progressively grew to a total of 24 fissure openings. In response to the complex and uncertain nature of the eruption, U.S. Geological Survey (USGS) team activities tended to coalesce around several interrelated core functional areas: science operations, emergency management and administration, and external communications. Upon cessation of the eruption, the USGS Hazard Response Executive Committee charged the Alaska Regional Office to lead an After-Action Review team, which focused on two basic questions: (1) what went well, and why?; and (2) what can be improved, and how? The purpose of the After-Action Review is to identify priorities for programmatic or policy improvements that the USGS can feasibly implement to advance strategic preparation for future disasters, and thereby reduce public vulnerabilities. Specifically, the review is intended to help USGS respond even better to the next eruption in Hawai'i or elsewhere by advancing any of the following goals:
Regional Director, Alaska
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508-4560
As part of a U.S. Geological Survey water-quality study started in 2018, in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency, a publicly available software package called R–QWTREND was developed for analyzing trends in stream-water quality. The R–QWTREND package is a collection of functions written in R, an open source language and a general environment for statistical computing and graphics. The package uses a parametric time-series model to express logarithmically transformed concentration in terms of flow-related variability, trend, and serially correlated model errors. Flow-related variability captures natural variability in concentration on the basis of concurrent and antecedent streamflow. The trend identifies systematic changes in concentration in terms of potential step trends, piecewise monotonic trends, or user-specified trends. Maximum likelihood estimation is used to estimate model parameters and determine the best-fit trend model. This report describes the time-series model and statistical methodology behind R–QWTREND and provides formal documentation for installing and using the package.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201014","collaboration":"Prepared in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency","usgsCitation":"Vecchia, A.V., and Nustad, R.A., 2020, Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality (ver. 1.2, March 2023): U.S. Geological Survey Open-File Report 2020–1014, 51 p., https://doi.org/10.3133/ofr20201014.","productDescription":"Report: viii, 52 p.; Appendix; Dataset","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109088","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":414697,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1014/versionHist.txt","text":"Version History","size":"2 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":374762,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System","linkHelpText":"USGS water data for the Nation"},{"id":414696,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1014/ofr20201014.pdf","text":"Report","size":"4.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–2014"},{"id":374759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1014/coverthb3.jpg"},{"id":374761,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1014/downloads/","text":"Appendix 1","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2020–2014 Appendix 1","linkHelpText":"R–QWTREND Software Package"}],"edition":"Version 1.0: May 13, 2020; Version 1.1: November 30, 2021; Version 1.2: March 28, 2023","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
Sustainability of dryland ecosystems depends on the functionality of soil-vegetation feedbacks that affect ecosystem processes, such as nutrient cycling, water capture and retention, soil erosion and deposition, and plant establishment and reproduction. Useful, common indicators can provide information on soil and site stability, hydrologic function, and biotic integrity. Evaluation of rangeland health thus relies on describing the condition and sustainability of these individual, measurable, and observable indicators that are linked to important ecosystem processes. This report focuses on the ~200,000 acres of the Grand Canyon-Parashant National Monument that is administered by the National Park Service (NPS)—one of the largest NPS units where livestock grazing is a permitted land-use activity. Many ecosystems in the monument are characterized by a low degree of resilience to improper grazing because of low and variable precipitation. The monument is marked by a high degree of environmental heterogeneity, including a large elevation gradient, widely differing precipitation patterns, a diversity of geologic substrates, and unique combinations of plant species.
The objective of this report is to (1) increase our understanding of the underlying landscape, soil, and climate setting factors that affect Grand Canyon-Parashant National Monument dryland ecosystem structure and function (also referred to as land potential) and (2) characterize the condition of monument ecosystems in relation to management concepts, such as rangeland health.
Data were analyzed by elevation zone using both univariate and multivariate approaches. Survey results document the high level of diversity within the study area, including 15 unique soil taxa and 271 species of plants. We collected three new plant species for Grand Canyon-Parashant National Monument and 17 new species for the NPS portion of the monument. Results also document a strong association between rangeland health indicators and elevation, topographic setting, and soils. Soil factors found to explain important variation across plots include the amount of exposed bedrock, soil rockiness, soil texture (and associated hydrologic properties), and soil depth. We also found that dominant species turnover across elevation may represent species’ differences in adaptation to climates, including Larrea tridentata, Coleogyne ramosissima, and Artemisia spp. Bromus rubens is the most common invasive species of concern recorded in this study, but other common invasive species are Bromus tectorum, Erodium cicutarium, and Schismus arabicus. Correlations between an index of cattle use and indicators of rangeland health suggest that areas with high cattle use have increased bare ground, decreased ground cover, increased frequency of Schismus arabicus, decreased cover of Coleogyne ramosissima and Ephedra spp., and increased cover of Gutierrezia spp. The few strong correlations observed between indicators of vascular plant community cover or abundance and indicators of cattle activity support rangeland assessment and monitoring strategies that do not rely solely on plant-based indicators are needed.
This work supports management of dryland ecosystems, including Grand Canyon-Parashant National Monument, using concepts of land potential. We conclude the report with recommendations on improving existing land-potential-based classification systems, associated interpretations, and methods for moving forward with a Grand Canyon-Parashant National Monument rangeland monitoring program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201040","usgsCitation":"Duniway, M.C., and Palmquist, E.C., 2020, Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona: U.S. Geological Survey Open-File Report 2020–1040, 42 p., https://doi.org/10.3133/ofr20201040.","productDescription":"Report: viii, 42 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-106479","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":374803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJSJHT","linkHelpText":"Rangeland Ecosystem Data, Grand Canyon - Parashant National Monument, AZ, USA"},{"id":374801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1040/coverthb.jpg"},{"id":374802,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1040/ofr20201040.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon-Parashant National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.005126953125,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 35.679609609368576\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
We developed an initial inventory of ground failure features from the November 30, 2018, magnitude 7.1 Anchorage earthquake. This inventory of 153 features is from ground-based observations soon after the earthquake (December 5–10) that include the presence or absence of liquefaction, landslides, and individual crack traces of lateral spreads and incipient landslides. This is not a complete inventory and simply shows general trends and examples of types and distribution of ground failures documented. Overflight observations (December 1–6) documented landslide and liquefaction presence or absence within the Chugach Mountains and along Cook Inlet in regions inaccessible to vehicles, which greatly expanded the geographic scope of this reconnaissance. Field-mapped ground-failure observations have been augmented with a set of 565 georeferenced and annotated images from both field and overflight reconnaissance cataloging additional ground-failure presence or absence from the Anchorage earthquake.
Tidal erosion, fresh snowfall, limited daylight, and adverse flying conditions contributed significantly to the uncertainty and incompleteness of ground-failure observations during this reconnaissance. Notably, substantial liquefaction features at the mouths of the Little Susitna River (December 1) and Ingram Creek (December 5) were absent during subsequent overlapping missions (December 6 and 9, respectively) because of tidal action. A large rockfall observed on December 1 on Rainbow Peak was not observed during a subsequent December 5 overflight because of snow cover, which suggests that the general lack of observations of landsliding within the Chugach Mountains is uncertain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201043","usgsCitation":"Grant, A.R.R., Jibson, R.W., Witter, R.C., Allstadt, K.E., Thompson, E.M., and Bender, A.M., 2020, Ground failure triggered by shaking during the November 30, 2018, magnitude 7.1 Anchorage, Alaska, earthquake: U.S. Geological Survey Open-File Report 2020–1043, 21 p., https://doi.org/10.3133/ofr20201043.","productDescription":"Report: iv, 21 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","ipdsId":"IP-106267","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":374798,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1043/coverthb.jpg"},{"id":374799,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1043/ofr20201043.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":374800,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99ONUNM","linkHelpText":"Field Reconnaissance of Ground Failure Triggered by Shaking during the 2018 M7.1 Anchorage, Alaska, Earthquake"}],"country":"United States","state":"Alaska","city":"Anchorage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.54541015625,\n 60.66241476534369\n ],\n [\n -148.82080078125,\n 60.66241476534369\n ],\n [\n -148.82080078125,\n 61.77312286453146\n ],\n [\n -151.54541015625,\n 61.77312286453146\n ],\n [\n -151.54541015625,\n 60.66241476534369\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035
The addition of surface water from the San Juan-Chama Drinking Water Project to the Albuquerque water supply and the reduction in per capita water use has led to decreased groundwater withdrawals. This decrease in withdrawals has resulted in rising groundwater levels since 2008 in portions of the aquifer underlying Albuquerque. The wells used to assess the Kirtland Air Force Base Bulk Fuels Facility (KAFB BFF) ethylene dibromide (EDB) groundwater contamination were installed with well screens that crossed the water table in order to monitor and sample groundwater within the EDB plume. While replacement wells have been installed, an understanding of the water-table response to decreases in regional groundwater withdrawals is required to evaluate the monitoring well network. Water-table elevation maps of the aquifer underlying the Albuquerque metropolitan area east of the Rio Grande for 2008 and 2016 and a map of the change in elevations in this 8-year period provide an improved understanding of the water-table elevations and the changes that are occurring.
The water-table elevation contours for both 2008 and 2016 show that groundwater generally flows from the Rio Grande and from the mountain-front recharge in the southeast toward the center of the study area, a major groundwater pumping center. The water-table elevation increased in most of the study area from 2008 to 2016. The area of greatest increase in the water-table elevation covers most of the northeastern part of the study area, where there has historically been pumping-related drawdown and subsequent groundwater-level rises in the production zone of the Santa Fe Group aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201036","collaboration":"Prepared in cooperation with Air Force Civil Engineer Center","usgsCitation":"Flickinger, A.K., and Mitchell, A.C., 2020, Water-table elevation maps for 2008 and 2016 and water-table elevation changes in the aquifer system underlying eastern Albuquerque, New Mexico: U.S. Geological Survey Open-File Report 2020–1036, 9 p., https://doi.org/10.3133/ofr20201036.","productDescription":"Report: vi, 9 p.; Data Release; Interactive Map","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-111755 ","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":374556,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://usgs.maps.arcgis.com/home/item.html?id=3b038837dfe347daa8691931182788f5","text":"Interactive map of the study area"},{"id":374553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1036/coverthb.jpg"},{"id":374554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1036/ofr20201036.pdf","text":"Report","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1036"},{"id":374555,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OHR8Z2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-tables elevations and other well construction data for 2008 and 2016 in eastern Albuquerque, New Mexico"}],"country":"United States","state":"New Mexico","city":"Albuquerque","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.6607666015625,\n 34.836349990763864\n ],\n [\n -105.9521484375,\n 34.836349990763864\n ],\n [\n -105.9521484375,\n 35.27701633139884\n ],\n [\n -106.6607666015625,\n 35.27701633139884\n ],\n [\n -106.6607666015625,\n 34.836349990763864\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The U.S. Geological Survey Western Ecological Research Center’s Santa Cruz Field Station, Santa Cruz, California, has been funded by the U.S. Navy to continue monitoring a suite of intertidal black abalone sites at San Nicolas Island, California. The nine rocky intertidal sites were established in 1980 by Glenn VanBlaricom (then of the U.S. Fish and Wildlife Service) to study the potential impact of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or semi-annually. Monitoring resumed in 2001, and regular annual monitoring cycles have been conducted at the sites since then. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years reduced the population there by approximately 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.
The subject of this report is the 2019 monitoring cycle of the sites and how the current status fits into the long-term data at San Nicolas Island. Since 2001, the monitored population has increased nearly tenfold to approximately 8.7 percent of the pre-disease level. This increase has resulted from generally higher levels of recruitment than seen in the first two decades of monitoring, punctuated by a few high recruitment events. Most of the population growth has been at two of the nine sites (sites 7 and 8). This pattern continued in 2019 with increasing numbers at sites 7 and 8 and the highest number of abalone counted and measured island-wide since 1996. However, counts declined at six of the sites during the last year and the increases in counts at sites 7 and 8 barely offset these losses. Recruitment rates have fallen since a peak in 2017 but 2019 continued to show some additional recruitment. The distance between adjacent black abalone, a metric relevant to potential reproduction, has decreased substantially since it was first consistently measured in 2005. Although sand burial can have devastating localized consequences to black abalone, the sand cover data we collected was not sufficient to suggest an obvious temporal or site-based pattern to sedimentation, and there is no indication that this was a factor in any of the declines recorded in 2019. Continued monitoring of these sites can provide island biologists with species trends to aid in adaptive management of the resource.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201047","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., 2020, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California: 2019, annual report: U.S. Geological Survey Open-File Report 2020–1047, 41 p., https://doi.org/10.3133/ofr20201047.","productDescription":"iv, 41 p.","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-111797","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":374605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1047/ofr20201047.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":374604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1047/coverthb.jpg"}],"country":"United States","state":"California","county":"Ventura County","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.59922790527342,\n 33.203647816301306\n ],\n [\n -119.42481994628906,\n 33.203647816301306\n ],\n [\n -119.42481994628906,\n 33.293229612321824\n ],\n [\n -119.59922790527342,\n 33.293229612321824\n ],\n [\n -119.59922790527342,\n 33.203647816301306\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
We acquired multiple types of seismic data across the Hollywood Fault in Hollywood, Calif., and the Santa Monica Fault in Beverly Hills, Calif., in May and June 2018. On the basis of our data, we infer near-surface locations of various traces of these faults.
From two separate profiles across the Hollywood Fault, we evaluated multiple seismic datasets and models, including guided-wave data, tomographic VP data, tomographic VS data, VP/VS and Poisson’s ratio models derived from tomographic VP and VS data, Rayleigh-wave–based VS models, Love-wave–based VS models, VP/VS and Poisson’s ratio models (derived from combinations of tomographic-based VP and surface-wave–based VS models), P-wave reflection images, and S-wave reflection images. All of these data and models can be used to delineate near-surface faulting, and the data consistently infer near-surface fault traces of the Hollywood Fault in the same locations. Importantly, the combined data indicate more than one near-surface fault trace of the Hollywood Fault. Between North Bronson and North Gower Avenues, evidence exists for a near-surface trace of the Hollywood Fault slightly south of Carlos Avenue. Farther west, along Argyle Avenue, our data contain high levels of cultural noise, but we interpret near-surface faulting slightly south of the intersection of Carlos and Argyle Avenues and between Carlos Avenue and Yucca Street.
For the Santa Monica Fault in Beverly Hills, we acquired guided-wave data only along Lasky Drive between Moreno Drive and South Santa Monica Boulevard, owing to limited access permissions. However, we used two separate source locations to generate the guided-wave data (SP1 and SP2). The data from more distant source location (relative to the recording array, SP1) were noisy, but on the basis of those data, we infer near-surface faulting at several locations along Lasky Drive, with concentrated near-surface faulting slightly south of the intersection of Lasky Drive and Charleville Boulevard. Guided-wave data generated at the closer source location (relative to recording array, SP2) more clearly show evidence for distributed near-surface faulting at several locations along Lasky Drive, with concentrated faulting near the intersection of Lasky Drive and Charleville Boulevard.
Although the seismic surveys across both faults provide strong evidence for the locations of near-surface fault traces, the seismic data provide little or no information about the rupture history of the fault traces.
Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
An existing two-dimensional, steady-state groundwater-flow model of the shallow groundwater-flow system of the Lac du Flambeau Reservation in Vilas County, Wisconsin, originally developed by the U.S. Geological Survey, was used to simulate the potential for wastewater from a proposed relocation of a wastewater lagoon to contaminate the Lac du Flambeau Band of Lake Superior Chippewa’s drinking-water-supply wells. This simulation was completed by the U.S. Geological Survey in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service. The simulated scenarios consisted of removing wastewater infiltration from existing lagoons and re-applying that infiltration at the proposed location. Two analyses were performed for the scenarios. First, the probable extent of the plume discharging from the proposed infiltration lagoons was mapped with a Monte Carlo algorithm that used uncertainty identified during the calibration process to simulate thousands of possible outcomes. Second, the Monte Carlo method was again used to simulate a probabilistic contributing area for the Tribe’s nearby “Main Pumphouse” supply wells. The purpose of the simulations was to evaluate the potential for infiltrated wastewater to be captured by the public-supply wells.
Most features of the previously developed model remained unchanged, including calibrated parameters such as hydraulic conductivity and recharge. Thus, the same covariance distributions that were generated during calibration of the regional model (Juckem and others, 2014) remained unchanged and were used to inform the Monte Carlo simulations for the scenario simulations described in this report. The reader is encouraged to read the full report by Juckem and others (available at https://doi.org/10.3133/sir20145020) for a detailed description of the model design and calibration, as well as a description of the Monte Carlo method, its limitations, and the original results.
Results for these new scenarios indicate that the probabilistic plume extent for the proposed infiltration lagoons does not reach the Main Pumphouse wells using pumping rates and wastewater volumes estimated for 2010. Similarly, the contributing area for the Main Pumphouse wells does not capture water from within the proposed infiltration lagoon footprint. However, at higher pumping rates and wastewater volumes, as projected by the Tribe for about 2035, the contributing area for the Main Pumphouse wells do include particles that originated within the proposed lagoon footprint, albeit at low probabilities. That is, for a few of the thousands of simulations that represented a range of calibration-informed parameter covariances, some amount of infiltrated wastewater was captured by the Main Pumphouse wells under projected 2035 conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201032","collaboration":"Prepared in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service","usgsCitation":"Juckem, P.F., and Fienen, M.N., 2020, Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin: U.S. Geological Survey Open-File Report 2020–1032, 10 p., https://doi.org/10.3133/ofr20201032.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-109305","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1032/coverthb.jpg"},{"id":374399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1032/ofr20201032.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1032"},{"id":374400,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z2YUW5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"GFLOW model files used to generate probabilistic waste-water plume extents and contributing areas to supply wells for a proposed waste-water infil-tration lagoon scenario, Lac du Flambeau, Wisconsin"}],"country":"United States","state":"Wisconsin ","county":"Vilas County","city":"Lac du Flambeau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.92378234863281,\n 45.94386878224691\n ],\n [\n -89.85013961791992,\n 45.94386878224691\n ],\n [\n -89.85013961791992,\n 45.98408084285212\n ],\n [\n -89.92378234863281,\n 45.98408084285212\n ],\n [\n -89.92378234863281,\n 45.94386878224691\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 55562
The National Petroleum Reserve in Alaska (NPR-A) encompasses more than 9.5 million hectares of federally managed land on the Arctic Coastal Plain of northern Alaska, where it supports a diversity of wildlife, including millions of migratory birds. Within the NPR-A, Teshekpuk Lake and the surrounding area provide important habitat for migratory birds, including large numbers of waterfowl and shorebirds that use the area for breeding and molting. This area has been designated by the Bureau of Land Management as the Teshekpuk Lake Special Area (TLSA) and is estimated to host 22 percent of the entire Pacific black brant (Branta bernicla nigricans) population as it undergoes flightless wing molt. Additionally, numerous other waterfowl species use the area for breeding and molting, including greater white-fronted geese (Anser albifrons), snow geese (Chen caerulescens), Canada geese (Branta hutchinsii), and tundra swans (Cygnus columbianus). A data-derived procedure was developed to define important habitats based on recent distributions of molting birds. That procedure was used to identify areas that could be prioritized for exclusion from oil and gas development within a pre-defined “Goose Molting Area” in the TLSA. This analysis was requested by the Bureau of Land Management to provide information for the development of alternative scenarios for an updated NPR-A, Integrated Activity Plan/Environmental Impact Statement. Habitat selections were based on the population densities of Pacific black brant and Canada geese and pre-defined thresholds for the minimum fraction of the population contained within selected areas. Selections were based on long-term records of population density combined with global-positioning system data to reveal small-scale patterns of habitat use. The highest population density of the Pacific black brant was found along the Beaufort Sea coast on the eastern edge of the study area, whereas Canada geese were somewhat more widely distributed. Depending on the selection criteria and width of protective buffers placed around selected habitat units, 52–85 percent of the Goose Molting Area was identified as high-priority habitat. The effectiveness of this approach to habitat protection assumes that buffers around selected habitat units are wide enough to provide adequate protection from disturbance related to oil and gas development. This assumption remained a key source of uncertainty that could be addressed through additional study of disturbance effects on molting waterfowl.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201034","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Flint, P.L., Patil, V., Shults, B., and Thompson, S.J., 2020, Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska: U.S. Geological Survey Open-File Report 2020-1034, 16 p., https://doi.org/10.3133/ofr20201034.","productDescription":"Report: iv, 16 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115467","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":374468,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZGNRTB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Habitat selection scenarios for molting waterfowl in the Goose Molting Area of the Teshekpuk Lake Special Area, for NPR-A Integrated Activity Plan/Environmental Impact Statement (2020)"},{"id":374466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1034/coverthb.jpg"},{"id":374467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1034/ofr20201034.pdf","text":"Report","size":"3.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1034"}],"country":"United States","state":"Alaska","otherGeospatial":"National Petroleum Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.59411621093747,\n 70.23346027955571\n ],\n [\n -151.7816162109375,\n 70.23346027955571\n ],\n [\n -151.6717529296875,\n 70.52306573985297\n ],\n [\n -152.0892333984375,\n 70.8248355501024\n ],\n [\n -153.0670166015625,\n 70.95790503334285\n ],\n [\n -154.59411621093747,\n 70.86448996613296\n ],\n [\n -154.59411621093747,\n 70.23346027955571\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 58th Annual Report of the River Master of the Delaware River. It covers the 2011 River Master report year, the period from December 1, 2010, to November 30, 2011.
During the report year, precipitation in the upper Delaware River Basin was 71.43 inches or 162 percent of the long-term average. On December 1, 2010, combined usable storage in the New York City reservoirs in the upper Delaware River Basin was 230.430 billion gallons or 85.1 percent of combined storage capacity. The reservoirs were at about 100 percent of usable capacity on May 31, 2011. Combined storage remained high (above 80 percent combined capacity) through November 2011. River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program.
Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 5 days during the report year (July 24–28, 2011). Conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were also made during the report year.
The quality of water in the Delaware Estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201020","usgsCitation":"DiFrenna, V.J., Andrews, W.J., Russell, K.L., Norris, J.M., and Mason, R.R., Jr., 2020, Report of the River Master of the Delaware River for the period December 1, 2010–November 30, 2011: U.S. Geological Survey Open-File Report 2020–1020, 127 p., https://doi.org/10.3133/ofr20201020.","productDescription":"x, 127 p.","numberOfPages":"141","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-112762","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":374239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1020/coverthb.jpg"},{"id":374254,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1020/ofr20201020.pdf","text":"Report","size":"4.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1020"}],"country":"United States","state":"New York, New Jersey, Pennsylvania ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.673583984375,\n 39.7240885773337\n ],\n [\n -73.828125,\n 39.7240885773337\n ],\n [\n -73.828125,\n 42.67435857693381\n ],\n [\n -76.673583984375,\n 42.67435857693381\n ],\n [\n -76.673583984375,\n 39.7240885773337\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Deputy Delaware River Master
Office of the Delaware River Master
U.S. Geological Survey
120 Route 209 South
Milford, PA 18337