Pests and invasive species have been defined as any organism that can have real or perceived adverse effects on operations, or the well-being of personnel, native plants, animals, their environment and ecosystem processes; attack or damage real property, supplies, equipment, or are otherwise undesirable (paraphrased from many sources including 53 Federal Register [FR] 15975, May 4, 1988, as amended at 78 FR 13507, February 28, 2013). Biosecurity programs and pest management plans can be developed and implemented with the goals of preventing the arrival of or eradication or control of pests and invasive species to reduce the potential for adverse effects. Such plans have been developed for Wake Atoll (U.S. Air Force, unpub. data 2017). Periodic plan reviews are an integral step for evaluating plan efficacy and updating plans with new information for improving plan effectiveness. This report summarizes an evaluation of past, current, and potential biosecurity and pest management for Wake with the intent this information can be used for updating existing plans. This document was prepared in cooperation with the U.S. Air Force (USAF) and surveys were performed for the 611th Civil Engineer Squadron Natural Resources Program ACES PROJECT no. YGFZ17002 under agreement number F2MUAA7116GW01 between the USAF and the U.S. Geological Survey’s Western Ecological Research Center (USGS-WERC).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221067","collaboration":"Prepared in cooperation with the U.S. Air Force","programNote":"Ecosystems Mission Area—Land Management Research and Species Management Research Programs","usgsCitation":"Hathaway, S.A., Jacobi, J.D., Peck, R., and Fisher, R.N., 2022, Updates for Wake Atoll biosecurity management, biological control, survey, and management, and integrated pest management plans: U.S. Geological Survey Open-File Report 2022-1067, 56 p., https://doi.org/10.3133/ofr20221067.","productDescription":"viii, 56 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-136103","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"links":[{"id":405629,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1067/ofr20221067.xml"},{"id":405628,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1067/ofr20221067.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":405627,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1067/covrthb.jpg"},{"id":501820,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113419.htm","linkFileType":{"id":5,"text":"html"}},{"id":405630,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1067/images"}],"contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This report addresses system characterization of the Instituto Nacional de Pesquisas Espaciais Amazônia-1 satellite 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. 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.
Amazônia-1 is a four-band imager with a 64-meter (m) pixel ground sample distance. Amazônia-1 was launched in February 2021 into a Sun-synchronous orbit of 752 kilometers with an inclination of 98.4 degrees and a swath width of 850 kilometers. The satellite has an expected lifetime of about 4 years. More information on Amazônia-1 is available in the “Land Remote Sensing Satellites Online Compendium” (https://calval.cr.usgs.gov/apps/compendium).
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 the Amazônia-1 satellite has an interior geometric performance in the range of −3.584 m (−0.056 pixel) to 0.320 m (0.005 pixel) in easting and −1.984 m (−0.031 pixel) to 2.048 m (0.032 pixel) in northing in band-to-band registration, an exterior geometric performance of −37.256 m (−0.621 pixel) to 54.758 m (0.913 pixel) in easting and −12.684 m (−0.211 pixel) to 54.898 m (0.915 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 0.030 to 0.143 in offset and 0.662 to 0.825 in slope, and a spatial performance in the range of 1.62 to 2.06 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.062 to 0.115.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System characterization of Earth observation sensors","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030N","usgsCitation":"Vrabel, J.C., Stensaas, G.L., Anderson, C., Christopherson, J., Kim, M., and Park, S., 2022, System characterization report on the Amazônia-1 multispectral sensor, chap. N of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 33 p., https://doi.org/10.3133/ofr20211030N.","productDescription":"v, 33 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-142103","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":405398,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/n/ofr20211030n.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–N"},{"id":405397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/n/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Land subsidence is a settling, sinking, or collapse of the land surface. In the southeastern United States, subsidence is frequently observed as sinkhole collapse in karst environments, wetland degradation and loss in coastal and other low-lying areas, and inundation of coastal urban communities. Human activities such as fluid extraction, mining, and overburden alteration can cause or exacerbate subsidence, which can result in damage to infrastructure and resources. Subsidence is a hazard that takes place throughout the United States; however, a systematic approach to recognize and develop informed responses to the drivers of subsidence has not yet been fully established. To address this problem, the U.S. Geological Survey (USGS) Southeast Region (SER) funded the gathering of a team of interdisciplinary USGS scientists to promote scientific collaboration. Southeast Region scientists welcomed scientists from other regions (see table 1.1 in Appendix 1) in September 2018 at the St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida for the first workshop of the Subsidence Flex Team (SFT) (see Appendix 2 for agenda). The SFT set out to review subsidence-related research and technology and develop a unifying framework for describing the processes and hazards associated with land subsidence. A more comprehensive understanding of subsidence hazards could help to inform regional vulnerability assessments that would prove invaluable to the public, community developers, policy makers, and resource managers in both inland and coastal states. The SFT analyzed USGS strengths and weaknesses to identify existing infrastructure and capabilities that could be leveraged to create a comprehensive and far-reaching subsidence-monitoring and mitigation program. Over the course of the 2-day workshop, interdisciplinary understandings of the processes and hazards related to subsidence were explored through individual presentations and group discussion. With all perspectives considered, the SFT recommended that subsidence-related research develop scientific approaches and metrics by which the subsidence component can be isolated and quantified in order to protect both the environment and human infrastructure from harm.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221064","usgsCitation":"Flocks, J., McGraw, E., Barras, J., Bernier, J., Bradley, M., Galloway, D., Landmeyer, J., McBride, W.S., Smith, C., Smith, K., Swarzenski, C., and Toth, L., 2022, Documenting the multiple facets of a subsiding landscape from coastal cities and wetlands to the continental shelf: U.S. Geological Survey Open-File Report 2022–1064, 22 p., https://doi.org/10.3133/ofr20221064.","productDescription":"viii, 22 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-106940","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":501871,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113357.htm","linkFileType":{"id":5,"text":"html"}},{"id":404582,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1064/covrthb.jpg"},{"id":404583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1064/ofr20221064.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1064"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.603515625,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 24.5271348225978\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
The locations of many faults in and near the Rialto-Colton groundwater subbasin are not precisely known because the spatial density of existing lithologic and hydrologic data used to infer the locations of faults can be sparse. The U.S. Geological Survey, in cooperation with the San Bernardino Valley Municipal Water District, analyzed structural control of groundwater flow in and near the Rialto-Colton groundwater subbasin using Interferometric Synthetic Aperture Radar (InSAR) methods. Faults commonly are barriers to groundwater flow, and the high spatial resolution of InSAR imagery can be used to infer the locations of buried faults where groundwater pumping occurs. InSAR results have revealed three areas in and near the Rialto-Colton groundwater subbasin where buried faults are interpreted as groundwater-flow barriers: the northwestern area about 3 miles northwest of the City of Rialto, the San Jacinto fault area west of the City of San Bernardino, and the southeastern area about 2 miles southeast of the City of Colton. The InSAR results were combined with knowledge gained from previous studies to better define the location and extent of faults acting as groundwater-flow barriers. New data about faults acting as groundwater-flow barriers can be incorporated into future conceptual and hydrologic models of the Rialto-Colton groundwater subbasin and provide water managers information to help effectively manage groundwater resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221030","collaboration":"Prepared in cooperation with the San Bernardino Valley Municipal Water District","programNote":"Water Availability and Use Science Program","usgsCitation":"Brandt, J.T., 2022, Mapping structural control through analysis of land-surface deformation for the Rialto-Colton groundwater subbasin, San Bernardino County, California, 1992–2010: U.S. Geological Survey Open-File Report 2022–1030, 11 p., https://doi.org/10.3133/ofr20221030.","productDescription":"Report: vi, 11 p.; Data Release","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-084965","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501769,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113347.htm","linkFileType":{"id":5,"text":"html"}},{"id":403230,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1030/images"},{"id":403228,"rank":1,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1030/ofr20221030.xml"},{"id":403229,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1030/ofr20221030.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":403232,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"Data release","description":"U.S. Geological Survey, 2014, Web interface: U.S. Geological Survey National Water Information System web page, accessed June 11, 2014, at https://doi.org/10.5066/F7P55KJN.","linkHelpText":"Web interface: U.S. Geological Survey National Water Information System web page"},{"id":404520,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1030/covrthb.jpg"},{"id":404546,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221030/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1030"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Rialto-Colton groundwater subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.51319885253905,\n 34.01851844336969\n ],\n [\n -117.2138214111328,\n 34.01851844336969\n ],\n [\n -117.2138214111328,\n 34.19362958613085\n ],\n [\n -117.51319885253905,\n 34.19362958613085\n ],\n [\n -117.51319885253905,\n 34.01851844336969\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
In light of ongoing and geographically widespread highly pathogenic avian influenza (HPAI) outbreaks in wild birds throughout much of Eurasia during 2020–21, the Interagency Steering Committee for Avian Influenza Surveillance in Wild Migratory Birds disseminated an informational memorandum in January 2021 to highlight the need for enhanced surveillance and heightened awareness in North America. This was followed by coordination of this August 2021 international HPAI webinar series facilitated by the U.S. Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS) Veterinary Services Training Program. In addition to heightening awareness, the webinars provided an opportunity for information exchange and facilitated virtual discussions between Federal, State, academic, and international partners on the ongoing Eurasian outbreak, lessons learned from the 2014–15 North American HPAI outbreak, and associated challenges and opportunities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221066","usgsCitation":"Hopkins, M.C., Mason, J.R., Haddock, G., and Ramey, A.M., 2022, Proceedings of the Highly Pathogenic Avian Influenza and Wild Birds Webinar Series, August 2–5, 2021: U.S. Geological Survey Open-File Report 2022–1066, 27 p., https://doi.org/10.3133/ofr20221066.","productDescription":"vi, 27 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-140410","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":404536,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1066"},{"id":403060,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1066/images/"},{"id":403057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1066/coverthb.jpg"},{"id":403058,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1066/ofr20221066.pdf","text":"Report","size":"2.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1066"},{"id":403059,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1066/ofr20221066.XML"}],"contact":"Associate Director, Ecosystems
U.S. Geological Survey
954 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
A reported fuel release in November 2021 at the Red Hill Bulk Fuel Storage Facility within the naval reservation at Red Hill led to the shutdown of several production wells in the Hālawa area, O‘ahu, Hawai‘i. Red Hill Shaft—one of the high-capacity production wells that shut down—was reactivated on January 29, 2022. Submersible pressure transducers were deployed at 20 wells in the Hālawa area to measure groundwater levels and evaluate the regional groundwater-level response to the resumption of groundwater withdrawals from Red Hill Shaft. Groundwater levels measured in wells from January 17 to March 3, 2022, ranged between 16 and 20 feet at all sites and generally between 17 and 19 feet at most sites. Average groundwater-level decreases measured in wells 10 days after the January 29, 2022, resumption of withdrawal from Red Hill Shaft ranged from about 0.1 to 0.4 foot. In general, greatest decreases in groundwater levels occurred in wells closest to Red Hill Shaft.
The groundwater-level data contain uncertainty because of several potential sources of error associated with (1) the accuracy of the measuring tapes and submersible pressure transducers used, (2) the accuracy of the measuring-point altitude at the top of each well, (3) the stability of the submersible pressure transducers’ suspension depth in each well, (4) well plumbness and alignment, and (5) human error. Because of the potential sources of error, comparability of groundwater-level data may be affected. Some sources of uncertainty, including the accuracy of measuring-point altitudes, can be addressed and lead to improved accuracy and comparability of groundwater levels. Data collected for this study are available in the U.S. Geological Survey National Water Information System database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221069","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, Groundwater-level monitoring from January 17 to March 3, 2022, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1069, 29 p., https://doi.org/10.3133/ofr20221069.","productDescription":"Report: vi, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-141201","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":501822,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113349.htm","linkFileType":{"id":5,"text":"html"}},{"id":404436,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221018","text":"Open-File Report 2022-1018","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, December 23, 2021, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1018, 10 p., https://doi.org/10.3133/ofr20221018.","linkHelpText":"- December 23, 2021, Red Hill Synoptic Groundwater-Level Survey, Hālawa Area, O‘ahu, Hawai‘i"},{"id":404435,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221048","text":"Open-File Report 2022-1048","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, January 18, 2022, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1048, 11 p., https://doi.org/10.3133/ofr20221048.","linkHelpText":"- January 18, 2022, Red Hill Synoptic Groundwater-Level Survey, Hālawa Area, O‘ahu, Hawai‘i"},{"id":404434,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the nation","description":"U.S. Geological Survey, 2022, USGS water data for the nation: U.S. Geological Survey National Water Information System database, https://doi.org/10.5066/F7P55KJN."},{"id":404433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1069/ofr20221069.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":404432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1069/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hālawa Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.96142578124997,\n 21.317522325157526\n ],\n [\n -157.85156249999997,\n 21.317522325157526\n ],\n [\n -157.85156249999997,\n 21.409605198965597\n ],\n [\n -157.96142578124997,\n 21.409605198965597\n ],\n [\n -157.96142578124997,\n 21.317522325157526\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
The U.S. Geological Survey Rocky Mountain Region hosted scientists, managers, program coordinators, and leadership team members for a virtual Science Exchange during September 15–17, 2020. The Science Exchange had 216 registered participants and included 48 talks over the 3-day period. Invited speakers presented information about the novel U.S. Geological Survey Earth Monitoring, Analysis, and Prediction (EarthMAP) concept. Scientists showcased their research and participated in discussions related to the EarthMAP concept and EarthMAP applications. In addition, the Colorado River Basin Pilot Project, one of the first EarthMAP Pilot Projects, was unveiled during the Science Exchange. This report provides synopses of session objectives and corresponding abstracts that were presented along with author affiliations and email address of the lead author. In addition, web links are provided for related programs and projects, and associated publications are referenced.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20221040","usgsCitation":"Anderson, P.J., and Tillery, A.C., 2022, Presented abstracts from the U.S. Geological Survey 2020 Rocky Mountain Region Science Exchange (September 15–17, 2020): U.S. Geological Survey Open-File Report 2022–1040, 23 p., https://doi.org/10.3133/ofr20221040.","productDescription":"x, 23 p.","onlineOnly":"Y","ipdsId":"IP-132301","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":405563,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221040/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1040"},{"id":403936,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1040/ofr20221040.xml"},{"id":403935,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1040/images"},{"id":403934,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1040/ofr20221040.pdf","text":"Report","size":"2.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1040"},{"id":403933,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1040/coverthb.jpg"}],"contact":"Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
P.O. Box 25046, Mail Stop 911
Denver, CO 80225
The Federal Interagency Sedimentation Project (FISP) standardizes and advances sediment science among federal agencies. It is important to ensure that the FISP bag samplers perform isokinetically under all tested and approved conditions and collect samples that are representative of the stream or river cross-section. A measure of a sampler’s isokinetic behavior is its intake efficiency, which is defined as the ratio of the velocity through the nozzle entrance of the sampler to the ambient stream velocity. The intake efficiencies of all FISP bag samplers and nozzle sizes were evaluated for this report. Samples were obtained across 31 U.S. Geological Survey streamflow-gaging stations between July 15, 2013, and June 17, 2020, where data were collected with all four bag samplers (US D-96, D-96-A1, D-99, and DH-2), each using various 3/16-inch, 1/4-inch, or 5/16-inch diameter nozzles.
Water temperature and ambient stream velocity outside the nozzle are two of several factors that are known to affect the intake efficiency of bag samplers. A regression curve was fitted to these data through LOWESS (locally weighted scatterplot smoothing), and a Kruskal-Wallis test was executed for the various samplers and nozzle sizes. Based on these results, there is no statistical evidence to indicate that water temperature and stream velocity have a noticeable effect on intake efficiency when the samplers are deployed under isokinetic conditions. Likewise, there is no statistical evidence to indicate that the type of bag sampler and nozzle diameter have a direct effect on intake efficiency.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221036","usgsCitation":"Manaster, A.E., Landers, M.N., and Straub, T.D., 2022, Intake efficiency field results for Federal Interagency Sedimentation Project bag samplers: U.S. Geological Survey Open-File Report 2022–1036, 27 p., https://doi.org/10.3133/ofr20221036.","productDescription":"Report: iv, 27 p.; Database","onlineOnly":"Y","ipdsId":"IP-134358","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":404073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1036/coverthb.jpg"},{"id":404075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1036/ofr20221036.pdf","text":"Report","size":"2.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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U.S. Geological Survey
405 North Goodwin Ave.
Urbana, IL 61801
Concentrations of suspended sediment were measured in discrete samples and turbidity was continuously monitored at four U.S. Geological Survey streamgages in western Washington State, including one gage on the Sauk River; two gages on the Suiattle River, a tributary to the Sauk River; and one gage on Downey Creek, a tributary to the Suiattle River. The Suiattle River is a sediment-rich stream with headwaters on Glacier Peak, a glaciated volcano in the northern Cascade Range.
Contributions of suspended sediment to the Suiattle River from unglaciated tributaries, represented by Downey Creek, were compared to the contributions from Glacier Peak in the upper Suiattle River watershed. During summer 2017, a period for which complete records of discharge and sediment data were available for all three streamgages in the Suiattle River Basin, the suspended-sediment load from Downey Creek (drainage area [DA] 93 square kilometers [km2]) was 1,400 metric tons, which is equivalent to a sediment yield of about 15 metric tons per km2. During the same period, the suspended-sediment load from the upper Suiattle River (DA 176 km2) was 142,000 metric tons, or a sediment yield of about 800 metric tons per km2; and the suspended-sediment load from the lower Suiattle River (DA 733 km2) was 230,000 metric tons, or a sediment yield of about 300 metric tons per km2. The Downey Creek Basin accounts for 13 percent of the drainage area of the Suiattle River watershed but contributed only 0.6 percent of the suspended-sediment load over the summer of 2017 and water year 2017 (October 1, 2016–September 30, 2017). In contrast, the upper Suiattle River Basin, which accounts for 24 percent of the entire Suiattle River watershed, contributed 62 percent of the suspended-sediment load during the summer of 2017.
Given the short period for which data were collected, it cannot be known with certainty whether the above values are representative of long-term means. The relatively minor contribution of suspended sediment from Downey Creek, however, is consistent with the expectation that the upper Suiattle River, which drains Glacier Peak, is the dominant contemporary source of suspended sediment to the Sauk River. During summer 2016, the suspended-sediment load in the upper Siuattle River (180,000 metric tons) was more than double the estimated load in the lower Sauk River (80,000 metric tons), even though the upper Suiattle River represents only 10 percent of the total contributing area to the lower Sauk River Basin. This ratio of relative contribution is interpreted as an indication of transient storage of sediment along the Suiattle and Sauk Rivers between the two streamgaging stations. In the glaciated upper Suiattle River Basin, sediment is transported by annual glacial-melt processes in spring and summer months, deposited during the summer base-flow period, and then remobilized by fall and winter floods for delivery to the lower Sauk River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221056","collaboration":"Prepared in cooperation with the Sauk-Suiattle Indian Tribe","usgsCitation":"Jaeger, K.L., Anderson, S.W., Senter, C.A., Curran, C.A., and Morris, S., 2022, Relative contributions of suspended sediment between the upper Suiattle River Basin and a non-glacial tributary, Washington, May 2016–September 2017: U.S. Geological Survey Open-File Report 2022–1056, 18 p., https://doi.org/10.3133/ofr20221056.","productDescription":"v, 18 p.","onlineOnly":"Y","ipdsId":"IP-132545","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":403971,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1056/ofr20221056.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1056"},{"id":403970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1056/coverthb.jpg"},{"id":501781,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113307.htm","linkFileType":{"id":5,"text":"html"}},{"id":403972,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221056/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1056"},{"id":404178,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W74K0K","text":"USGS data release","description":"USGS data release","linkHelpText":"Suspended sediment and water temperature data in the Suiattle River and the Downey Creek Tributary, Washington for select time periods over 2013 - 2017 (ver. 2.0, October 2021)"},{"id":403974,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1056/ofr20221056.XML"},{"id":403973,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1056/images"}],"country":"United States","state":"Washington","otherGeospatial":"Upper Suiattle River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.4,\n 48.0\n ],\n [\n -121.0,\n 48.0\n ],\n [\n -121.0,\n 48.4\n ],\n [\n -121.4,\n 48.4\n ],\n [\n -121.4,\n 48.0\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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Numerous porphyry copper-molybdenum-gold and epithermal deposits define a belt that extends from Eastern Alaska to western Yukon, Canada. An orientation study conducted near the Taurus porphyry deposit was designed to test methods that require minimal sample collection, preparation, and analytical time to determine the viability of indicator mineral studies as a reconnaissance exploration method. Bulk stream sediments and altered and mineralized rocks were sieved to the 0.105−0.25 millimeter fraction (+140, −60 mesh) and passed over a shaking table to create a moderate to heavy mineral separate that was mounted in epoxy and subsequently analyzed using automated scanning electron microscope (SEM) techniques. Seven polished thin sections of core were also analyzed. Among the advantages of automated SEM techniques compared to visual mineral identification are that thousands of grains can be rapidly identified in each sample (about 1 hour per sample) and small quantities of indicator minerals that may be missed during traditional visual analyses can be detected. Automated SEM analyses of stream sediment and rock samples show that specific minerals (chalcopyrite, bornite, and jarosite) are indicators of potential mineralized areas. Svanbergite, an aluminum sulfate phosphate mineral, was identified in mineralized rocks and in nearly all stream sediment samples (up to 9 kilometers) downstream from the Taurus and other porphyry occurrences but not epithermal occurrences. It was not identified in areas with no known mineralization and thus it is possibly one of the best indicator minerals for porphyry copper (+/- molybdenum, gold) occurrences.
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Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
P.O. Box 25046, Mail Stop 973
Denver, CO 80225
Phase 3 of the Earth Mapping Resources Initiative (Earth MRI) focuses on geologic belts that are favorable for hosting mineral systems that could contain the critical minerals antimony, barite, beryllium, chromium, fluorspar, hafnium, magnesium, manganese, uranium, vanadium, and zirconium. Prior phases of the Earth MRI program in Alaska focused only on rare earth elements, aluminum, cobalt, graphite, lithium, niobium, platinum-group metals, tantalum, tin, titanium, and tungsten. An additional 11 critical minerals planed for future phases of Earth MRI (As, Bi, Cs, Ga, Ge, In, Re, Rb, Sc, Sr, Te) are considered prospective in these focus areas. Together, Alaska focus areas address 22 of the 35 minerals or mineral material groups presently deemed critical. This report describes the methodology and techniques utilized to define focus areas for future data acquisition in Alaska; the conterminous United States are covered in a separate report.
Focus areas are identified using a mineral systems framework, which accounts for all the possible tectonic and geologic settings where co-genetic mineral deposits may form. These deposits contain many commodities, including byproduct and critical minerals. Large system-scale processes may be evaluated using such a framework to determine the influence they play on critical mineral endowment within the deposits. Analyzing larger mineral systems provides an integrated and broad context to determine how and where critical minerals are sourced, transported, and deposited in geologic systems.
Statewide geological, geochemical, geophysical, and mineral occurrence datasets informed the delineation of focus areas in Alaska. For some mineral systems, previously published data-driven prospectivity analyses for critical mineral-bearing deposit types provided the basis for focus areas. We report a total of 22 new focus areas that are prospective for phase 3 critical minerals. These new focus areas represent four different mineral systems that are known or suspected to occur in Alaska. An additional 55 focus areas that were previously identified for phase 1 and phase 2 commodities were also identified as being prospective for phase 3 critical minerals. Collectively, 102 focus areas in Alaska have known or suspected potential for hosting phase 1, phase 2, and (or) phase 3 critical minerals. These focus areas represent 17 different mineral systems also containing critical minerals that are planned for consideration in future Earth MRI phases. Thus, the focus areas delineated herein, and in previous reports for Alaska, are comprehensive for all critical minerals as presently defined and may be used to guide the collection of new geologic, geochemical, and geophysical data in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191023E","collaboration":"Prepared in cooperation with the Alaska Division of Geology & Geophysics","usgsCitation":"Kreiner, D.C., Jones, J.V., III, and Case, G. N., 2022, Alaska focus area definition for data acquisition for potential domestic sources of critical minerals in Alaska for antimony, barite, beryllium, chromium, fluorspar, hafnium, magnesium, manganese, uranium, vanadium, and zirconium, chap. 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Niobium, Platinum Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten"},{"id":501525,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113261.htm","linkFileType":{"id":5,"text":"html"}},{"id":403736,"rank":8,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023B","text":"Open-File Report 2019-1023-B","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Resources of 11 Critical Minerals in the Conterminous United States, Hawaii, and Puerto Rico—Aluminum, Cobalt, Graphite, Lithium, Niobium, Platinum-Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten"},{"id":403735,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023A","text":"Open-File Report 2019-1023-A","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Sources of Critical Minerals—Rare Earth Elements"},{"id":403663,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WA7JZY","text":"USGS data release","description":"USGS data release","linkHelpText":"GIS, supplemental data table, and references for focus areas of potential domestic resources of 13 critical minerals in the United States and Puerto Rico—Antimony, barite, beryllium, chromium, fluorspar, hafnium, helium, magnesium, manganese, potash, uranium, vanadium, and zirconium"}],"country":"United 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\"}}]}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The Earth Mapping Resources Initiative (Earth MRI) is conducted in phases to identify areas for acquiring new geologic framework data to identify potential domestic resources of the 35 mineral materials designated as critical minerals for the United States. This report describes the data sources and summary results for 13 critical minerals evaluated in the conterminous United States and Puerto Rico during phase 3 of the study (antimony, barite, beryllium, chromium, fluorspar, hafnium, helium, magnesium, manganese, potash, uranium, vanadium, and zirconium). Phases 1 and 2 of the Earth MRI addressed aluminum, cobalt, graphite, lithium, niobium, platinum-group elements (PGEs), rare earth elements (REEs), tantalum, tin, titanium, and tungsten. Critical minerals in Alaska are covered in a separate report. No focus areas for phase 3 critical minerals are delineated for Hawaii.
The geologic, geochemical, topographic, and geophysical mapping provided by the Earth MRI documents geologic features that reflect the extent of individual mineral systems and provides information about critical mineral deposits that may not have been previously considered. The mineral-systems approach links critical mineral commodities to deposit types that represent the manifestations of large mineral systems.
Each of the 13 critical mineral commodities for phase 3 of the Earth MRI is discussed in terms of its importance to the Nation’s economy, modes of occurrence, mineral systems, and deposit types, and is accompanied by maps and tables listing examples of focus areas in the conterminous United States and Puerto Rico. Examples of important mineral systems for this group of 13 critical minerals include basin brine path systems for barite and fluorspar, Carlin-type systems and Coeur d’Alene systems for antimony, chemical weathering and volcanogenic seafloor systems for manganese, Climax-type systems for beryllium, mafic magmatic systems for chromium, marine evaporite systems for potash and magnesium, meteoric recharge systems for uranium, petroleum systems for helium, and placer systems for zirconium and hafnium.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191023D","collaboration":"Prepared in cooperation with the Association of American State Geologists","usgsCitation":"Hammarstrom, J.M., Dicken, C.L., Woodruff, L.G., Andersen, A.K., Brennan, S., Day, W.C., Drenth, B.J., Foley, N.K., Hall, S., Hofstra, A.H., McCafferty, A.E., Shah, A.K., and Ponce, D.A., 2022, Focus areas for data acquisition for potential domestic resources of 13 critical minerals in the conterminous United States and Puerto Rico—Antimony, barite, beryllium, chromium, fluorspar, hafnium, helium, magnesium, manganese, potash, uranium, vanadium, and zirconium, chap. 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Mineral Resources Program
U.S. Geological Survey
913 National Center
Reston, VA 20192
The Old Erie Canal has undergone sedimentation and aquatic growth that have restricted flow and diminished the aesthetic quality of the canal during the nearly 200 years since its construction. During 2018–2019, the U.S. Geological Survey (USGS) in cooperation with the Madison County Planning Department and the New York State Canal Corporation conducted a study of the Old Erie Canal between the Town of DeWitt, New York, and its junction with the current Erie Canal of the New York State Canal System near Rome, N.Y. The study comprised bathymetric, velocity, and water-quality surveys and documentation of the canal infrastructure. The USGS established benchmarks and staff gages along the 30.8 miles of the canal study area to reference the water-surface level in the canal to the North American Vertical Datum of 1988 (NAVD 88). Bathymetric survey results indicated that during the time of the survey, the canal depths ranged from 1.26 feet (ft) to 7.33 ft between the Butternut and Durhamville aqueducts (with a mean depth of 3.52 ft). Shallow depths are located throughout the canal, but the section north of the Durhamville aqueduct was the shallowest, with depths ranging from 0.68 ft to 2.44 ft (and a mean depth of 1.36 ft). The reach-averaged water velocity was 0.28 feet per second. The system generally flows west to east from the Butternut aqueduct to the entrance to the Erie Canal.
Water-quality data (dissolved oxygen, water temperature, specific conductance, pH, and turbidity) were collected concurrently with the bathymetric survey (spring 2018) to characterize changes in water quality along the length of the canal. Specific-conductance values measured upstream from the hamlet of Kirkville, Manlius, N.Y. may reflect road salts being flushed into the canal through the Butternut and Limestone feeder system (designed to divert water from nearby creeks to supply water for the Old Erie Canal) from recent stormwater runoff. Increases in pH in the downstream direction are possibly caused by increasing amounts of aquatic vegetation. During the time of the survey, turbidity was highest near inflows from the canal feeder system and tributary inputs which were elevated by stormwater runoff that transported sediment into the canal.
The canal infrastructure was documented to provide a baseline assessment. The feeder system, designed to bring water into the canal, does not deliver flow when the creeks supplying water to those feeders are at base flow, but does bring water into the system when flows in the feeder creeks are elevated. A recent report provides an example of repair work completed on the Chittenango feeder to improve flow through the feeder into the canal (Welch and Madison County Planning Department, 1996). Two non-regulated tributaries, Meadow Brook and Pools Brook, consistently delivered flow to the canal. Outfalls where canal water discharges into nearby creeks were sealed in the Butternut and Limestone aqueducts. Outfalls in the Chittenango, Cowaselon, and Durhamville aqueducts were found with flashboards installed at an elevation that allows water to be discharged from the canal. These structures are designed to accept additional flashboards to raise the canal water surface with the potential to convey flow farther down the system. The general condition of the channel was open and navigable between Butternut aqueduct and Chittenago aqueduct. On the segment of the canal east of the Chittenango aqueduct, an increasing number of downed trees and tangled wads of vegetation affected flow and made navigation by boat difficult to the Durhamville aqueduct. North of the Durhamville aqueduct, numerous downed trees and an increased density of aquatic vegetation limited navigation by boat and reduced the flow rate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211125","usgsCitation":"Wernly, J.F., 2022, Characterization of the bathymetry, hydrodynamics, water quality, infrastructure, and channel condition of the Old Erie Canal from DeWitt to its junction with the current Erie Canal in Verona, near Rome, New York, 2018–19: U.S. Geological Survey Open-File Report 2021–1125, 75 p., https://doi.org/10.3133/ofr20211125.","productDescription":"Report: viii, 75 p.; Data Release","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118164","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":402850,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1125/ofr20211125.XML"},{"id":402848,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1125/ofr20211125.pdf","text":"Report","size":"94.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1125"},{"id":402847,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1125/coverthb.jpg"},{"id":402849,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QRL294","text":"USGS data release","linkHelpText":"Geospatial dataset of the characterization of the bathymetry, hydrodynamics, water quality, infrastructure, and channel condition of the Old Erie Canal from DeWitt to Rome, New York 2018–2019"},{"id":402851,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1125/images/"},{"id":403542,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20211125/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2021-1125"},{"id":501536,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113265.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Old Erie Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.13250732421875,\n 42.974511174899156\n ],\n [\n -76.11328125,\n 42.968984647488014\n ],\n [\n -75.9375,\n 42.96044267380142\n ],\n [\n -75.74798583984375,\n 42.96446257387128\n ],\n [\n -75.57769775390625,\n 43.002638523957906\n ],\n [\n -75.41839599609375,\n 43.1270477646888\n ],\n [\n -75.35522460937499,\n 43.207177786666655\n ],\n [\n -75.42388916015625,\n 43.271206115959785\n ],\n [\n -75.52001953125,\n 43.25920592943639\n ],\n [\n -75.65460205078125,\n 43.23920036180898\n ],\n [\n -75.92926025390625,\n 43.219188223481325\n ],\n [\n -76.09405517578125,\n 43.13105676219153\n ],\n [\n -76.18194580078124,\n 43.07891929985966\n ],\n [\n -76.18743896484375,\n 43.022721607058344\n ],\n [\n -76.13250732421875,\n 42.974511174899156\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Climate model projections are commonly used to assess potential impacts of global warming on a breadth of social, economic, and environmental topics. Modeling centers throughout the world coordinate to apply a consistent suite of radiative forcing experiments so that all model outputs can be collectively analyzed and compared. Three generations of model outputs have been produced and made available to the scientific community through the Coupled Model Intercomparison Project (CMIP): CMIP3 disseminated during the mid-2000s, CMIP5 during the early-2010s, and CMIP6 during the late-2010s. Twenty-first century sea-ice projections from CMIP3 and CMIP5 models have been used in Bayesian network assessments of how climate change could impact the future persistence of polar bears (Ursus maritimus) throughout their range. In this report, we compare sea-ice projections by CMIP6 models to those of CMIP5 models in each of four polar bear ecoregions over the 21st century. We evaluate differences between the two CMIP generations with respect to other sources of variability that affect uncertainties of the model projections: (1) variability from different models; (2) variability from different greenhouse gas emissions scenarios; and (3) natural (internal) variability in the earth’s climate system. We found that natural variability as well as that attributable to models dominated uncertainties in sea-ice projections in all months and ecoregions during the first half of the 21st century, while emissions scenarios dominated uncertainties during the late 21st century. By comparison, we found only slight differences between the CMIP6 and CMIP5 model projections of sea ice. Applying CMIP6 instead of CMIP5 sea-ice projections to the polar bear Bayesian network model developed in 2016, therefore, would not qualitatively change the population status outcomes published therein.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221062","collaboration":"Prepared in cooperation with the U.S Fish and Wildlife Service","usgsCitation":"Douglas, D.C., and Atwood, T.C., 2022, Comparisons of Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) sea-ice projections in polar bear (Ursus maritimus) ecoregions during the 21st century: U.S. Geological Survey Open-File Report 2022–1062, 27 p., https://doi.org/10.3133/ofr20221062.","productDescription":"vii, 27 p.","onlineOnly":"Y","ipdsId":"IP-139269","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":403336,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221062/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1062"},{"id":403335,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1062/ofr20221062.XML"},{"id":403334,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1062/images"},{"id":403333,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1062/ofr20221062.pdf","text":"Report","size":"16.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1062"},{"id":403332,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1062/coverthb.jpg"}],"contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The 2012 Little Bear Fire resulted in substantial loss of vegetation in the Eagle Creek Basin, south-central New Mexico, which has been expected to cause a variety of hydrologic responses that could influence geomorphic change to North Fork Eagle Creek. To monitor geomorphic change, surveys of a downstream study reach of North Fork Eagle Creek were conducted in 2017, 2018, and 2019 by the U.S. Geological Survey in cooperation with the Village of Ruidoso, N. Mex. The study included surveys of select cross sections, woody debris accumulations, and pools found in the channel of the study reach. During 2017–19, high-flow events resulting from both monsoonal rainfall and snowmelt runoff occurred in the study reach, and the events appeared to have caused some minor localized geomorphic changes in the study reach, which were evaluated through comparison of the 2017, 2018, and 2019 survey results.
Comparisons of the cross-section survey results indicated that minor geomorphic changes had occurred in 4 of the 14 cross sections surveyed from 2017 to 2019. These geomorphic changes included aggradation or degradation of surface materials by about 1–2 feet in some parts of the affected cross sections. During the 2019 survey, 164 distinct accumulations of woody debris and 228 pools were identified in the study reach. Of the woody debris accumulations identified during the 2019 survey, 67 were certain to have also been present during the 2018 survey, and 21 were certain to have also been present during all three surveys (2017–19), indicating that most of the woody debris accumulations surveyed in 2017 were likely transported during the high-flow events between the 2017 and 2018 surveys. Most woody debris accumulations identified in 2019 did not appear to have substantially influenced geomorphic change in the locations where they were found but may have driven local geomorphic changes.
Because the study began 5 years after the 2012 Little Bear Fire and the geomorphic scope of the study has so far been limited, it cannot be said that the changes observed between the 2017 and 2019 surveys are representative of a pattern of geomorphic change following the Little Bear Fire. Once geomorphic changes identified during the 2017 through 2019 surveys can be compared with results from the remaining planned geomorphic surveys, it may be possible to develop an understanding of the patterns in geomorphic change following the 2012 Little Bear Fire.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221041","collaboration":"Prepared in cooperation with Village of Ruidoso, New Mexico","usgsCitation":"Graziano, A.P., and Chavarria, S.B., 2022, Geomorphic survey of North Fork Eagle Creek, New Mexico, 2019: U.S. Geological Survey Open-File Report 2022–1041, 36 p., https://doi.org/10.3133/ofr20221041.","productDescription":"Report: v, 36 p.; Data Release; Dataset","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-123645","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":403220,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97ALYNZ","text":"USGS data release","linkHelpText":"Data supporting the 2019 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":501773,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113257.htm","linkFileType":{"id":5,"text":"html"}},{"id":403221,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":403219,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1041/images"},{"id":403218,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1041/ofr20221041.XML"},{"id":403215,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1041/coverthb.jpg"},{"id":403216,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1041/ofr20221041.pdf","text":"Report","size":"2.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1041"}],"country":"United States","state":"New Mexico","otherGeospatial":"North Fork Eagle Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.5,\n 33.0\n ],\n [\n -105.1,\n 33.0\n ],\n [\n -105.1,\n 33.4\n ],\n [\n -105.5,\n 33.4\n ],\n [\n -105.5,\n 33.0\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Anthropogenic activities, including groundwater withdrawals, return flow from irrigated agriculture, and treated wastewater-effluent disposal have the potential to affect groundwater quality in the Lucerne Valley groundwater basin, located in the southwest Mojave Desert. Questions regarding the current state and potential future of groundwater quality in this basin were addressed by (1) considering groundwater data from and findings of historical water-quality studies, (2) evaluating recent (1990–2021) U.S. Geological Survey water-quality and geochemical-tracer data, and (3) assessing groundwater-quality results from samples collected in 2021 to better understand the transport of applied treated wastewater effluent in the subsurface and associated effects of this practice on water quality. As observed by previous studies, differences in groundwater quality existed among the upper, middle, and lower aquifers of the Lucerne Valley groundwater basin, with the lower aquifer characterized by high dissolved-solid content relative to the middle and upper aquifers. Stable and radioisotope tracers indicate that most of the groundwater sampled in the basin was recharged during cooler, wetter climate conditions than those of the present day (2022). Analyses of the 2021 samples collected to examine the subsurface transport of applied treated wastewater effluent were not conclusive but indicate that water from applied treated wastewater effluent is currently (2022) limited to the upper aquifer and likely to remain so given the extensive confining unit below the upper aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221063","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Fackrell, J.K., 2022, Groundwater quality of the Lucerne Valley groundwater basin, California: U.S. Geological Survey Open-File Report 2022-1063, 19 p., https://doi.org/10.3133/ofr20221063.","productDescription":"viii, 19 p.","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-137528","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501818,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113259.htm","linkFileType":{"id":5,"text":"html"}},{"id":403158,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1063/ofr20221063.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022–1063"},{"id":403163,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225048","text":"Scientific Investigations Report 2022-5048","description":"Stamos, C.L., Larsen, J.D., Powell, R.E., Matti, J.C., and Martin, P., 2022, Hydrogeology and simulation of groundwater flow in the Lucerne Valley groundwater basin, California: U.S. Geological Survey Scientific Investigations Report 2022-5048, 120 p., https://doi.org/10.3133/sir20225048.","linkHelpText":"- Hydrogeology and Simulation of Groundwater Flow in the Lucerne Valley Groundwater Basin, California"},{"id":403159,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1063/ofr20221063.xml"},{"id":403160,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1063/images"},{"id":403157,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1063/covrthb.jpg"},{"id":403185,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221063/full","text":"Report","description":"Open-File Report 2022-1063"}],"country":"United States","state":"California","otherGeospatial":"Lucerne Valley Groundwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.666667,\n 34.266667\n ],\n [\n -117.083333,\n 34.266667\n ],\n [\n -117.083333,\n 34.666667\n ],\n [\n -116.666667,\n 34.666667\n ],\n [\n -116.666667,\n 34.266667\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
In early October of 2020, the U.S. Geological Survey (USGS) held a virtual workshop to discuss Gulf and Atlantic Coastal Plains site-response models. Earthquake researchers came together to assess (1) research related to proposed Coastal Plains amplification models and (2) USGS plans for implementing these models. Presentations spanned a broad range of topics from Atlantic and Gulf Coastal Plains geophysical properties including seismic velocity and attenuation, to ground motion amplification models and their impacts on seismic hazard. Interspersed with these presentations were discussions regarding the definition and extent of the Atlantic and Gulf Coastal Plains, potential complexities of wave propagation in the Atlantic and Gulf Coastal Plains, and problems that need to be overcome to implement various proposed site-response models. Based on feedback from this workshop, the USGS working group on Coastal Plain Amplification is considering applying published models that depend on sediment thickness. The working group is also exploring potential application of models that depend on the length of path traversed across the Coastal Plain, including the Gulf Coastal Plain ground-motion model adjustments from the Next Generation Attenuation Relationships for the Eastern United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20221006","usgsCitation":"Boyd, O.S., Pratt, T.L., Chapman, M.C., Shumway, A., Rezaeian, S., Moschetti, M.P., and Petersen, M.D., 2022, U.S. Geological Survey coastal plain amplification virtual workshop: U.S. Geological Survey Open-File Report 2022–1006, 25 p., https://doi.org/10.3133/ofr20221006.","productDescription":"vi, 25 p.","onlineOnly":"Y","ipdsId":"IP-128818","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":402497,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1006/ofr20221006.pdf","text":"Report","size":"849 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1006"},{"id":402498,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1006/ofr20221006.xml"},{"id":402496,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1006/coverthb.jpg"},{"id":405344,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1006/images"},{"id":405560,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221006/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1006"}],"country":"United States","otherGeospatial":"Gulf and Atlantic Coast Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.716796875,\n 25.522614647623293\n ],\n [\n -81.03515625,\n 31.541089879585808\n ],\n [\n -75.5419921875,\n 35.35321610123823\n ],\n [\n -73.95996093749999,\n 40.38002840251183\n ],\n [\n -69.5654296875,\n 41.57436130598913\n ],\n [\n -70.48828125,\n 42.19596877629178\n ],\n [\n -70.224609375,\n 43.51668853502906\n ],\n [\n -66.97265625,\n 44.62175409623324\n ],\n [\n -68.2470703125,\n 45.920587344733654\n ],\n [\n -71.630859375,\n 43.45291889355465\n ],\n [\n -76.025390625,\n 40.613952441166596\n ],\n [\n -78.31054687499999,\n 38.54816542304656\n ],\n [\n -81.4306640625,\n 33.578014746143985\n ],\n [\n -83.056640625,\n 30.86451022625836\n ],\n [\n -92.98828125,\n 30.977609093348686\n ],\n [\n -96.328125,\n 30.29701788337205\n ],\n [\n -98.4375,\n 28.57487404744697\n ],\n [\n -98.0859375,\n 26.470573022375085\n ],\n [\n -97.20703125,\n 25.997549919572112\n ],\n [\n -96.9873046875,\n 27.371767300523047\n ],\n [\n -95.5810546875,\n 28.65203063036226\n ],\n [\n -93.8232421875,\n 29.305561325527698\n ],\n [\n -91.40625,\n 29.19053283229458\n ],\n [\n -89.9560546875,\n 28.8831596093235\n ],\n [\n -88.9892578125,\n 29.84064389983441\n ],\n [\n -86.17675781249999,\n 30.031055426540206\n ],\n [\n -84.111328125,\n 29.49698759653577\n ],\n [\n -83.1005859375,\n 28.76765910569123\n ],\n [\n -82.529296875,\n 26.82407078047018\n ],\n [\n -81.123046875,\n 25.045792240303445\n ],\n [\n -80.5078125,\n 24.726874870506972\n ],\n [\n -79.716796875,\n 25.522614647623293\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
P.O. Box 25046, Mail Stop 966
Denver, CO 80225
Atmospheric dust deposited to snow cover (dust-on-snow) diminishes snow-surface albedo (SSA) to result in early onset and accelerated rate of melting, effects that challenge management of downstream water resources. During ongoing investigations to identify the light-energy absorbing dust particles most responsible for diminished SSA in the Upper Colorado River Basin of the Colorado Rocky Mountains, we found microplastic particles, which are defined as those less than 5 millimeters in any dimension. In each of the 38 samples that represented the last remaining dust layer during melt seasons of 2013–16, microplastics were identified by size, shape, and color, and their relative amounts were visually estimated using stereomicroscopy. Considering the remote, high-elevation settings of the sample sites, the microplastic particles must have been deposited from the atmosphere. The possible role of microplastics for diminishing SSA of snow cover in the Upper Colorado River Basin may be linked to the solar-energy absorptive properties of polymers and is the subject of ongoing investigation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221061","usgsCitation":"Reynolds, R.L., Goldstein, H.L., Kokaly, R.F., and Derry, J., 2022, Microplastic particles in dust-on-snow, Upper Colorado River Basin, Colorado Rocky Mountains, 2013–16: U.S. Geological Survey Open-File Report 2022–1061, 7 p., https://doi.org/10.3133/ofr20221061.","productDescription":"vi, 7 p.","onlineOnly":"Y","ipdsId":"IP-141503","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501783,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113221.htm","linkFileType":{"id":5,"text":"html"}},{"id":402600,"rank":3,"type":{"id":34,"text":"Image 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\"}}]}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
P.O. Box 25046, Mail Stop 980
Denver, CO 80225
In this study we examine the potential effects of three predicted sea level rise (SLR) scenarios on the nearshore eelgrass (Zostera marina L.) and surf smelt (Hypomesus pretiosus) spawning habitats along a beach on Bainbridge Island, Washington. Baseline bathymetric, geomorphological, and biological surveys were conducted to determine the existing conditions at the study site. The results of these surveys were coupled with a predictive model that estimates SLR-induced changes to coastal ecosystems based upon local topography and land-cover data. This model simulates the changes in nearshore habitat through time. The model inputs for SLR are probable values reported by the Intergovernmental Panel on Climate Change, and by user-defined values. The predicted effects of SLR are presented as (1) habitat type change and (2) the graphic response of developed dry land depicting the influence of shoreline armoring. This report describes the geophysical and biological characteristics at the Bainbridge Island study site, the modeling methods used to produce depictions of habitat changes, and a possible decrease in surf smelt spawning and an increase in eelgrass habitat availability in response to increases in sea level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221054","usgsCitation":"Smith, C.D., and Liedtke, T.L., 2022, Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington: U.S. Geological Survey Open-File Report 2022–1054, 17 p., https://doi.org/10.3133/ofr20221054.","productDescription":"Report: v, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-117971","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":402574,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGJ3ZH","text":"USGS data release","description":"USGS Data Release.","linkHelpText":"Data collected in 2010 to evaluate habitat availability for surf smelt and eelgrass in response to sea level rise on Bainbridge Island, Puget Sound, Washington State, USA"},{"id":402572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1054/coverthb.jpg"},{"id":402573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1054"},{"id":402619,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221054/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1054"},{"id":402575,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1054/images"},{"id":402576,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.XML"},{"id":501780,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113219.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6678466796875,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.487513008956554\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
In oil spill research, a topic of increasing attention during the last decade has been the environmental impact of the partial oxidation products that result from transformation of the petroleum in freshwater, marine, and terrestrial ecosystems. This report describes the isolation and characterization of the partial oxidation products from crude oil contaminating groundwater at the long-term U.S. Geological Survey Bemidji research site in Minnesota. As the result of a pipeline burst in August 1979, a body of light aliphatic crude oil is present from the land surface to 2 meters below the water table in a shallow sand and gravel aquifer in a remote area outside Bemidji, Minnesota, United States. Biodegradation has resulted in the formation of a plume of dissolved organic carbon (DOC) downgradient from the oil body. Groundwater has also been contaminated in an area known as the spray zone, from vertical infiltration of DOC resulting from biodegradation of oil in the soil column, and possibly from photooxidation of oil at the soil surface. The majority of DOC in the contaminated groundwater is in the form of nonvolatile organic acids (NVOAs) which represent the partial oxidation products of the crude oil constituents. The NVOAs have been classified into three fractions according to their isolation on XAD resins: hydrophobic neutrals (HPON), hydrophobic acids (HPOA), and hydrophilic acids (HPIA). These fractions of NVOAs were isolated from wells downgradient from the oil body (sampling well numbers 533, 532, 530, 515), in the spray zone (603), and from an uncontaminated well upgradient of the oil body (310) between the years 1986 and 1989, and again from wells 530 and 603 in 1998. The samples have been characterized by elemental analysis, radiocarbon dating, carbon-13 nuclear magnetic resonance spectroscopy (13C NMR), and negative-mode (-) electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FTICR-MS), with a particular focus on fractions from wells 310, 530, and 603.
All the characterization data indicate that the NVOAs from contaminated wells are distinguishable from the background DOC. Carbon-14 (14C) ages of NVOAs from contaminated wells ranged from 3,615 to 18,985 years before the present, whereas the background DOC from the aquifer was post-bomb (post 1950). By elemental analysis, NVOAs from contaminated wells had higher sulfur but lower nitrogen contents than the background. By electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, number average molecular weights determined from assigned molecular formulas ranged from 416 to 486 daltons for the HPOA and HPIA fractions from both background and contaminant wells. NVOAs from contaminated wells had significantly greater numbers of assigned molecular formulas containing sulfur, with elevated concentrations of the S1O4-10 species in particular. Compared to the background, HPOA and HPIA fractions from contaminant wells had a broader range of double bond equivalents (DBEs) within On compound classes (n is number of atoms). Additionally, within On compound classes, contaminant well HPOA fractions had a greater abundance of lower n (less than eight) than the background. Contaminant well double bond equivalents versus carbon number (C#) plots of oxygen compound classes suggest oil-derived aliphatic compounds in the range from C12 to C22 in HPOA and HPIA fractions and oil-derived compounds containing aromatic or saturated rings in the approximate range from C20 to C30 are present in HPOA fractions.
The data suggest the NVOAs originate from biodegradation of several classes of C12 and greater crude oil constituents: sulfur-containing constituents, including possibly the resins and asphaltenes; constituents containing aromatic rings substituted with methyl groups, including alkylaromatic and naph-
thenoaromatic compounds, and C12 to C22 alkyl constituents. The overall similarities of the carbon-13 nuclear magnetic resonance spectra for the well 603 and 530 samples from the two sampling dates suggest that a steady state in the composition of the partial oxidation products in each of the two wells had been reached between 1986–1989 and 1998.
Chief, USGS National Water Quality Laboratory
U.S. Geological Survey
Box 25585, Mail Stop 407
Denver, CO 80225-0585
The Community for Data Integration is a community of practice whose purpose is to advance the data integration capabilities of the U.S. Geological Survey. In fiscal year 2020, the Community for Data Integration held 11 monthly forums, facilitated 13 collaboration areas, and supported 13 projects. The activities supported the broad U.S. Geological Survey priority of producing building blocks for doing integrated predictive science. Specifically, the activities supported tools and methods for findable, accessible, interoperable, and reusable (FAIR) data and wildland fire and water prediction. Through these efforts, community members were informed of new and emerging technologies and data topics that helped them accomplish their professional responsibilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20221034","usgsCitation":"Hsu, L., Liford, A.N., and Donovan, G.C., 2022, Community for data integration 2020 annual report: U.S. Geological\nSurvey Open-File Report 2022–1034, 16 p., https://doi.org/10.3133/ofr20221034.","productDescription":"iii, 16 p.","onlineOnly":"Y","ipdsId":"IP-133268","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":402432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1034/coverthb.jpg"},{"id":402433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1034/ofr20221034.pdf","text":"Report","size":"1.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1034"},{"id":402434,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1034/images"},{"id":402435,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1034/ofr20221034.xml"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
This report assesses the status and trends of selected ecological health indicators of the Upper Mississippi River System (UMRS) based on the data collected and analyzed by the Long Term Resource Monitoring element of the Upper Mississippi River Restoration program, supplemented with data from other sources. This report has four objectives: providing a brief introduction of the UMRS, including its significance, history, modern-day stressors, and recent research; using ecological indicators to describe the status of the river system and where and how it has changed from circa 1993 to 2019; discussing management and restoration implications of these changes; and highlighting the fundamental role of long-term monitoring in the understanding, management, and restoration of large-floodplain rivers.
The data were collected in the six Long Term Resource Monitoring element study reaches that spanned much of the UMRS and the various gradients contained therein. These study reaches included Navigation Pools 4, 8, 13, and 26; the part of the Unimpounded Reach of the Upper Mississippi River between Grand Tower and Cairo, Illinois; and the La Grange Pool on the Illinois River. The indicators included in this report describe the status and trends for the hydrology, geomorphology, floodplain vegetation, water quality, vegetation, and fishes of the UMRS. Many of the indicators of river ecosystem health changed significantly over the nearly 30 years of our evaluation. However, there was substantial spatial variability in the magnitude and timing of those changes among study reaches. Few indicators changed everywhere or nowhere; most indicators changed in some reaches but not others. The quantitative assessments of these indicators describe how the conditions of the river differ across hydrogeomorphic and climate gradients and through time and are intended to support the restoration and management of the UMRS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221039","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Species Management Research Program and Land Management Research Program","usgsCitation":"Houser, J.N., ed., 2022, Ecological status and trends of the Upper Mississippi and Illinois Rivers (ver. 1.1, July 2022): U.S. Geological Survey Open-File Report 2022–1039, 199 p., https://doi.org/10.3133/ofr20221039.","productDescription":"xiv, 199 p.","numberOfPages":"220","onlineOnly":"N","ipdsId":"IP-125605","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":402335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1039/coverthb2.jpg"},{"id":402336,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1039/ofr20221039.pdf","text":"Report","size":"41.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1039"},{"id":403771,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2022/1039/versionHist.txt","size":"3.11 kB","linkFileType":{"id":2,"text":"txt"}},{"id":501772,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113198.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, North Dakota, South Dakota, Wisconsin","otherGeospatial":"Illinois River, upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.329833984375,\n 46.172222978455395\n ],\n [\n -90.340576171875,\n 46.30140615437332\n ],\n [\n -92.384033203125,\n 46.49082901981415\n ],\n [\n -93.087158203125,\n 46.74738913515841\n ],\n [\n -93.262939453125,\n 47.42065432071318\n ],\n [\n -94.3505859375,\n 47.76148371616669\n ],\n [\n -95.712890625,\n 47.30903424774781\n ],\n [\n -96.1083984375,\n 46.912750956378915\n ],\n [\n -96.1083984375,\n 46.18743678432541\n ],\n [\n -96.6357421875,\n 45.89000815866184\n ],\n [\n -97.393798828125,\n 45.867062714815475\n ],\n [\n -97.591552734375,\n 45.72152152227954\n ],\n [\n -96.50390625,\n 44.56699093657141\n ],\n [\n -95.43823242187499,\n 43.51668853502906\n ],\n [\n -95.042724609375,\n 42.70665956351041\n ],\n [\n -94.559326171875,\n 41.82045509614034\n ],\n [\n -94.02099609375,\n 41.20345619205131\n ],\n [\n -93.043212890625,\n 39.66491373749128\n ],\n [\n -92.61474609375,\n 39.172658670429946\n ],\n [\n -91.790771484375,\n 38.84826438869913\n ],\n [\n -90.977783203125,\n 38.762650338334154\n ],\n [\n -90.76904296874999,\n 38.736946065676\n ],\n [\n -91.14257812499999,\n 38.35888785866677\n ],\n [\n -91.58203125,\n 37.43997405227057\n ],\n [\n -90.8349609375,\n 36.86204269508728\n ],\n [\n -89.18701171875,\n 37.046408899699564\n ],\n [\n -88.72558593749999,\n 37.87485339352928\n ],\n [\n -88.87939453125,\n 38.685509760012\n ],\n [\n -87.69287109375,\n 40.863679665481676\n ],\n [\n -86.748046875,\n 41.178653972331674\n ],\n [\n -86.781005859375,\n 41.5579215778042\n ],\n [\n -87.593994140625,\n 41.46742831254425\n ],\n [\n -87.86865234374999,\n 42.374778361114195\n ],\n [\n -88.494873046875,\n 43.31718491566705\n ],\n [\n -89.3408203125,\n 43.810747313446996\n ],\n [\n -89.6484375,\n 43.937461690316646\n ],\n [\n -89.40673828125,\n 44.50434127765394\n ],\n [\n -89.329833984375,\n 46.172222978455395\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: June 22, 2022; Version 1.1: July 14, 2022","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
The National Cooperative Geologic Mapping Program is publishing a strategic plan titled “Renewing the National Cooperative Geologic Mapping Program as the Nation’s Authoritative Source for Modern Geologic Knowledge.” The plan provides a vision, mission, and goals for the program for the years 2020–30:
Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
In 2016, an interdisciplinary, international group of 53 scientists introduced a framework named “the FAIR Principles” for addressing 21st century scientific data challenges. The FAIR Principles are increasingly used as a guide for producing digital scientific products that are findable, accessible, interoperable, and reusable (FAIR), especially to enable use of such products in automated systems. Data aligned with the FAIR Principles can increase the efficiency of science integration capabilities such as those envisioned for the U.S. Geological Survey (USGS) Earth Monitoring, Analyses, and Projections (EarthMAP) initiative.
The FAIR Principles clearly define the characteristics of reusable scientific products, but it is less clear how to facilitate consistency in achieving these characteristics across the Bureau. USGS data are produced by local research projects distributed over more than 100 centers in 7 regions. After data are approved for release, they could be managed in numerous repositories and online data systems. The diversity of USGS data is illustrated by the topical range of the USGS mission areas: Core Science Systems, Ecosystems, Energy and Minerals, Natural Hazards, and Water Resources. In the USGS context, realizing the EarthMAP vision for automated, predictive, integrated science that provides timely and actionable results involves providing knowledge and support services and developing the skills, infrastructure, and culture to enable Bureau-wide implementation of the FAIR Principles.
In 2019, the USGS Community for Data Integration funded a project to convene a broadly representative workshop and produce recommendations to enable consistency with the FAIR Principles across the USGS. The workshop, held in Fort Collins, Colorado, in September 2019, brought together 28 participants for 3 days to engage with the FAIR Principles, analyze USGS use cases, and discuss the roles of data producers and managers, data storage and catalogs, value-added services, and policy makers in implementing the FAIR Principles. Workshop participants agreed that scientific reproducibility requires the extension of the FAIR Principles beyond measured data to include physical samples, research methods, software, and tools at the USGS. Workshop discussions focused on how the USGS can implement the FAIR Principles by supporting research teams in creating data, metadata, and other scientific products and also by supporting enterprise systems that maintain and leverage the products’ consistency with the FAIR Principles.
The resulting FAIR roadmap of recommendations describes nine proposed interdependent strategies that could be achieved by coordinated actions taken by different parts of the USGS. A proposed early action would be the creation of a coordinating council that includes representatives from the groups engaged in activities consistent with better alignment with the FAIR Principles. The nine proposed strategies, which are presented in more detail in this roadmap report, focus on enabling improvements to individual data products, providing infrastructure, and structuring administrative activities to support an organizational culture that values the FAIR Principles.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221043","usgsCitation":"Lightsom, F.L., Hutchison, V.B., Bishop, B., Debrewer, L.M., Govoni, D.L., Latysh, N., and Stall, S., 2022, Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data: U.S. Geological Survey Open-File Report 2022–1043, 23 p., https://doi.org/10.3133/ofr20221043.","productDescription":"vi, 23 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125836","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":402133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1043/coverthb.jpg"},{"id":402134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1043/ofr20221043.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1043"},{"id":402135,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1043/images/"},{"id":402136,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1043/ofr20221043.XML"}],"contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 4 (October–December), 2021. All data used to compile the Cal/Val analysis results presented in this report are freely available from the USGS EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the Cal/Val Team continued to closely monitor this quarter was the Landsat 8 Thermal Infrared Sensor (TIRS) response degradation, which has been observed since the two November 2020 safehold events. Detailed analysis results characterizing this degradation have been included in this report. Additional information about the safehold events is here: https://www.usgs.gov/core-science-systems/nli/landsat/november-19-2020-landsat-8-data-availability-update-recent-safehold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221033","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Tuli, F.T.Z., Shaw, J.L., Hasan, M.N., Denevan, A., Franks, S., Micijevic, E., Choate, M.J., Anderson, C., Markham, B., Thome, K., Kaita, E., Barsi, J., Levy, R., and Ong, L., 2022, ECCOE Landsat Quarterly Calibration and Validation report— Quarter 4, 2021: U.S. Geological Survey Open-File Report 2022–1033, 38 p., https://doi.org/10.3133/ofr20221033.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-137795","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":401936,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1033/ofr20221033.pdf","text":"Report","size":"3.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1033"},{"id":401934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1033/coverthb.jpg"},{"id":402059,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221033/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":401939,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":401938,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1033/images"},{"id":401937,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1033/ofr20221033.XML"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198