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 due to 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, that 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.
Upper Klamath Lake indices of year-class strength indicated that the 2019 year-class was the strongest in the past 5 years of monitoring. Low detections of age-1 and older suckers indicate that the 2018 cohort experienced poor survival within the first year of life. Shortnose suckers constituted the smallest proportion and suckers with uncertain species identification constituted the largest proportion of the 2019 year-class. Small numbers of Lost River sucker were captured consistently throughout the sampling season.
The relative abundance of age-0 suckers is not a good indicator of year-class strength in Clear Lake. There were no age-0 suckers captured in Clear Lake during the 2015 and 2019 sampling seasons. Most suckers captured were age-1 Klamath largescale/shortnose suckers, which indicated a relatively strong 2018 cohort. Four-year old juveniles from the 2015 cohort were present in 2019 in Clear Lake. Cohorts that do not recruit to our sampling gear until a year or more of age seem to indicate that (1) a stream resident life history is contributing to the lake population and (2) juvenile suckers occupy the Willow Creek drainage for a full year or more. Although these suckers could be either the non-endangered Klamath largescale or the endangered shortnose suckers, a stream resident life history 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 in most years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211119","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bart, R.J., Kelsey, C.M., Burdick, S.M., Hoy, M.S., and Ostberg, C.O., 2021, Growth, survival, and cohort formation of juvenile Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2019 Monitoring Report: U.S. Geological Survey Open-File Report 2021–1119, 26 p., https://doi.org/10.3133/ofr20211119.","productDescription":"vi, 26 p.","onlineOnly":"Y","ipdsId":"IP-125594","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":393120,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1119/ofr20211119.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1119"},{"id":393119,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1119/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 -122.16384887695312,\n 42.21733067375916\n ],\n [\n -121.75048828124999,\n 42.21733067375916\n ],\n [\n -121.75048828124999,\n 42.595554553719204\n ],\n [\n -122.16384887695312,\n 42.595554553719204\n ],\n [\n -122.16384887695312,\n 42.21733067375916\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.25473022460936,\n 41.78052894057897\n ],\n [\n -121.04324340820312,\n 41.78052894057897\n ],\n [\n -121.04324340820312,\n 41.94621306986162\n ],\n [\n -121.25473022460936,\n 41.94621306986162\n ],\n [\n -121.25473022460936,\n 41.78052894057897\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
Flow management is complex in the Willamette River Basin where the U.S. Army Corps of Engineers owns and operates a system of 13 dams and reservoirs (hereinafter Willamette Project), which are spread throughout three large tributaries including the Middle Fork Willamette, McKenzie, and Santiam Rivers. The primary purpose of the Willamette Project is flood-risk management, which provides critical protection to the Willamette Valley, but flow managers must also consider factors such as power generation, water-quality improvement, irrigation, recreation, and protection for aquatic species such as U.S. Endangered Species Act-listed Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss). Flow-management decision-making in the basin can benefit from models that allow for flow-scenario comparisons and a wide range of modeling methods are available. For this study, we examined existing datasets and modeling efforts in the basin and provided an overview of available options. Most previous studies used Physical Habitat Simulation System, habitat data were collected from a series of transects within modeled reaches, and habitat suitability indices were obtained from the literature, or using expert opinion. These studies provide information for specific reaches of the Willamette River Basin, which limits their ability to provide broad-scale predictive capability. Recent efforts to develop a two-dimensional hydraulic model in the mainstem Willamette River, and in specific reaches of primary tributaries downstream from Project dams, have bolstered modeling capabilities in the basin. This work has developed spatially continuous water depth and velocity data in more than 250 kilometers (km) of river downstream from Project dams and has predictive capability throughout the year at flows up to normal peak levels. Additionally, other methods are described for estimating habitat availability, which include habitat suitability criteria, logistic regression, occupancy and abundance modeling, and energetic based approaches. There are strengths and weaknesses to each approach and selection of the preferred approach in the Willamette River Basin will depend on the desired metrics of interest and the risk tolerance of managers and stakeholders in the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211114","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., Perry, R.W., Hansen, G.S., White, J., Stratton Garvin, L., and Wallick, J.R., 2021, Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon: U.S. Geological Survey Open-File Report 2021–1114, 24 p., https://doi.org/10.3133/ofr20211114.","productDescription":"vii, 24 p.","onlineOnly":"Y","ipdsId":"IP-127909","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":393073,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1114/ofr20211114.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1114"},{"id":393072,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1114/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.33251953125,\n 43.41302868475145\n ],\n [\n -121.59667968749999,\n 43.41302868475145\n ],\n [\n -121.59667968749999,\n 45.79050946752472\n ],\n [\n -123.33251953125,\n 45.79050946752472\n ],\n [\n -123.33251953125,\n 43.41302868475145\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
Golden Eagles (Aquila chrysaetos) are among the highest profile species killed by collisions with wind turbines at the Altamont Pass Wind Resource Area (APWRA) in the northern Diablo Range of west-central California. Understanding the distribution, site occupancy, and nesting status of eagles near the APWRA is needed to identify and minimize possible population-level impacts. We established a broad-scale survey design across a 5,185-km square-kilometer region of the Diablo Range, including the APWRA, to monitor site occupancy, abundance, and reproduction of Golden Eagles. During the study period we identified as many as 230 territorial pairs of Golden Eagles in the study area, up to 21 of which overlapped with the APWRA in any given year. On average, we detected a similar density of pairs at sites surveyed in the APWRA (1 pair per 17.8 km2 surveyed) relative to sites surveyed in the surrounding region (1 pair per 20.3 km2 surveyed). In 2020 and 2021, estimates of the proportion of pairs that successfully fledged at least one young (nesting success) were 0.27 and 0.26, respectively, which were above the seven-year average (0.22). On average, eagle pairs monitored in the APWRA had similar reproductive output (0.37 young fledged per pair) relative to pairs monitored outside of the APWRA (0.30 young fledged per pair). We observed a substantially higher proportion of territorial subadult pair members at the APWRA (mean = 29 percent of 16 pairs aged) relative to pairs monitored and aged in the surrounding region (mean = 3 percent of 122 pairs), indicating potentially higher rates of adult mortality or displacement at territories overlapping with the APWRA. Emergent threats to eagles in the study region, including a severe wildfire that impacted over 60 historical breeding territories in 2020, may interact with existing threats to affect population status and thus warrants further investigation. Our study provides wind energy developers, land managers, and regulatory agencies with key information on the spatial distribution, habitat quality, and population status of Golden Eagles needed to promote compatible wind energy production and long-term conservation of this federally protected wildlife species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211107","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and East Bay Regional Park District","usgsCitation":"Wiens, J.D., and Kolar, P.S., 2021, Golden eagle population surveys in the vicinity of the Altamont Pass Wind Resource Area, California, 2014–21: U.S. Geological Survey Open-File Report 2021–1107, 18 p., https://doi.org/10.3133/ofr20211107.","productDescription":"iv, 17 p.","onlineOnly":"Y","ipdsId":"IP-124051","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":402981,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211107/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2021-1107"},{"id":397094,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1107/images"},{"id":397095,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1107/ofr20211107.XML"},{"id":393064,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1107/coverthb.jpg"},{"id":393065,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1107/ofr20211107.pdf","text":"Report","size":"9.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1107"}],"country":"United States","state":"California","otherGeospatial":"Altamont Pass Wind Resource Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.94000244140624,\n 37.40943717748788\n ],\n [\n -121.30004882812499,\n 37.40943717748788\n ],\n [\n -121.30004882812499,\n 37.86834903305901\n ],\n [\n -121.94000244140624,\n 37.86834903305901\n ],\n [\n -121.94000244140624,\n 37.40943717748788\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Pre-Cretaceous, predominantly dioritic plutonic rocks in the Lane Mountain area, California, intrude metasedimentary and metavolcanic rocks considered part of the El Paso terrane. New geochronologic (uranium-lead zircon), geochemical, and isotopic data provide a reliable basis for dividing these pre-Cretaceous plutonic rocks into two mappable suites of Permian–Triassic and Late Jurassic ages. The 26 Permian–Triassic samples included in this report have a mean age of ~248 mega-annum (Ma), range in composition from monzodiorite to quartz monzonite and granodiorite, and have a mean initial 87Sr/86Sr ratio (Sri) of ~0.7045. The 22 Late Jurassic samples have a mean age of ~149 Ma, range in composition from gabbro to granite, and have a mean Sri of ~0.7055. Accurate mapping of these two plutonic suites and their detailed field relations with the associated metamorphic rocks is essential for resolving the geologic history and regional tectonic significance of the Lane Mountain area.
The sub-0.706 Sri values of both plutonic suites at Lane Mountain are consistent with previous suggestions that the El Paso terrane is allochthonous and did not develop on Precambrian continental lithosphere. Both suites are considered parts of northwest-trending magmatic arcs interpreted to have formed above east-dipping subduction zones along the evolving North American continental margin, and both arcs are interpreted to cross a major east-west-trending boundary between the El Paso terrane and rocks considered part of ancestral North America in the San Bernardino Mountains area to the south. The El Paso terrane thus appears to have been attached to the San Bernardino Mountains area at least since Permian–Triassic time, although the boundary probably has been modified by Cenozoic faulting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211094","usgsCitation":"Stone, P., Brown, H.J., Cecil, M.R., Fleck, R.J., Vazquez, J.A., and Fitzpatrick, J.A., 2021, Geochronologic, isotopic, and geochemical data from pre-Cretaceous plutonic rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2021–1094, 74 p., https://doi.org/10.3133/ofr20211094.","productDescription":"viii, 74 p.","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-121822","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":436088,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KRD45S","text":"USGS data release","linkHelpText":"Tabular geochronologic, geochemical, and isotopic data from igneous rocks in the Lane Mountain area, San Bernardino County, California"},{"id":414904,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221115","text":"Open-File Report 2022-1115","description":"Stone, P., Cecil, M.R., Brown, H.J., and Vazquez, J.A., 2023, Geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2022–1115, 34 p., https://doi.org/10.3133/ofr20221115.","linkHelpText":"- Geochronologic and Geochemical Data from Metasedimentary and Associated Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":392864,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191070","text":"Open-File Report 2019-1070","linkHelpText":"- Geochronologic, Isotopic, and Geochemical Data from Igneous Rocks in the Lane Mountain Area, San Bernardino County, 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Bernardino\",\"state\":\"CA\"}}]}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
The U.S. Geological Survey, in cooperation with the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey, conducted a groundwater-quality investigation to (1) describe the occurrence and distribution of PFAS, and (2) document any changes in groundwater quality in the Columbia aquifer public water-supply wells in the Delaware Coastal Plain between 2000 and 2008 and between 2008 and 2018. Thirty public water-supply wells located throughout the Columbia aquifer of the Delaware Coastal Plain were sampled from August through November 2018. Groundwater collected from the wells was analyzed for the occurrence and distribution of 18 per- and polyfluorinated alkyl substances (PFAS) as well as groundwater age. Descriptive statistical analyses were performed to assess PFAS analytical results within the well network and the combined perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) concentrations were compared to the U.S. Environmental Protection Agency’s (EPA) health advisory level (HAL) for informational purposes only and not for evidence of compliance or noncompliance with Federal regulations. The EPA’s HAL is a health-based reference level for public drinking water as supplied to customers and is not applied to source (raw) water. Groundwater-age data were compared for sites sampled in 2000, 2008, and 2018 to document any changes.
All samples were analyzed for 18 PFAS using EPA Method 537 (modified). Forty-four percent of the analyzed PFAS were detected in the study well network. Sixteen of the sampled wells have one or more PFAS detections, and as many as eight different PFAS were found in a single sample. Wells with a higher number of PFAS detected (five or more) were in New Castle and Sussex Counties. The PFAS most frequently detected were PFOA, with 47 percent detection; perfluorohexanoic acid (PFHxA), with 33 percent detection; and PFOS and perfluorohexane sulfonate (PFHxS), with 27 percent detection each. PFAS concentrations were below 1,000 parts per trillion (ppt). Two wells exceeded the EPA’s lifetime-drinking water health advisory level of 70 ppt for combined concentrations of PFOA and PFOS.
The average age of groundwater entering the screens of the supply wells sampled in 2018 ranged from 8.2 to 45.8 years, with a median groundwater age of 25.7 years. Groundwater age was positively correlated with well depth and negatively correlated with dissolved oxygen. Groundwater age and PFAS concentrations were negatively correlated in the Columbia aquifer. Data from the 23 resampled wells indicate a significant positive difference in the average modeled groundwater-sample-age results. The average groundwater age from samples collected in 2018 was generally 5 years older than the average groundwater age from samples collected in 2008. The same pattern was found during cycle two (2008) of this study, where the 2008 groundwater age was on average 7 years older than the samples collected in 2000. The distribution of groundwater sample ages among the 17 trend wells and during the three study cycles (2000, 2008, and 2018) indicates that sample-age medians were statistically different from zero; well-water sample-age data show a slight increase in groundwater sample age.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211109","collaboration":"Prepared in cooperation with the Delaware Geological Survey and Delaware Department of Natural Resources and Environmental Control","usgsCitation":"Reyes, B., 2021, Occurrence and distribution of PFAS in sampled source water of public drinking-water supplies in the surficial aquifer in Delaware, 2018; PFAS and groundwater age-dating results: U.S. Geological Survey Open-File Report 2021–1109, 27 p., https://doi.org/10.3133/ofr20211109.","productDescription":"Report: vii, 27 p.; Data Release; Database","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122437","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":392630,"rank":7,"type":{"id":39,"text":"HTML 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\"}}]}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
Leavenworth Creek, a tributary of South Clear Creek and Clear Creek near Georgetown, Colorado, contains copper, lead, and zinc at concentrations close to or in excess of aquatic-life standards. In the summer of 2012, the U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service and the Colorado Division of Reclamation, Mining and Safety, conducted monitoring to (1) quantify the effects of diel cycling and perform synoptic sampling in a way to minimize those effects, (2) separate “point” or distinct single tributaries or sources of load from diffuse load sources along the study reach to aid remediation planning, and (3) quantify metal loading from transmountain diversion of water from Peru Creek through the Vidler Tunnel into Leavenworth Creek. The study included monitoring for diel cycles in June 2012 and diel and synoptic sampling in August 2012 along an approximately 2-kilometer stream reach. Synoptic samples were collected at 26 stream and 35 inflow, tributary, mine waste seep, and mine tunnel sites from August 28 to 30, 2012.
In June 2012, temperature, dissolved oxygen, and pH showed strong diel signals at two sites in Leavenworth Creek, with temperature and pH having minimum values near dawn and maximum values during the afternoon and dissolved oxygen having maximum values in the early morning and minimum values in late afternoon. Concentrations of zinc, cadmium, cobalt, manganese, and yttrium showed strong diel fluctuations at both sites with minimum concentrations during daytime and maximum concentrations during nighttime. Because of these diel cycles, all stream sites were sampled during synoptic sampling at 1200 hours on August 30, 2012. During synoptic sampling from August 28 to 30, 2012, zinc showed maximum concentrations at nighttime and minimum concentrations at midday and diel variation ranged from 26 to 33 percent.
Inflows from the Wilcox Tunnel and Waldorf seep area were the greatest source of zinc load to the stream (about 45 percent), and a left-bank inflow in the dispersed tailings area was the greatest source of lead (about 45 percent) and manganese (about 25 percent) loads to the stream, and a secondary source for zinc (about 40 percent). Copper load was almost equally divided (about 35 percent) between these two sources. Diffuse loading, likely from left-bank sources, was evident for copper, lead, manganese, and zinc in the stream reach from approximately 800 to 1,200 meters, and for copper, lead, and, to a lesser extent, manganese in the reach containing left-bank dispersed tailings (from approximately 1,300 to 1,800 meters). The load values reported herein are minimum estimates because the stream synoptic samples were collected at 1200 hours when positively charged elements, including copper, lead, manganese, and zinc, have minimum concentrations. Diel patterns measured for zinc during the synoptic sampling indicate maximum daily zinc loads were as much as 33 percent greater than those measured at 1200 hours on August 30, 2012.
Transmountain diversion of water through Vidler Tunnel negatively affects water quality in Leavenworth Creek as indicated by much greater metal loads and concentrations and a visually evident mixing zone where Vidler Tunnel water joins Leavenworth Creek when diversion is active compared to when it is not.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211078","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Forest Service and the Colorado Division of Reclamation, Mining and Safety","usgsCitation":"Walton-Day, K., Runkel, R.L., Smith, C.D., and Kimball, B.A., 2021, Quantification of metal loading using tracer dilution and instantaneous synoptic sampling and importance of diel cycling in Leavenworth Creek, Clear Creek County, Colorado, 2012: U.S. Geological Survey Open-File Report 2021–1078, 37 p., https://doi.org/10.3133/ofr20211078.","productDescription":"Report: viii, 37 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-102543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":392247,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGC2V4","text":"USGS data release","linkHelpText":"Stream discharge, sodium, bromide, and specific conductance data for stream and hyporheic zone samples affected by injection of sodium bromide tracer, Leavenworth Creek, Clear Creek County, Colorado, August 2012"},{"id":392246,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1078/ofr20211078.pdf","text":"Report","size":"5.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1078"},{"id":392245,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1078/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Clear Creek County","otherGeospatial":"Leavenworth Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.86219787597655,\n 39.595371402863655\n ],\n [\n -105.69602966308594,\n 39.595371402863655\n ],\n [\n -105.69602966308594,\n 39.71405356154611\n ],\n [\n -105.86219787597655,\n 39.71405356154611\n ],\n [\n -105.86219787597655,\n 39.595371402863655\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021).
Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts.
The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information.
The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are:
(1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time.
Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise.
(2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced.
Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate.
(3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts.
Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity.
The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211102","usgsCitation":"Keisman, J.L., Bristol, S., Brown, D.S., Flickinger, A.K., Gunther, G., Murdoch, P.S., Musgrove, M., Nelson, J.C., Steyer, G.D., Thomas, K.A., and Waite, I.R., 2021, Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2021-1102, 110 p., https://doi.org/10.3133/ofr20211102.","productDescription":"Report: v, 110 p.; Data Release","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-129970","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":392008,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BB5NMZ","linkHelpText":"USGS Earthmap Capacity Assessment Dataset"},{"id":392006,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1102/images"},{"id":392005,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1102/ofr20211102.xml"},{"id":392004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1102/ofr20211102.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":392003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1102/covrthb.jpg"}],"contact":"Director,
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Upper Esopus Creek is the primary tributary to the Ashokan Reservoir, part of the New York City water-supply system. Elevated concentrations of suspended sediment and turbidity in the watershed of the creek are of concern for the system.
Water samples were collected through a range of streamflow and turbidity at 14 monitoring sites in the upper Esopus Creek watershed for analyses of suspended-sediment concentration (SSC) and measurements of turbidity. Analyses of the samples provided data that were used to develop cross-section coefficients and turbidity-SSC regression equations for the monitoring sites for the period October 2016 through September 2019. The equations can be used to estimate SSC at a 15-minute timestep for the monitored sites. The equations can be validated for future use by the collection and analysis of additional data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211065","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Siemion, J., Bonville, D.B., McHale, M.R., and Antidormi, M.R., 2021, Turbidity–suspended-sediment concentration regression equations for monitoring stations in the upper Esopus Creek watershed, Ulster County, New York, 2016–19: U.S. Geological Survey Open-File Report 2021–1065, 27 p., https://doi.org/10.3133/ofr20211065.","productDescription":"Report: vi, 27 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120199","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":391805,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MV3NZ8","text":"USGS data release","linkHelpText":"Suspended-sediment concentration and turbidity data for sites in the upper Esopus Creek watershed New York, 2016–19"},{"id":391807,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1065/images"},{"id":391804,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1065/ofr20211065.pdf","text":"Report","size":"2.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1065"},{"id":391806,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1065/ofr20211065.XML"},{"id":391803,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1065/coverthb.jpg"}],"country":"United States","state":"New York","county":"Ulster County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-73.9109,42.1271],[-73.916,42.1199],[-73.9245,42.1019],[-73.9311,42.082],[-73.93,42.0765],[-73.9302,42.0679],[-73.9341,42.0575],[-73.937,42.0398],[-73.9347,42.0293],[-73.9331,42.0216],[-73.9436,41.9913],[-73.9504,41.9664],[-73.9556,41.9528],[-73.9551,41.9464],[-73.954,41.9401],[-73.9567,41.9301],[-73.9625,41.9179],[-73.9639,41.9138],[-73.9609,41.9088],[-73.9423,41.8827],[-73.9389,41.8704],[-73.939,41.8654],[-73.9423,41.8596],[-73.9448,41.8559],[-73.9461,41.851],[-73.9477,41.8346],[-73.9463,41.8142],[-73.9504,41.7979],[-73.9488,41.7847],[-73.946,41.7719],[-73.9414,41.7592],[-73.9408,41.7592],[-73.938,41.7469],[-73.9389,41.7337],[-73.9424,41.7142],[-73.9439,41.6993],[-73.9411,41.6884],[-73.9513,41.6149],[-73.9525,41.59],[-73.9999,41.5855],[-74.0521,41.5816],[-74.0575,41.5926],[-74.0677,41.604],[-74.0886,41.5988],[-74.0983,41.6089],[-74.1246,41.6133],[-74.1325,41.6152],[-74.1282,41.5833],[-74.1858,41.5944],[-74.187,41.5908],[-74.1907,41.5913],[-74.2458,41.6036],[-74.25,41.6059],[-74.2502,41.6291],[-74.2606,41.6337],[-74.2667,41.6324],[-74.2754,41.6284],[-74.281,41.6257],[-74.2989,41.6182],[-74.3156,41.6115],[-74.3187,41.6084],[-74.3404,41.5954],[-74.3521,41.5982],[-74.3583,41.5938],[-74.3675,41.5916],[-74.3681,41.5961],[-74.3705,41.597],[-74.3736,41.5975],[-74.376,41.5994],[-74.3772,41.6044],[-74.3807,41.6117],[-74.3843,41.6167],[-74.3873,41.6217],[-74.3884,41.6299],[-74.392,41.6345],[-74.3926,41.6399],[-74.3943,41.6458],[-74.4004,41.6486],[-74.4449,41.6726],[-74.4833,41.6942],[-74.5755,41.7453],[-74.4892,41.8377],[-74.4573,41.8747],[-74.5124,41.8992],[-74.6363,41.9542],[-74.7235,41.9915],[-74.78,42.0182],[-74.667,42.0697],[-74.5538,42.1212],[-74.5312,42.1464],[-74.504,42.1449],[-74.4516,42.1694],[-74.3077,42.1142],[-74.2496,42.1095],[-74.0767,42.0968],[-74.0424,42.1682],[-74.0259,42.1621],[-74.0054,42.1642],[-74.0038,42.18],[-73.9189,42.1286],[-73.9109,42.1271]]]},\"properties\":{\"name\":\"Ulster\",\"state\":\"NY\"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Anas acuta (Northern pintail; hereafter pintail) was selected as a model species on which to base a decision-support framework linking regional actions to continental-scale population and harvest objectives. This framework was then used to engage stakeholders, such as Landscape Conservation Cooperatives’ (LCCs’) habitat management partners within areas of importance to pintails, while maximizing cross-taxa effects from the framework. The mathematical framework for the model had been previously developed for pintails. A key assumption incorporated into the model is that density dependence in survival occurs during the post-hunting (winter) period, where resources are hypothesized to be limiting. Because few data are available to directly inform this process, the approach used was to build a hierarchical Bayesian integrated population model (IPM) that simultaneously uses data from bird-band recoveries, breeding population counts, and harvest surveys to estimate values of parameters of an annual population projection model, including population size, survival rate, reproductive rate, and process and observation error variances, that are logically consistent with each other, given the mathematical structure imposed through the IPM.
The main accomplishments of this study are (1) development of an IPM for pintail to guide harvest and habitat management, (2) development of a Prairie Parkland Region breeding submodel to predict pintail productivity, (3) development of statistical methodology to estimate pintail productivity (as measured by the ratio of juvenile to adults in hunter-collected wing samples) and winter survival and to relate these estimates to covariates, and (4) illustration of how to use a model and estimated parameter values to predict pintail population size and sustainable harvest as a function of habitat.
Estimation of pintail survival from bird-banding data shows that there has been relatively little variation in survival over the period 1960–2013. A productivity model showed strong effects of breeding ground conditions, wintering-ground precipitation, and density dependence on pintail productivity. Thus, most temporal variation in pintail demographic rates has been due to effects on reproduction and not survival, including effects of breeding or wintering-ground habitat. These results indicate that habitat conservation efforts may be most effective if they focus on maintaining or increasing breeding and wintering-ground habitat to increase pintail productivity rather than pintail survival. Environmental perturbations in excess of historical experience, such as what could occur under climate change, might have meaningful effects on survival but cannot be estimated with current data. Direct effects of climate, land use, or management are likely to be greater on productivity than survival, but substantial uncertainty remains about predictions of equilibrium population size and sustainable yield.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201084","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Osnas, E.E., Boomer, G.S., Devries, J.H., and Runge, M.C., 2021, Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species: U.S. Geological Survey Open-File Report 2020–1084, 31 p., https://doi.org/10.3133/ofr20201084.","productDescription":"Report: vi, 31 p.; Data Release","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-083951","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":391433,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93YTR3X","text":"USGS data release","linkHelpText":"Data release—Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species"},{"id":391431,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1084/coverthb.jpg"},{"id":391432,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1084/ofr20201084.pdf","text":"Report","size":"6.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1084"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
The Digital Shoreline Analysis System version 5 software is an add-in to Esri ArcGIS Desktop version 10.4–10.7 that enables a user to calculate rate-of-change statistics from a time series of vector shoreline positions. The Digital Shoreline Analysis System provides an automated method for establishing measurement locations, performs rate calculations, provides the statistical data necessary to assess the reliability of the rates, and includes a beta model for forecasting shoreline position. The Digital Shoreline Analysis System version 5.1 includes updates to the interface and the application of proxy-datum bias. This in-depth user guide provides comprehensive instruction on the installation and use of the program, including how to create a reference baseline for measurements, steps needed to generate measurement transects and metadata, guidelines on how to manually add or edit existing transects, and an explanation of the visualization options to display calculated rates of shoreline change.
Note: As of May 2024, the current version of the Digital Shoreline Analysis System (DSAS), version 6.0, is a standalone desktop application for calculating shoreline or boundary change over time. The user guide for DSAS version 5.1 is applicable to many aspects of version 6.0. The user guide provides relevant information on the DSAS workflow, including how to define a reference baseline for measurements, attribute requirements for baselines and shorelines, and supporting information on rate calculations and statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211091","usgsCitation":"Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2021, Digital Shoreline Analysis System (DSAS) version 5.1 user guide: U.S. Geological Survey Open-File Report 2021–1091, 104 p., https://doi.org/10.3133/ofr20211091.","productDescription":"Report: xi, 104 p.; Software Release","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123671","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":390774,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas","text":"Digital Shoreline Analysis System (DSAS)"},{"id":390775,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P13WIZ8M","text":"Digital Shoreline Analysis System version 6.0"},{"id":390767,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1091/ofr20211091.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1091"},{"id":390766,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1091/coverthb.jpg"}],"contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
During September and October 2019, the U.S. Geological Survey mapped the shoreface and inner continental shelf offshore of the Rockaway Peninsula in New York using high-resolution chirp seismic reflection and single-beam bathymetry geophysical techniques. The results from this study are important for assessing the Quaternary evolution of the Rockaway Peninsula and determining coastal sediment availability, which is crucial for establishing sediment budgets, understanding sediment dispersal, and managing coastlines. This report presents preliminary interpretations of seismic profiles and maps of shoreface and Holocene sediment thickness from the shoreline to about 2 kilometers offshore. The results indicate that shoreface and Holocene sediment thickness demonstrates zonal variability because of underlying geology and sediment availability. Based on geomorphic features and underlying stratigraphy, the study area is separated into west, west-central, east-central, and east zones. Holocene sediment, which includes the shoreface and seafloor features with positive morphology (for example, nearshore bars, ebb-tide deltas, and sorted bedforms), thickens to the west and may be related to accommodation and westward dip of the regional unconformity. Shoreface units, which are thought to represent the active volume of littoral sediment, are thickest in the west-central peninsula where the geologic base of the shoreface is deeper. Shoreface units with moderate thickness are in the western and eastern peninsula where there are positive morphological features (for example, deposits accumulating updrift from the jetty, ebb-tide deltas, and so on). The thinnest shorefaces are in the east-central Rockaway Peninsula because of less accommodation caused by the shoaling regional unconformity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211100","collaboration":"Prepared in cooperation with the National Fish and Wildlife Foundation","usgsCitation":"Wei, E.A., Miselis, J.L., and Forde, A.S., 2021, Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York: U.S. Geological Survey Open-File Report 2021–1100, 14 p., https://doi.org/10.3133/ofr20211100.","productDescription":"Report: iv, 14 p.; 2 Data Releases","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125818","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":391426,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211100/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391345,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1100/images/"},{"id":391343,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZO8QKJ","linkHelpText":"Archive of chirp subbottom profile data collected in 2019 from Rockaway Peninsula, New York"},{"id":391346,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.XML"},{"id":391344,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WNJSFN","linkHelpText":"Coastal bathymetry and backscatter data collected in September and October 2019 from Rockaway Peninsula, New York"},{"id":391342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.pdf","text":"Report","size":"11.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1100"},{"id":391341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1100/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Rockaway Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.76152038574219,\n 40.57067539946112\n ],\n [\n -73.74229431152344,\n 40.593620934177494\n ],\n [\n -73.76083374023438,\n 40.59414233212419\n ],\n [\n -73.82469177246094,\n 40.58527801407785\n ],\n [\n -73.8885498046875,\n 40.563372896916164\n ],\n [\n -73.92974853515625,\n 40.549287249082035\n ],\n [\n -73.94622802734375,\n 40.53937335015618\n ],\n [\n -73.9441680908203,\n 40.529979881843865\n ],\n [\n -73.92974853515625,\n 40.526326510744006\n ],\n [\n -73.883056640625,\n 40.53311118427234\n ],\n [\n -73.83018493652344,\n 40.54772199417569\n ],\n [\n -73.77388000488281,\n 40.56389453066509\n ],\n [\n -73.76152038574219,\n 40.57067539946112\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
This report provides a step-by-step method for compiling hydraulic fracturing data in the United States from the IHS Markit, 2019, U.S. Well History and Production Relational Database. Data on hydraulically fractured wells include their location (geologic province, State, county), well type (oil or gas), orientation (directional, horizontal, or vertical), spud date, completion date and the hydraulic fracturing treatments, treatment fluids types, treatment fluid volumes, additive types, agent types (“proppants”), and proppant amounts injected. This method also describes how to associate each unique well with the hydraulic fracturing treatments to provide an indication of the total amount of all treatment fluids injected into a well for hydraulic fracturing and the volume of each individual treatment fluid type injected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211090","usgsCitation":"Varela, B.A., and Gallegos, T.J., 2021, Method for compiling temporally and spatially aggregated data on hydraulic fracturing—Treatments and wells: U.S. Geological Survey Open-File Report 2021–1090, 30 p., https://doi.org/10.3133/ofr20211090.","productDescription":"vi, 30 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118145","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":436123,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P933SF16","text":"USGS data release","linkHelpText":"Spatial and Temporal Data on Hydraulic Fracturing Fluid Types and Amounts Injected into Oil and Gas Wells Across the U.S., 2015-2019"},{"id":391203,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1090/coverthb.jpg"},{"id":391204,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1090/ofr20211090.pdf","text":"Report","size":"730 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1090"}],"contact":"Geology, Energy and Minerals Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Improving the probability of detecting invasive giant snakes is vital for the management of emerging or established populations. Burmese pythons occupy thousands of square kilometers of mostly inaccessible habitats in Florida. Environmental DNA (eDNA) methods have been shown to be time and cost effective in a number of systems and may be preferable to traditional detection methods for constrictor snakes, having been shown to be effective at detecting Burmese pythons where traditional and novel detection methods have failed. The purposes of this study were (1) to estimate Burmese python eDNA occurrence in the Greater Everglades Ecosystem based on land-use type; and (2) to conduct preliminary surveys within the Greater Everglades Ecosystem for positive eDNA detections. Twenty-eight sites were sampled in the Greater Everglades Ecosystem, with 5 field replicate samples per site, for a total of 140 water samples collected. Python eDNA was detected in samples from 25 of the 28 sites by using droplet digital polymerase chain reaction amplification. Abiotic parameters were collected and explored, but we found no conclusive relationship among them and python eDNA detections. eDNA monitoring of aquatic habitats can assist in identifying newly colonized areas where pythons have not been previously detected, as well as movement corridors and pathways of dispersal. This information could be used to delimit a population boundary as it expands further to the north in peninsular Florida.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211082","usgsCitation":"Beaver, C.E., Meigs-Friend, G., and Hunter, M.E., 2021, Environmental DNA surveys of Burmese pythons in the Greater Everglades Ecosystem: U.S. Geological Survey Open-File Report 2021–1082, 17 p., https://doi.org/10.3133/ofr20211082.","productDescription":"Report: vi, 17 p.; Data Releases","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-122212","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":390968,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HVM4VQ","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Droplet digital PCR data for environmental DNA surveys of Burmese pythons in the Greater Everglades Ecosystem"},{"id":390967,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1082/ofr20211082.pdf","text":"Report","size":"1.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1082"},{"id":390966,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1082/coverthb.jpg"},{"id":390969,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1082/images"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.84814453125,\n 25.552353652165465\n ],\n [\n -80.87585449218749,\n 24.946219074360055\n ],\n [\n -80.2001953125,\n 25.199970890386\n ],\n [\n -79.8211669921875,\n 26.701452590314393\n ],\n [\n -82.15576171875,\n 26.598351182358265\n ],\n [\n -81.84814453125,\n 25.552353652165465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
The stratigraphy, water-bearing zones, and quality of groundwater were characterized in a 1,400-ft-deep test hole drilled during 2013 in fractured bedrock in Sullivan County, Pa., by collection and analysis of measurements made during drilling, geophysical logs, and depth-specific hydraulic tests and water samples. The multidisciplinary characterization of the test hole was a cooperative effort between the Pennsylvania Department of Natural Resources, Bureau of Geological Survey (BGS), and the U.S. Geological Survey (USGS). The study provided information to aid the bedrock mapping of the Laporte 7.5-minute quad-rangle by BGS to help quantify the depth and character of fresh and saline groundwater in an area of shale-gas exploration (described in this report), which could help gas operators protect groundwater resources.
The Laporte test hole was drilled with air-hammer methods in an upland setting in the headwaters of Loyalsock Creek in the Glaciated High Plateau section of the Appalachian Plateaus physiographic province. Bedrock residuum and till were penetrated from land surface to 8.5 ft, the Huntley Mountain Formation of Mississippian and Devonian age was penetrated from 8.5 to 540 ft, and the Catskill Formation of Devonian age was penetrated from 540 to 1,400 ft. Fractures, determined from optical televiewer, acoustic televiewer, and video logs, were commonly encountered to 200 ft bls (below land surface), then decreased exponentially with depth, except at a highly fractured zone from 637 to 644 ft bls. Most fractures were along bedding planes and had a strike of about 243 degrees and dip about 4 degrees to the northwest, consistent with the test-hole location on the north limb of the Muncy Creek anticline. Few fractures were noted below 650 ft.
The depths of fresh and saline water-bearing fracture zones were identified in the test hole by geophysical-log analysis and were verified by pumping samples from zones isolated with packers and by collecting samples in the open hole with a wire-line point sampler. Six water-bearing zones associated with single or multiple fractures were identified at depths of 130–135, 180, 267–275, 425, 637–644, and 1,003 ft bls. Under ambient conditions, fresh water entered the hole from fractures at 130-135 and 180 ft bls, flowed downward and exited at fractures from 267–275, 425, and 637–644 ft. When pumped at 16.2 gal/min, most of the water from the open test hole was contributed from the fracture at 180 ft bls. Transmissivity, estimated from analysis of the specific-capacity data and flowmeter logs, is about 850 ft2/d for the entire open hole, and about 60 percent of the transmissivity is contributed from the fracture zone at 180 ft bls. The hydraulic heads in the deep water-bearing zones at 425 and 637–644 ft were about 100 ft lower than hydraulic heads in shallow water-bearing zones at 180 ft bls and above, indicating a large downward vertical hydraulic gradient.
Water samples pumped from fracture zones isolated by packers at and above the water-bearing zone at 450 ft bls were fresh with dissolved-solids contents of 105 mg/L or less. The sample isolated at 637–644 ft bls was probably affected by leakage around packers, but the specific-conductance samples collected during drilling that were believed to be representa-tive of the fracture zone at 637–644 ft bls indicated slightly saline water. Below the 637–644 ft zone, a flowmeter log in the open hole did not detect any vertical flow, and the temperature log approached the geothermal gradient, indicating little ambient fluid flow and minimal fracture transmissivity below this depth. A petrophysical-log analysis using estimates of formation water resistivity from Archie’s Equation indicated an apparent transition from fresh to saline water in the sandstones occurs between 450 to 900 ft bls, with saline water indicated below 900 ft.
Small seeps of saline water were delineated at 958, 989, and 1,003 ft bls by a time series of specific-conductance logs, and a discrete-point water sample at 990 ft bls with total dissolved-solids concentration of 19,900 mg/L verified that highly saline water was present below 900 ft bls. Occurrence of saline water at a depth of about 900 ft bls is below altitude of streams within 3 to 5 miles of the test hole but is about 930 ft above the altitude at the mouth of Loyalsock Creek where is enters the West Branch Susquehanna River at Montours-ville, Pa. The depth to saline water in this test hole is close to depths estimated at two other deep test holes drilled by the BGS in upland settings in Bradford and Tioga Counties in north-ern Pennsylvania.
The saline water from 990 ft bls had a chemical composition similar to Appalachian Basin brines that had been diluted with fresh water. Predominant ions in the saline water were sodium, chloride, and calcium. Trace constituents of strontium, bromide, barium, lithium, and molybdenum were all more than 5,000 times greater than in freshwater samples from 167 or 270 ft bls. Methane concentration in the saline water sample from 990 ft was 120 mg/L. The concentration ratios of methane to higher-chain hydrocarbon gases and isotopic ratios of 13C/12C and 2H/1H of methane indicate that the gases are likely of thermogenic origin. In the sample from 990 ft bls, the 13C/12C of methane was less negative (-34.81 per mil) than 13C/12C of ethane (-37.1 per mil). Isotopic reversals such as this are generally found in gases from rocks older than the Catskill Formation, so its recognition in a natural upland setting at relatively shallow depth could be important when interpreting isotopic results to identify the origin of stray gas in the area.
","language":"English","publisher":"Pennsylvania Geological Survey","usgsCitation":"Risser, D.W., Williams, J., and Bierly, A.D., 2021, Geohydrologic and water-quality characterization of a fractured-bedrock test hole in an area of Marcellus Shale gas development, Sullivan County, Pennsylvania: Open-File Report OFMI 21-02.0, xii, 56 p.","productDescription":"xii, 56 p.","ipdsId":"IP-107313","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":393593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":393564,"type":{"id":15,"text":"Index Page"},"url":"https://maps.dcnr.pa.gov/publications/Default.aspx?id=995"}],"country":"United States","state":"Pennsylvania","county":"Sullivan County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.61453247070312,\n 41.28967402411714\n ],\n [\n -76.37832641601562,\n 41.28967402411714\n ],\n [\n -76.37832641601562,\n 41.46742831254425\n ],\n [\n -76.61453247070312,\n 41.46742831254425\n ],\n [\n -76.61453247070312,\n 41.28967402411714\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Risser, Dennis W. 0000-0001-9597-5406 dwrisser@usgs.gov","orcid":"https://orcid.org/0000-0001-9597-5406","contributorId":898,"corporation":false,"usgs":true,"family":"Risser","given":"Dennis","email":"dwrisser@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bierly, Aaron D.","contributorId":270527,"corporation":false,"usgs":false,"family":"Bierly","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":16182,"text":"Pennsylvania Geological Survey","active":true,"usgs":false}],"preferred":false,"id":829530,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70225614,"text":"ofr20211030G - 2021 - System characterization report on Resourcesat-2 Advanced Wide Field Sensor","interactions":[{"subject":{"id":70225614,"text":"ofr20211030G - 2021 - System characterization report on Resourcesat-2 Advanced Wide Field Sensor","indexId":"ofr20211030G","publicationYear":"2021","noYear":false,"chapter":"G","displayTitle":"System Characterization Report on Resourcesat-2 Advanced Wide Field Sensor","title":"System characterization report on Resourcesat-2 Advanced Wide Field Sensor"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2024-08-30T10:49:11.047682","indexId":"ofr20211030G","displayToPublicDate":"2021-10-28T14:32:18","publicationYear":"2021","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":"2021-1030","chapter":"G","displayTitle":"System Characterization Report on Resourcesat-2 Advanced Wide Field Sensor","title":"System characterization report on Resourcesat-2 Advanced Wide Field Sensor","docAbstract":"This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Advanced Wide Field Sensor (AWiFS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2 is a medium-resolution satellite launched in 2011 on the Polar Satellite Launch Vehicle-C16. Resourcesat-2 carries the same sensing elements as Resourcesat-1 (launched in October 2003) and provides continuity for the mission. The objectives of the Resourcesat mission are to provide remote sensing data services to global users, focusing on data for integrated land and water resources management.
Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 launch vehicle for continuity of data and improved temporal resolution. The two satellites operating in tandem improved the revisit capability from 5 days to 2–3 days. The Resourcesat-2 platform is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that AWiFS has an interior geometric performance in the range of −16.080 (−0.268 pixel) to 35.520 meters (m; 0.592 pixel) in easting and −25.680 (−0.428 pixel) to 23.400 m (0.390 pixel) in northing in band-to-band registration, an exterior geometric error of −64.262 (−1.071 pixels) to −19.059 m (−0.318 pixel) in easting and −29.028 (−0.484 pixel) to 41.249 m (0.687 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 2.29–2.36 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.030–0.035.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030G","usgsCitation":"Ramaseri Chandra, S.N., Kim, M., Christopherson, J., Stensaas, G.L., and Anderson, C., 2021, System characterization report on Resourcesat-2 Advanced Wide Field Sensor, chap. G of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors (ver. 1.2, August 2024): U.S. Geological Survey Open-File Report 2021–1030, 17 p., https://doi.org/10.3133/ofr20211030G.","productDescription":"Report: iv, 17 p.; Version History","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-126658","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":392291,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/g/versionHist.txt","text":"Version History","size":"1.8 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2021–1030G Version History"},{"id":391064,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/g/images"},{"id":391063,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/g/ofr20211030g.xml","text":"Report","size":"79.7 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1030G xml"},{"id":433255,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/g/ofr20211030g.pdf","text":"Report","size":"2.2 MB","description":"OFR 2021–1030G"},{"id":391061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/g/coverthb3.jpg"}],"edition":"Version 1.0: September 28, 2021; Version 1.1: November 30, 2021; Version 1.2: August 29, 2024","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
A telemetry study was conducted during August–December 2020 to evaluate behavior and movement patterns of adult smallmouth bass (Micropterus dolomieu) in the forebay of Bonneville Dam, Washington. A total of 40 smallmouth bass were collected, tagged, and released during August–September in seven distinct areas of the dam forebay and monitored until mid-December. Movement data from 36 tagged smallmouth bass were used in behavior analyses with an average detection duration (elapsed time from release to last detection) of 53.3 days. Nine smallmouth bass eventually moved upstream out of the array and sixteen smallmouth bass moved downstream out of the array. Smallmouth bass showed high site fidelity, primarily remaining within their zone of release or moving into nearby adjacent zones. Tagged smallmouth bass spent the greatest percentage of time in their zone of release in all zones except the Boat Rock zone; the five smallmouth bass released in the Boat Rock zone moved to the Goose Island zone, where they stayed most of their time. Smallmouth bass movements to zones farthest away from their zone of release were not common and smallmouth bass residence time in those zones was short. A large percentage of tagged smallmouth bass moved among three zones located immediately upstream from the Bonneville Dam spillway, which was not operated during the study. Results from the study provided new insights into smallmouth bass behavior patterns during fall months in the forebay of Bonneville Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211099","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., Hansen, G.S., and Evans, S.D., 2021, Behavior and movement of smallmouth bass (Micropterus dolomieu) in the forebay of Bonneville Dam, Columbia River, August–December 2020: U.S. Geological Survey Open-File Report 2021–1099, 13 p., https://doi.org/10.3133/ofr20211099.","productDescription":"vii, 13 p.","onlineOnly":"Y","ipdsId":"IP-127395","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":403444,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211099/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2021-1099"},{"id":391094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1099/coverthb.jpg"},{"id":391095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1099/ofr20211099.pdf","text":"Report","size":"26.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1099"},{"id":397378,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1099/images"},{"id":397379,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1099/ofr20211099.XML"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Bonneville Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.97381973266602,\n 45.624362920967556\n ],\n [\n -121.91717147827148,\n 45.624362920967556\n ],\n [\n -121.91717147827148,\n 45.65736777757339\n ],\n [\n -121.97381973266602,\n 45.65736777757339\n ],\n [\n -121.97381973266602,\n 45.624362920967556\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
Land-surface deformation (subsidence) caused by groundwater withdrawal is identified as an undesirable result in the Pajaro Valley Water Management Agency’s Basin Management Plan and California’s Sustainable Groundwater Management Act. In Pajaro Valley, groundwater provides nearly 90 percent of the total water supply. To aid the development of sustainable groundwater management criteria, the U.S. Geological Survey, in cooperation with the Pajaro Valley Water Management Agency, performed an analysis of land-surface deformation (subsidence and uplift) in Pajaro Valley for 2015–18, using Interferometric Synthetic Aperture Radar and continuous Global Positioning System methods. Land-surface deformation results were then compared with subsurface geology and groundwater altitudes to better understand the hydromechanical response of the coastal aquifer system. The results indicate the land surface is generally stable with only small magnitudes (less than 1 inch) of seasonal land-surface deformation (subsidence in the summer and uplift in the winter) during 2015–18. During this time, the largest magnitude of land-surface deformation was less than 2 inches of subsidence and was localized in one area just north of the city limits of Watsonville, California. Groundwater altitudes during 2015–18 demonstrated seasonal variability and annual to multi-annual increases after reaching historical lows by the mid-1990s. The small magnitudes of land-surface deformation coupled with groundwater-altitude increases in most areas indicate that the subsidence likely is largely elastic and recoverable. The Corralitos-Pajaro Valley groundwater basin contains fine-grained (clay) sediments that have the potential for permanent aquifer-system compaction and resultant land subsidence. However, groundwater altitudes throughout the Pajaro Valley have increased above historical lows, and observed increases in groundwater altitudes coincided with changes in groundwater management activities. Observed relations between groundwater management activities and groundwater altitudes indicate that management of groundwater supplies could minimize the potential for permanent land-surface deformation in Pajaro Valley.
","language":"English","publisher":"U.S. Geological","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211101","collaboration":"Prepared in cooperation with the Pajaro Valley Water Management Agency","programNote":"Water Availability and Use Science Program","usgsCitation":"Brandt, J.T., Earll, M.M., Sneed, M., and Henson, W., 2021, Detection and measurement of land-surface deformation, Pajaro Valley, Santa Cruz and Monterey counties, California, 2015–18: U.S. Geological Survey Open-File Report 2021–1101, 16 p., https://doi.org/10.3133/ofr20211101.","productDescription":"Report: vi, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","ipdsId":"IP-118756","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":390883,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FNARQO","linkHelpText":"Interferometric Synthetic Aperture Radar and Water Level Data, Pajaro Valley, Santa Cruz and Monterey Counties, California, 1970–2018"},{"id":390882,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1101/images"},{"id":390881,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1101/ofr20211101.xml"},{"id":390880,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1101/ofr20211101.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":390879,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1101/covrthb.jpg"}],"country":"United States","state":"California","county":"Monterey County, Santa Cruz County","otherGeospatial":"Pajaro Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.89468383789061,\n 36.71356812817935\n ],\n [\n -121.57058715820312,\n 36.71356812817935\n ],\n [\n -121.57058715820312,\n 36.97074107796435\n ],\n [\n -121.89468383789061,\n 36.97074107796435\n ],\n [\n -121.89468383789061,\n 36.71356812817935\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Linear Imaging Self Scanning-3 (LISS–3) sensor and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2 is a medium-resolution satellite launched in 2011 on the Polar Satellite Launch Vehicle-C16 launch vehicle. Resourcesat-2 carries the same sensing elements as Resourcesat-1 (launched in October 2003) and provides continuity for the mission. The objectives of the Resourcesat mission are to provide remote sensing data services to global users, focusing on data for integrated land and water resources management.
Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 launch vehicle for continuity of data and improved temporal resolution. The two satellites operating in tandem improved the revisit capability from 5 days to 2–3 days. The Resourcesat-2 platform is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Advanced Wide Field Sensor and LISS–3, as well as the Linear Imaging Self Scanning-4 for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that LISS–3 has an interior geometric performance in the range of −4.620 (−0.154 pixel) to 13.230 meters (m; 0.441 pixel) in easting and −12.360 (−0.412 pixel) to 1.500 m (0.050 pixel) in northing in band-to-band registration, an exterior geometric error of −27.805 (−0.927 pixel) to 26.578 m (0.886 pixel) in easting and −35.341 (−1.178 pixel) to −6.286 m (−0.210 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.096 to 0.036 in offset and 0.585–0.946 in slope, and a spatial performance in the range of 1.87–1.95 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.045–0.070.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030H","usgsCitation":"Ramaseri Chandra, S.N., Christopherson, J., Anderson, C., Stensaas, G.L., and Kim, M., 2021, System characterization report on Resourcesat-2 Linear Imaging Self Scanning-3 (LISS–3) sensor (ver. 1.2, December 2024), chap. H of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 20 p., https://doi.org/10.3133/ofr20211030H.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-126659","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":433262,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/h/versionHist.txt","text":"Version History","size":"2.07 KB","linkFileType":{"id":2,"text":"txt"}},{"id":390427,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/h/images"},{"id":390426,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/h/ofr20211030h.xml","size":"75.7 kB","linkFileType":{"id":8,"text":"xml"}},{"id":390425,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/h/ofr20211030h.pdf","text":"Report","size":"3.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–H"},{"id":390424,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/h/coverthb4.jpg"},{"id":464526,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030H/full"}],"edition":"Version 1.0: October 21, 2021; Version 1.1: August 29, 2024; Version 1.2: December 2, 2024","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The U.S. Geological Survey, at the request of the U.S. Agency for International Development, led a 5-year regional project to develop and apply methods for water availability and suitability mapping for managed aquifer recharge (MAR) in the Middle East and North Africa region. A regional model of surface runoff for the period from 1984 to 2015 was developed to characterize water availability using remote sensing data on climate, vegetation, and topography in Jordan, Lebanon, and surrounding areas. Surface runoff was accumulated to characterize potential streamflow available for MAR and these data were combined with land surface slope to prepare a regional screening map of MAR suitability, illustrating suitability mapping concepts and methods. The application of the methods is demonstrated by the evaluation of water availability and suitability for potential MAR in study areas in Jordan and Lebanon. Locations suitable for MAR are present in both Jordan and Lebanon, but limitations exist in both countries, related primarily to water availability in Jordan and land areas of suitable terrain in Lebanon. An additional feasibility study including field investigations would likely provide decision makers with essential information for further development of the use of MAR in Jordan, Lebanon, and the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211089","collaboration":"Prepared in cooperation with the U.S. Agency for International Development","usgsCitation":"Goode, D.J., ed., 2021, Managed aquifer recharge suitability—Regional screening and case studies in Jordan and Lebanon: U.S. Geological Survey Open-File Report 2021–1089, 87 p., https://doi.org/10.3133/ofr20211089.","productDescription":"Report: xi, 87 p.; 2 Data Releases","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-124064","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":436143,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WDQ4VF","text":"USGS data release","linkHelpText":"Regional screening for managed aquifer recharge suitability in Jordan, Lebanon, and surrounding areas"},{"id":390660,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/P9WDQ4VF","text":"USGS data release","linkHelpText":"- Regional screening for managed aquifer recharge suitability in Jordan, Lebanon, and surrounding areas"},{"id":389216,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971ZVHF","text":"USGS data release","linkHelpText":"Assembly of satellite-based rainfall datasets in situ data and rainfall climatology contours for the MENA region"},{"id":389217,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TXLT1X","text":"USGS data release","linkHelpText":"Modeling accumulated surface runoff and water availability for aquifer storage and recovery in the MENA region from 1984–2015"},{"id":389215,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1089/ofr20211089.pdf","text":"Report","size":"22.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1089"},{"id":389214,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1089/coverthb.jpg"}],"country":"Jordan, Lebanon","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[35.54567,32.39399],[35.71992,32.70919],[36.83406,32.31294],[38.79234,33.37869],[39.19547,32.16101],[39.00489,32.01022],[37.00217,31.50841],[37.99885,30.5085],[37.66812,30.33867],[37.50358,30.00378],[36.74053,29.86528],[36.50121,29.50525],[36.06894,29.19749],[34.95604,29.35655],[34.9226,29.50133],[35.42092,31.10007],[35.39756,31.48909],[35.54525,31.7825],[35.54567,32.39399]]],[[[35.8211,33.27743],[35.5528,33.26427],[35.46071,33.08904],[35.12605,33.0909],[35.48221,33.90545],[35.97959,34.61006],[35.9984,34.64491],[36.44819,34.59394],[36.61175,34.20179],[36.06646,33.82491],[35.8211,33.27743]]]]},\"properties\":{\"name\":\"Jordan\"}}]}","contact":"U.S. Geological Survey
Office of International Programs
917 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
directoroip@usgs.gov
Trace-metal concentrations in sediment and in the clam Limecola petalum (formerly reported as Macoma balthica and M. petalum), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by the U.S. Geological Survey (USGS) for the period January 2019 to December 2019. These data append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2019 data within the context of the longer, multidecadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving-Water Monitoring Program, initiated in 1994.
Significant reductions in silver and copper contamination occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements in surface sediments have continued to decrease, although more slowly. Silver appears to have stabilized at concentrations about twice the regional background concentration. Presently, sediment copper concentrations appear to be near the regional background level. Over the same period (1994–2019), sedimentary iron and zinc also exhibited modest declines. Sedimentary aluminum, chromium, mercury, nickel, and selenium have not exhibited any trend. Since 1994, concentrations of silver and copper in L. petalum have varied seasonally, apparently in response to a combination of site-specific metal exposures and cyclic growth and reproduction, as reported previously. Seasonal patterns for other elements, including chromium, mercury, nickel, selenium, and zinc, were generally similar in timing and magnitude as those for silver and copper. The annual growth and reproductive cycle explained a small amount of the variance in annual silver and zinc tissue metal concentrations. However, interannual trends are not apparent for any element.
Biological effects of elevated silver and copper contamination at the Palo Alto site have been interpreted from data collected during and after the recession of these contaminants. Concentrations of both elements in the soft tissues of L. petalum declined with sedimentary copper and silver. This pattern was associated with changes in the reproductive activity of L. petalum, as well as the structure of the benthic invertebrate community. Reproductive activity of L. petalum increased as metal concentrations in L. petalum declined and presently is stable with almost all animals initiating reproduction in the fall and spawning the following spring. Analyses of the benthic community structure indicate that the infaunal invertebrate community has shifted from one dominated by several opportunistic species when silver and copper exposures were highest to one in which the species abundance is more evenly distributed, a pattern that indicates a more stable community that is subjected to fewer stressors. Importantly, this long-term change is unrelated to other metals and other measured environmental factors, including salinity and sediment composition. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals. Both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2019. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2019.
An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like L. petalum. However, within two months of this event, animals returned to the mudflat. The resilience of the community suggested that the disturbance was not caused by a persistent toxin or anoxia. The reproductive mode of most species that were present in 2019 was indicative of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2019 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, those that have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211079","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Croteau, M.-N., Thompson, J.K., Parchaso, F., Stewart, R., Shrader, K.H., Zierdt Smith, E.L., and Luoma, S.N., 2021, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2019: U.S. Geological Survey Open-File Report 2021–1079, 59 p., https://doi.org/10.3133/ofr20211079.","productDescription":"Report: viii, 59 p.; Data Release","numberOfPages":"59","onlineOnly":"Y","ipdsId":"IP-119549","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":416178,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","description":"Cain, D.J., Croteau, M.-N., Thompson, J.K., Parchaso, F., Stewart, R., Zierdt Smith, E.L., Shrader, K.H., Kieu, L.H., and Luoma, S.N., 2023, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2020: U.S. Geological Survey Open-File Report 2023–1017, 51 p., https://doi.org/10.3133/ofr20231017.","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":390272,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California; 2016"},{"id":390273,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California; 2015"},{"id":390267,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IBQ23S","linkHelpText":"Data for monitoring trace metal and benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California"},{"id":390268,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1079/covrthb.jpg"},{"id":390269,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1079/ofr20211079.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":390270,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":390271,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2017"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.16728210449219,\n 37.385980767871416\n ],\n [\n -121.90361022949219,\n 37.385980767871416\n ],\n [\n -121.90361022949219,\n 37.496107562317064\n ],\n [\n -122.16728210449219,\n 37.496107562317064\n ],\n [\n -122.16728210449219,\n 37.385980767871416\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Water Resources, Earth System Processes Division
U.S. Geological Survey
411 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Autonomous underwater vehicles are uniquely designed to provide spatially dense water-quality data along with bathymetry and velocimetry. The U.S. Environmental Protection Agency Region 5 requested technical assistance from the U.S. Geological Survey in support of ongoing investigations at the Chemical Recovery Systems site to collect spatially dense water-quality and bathymetry data in the East Branch Black River in Elyria, Ohio. This report was prepared in cooperation with the U.S. Environmental Protection Agency to present the results of the autonomous underwater vehicle survey near the Chemical Recovery Systems site on March 22, 2021. Plots of distributions of water temperature, specific conductance, pH, and dissolved oxygen are presented that may help guide and focus future U.S. Environmental Protection Agency efforts at the site to determine the degree of groundwater/surface-water interaction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211086","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Wilson, J.L., and Dobrowolski, E.G., 2021, Water-quality distributions in the East Branch Black River near the Chemical Recovery Systems site in Elyria, Ohio, 2021: U.S. Geological Survey Open-File Report 2021–1086, 10 p., https://doi.org/10.3133/ofr20211086.","productDescription":"Report: vii, 10 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-128518","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":390284,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://waterdata.usgs.gov/oh/nwis/uv?site_no=04200500","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS 04200500 Black River at Elyria OH, in USGS water data for the Nation"},{"id":390281,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1086/coverthb.jpg"},{"id":390282,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1086/ofr20211086.pdf","text":"Report","size":"4.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021"},{"id":390283,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FEBCBY","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Autonomous underwater vehicle water-quality and sonar measurements in the East Branch Black River near Elyria, Ohio, 2021"}],"country":"United States","state":"Ohio","city":"Elyria","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.23541259765625,\n 41.2509675141624\n ],\n [\n -81.9635009765625,\n 41.2509675141624\n ],\n [\n -81.9635009765625,\n 41.49623534616764\n ],\n [\n -82.23541259765625,\n 41.49623534616764\n ],\n [\n -82.23541259765625,\n 41.2509675141624\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
On March 12, 2019, Congress passed the John D. Dingell, Jr., Conservation, Management, and Recreation Act (Public Law 116–9; 133 Stat. 580), in which Title V, §5001 (43 U.S.C. 31k) authorized the establishment of the National Volcano Early Warning and Monitoring System (NVEWS) within the U.S. Geological Survey (USGS). Conceived by the USGS Volcano Hazards Program in 2005, NVEWS is designed to be a proactive, fully integrated national-scale volcano monitoring system to ensure that the 161 potentially active volcanoes in the United States and its territories are monitored at levels commensurate with the threat they pose. The core of this report is the first USGS NVEWS five-year management plan, which was presented to Congress on March 12, 2020, and which details the principal elements of NVEWS that will be developed over the next five years, pending sufficient funding. These elements are improvements and enhancements to the monitoring network, a National Volcano Data Center, an external grants activity, an Advisory Committee, an Implementation Committee, and partnerships, with estimated cost projections and annual milestones.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211092","usgsCitation":"Cervelli, P.F., Mandeville, C.W., Avery, V.F., and Wilkins, A.M., 2021, Five-year management plan for establishing and operating NVEWS—The National Volcano Early Warning System: U.S. Geological Survey Open-File Report 2021–1092, 11 p., https://doi.org/10.3133/ofr20211092.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-117913","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":390179,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1092/coverthb.jpg"},{"id":390180,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1092/ofr20211092.pdf","text":"Report","size":"2.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1092"}],"country":"United States","otherGeospatial":"Northern Mariana Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 143.08593749999997,\n 13.410994034321702\n ],\n [\n 146.513671875,\n 13.410994034321702\n ],\n [\n 146.513671875,\n 16.720385051694\n ],\n [\n 143.08593749999997,\n 16.720385051694\n ],\n [\n 143.08593749999997,\n 13.410994034321702\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.55468749999997,\n 17.476432197195518\n ],\n [\n -153.28125,\n 17.476432197195518\n ],\n [\n -153.28125,\n 22.755920681486405\n ],\n [\n -158.55468749999997,\n 22.755920681486405\n ],\n [\n -158.55468749999997,\n 17.476432197195518\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.5078125,\n 31.20340495091737\n ],\n [\n -105.1171875,\n 31.20340495091737\n ],\n [\n -105.1171875,\n 48.922499263758255\n ],\n [\n -125.5078125,\n 48.922499263758255\n ],\n [\n -125.5078125,\n 31.20340495091737\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.328125,\n 69.83962194067463\n ],\n [\n -149.765625,\n 70.95969716686398\n ],\n [\n -155.91796874999997,\n 71.30079291637452\n ],\n [\n -162.94921875,\n 70.4367988185464\n ],\n [\n -166.640625,\n 68.52823492039876\n ],\n [\n -167.34375,\n 65.6582745198266\n ],\n [\n -165.41015625,\n 62.186013857194226\n ],\n [\n -165.41015625,\n 60.23981116999893\n ],\n [\n -164.00390625,\n 58.53959476664049\n ],\n [\n -164.53125,\n 56.07203547180089\n ],\n [\n -164.35546875,\n 53.85252660044951\n ],\n [\n -152.75390624999997,\n 56.84897198026975\n ],\n [\n -149.4140625,\n 59.62332522313024\n ],\n [\n -143.96484375,\n 59.62332522313024\n ],\n [\n -137.4609375,\n 57.42129439209407\n ],\n [\n -131.66015625,\n 52.3755991766591\n ],\n [\n -130.60546875,\n 53.4357192066942\n ],\n [\n -131.66015625,\n 57.326521225217064\n ],\n [\n -136.58203125,\n 59.88893689676585\n ],\n [\n -140.625,\n 60.50052541051131\n ],\n [\n -141.328125,\n 69.83962194067463\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Hazards Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Contact Volcano Hazards Program
","tableOfContents":"The challenges associated with field measurements of turbidity are well known and result primarily from differences in reported values that depend on instrument design and the resulting need for reporting units that are specific to those designs. A critical challenge for making comparable turbidity measurements is the selection and use of appropriate turbidity standards for sensor calibration. The accepted primary standards for turbidity measurements use formazin made from scratch; all others should relate back to readings obtained using standard formazin. However, because turbidity is a qualitative property of water, comparing standards is not as simple as it is for many chemical measurements. The U.S. Geological Survey “National Field Manual for the Collection of Water-Quality Data” currently allows for the use of two standards, formazin and polymer beads, for the calibration of field turbidimeters. Another challenge for making comparable turbidity measurements is selection of turbidity sensors. A turbidity sensor commonly used in the U.S. Geological Survey, the Yellow Springs Instruments (YSI) 6136, has been replaced by the manufacturer with the YSI EXO turbidity sensor. Both sensors operate on the same principles but have slight design differences that result in readings that are not directly comparable on a 1:1 basis.
Differences in calibration standards and sensors are a cause of concern in ongoing studies that require switching calibration standards or sensor types, and for comparisons of data collected with sensors calibrated by using different calibration standards, different sensor types, or both. The objectives of this study were to evaluate the response of two YSI turbidity sensors in both formazin-based standards (StablCal) and polymer turbidity standards (in this case YSI brand; however, other brands are available) and to compare the performance of the YSI EXO and YSI 6136 turbidity sensors under similar laboratory and environmental (field) conditions. To quantify these differences, a series of laboratory and field side-by-side comparisons were conducted. Nine field comparisons of YSI EXO and YSI 6136 sensors were performed at site locations in Kansas and Virginia. Two field comparisons of StablCal and polymer calibration standards were performed in Kansas, both using YSI EXO turbidity sensors. Five laboratory comparisons between the YSI EXO and YSI 6136 turbidity sensors were performed, and seven laboratory comparisons between StablCal and polymer turbidity standards were performed using YSI EXO turbidity sensors. The results can help the USGS and others better understand how turbidity data can differ depending on the sensors and calibration standards used.
Key findings and conclusions include the following—
Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
A U.S. Geological Survey-led assessment of data gaps and science needs across the Great Lakes ecosystem indicated the following:
• Expanded data collection or monitoring would provide basic ecosystem, social, and public health data to manage the Great Lakes system and to develop and test models and decision support tools.
• New science and advanced technologies (for example, sensors and high-performance computing capability) would improve the understanding of critical threats, such as harmful algae blooms and high-water levels.
Although there is significant scientific knowledge in specific areas or for specific topics, managers could use improved models and decision support tools, strengthened by extensive data collection and developed at multiple scales, to better inform decision making in the future. Enhanced coordination of agency efforts and associated data collection across data types (for example, prey fish populations and water levels) is needed to effectively manage the Great Lakes.
This report highlights the data gaps; benefits of better, more structured coordination; and areas of concern specifically related to data collection/measurement and science efforts. It summarizes and analyzes stakeholder feedback and information from review of scientific literature. Finally, the report outlines steps necessary to create an integrated Great Lakes science plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211096","usgsCitation":"Carl, L.M., Hortness, J.E., and Strach, R.M., 2021, U.S. Geological Survey Great Lakes Science Forum—Summary of remaining data and science needs and next steps: U.S. Geological Survey Open-File Report 2021–1096, 4 p., https://doi.org/10.3133/ofr20211096.","productDescription":"iii, 4 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-133589","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":390007,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1096/ofr20211096.xml","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1096 xml"},{"id":390006,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1096/ofr20211096.pdf","text":"Report","size":"655 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1096"},{"id":390005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1096/coverthb.jpg"}],"contact":"Director, Midwest Regional Director’s Office
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
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 an example of a prototype tool for optimizing tidal marsh management decisions for selected marsh management units at the Rachel Carson National Wildlife Refuge in Maine. The goal was to create a prototype that could be available for future implementation. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of seven marsh management units within the refuge and estimated the outcomes of each action in terms of regional 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 could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale.
Management costs were estimated using limited available information, and estimated costs of individual management actions reflected relative differences among actions rather than actual expected expenditures. Results from this prototype showed how, for the objectives, actions, and estimated outcomes used for this example, total management benefits may increase consistently up to a certain estimated cost, and may continue to increase, at a lower rate, with further expenditures. Potential management actions in optimal portfolios at moderate total estimated costs included breaching or removing dikes, roads, or embankments; planting Spartina alterniflora (smooth cordgrass); and digging runnels, or shallow creeks, on the marsh platform to improve surface-water drainage. Potential management actions in optimal portfolios at high estimated costs (for example, up to $550,000) included breaching embankments to restore tidal exchange followed by planting salt marsh vegetation. The potential management benefits were derived from predicted increases in the numbers of tidal marsh obligate birds and spiders (as an indicator of trophic health), and expected improvement in the capacity of marsh elevation to keep pace with sea-level rise and reduced duration of marsh-surface inundation. The prototype presented here does not resolve current management decisions; rather, it provides a framework for decision making at the Rachel Carson National Wildlife Refuge that can be updated for implementation 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/ofr20211080","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., O’Brien, K.M., Benvenuti, B., and Kleinert, R., 2021, Optimization of salt marsh management at the Rachel Carson National Wildlife Refuge, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1080, 35 p., https://doi.org/10.3133/ofr20211080.","productDescription":"vi, 35 p.","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126540","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":389743,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1080/coverthb.jpg"},{"id":389744,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1080/ofr20211080.pdf","text":"Report","size":"4.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1080"},{"id":389737,"rank":1,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":389746,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1080/images/"},{"id":389747,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1080/ofr20211080.XML"}],"country":"United States","state":"Maine","otherGeospatial":"Rachel Carson National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.63796997070312,\n 43.20417480788432\n ],\n [\n -70.61325073242188,\n 43.153101551466385\n ],\n [\n -70.477294921875,\n 43.257205668363206\n ],\n [\n -70.43472290039062,\n 43.38508989465156\n ],\n [\n -70.53634643554688,\n 43.393073720674415\n ],\n [\n -70.63796997070312,\n 43.31418735795809\n ],\n [\n -70.63796997070312,\n 43.20417480788432\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430