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
Surface-water-quality data in the Rapid Creek Basin in South Dakota were compiled to assess basic trends in the water quality of Rapid Creek. Spatial and temporal patterns in water quality were described for major ions, sediment, total suspended solids, nutrients, field measurements, bacteria, and select metals for the period of 1970–2020, and a water-quality trend analysis was completed for sites with enough data for selected constituents.
Major ions and total suspended solids had higher median concentrations in the lower basin (downstream from the city of Rapid City) relative to the upper and middle basins. Nutrient concentrations were generally low, and increased concentrations were only detected at the sites downstream from the City of Rapid City Water Reclamation Facility. Fecal indicator bacteria (Escherichia coli and fecal coliform) concentrations were highest downstream from the main urbanized area of Rapid City.
Water-quality trends were analyzed for total dissolved solids, specific conductance, calcium, magnesium, total suspended solids, total phosphorus, dissolved phosphorus, and total Kjeldahl nitrogen for the period of 1979–2019. Concentrations for major ions and total dissolved solids typically changed by less than 15 percent. Total dissolved solids concentrations upstream from Rapid City were generally decreasing, whereas concentrations downstream were generally increasing. The flow-averaged geometric mean concentration of total dissolved solids at three sites upstream from Rapid City decreased overall by 3–5 percent, and concentrations at two sites downstream from Rapid City increased by at least 7 percent between 1979 and 2019. Trends in specific conductance in the Rapid Creek Basin were mixed with alternating increasing and decreasing trends at many of the sites between 1979 and 2014. Total suspended solids concentrations were observed to be decreasing at two sites analyzed for trends. Concentrations in total phosphorus were observed to be decreasing at every site analyzed for trends between 1989 and 2014. Significant downward trends in total Kjeldahl nitrogen were observed at two sites in the lower Rapid Creek Basin for the trend period of 1999–2019. The decreases in total suspended solids and nutrient concentrations in the Rapid Creek Basin could be related to several processes such as the implementation of a stormwater management plan in Rapid City, improvements to the water reclamation facility downstream from Rapid City, and residual climatic effects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225086","collaboration":"Prepared in cooperation with the City of Rapid City","usgsCitation":"Tatge, W.S., Hoogestraat, G.K., and Nustad, R.A., 2022, Water-quality data and trends in the Rapid Creek Basin, South Dakota, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2022–5086, 67 p., https://doi.org/10.3133/sir20225086.","productDescription":"Report: viii, 67 p.; Data Release; Dataset","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-133856","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":405392,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225086/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":405347,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5086/sir20225086.XML"},{"id":405350,"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":405346,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5086/sir20225086.pdf","text":"Report","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5086"},{"id":405345,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5086/coverthb.jpg"},{"id":405349,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D8BSXR","text":"USGS data release","linkHelpText":"Model scripts and water-quality data for trends in the Rapid Creek Basin, South Dakota, 1970–2020"},{"id":405348,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5086/images"}],"country":"United States","state":"South Dakota","otherGeospatial":"Rapid Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0185546875,\n 43.84443209873525\n ],\n [\n -102.64251708984374,\n 43.84443209873525\n ],\n [\n -102.64251708984374,\n 44.213709909702054\n ],\n [\n -104.0185546875,\n 44.213709909702054\n ],\n [\n -104.0185546875,\n 43.84443209873525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Decades of research on the effects of urbanization on stream ecology have shown that urban stream problems are inherently wicked. These problems are wicked in the sense that they are difficult to solve because information is incomplete, changing, or conflicting and because finding potential solutions often requires input from stakeholders who can have conflicting and competing values. The 5th Symposium on Urbanization and Stream Ecology (SUSE5) in February 2020 brought together diverse perspectives from scientists, managers, practitioners, and local communities. Participants at SUSE5 discussed the state of the science in urban stream ecology and worked through in-depth case studies in teams to tackle complex real-world problems in urban stream management. The papers in this special series on urbanization and stream ecology include empirical research studies and synthesis papers sparked by discussions at SUSE5 and advance multidisciplinary solutions to wicked urban stream problems.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/721470","usgsCitation":"Fork, M.L., Hopkins, K.G., Chappell, J., Hawley, R.J., Kaushal, S., Murphy, B.M., Rios-Touma, B., and Roy, A.H., 2022, Urbanization and stream ecology: Moving the bar on multidisciplinary solutions to wicked urban stream problems: Freshwater Science, v. 41, no. 3, 6 p., https://doi.org/10.1086/721470.","productDescription":"6 p.","ipdsId":"IP-142003","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":405387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fork, Megan L.","contributorId":139659,"corporation":false,"usgs":false,"family":"Fork","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":12868,"text":"Nicholas School of the Environment, Duke University, Durham, NC, USA","active":true,"usgs":false}],"preferred":false,"id":849355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":849356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chappell, Jessica","contributorId":219589,"corporation":false,"usgs":false,"family":"Chappell","given":"Jessica","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":849357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawley, Robert J.","contributorId":167574,"corporation":false,"usgs":false,"family":"Hawley","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":24758,"text":"Sustainable Streams, LLC, Louisville, KY","active":true,"usgs":false}],"preferred":false,"id":849358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaushal, Sujay S.","contributorId":210125,"corporation":false,"usgs":false,"family":"Kaushal","given":"Sujay S.","affiliations":[{"id":38074,"text":"Univ. of Maryland","active":true,"usgs":false}],"preferred":false,"id":849359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Brian M. 0000-0002-7670-2469","orcid":"https://orcid.org/0000-0002-7670-2469","contributorId":292734,"corporation":false,"usgs":false,"family":"Murphy","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":849360,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rios-Touma, Blanca","contributorId":295395,"corporation":false,"usgs":false,"family":"Rios-Touma","given":"Blanca","email":"","affiliations":[{"id":63858,"text":"Universidad de Las Américas","active":true,"usgs":false}],"preferred":false,"id":849361,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":849362,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70235807,"text":"70235807 - 2022 - Magnetotelluric investigations of the Kīlauea Volcano, Hawaii","interactions":[],"lastModifiedDate":"2022-08-22T14:35:53.522926","indexId":"70235807","displayToPublicDate":"2022-08-22T09:35:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Magnetotelluric investigations of the Kīlauea Volcano, Hawaii","docAbstract":"In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the U.S. Geological Survey (USGS) Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kīlauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kīlauea and the East and Southwest Rift zones, which has implications for understanding Kīlauea's plumbing system. An improved understanding of the rift zones has implications in understanding large-scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi-station robust processing techniques. In total, data were acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone, where electrical contact resistances are on the order of 100 kΩ. A three-dimensional (3D) MT model study was done to guide interpretation of the observed MT measurements. Synthetic modeling demonstrates that conductive bodies in the upper 3 km can be spatially resolved where MT station sampling is good. Resistivity anomalies in the 3D inversions have a high degree of spatial correlation with previously published seismic velocity anomalies beneath Kīlauea. Melt fractions between 0.096 and 0.117 are calculated for the Kīlauea and Puʻuʻōʻō low resistivity anomalies, respectively.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB024418","usgsCitation":"Hoversten, G., Gasperikova, E., Mackie, R., Myer, D., Kauahikaua, J.P., Newman, G.A., and Cuevas, N., 2022, Magnetotelluric investigations of the Kīlauea Volcano, Hawaii: Journal of Geophysical Research: Solid Earth, v. 127, no. 8, e2022JB024418, 24 p., https://doi.org/10.1029/2022JB024418.","productDescription":"e2022JB024418, 24 p.","ipdsId":"IP-135899","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":446701,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022jb024418","text":"External Repository"},{"id":405386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.29131889343262,\n 19.396901484778134\n ],\n [\n -155.28496742248535,\n 19.39892544698541\n ],\n [\n -155.2786159515381,\n 19.399087362874425\n ],\n [\n -155.2730369567871,\n 19.39827778181811\n ],\n [\n -155.2676296234131,\n 19.400949384016776\n ],\n [\n -155.26385307312012,\n 19.403944764615613\n ],\n [\n -155.25887489318848,\n 19.40629245679785\n ],\n [\n -155.2511501312256,\n 19.4109877394962\n ],\n [\n -155.24694442749023,\n 19.408882974361152\n ],\n [\n -155.24042129516602,\n 19.408478208711944\n ],\n [\n -155.23784637451172,\n 19.410906787494763\n ],\n [\n -155.23836135864258,\n 19.414306736852605\n ],\n [\n -155.24102210998535,\n 19.414306736852605\n ],\n [\n -155.2434253692627,\n 19.418758943963656\n ],\n [\n -155.24943351745605,\n 19.42353481237166\n ],\n [\n -155.25372505187985,\n 19.427662992293143\n ],\n [\n -155.25853157043457,\n 19.4298484568423\n ],\n [\n -155.26239395141602,\n 19.43081976498137\n ],\n [\n -155.2672004699707,\n 19.430576938491143\n ],\n [\n -155.2708911895752,\n 19.4313863587134\n ],\n [\n -155.27406692504883,\n 19.432033891986865\n ],\n [\n -155.2799892425537,\n 19.429605628899985\n ],\n [\n -155.28857231140134,\n 19.42013505603468\n ],\n [\n -155.29492378234863,\n 19.416492381036047\n ],\n [\n -155.2946662902832,\n 19.413416280797698\n ],\n [\n -155.29646873474118,\n 19.410663931248664\n ],\n [\n -155.29698371887207,\n 19.407021044033193\n ],\n [\n -155.29131889343262,\n 19.396901484778134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoversten, G.M.","contributorId":295409,"corporation":false,"usgs":false,"family":"Hoversten","given":"G.M.","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":849391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gasperikova, Erika","contributorId":193561,"corporation":false,"usgs":false,"family":"Gasperikova","given":"Erika","affiliations":[],"preferred":false,"id":849392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mackie, Randall","contributorId":295410,"corporation":false,"usgs":false,"family":"Mackie","given":"Randall","email":"","affiliations":[{"id":63861,"text":"CGG Multiphysics","active":true,"usgs":false}],"preferred":false,"id":849393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Myer, David","contributorId":206497,"corporation":false,"usgs":false,"family":"Myer","given":"David","email":"","affiliations":[],"preferred":false,"id":849394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauahikaua, James P. 0000-0003-3777-503X jimk@usgs.gov","orcid":"https://orcid.org/0000-0003-3777-503X","contributorId":2146,"corporation":false,"usgs":true,"family":"Kauahikaua","given":"James","email":"jimk@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":849395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, Greg A.","contributorId":295412,"corporation":false,"usgs":false,"family":"Newman","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":63862,"text":"Lawrence Berkeley National Laboratory, Sandia National Laboratory","active":true,"usgs":false}],"preferred":false,"id":849396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cuevas, Nestor","contributorId":295414,"corporation":false,"usgs":false,"family":"Cuevas","given":"Nestor","email":"","affiliations":[{"id":63864,"text":"Electromagnetic Instruments","active":true,"usgs":false}],"preferred":false,"id":849397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256645,"text":"70256645 - 2022 - Role of landscape features in resource selection by female Greater Prairie-chickens within a constrained environment","interactions":[],"lastModifiedDate":"2024-08-29T14:15:54.163395","indexId":"70256645","displayToPublicDate":"2022-08-22T09:10:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Role of landscape features in resource selection by female Greater Prairie-chickens within a constrained environment","docAbstract":"Greater Prairie-chickens (Tympanuchus cupido) historically occupied 20 states within the contiguous United States; however, due to habitat degradation and loss, they are currently found in 11 states, only four of which have a stable population. Kansas supports a relatively large abundance of Greater Prairie-chickens, where the Flint Hills ecoregion historically supported the largest population density of all ecoregions. In the past decade, the Flint Hills population has declined by 75 % to an estimated 8,334 individuals in 2021 from 34,180 individuals in 2015 due to landscape changes and intensification of grassland management practices. The Fort Riley Military Reservation in the northwest portion of the Flint Hills ecoregion is one of a few areas within the ecoregion that does not implement grazing or vast annual burning. The Greater Prairie-chicken population within Fort Riley has remained relatively stable over the past 25 years despite being constrained by surrounding landscape features and development. We analyzed multiple scales of resource selection by 46 female Greater Prairie-chickens during March-April 2019–2021 on Fort Riley to investigate why this population is doing relatively well compared to populations in surrounding areas. We tested landscape feature, vegetation, and burn mosaic variables to evaluate which variables had the greatest influence on resource selection. Landscape features had the greatest influence on resource selection. Females avoided trees within Fort Riley for both breeding season use and nest-site selection at a greater margin than any other study in Kansas. Additionally, fourth-order selection was not evident within this study system, contrary to studies within surrounding areas. Our findings join a growing body of literature that suggests containment of woody encroachment as a high priority for managers to maintain or expand prairie grouse habitat in many different environments. This containment is especially critical on Fort Riley because of its constrained environment, and further woody encroachment could lead to loss of habitat that is inescapable by the Greater Prairie-chicken population on Fort Riley. Spatially-explicit evaluations of habitat availability are increasingly important as more areas within the Greater Prairie-chicken range become constrained by urbanization, agricultural expansion, and intensive management practices.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02267","usgsCitation":"Gehrt, J., Moon, D.A., Stratton, S.C., and Haukos, D.A., 2022, Role of landscape features in resource selection by female Greater Prairie-chickens within a constrained environment: Global Ecology and Conservation, v. 38, e02267, 13 p., https://doi.org/10.1016/j.gecco.2022.e02267.","productDescription":"e02267, 13 p.","ipdsId":"IP-139155","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446703,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02267","text":"Publisher Index Page"},{"id":433302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Fort Riley Military Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.82607950738709,\n 39.04415304738848\n ],\n [\n -96.82067969589669,\n 39.04542338932923\n ],\n [\n -96.81264803264634,\n 39.066451102696\n ],\n [\n -96.7923343945162,\n 39.058185802106635\n ],\n [\n -96.76938890462613,\n 39.05945727775277\n ],\n [\n -96.75305336218368,\n 39.08838501409363\n ],\n [\n -96.73759510366125,\n 39.078835126800456\n ],\n [\n -96.70508270366084,\n 39.09431408766408\n ],\n [\n -96.7173117835789,\n 39.13021716548451\n ],\n [\n -96.68243974776027,\n 39.13008052495802\n ],\n [\n -96.68090450090028,\n 39.20341992876942\n ],\n [\n -96.84367647787,\n 39.301076682296724\n ],\n [\n -96.95952320021819,\n 39.3101541162184\n ],\n [\n -96.96098961442516,\n 39.209101370407836\n ],\n [\n -96.90984125155101,\n 39.18116605625954\n ],\n [\n -96.88033683304346,\n 39.18182625944928\n ],\n [\n -96.88913531828524,\n 39.15454056170077\n ],\n [\n -96.87740400462953,\n 39.13975638913726\n ],\n [\n -96.83047875000798,\n 39.137481625428194\n ],\n [\n -96.86753927807851,\n 39.07132797338471\n ],\n [\n -96.82607950738709,\n 39.04415304738848\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gehrt, Jacquelyn M.","contributorId":341459,"corporation":false,"usgs":false,"family":"Gehrt","given":"Jacquelyn M.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moon, Derek A.","contributorId":341460,"corporation":false,"usgs":false,"family":"Moon","given":"Derek","email":"","middleInitial":"A.","affiliations":[{"id":81742,"text":"Fort Riley Environmental Division","active":true,"usgs":false}],"preferred":false,"id":908460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton, Shawn C.","contributorId":341461,"corporation":false,"usgs":false,"family":"Stratton","given":"Shawn","email":"","middleInitial":"C.","affiliations":[{"id":81743,"text":"Fort Riley Training Division","active":true,"usgs":false}],"preferred":false,"id":908461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":908462,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255669,"text":"70255669 - 2022 - GSPy: A new toolbox and data standard for Geophysical Datasets","interactions":[],"lastModifiedDate":"2026-03-10T13:23:35.700958","indexId":"70255669","displayToPublicDate":"2022-08-22T06:45:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17985,"text":"Frontiers in Earth Science - Environmental Informatics and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"GSPy: A new toolbox and data standard for Geophysical Datasets","docAbstract":"The diversity of geophysical methods and datatypes, as well as the isolated nature of various specialties (e.g., electromagnetic, seismic, potential fields) leads to a profusion of separate data file formats and documentation conventions. This can hinder cooperation and reduce the impact of datasets researchers have invested in heavily to collect and prepare. An open, portable, and well-supported community data standard could greatly improve the interoperability, transferability, and long-term archival of geophysical data. Airborne geophysical methods particularly need an open and accessible data standard, and they exemplify the complexity that is common in geophysical datasets where critical auxiliary information on the survey and system parameters are required to fully utilize and understand the data. Here, we propose a new Geophysical Standard, termed the GS convention, that leverages the well-established and widely used NetCDF file format and builds on the Climate and Forecasts (CF) metadata convention. We also present an accompanying open-source Python package, GSPy, to provide methods and workflows for building the GS-standardized NetCDF files, importing and exporting between common data formats, preparing input files for geophysical inversion software, and visualizing data and inverted models. By using the NetCDF format, handled through the Xarray Python package, and following the CF conventions, we standardize how metadata is recorded and directly stored with the data, from general survey and system information down to specific variable attributes. Utilizing the hierarchical nature of NetCDF, GS-formatted files are organized with a root Survey group that contains global metadata about the geophysical survey. Data are then organized into subgroups beneath Survey and are categorized as Tabular or Raster depending on the geometry and point of origin for the data. Lastly, the standard ensures consistency in constructing and tracking coordinate reference systems, which is vital for accurate portability and analysis. Development and adoption of a NetCDF-based data standard for geophysical surveys can greatly improve how these complex datasets are shared and utilized, making the data more accessible to a broader science community. The architecture of GSPy can be easily transferred to additional geophysical datatypes and methods in future releases.
A paucity of detailed relative sea-level (RSL) reconstructions from low latitudes hinders efforts to understand the global, regional, and local processes that cause RSL change. We reconstruct RSL change during the past ~5 ka using cores of mangrove peat at two sites (Snipe Key and Swan Key) in the Florida Keys. Remote sensing and field surveys established the relationship between peat-forming mangroves and tidal elevation in South Florida. Core chronologies are developed from age-depth models applied to 72 radiocarbon dates (39 mangrove wood macrofossils and 33 fine-fraction bulk peat). RSL rose 3.7 m at Snipe Key and 5.0 m at Swan Key in the past 5 ka, with both sites recording the fastest century-scale rate of RSL rise since ~1900 CE (~2.1 mm/a). We demonstrate that it is feasible to produce near-continuous reconstructions of RSL from mangrove peat in regions with a microtidal regime and accommodation space created by millennial-scale RSL rise. Decomposition of RSL trends from a network of reconstructions across South Florida using a spatio-temporal model suggests that Snipe Key was representative of regional RSL trends, but Swan Key was influenced by an additional local-scale process acting over at least the past five millennia. Geotechnical analysis of modern and buried mangrove peat indicates that sediment compaction is not the local-scale process responsible for the exaggerated RSL rise at Swan Key. The substantial difference in RSL between two nearby sites highlights the critical need for within-region replication of RSL reconstructions to avoid misattribution of sea-level trends, which could also have implications for geophysical modeling studies using RSL data for model tuning and validation.
Large-area, high-resolution digital elevation models (DEMs) created from light detection and ranging (LIDAR) and/or multibeam echosounder data sets are commonly used in many scientific disciplines. These DEMs can span thousands of square kilometers, typically with a spatial resolution of 1 m or finer, and can be difficult to process and analyze without specialized computers and software. Such DEMs often can be subsampled to expedite analysis with negligible impact on results for large-scale geospatial analyses. Subsampling can be achieved by creating a grid of points that specify the locations from which to extract elevation values from the DEM. This paper presents a method that can be used to accurately perform subsampling of large-scale, high-resolution DEMs using GIS software. This subsampling method was applied to two LIDAR-derived DEMs encompassing 242 km2 of the northern Florida Reef Tract as an example application and to test subsampling accuracy. Results indicate that subsampling 1-m-resolution DEMs using a 2-m-spaced grid results in no significant difference in mean elevation or other basic statistics for analyses performed over multiple spatial scales ranging from 1 km2 to 242 km2.
An uncrewed aerial vehicle (UAV) multirotor aeromagnetic system using a 5-m sling load for a magnetic sensor system is described and characterized. Four magnetic surveys with identical flight lines were completed, at two nominal altitudes of 25 and 40 m. The surveys were used to assess the repeatability of data collected with the described UAV aeromagnetic system, and comparison with a ground survey was used to assess the precision. The 5-m sling is designed to reduce magnetic interference from the UAV. A magnetic compensation model was developed for this particular UAV aeromagnetic system. This custom compensation model reduces the noise in the collected data by a factor of five over the uncompensated data, and the 5-m sling further reduces the noise by an estimated factor of four over a similar system with a 3-m sling. The precision of the UAV aeromagnetic system was then estimated to be sub-nT, with 50% of the noise component <0.3 nT, and 90% <0.6 nT.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jappgeo.2022.104779","usgsCitation":"Phelps, G., Bracken, R.E., Spritzer, J., and White, D.S., 2022, Achieving sub-nanoTesla precision in multirotor UAV aeromagnetic surveys: Journal of Applied Geophysics, v. 206, 104779, 16 p., https://doi.org/10.1016/j.jappgeo.2022.104779.","productDescription":"104779, 16 p.","ipdsId":"IP-130875","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":446713,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jappgeo.2022.104779","text":"Publisher Index Page"},{"id":435723,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HCY1NQ","text":"USGS data release","linkHelpText":"UASmagpy: Python code for compensating rotary-wing sling-load UAS aeromagnetic data"},{"id":435722,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92MXMM5","text":"USGS data release","linkHelpText":"Uncrewed aerial system aeromagnetic test survey at the Boulder Magnetic Observatory"},{"id":411343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":860859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bracken, Robert E. 0000-0001-7759-2743 rbracken@usgs.gov","orcid":"https://orcid.org/0000-0001-7759-2743","contributorId":2640,"corporation":false,"usgs":true,"family":"Bracken","given":"Robert","email":"rbracken@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":860860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spritzer, John 0000-0002-2147-530X jspritzer@usgs.gov","orcid":"https://orcid.org/0000-0002-2147-530X","contributorId":244361,"corporation":false,"usgs":true,"family":"Spritzer","given":"John","email":"jspritzer@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":860861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, David S.","contributorId":173069,"corporation":false,"usgs":false,"family":"White","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":860862,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237919,"text":"70237919 - 2022 - Whole-ecosystem experiment illustrates short timescale hydrodynamic, light, and nutrient control of primary production in a terminal slough","interactions":[],"lastModifiedDate":"2022-11-01T13:50:50.001339","indexId":"70237919","displayToPublicDate":"2022-08-21T08:28:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Whole-ecosystem experiment illustrates short timescale hydrodynamic, light, and nutrient control of primary production in a terminal slough","docAbstract":"Estuaries are among the most productive of aquatic ecosystems. Yet the collective understanding of patterns and drivers of primary production in estuaries is incomplete, in part due to complex hydrodynamics and multiple controlling factors that vary at a range of temporal and spatial scales. A whole-ecosystem experiment was conducted in a deep, pelagically dominated terminal channel of the Sacramento-San Joaquin Delta (California, USA) that seasonally appears to become nitrogen limited, to test whether adding calcium nitrate would stimulate primary productivity or increase phytoplankton density. Production did not respond consistently to fertilization, in part because nitrate and phytoplankton were dispersed away from the manipulated area within 1–3 days. Temporal and spatial patterns of gross primary production were more strongly related to stratification and light availability (i.e., turbidity) than nitrogen, highlighting the role of hydrodynamics in regulating system production. Similarly, chlorophyll was positively related not only to stratification but also to nitrogen—with a positive interaction—suggesting stratification may trigger nutrient limitation. The average rate of primary production (4.3 g O2 m−2 d−1), metabolic N demand (0.023 mg N L−1 d−1), and ambient dissolved inorganic nitrogen concentration (0.03 mg N L−1) indicate that nitrogen can become limiting in time and space, especially during episodic stratification events when phytoplankton are isolated within the photic zone, or farther upstream where water clarity increases, dispersive flux decreases, and stratification is stronger and more frequent. The role of hydrodynamics in organizing habitat connectivity and regulating physical and chemical processes at multiple temporal and spatial scales is critical for determining resource availability and evaluating biogeochemical processes in estuaries.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-022-01111-8","usgsCitation":"Loken, L.C., Sadro, S., Lenoch, L., Stumpner, P., Dahlgren, R.A., Burau, J.R., and Van Nieuwenhuyse, E.E., 2022, Whole-ecosystem experiment illustrates short timescale hydrodynamic, light, and nutrient control of primary production in a terminal slough: Estuaries and Coasts, v. 45, p. 2428-2449, https://doi.org/10.1007/s12237-022-01111-8.","productDescription":"22 p.","startPage":"2428","endPage":"2449","ipdsId":"IP-136358","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":446716,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-022-01111-8","text":"Publisher Index Page"},{"id":408986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River Deep Water Ship Channel","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5493802954393,\n 38.55374191573719\n ],\n [\n -121.70672314658754,\n 38.55374191573719\n ],\n [\n -121.70672314658754,\n 38.26810056353631\n ],\n [\n -121.5493802954393,\n 38.26810056353631\n ],\n [\n -121.5493802954393,\n 38.55374191573719\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2022-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":856204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lenoch, Leah 0000-0003-4613-0858","orcid":"https://orcid.org/0000-0003-4613-0858","contributorId":270181,"corporation":false,"usgs":true,"family":"Lenoch","given":"Leah","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahlgren, Randy A 0000-0002-8961-875X","orcid":"https://orcid.org/0000-0002-8961-875X","contributorId":269424,"corporation":false,"usgs":false,"family":"Dahlgren","given":"Randy","email":"","middleInitial":"A","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":856207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Nieuwenhuyse, Erwin E 0000-0002-9032-2681","orcid":"https://orcid.org/0000-0002-9032-2681","contributorId":269423,"corporation":false,"usgs":false,"family":"Van Nieuwenhuyse","given":"Erwin","email":"","middleInitial":"E","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":856209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70242886,"text":"70242886 - 2022 - Revised earthquake recurrence intervals in California, USA: New paleoseismic sites and application of event likelihoods","interactions":[],"lastModifiedDate":"2023-04-21T12:02:06.957613","indexId":"70242886","displayToPublicDate":"2022-08-21T07:00:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Revised earthquake recurrence intervals in California, USA: New paleoseismic sites and application of event likelihoods","docAbstract":"Recurrence intervals for ground rupturing earthquakes are critical data for assessing seismic hazard. Recurrence intervals are presented here for 38 paleoseismic sites in California. Eleven of these include new or updated data; the remainder use data previously included in the Unified California Earthquake Rupture Forecast Version 3 (UCERF3). The methods and results are consistent with UCERF3. In addition, revised recurrence intervals are presented at every site. The revised recurrence intervals incorporate uncertainty in the interpretation of paleoseismic evidence, which is expressed as event likelihood. Event likelihood is the probability that the evidence has been correctly interpreted as a unique earthquake. Event likelihoods are estimated here for 85 inferred past earthquakes at eight paleoseismic sites in California, using a single, consistent methodology. The average event likelihood is 0.85. The revised recurrence intervals are 16% longer, on average, than conventional estimates, and their confidence intervals are disproportionately wider. These recurrence intervals are suitable for inclusion in a “grand inversion” rupture forecast, and they may be important for addressing a systematic misfit in the UCERF3 grand inversion. The revised recurrence intervals may also be important for assessing the unusually long earthquake hiatus in California. Other applications may not need to consider event likelihoods because the effects are small relative to typical uncertainties.
Synthesizing large, complex data sets to inform resource managers towards effective environmental stewardship is a universal challenge. In Chesapeake Bay, a well-studied and intensively monitored estuary in North America, the challenge of synthesizing data on water quality and land use as factors related to a key habitat, submerged aquatic vegetation, was tackled by a team of scientists and resource managers operating at multiple levels of governance (state, federal). The synthesis effort took place over a two-year period (2016–2018), and the results were communicated widely to a) scientists via peer review publications and conference presentations; b) resource managers via web materials and workshop presentations; and c) the public through newspaper articles, radio interviews, and podcasts. The synthesis effort was initiated by resource managers at the United States Environmental Protection Agencys’ Chesapeake Bay Program and 16 scientist participants were recruited from a diversity of organizations. Multiple short, immersive workshops were conducted regularly to conceptualize the problem, followed by data analysis and interpretation that supported the preparation of the synthetic products that were communicated widely. Reflections on the process indicate that there are a variety of structural and functional requirements, as well as enabling conditions, that need to be considered to achieve successful outcomes from synthesis efforts.
The U.S. Geological Survey maintains a network of hydrologic monitoring stations across Kansas in cooperation with Federal, State, Tribal, and local agencies. During water year 2021, this network included 230 real-time surface water data collection sites, referred to as “streamgages.” A water year is the 12-month period from October 1 through September 30 and is designated by the calendar year in which it ends. These real-time data are routinely collected and calibrated by U.S. Geological Survey personnel via regular measurements of streamflow and water levels. Analyses of these data provide an understanding of hydrologic conditions in the State critical to the management of water resources, industrial and agricultural uses, protection of life and property during flooding, operation of reservoirs, recreation, and other activities.
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U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The maps and graphs in this summary describe national streamflow conditions for water year 2021 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2021 was from October 1, 2020, to September 30, 2021) in the context of streamflow ranks relative to the 92-year period of water years 1930–2021. Annual runoff in the Nation’s rivers and streams during water year 2021 (9.43 inches) was higher than the long-term (1930–2021) mean annual runoff of 9.42 inches for the contiguous United States. Nationwide, the 2021 streamflow ranked the 46th highest out of the 92 years.
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415 National Center
Reston, Virginia 20192
The glacial geology and hydrogeology of valley-fill aquifers and their surrounding uplands are described within a 112-square-mile area in southern Otsego and northwestern Delaware Counties, New York, centered around the City of Oneonta. The major valleys include those of the Susquehanna River, Otego Creek, Charlotte Creek, and Schenevus Creek. A variety of data were analyzed to provide a broad picture of the glacial deposits, hydrogeologic framework, aquifer occurrence, and water-resource potential in the area. Both valley-fill and bedrock aquifers are used for water supply within the study area. The valley-fill aquifers consist of coarse-grained stratified drift, are mostly limited to the larger valleys, and have well yields that typically are much greater than those obtained from the bedrock aquifers. The bedrock aquifers generally have lower well yields, are the sole source of groundwater in upland areas, and are tapped in valley areas where sediments are very silty or are absent.
Through and non-through valleys and their orientations relative to ice flow have resulted in a variety of deglacial environments and deposits, some of which depart from glacial stratigraphy typically observed elsewhere in central New York. In comparison to through valleys with low in-valley divides, the regional thinning of ice over the high bedrock divides of the non-through valleys resulted in the earlier and more widespread stagnation of glacial ice, development of dead-ice sinks, and earlier diversion of meltwater from ice north of the divides. As the main through valley in the study area, the Susquehanna River valley is characterized by multiple inferred ice-margin positions with associated outwash deposition or ice-contact deposits. Throughout the study area, valleys orientated parallel or subparallel to the ice flow facilitated the development of long ice tongues; valleys oriented perpendicular to the ice flow led to little ice-tongue development, but they did facilitate the deposition of the extensive kame moraines that now occupy several-mile-long valley reaches. Lacustrine sediments were deposited in proglacial lakes. These sediments underlie most valleys that were oriented parallel and subparallel to ice flow, but they are largely absent in the Charlotte Creek valley, which was oriented perpendicular to the ice flow and now contains an extensive kame moraine. Beneath these lacustrine deposits, sand and gravel were deposited as subaqueous fans, eskers, and the distal parts of delta (kame) terraces, each with variable silt content.
The presence of coarse-grained stratified deposits, their saturated thicknesses, and their recharge potential are the primary controls on aquifer locations in the study area. The most widespread aquifers in the study area consist of sand and gravel and are confined mostly beneath lacustrine deposits. Confined aquifer yields are enhanced by hydraulic connections with unconfined ice-contact deposits along the valley walls, especially where tributary streams cross these deposits and provide additional recharge through streambed infiltration. The Susquehanna River and other large valley creeks provide a potentially large source of recharge to aquifers where groundwater withdrawals from nearby production wells induce infiltration of river water into aquifers. Unconfined aquifers are present where ice-contact deposits extend below the valley floor and are sufficiently saturated. Most surficial outwash deposits in the study area are thinly saturated; thus their water-resource potential is likely to be limited.
The upland areas contain very little stratified drift; therefore, characterization was limited to delineating areas of thick till and thin, or absent, till. Recharge of bedrock aquifers is greatest in areas overlain by thin till or where bedrock is exposed at land surface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225069","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Heisig, P.M., and Fleisher, P.J., 2022, Glacial geology and hydrogeology of valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York: U.S. Geological Survey Scientific Investigations Report 2022–5069, 35 p., 1 pl., https://doi.org/10.3133/sir20225069.","productDescription":"Report: vii, 35 p.; 1 Plate: 36.00 × 40.00 inches; 1 Figure: 25.00 × 17.00 inches ; Data Releases","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118408","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":405214,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCQS14","text":"USGS data release","linkHelpText":"Geospatial datasets of the glacial geology and hydrogeology of valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York"},{"id":405211,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5069"},{"id":405199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5069/coverthb.jpg"},{"id":405219,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069_plate01.pdf","text":"Plate 1","size":"177 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of glacial geology and hydrogeology of valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York [layered pdf; to toggle layers, download the file (right-click and select \"Save link as...\") and open it with Adobe Acrobat Reader]"},{"id":405210,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5069"},{"id":405212,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069.XML"},{"id":405213,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5069/images/"},{"id":405218,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069_fig04a.pdf","text":"Figure 4A","size":"423 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Primary longitudinal hydrogeologic section A.1–A.1′ and secondary longitudinal hydrogeologic section A.2–A.2′ along the Susquehanna River valley, Otsego County, New York"},{"id":405216,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGQUJL","text":"USGS data release","linkHelpText":"Horizontal-to-vertical spectral ratio (HVSR) soundings in Broome, Chenango, Franklin, Orange, Rensselaer, and Saratoga Counties, New York, and Susquehanna County, Pennsylvania 2010–2019"},{"id":405215,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92NSO7T","text":"USGS data release","linkHelpText":"Horizontal-to-vertical spectral ratio soundings and depth-to-bedrock data for valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York, 2016–2018"}],"country":"United States","state":"New York","county":"Delaware County, Otsego County","otherGeospatial":"Oneonta area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1667,\n 42.4167\n ],\n [\n -74.9167,\n 42.4167\n ],\n [\n -74.9167,\n 42.5833\n ],\n [\n -75.1667,\n 42.5833\n ],\n [\n -75.1667,\n 42.4167\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
The use of simple models for response prediction of building structures is preferred in earthquake engineering for risk evaluations at regional scales, as they make computational studies more feasible. The primary impediment in their gainful use presently is the lack of viable methods for quantifying (and reducing upon) the modeling errors/uncertainties they bear. This study presents a Bayesian calibration method wherein the modeling error is embedded into the parameters of the model. The method is specifically described for coupled shear-flexural beam models here, but it can be applied to any parametric surrogate model. The major benefit the method offers is the ability to consider the modeling uncertainty in the forward prediction of any degree-of-freedom or composite response regardless of the data used in calibration. The method is extensively verified using two synthetic examples. In the first example, the beam model is calibrated to represent a similar beam model but with enforced modeling errors. In the second example, the beam model is used to represent the detailed finite element model of a 52-story building. Both examples show the capability of the proposed solution to provide realistic uncertainty estimation around the mean prediction.
","language":"English","publisher":"Wiley","doi":"10.1002/stc.3078","usgsCitation":"Ghahari, S., Sargsyan, K., Celebi, M., and Taciroglu, E., 2022, Quantifying modeling uncertainty in simplified beam models for building response prediction: Structural Control and Health Monitoring, v. 29, no. 11, e3078, https://doi.org/10.1002/stc.3078.","productDescription":"e3078","ipdsId":"IP-139979","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":446722,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1882634","text":"Publisher Index Page"},{"id":407408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Ghahari, S. Farid","contributorId":296977,"corporation":false,"usgs":false,"family":"Ghahari","given":"S. Farid","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":853025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sargsyan, Khachik","contributorId":296978,"corporation":false,"usgs":false,"family":"Sargsyan","given":"Khachik","email":"","affiliations":[{"id":64263,"text":"Sandia Laboratories","active":true,"usgs":false}],"preferred":false,"id":853026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":853027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taciroglu, Ertugrul","contributorId":296979,"corporation":false,"usgs":false,"family":"Taciroglu","given":"Ertugrul","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":853028,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70235868,"text":"70235868 - 2022 - The Water Recycling Revolution: Tapping into the future","interactions":[],"lastModifiedDate":"2022-09-15T15:19:15.334305","indexId":"70235868","displayToPublicDate":"2022-08-19T09:18:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"The Water Recycling Revolution: Tapping into the future","docAbstract":"The Water Recycling Revolution discusses issues affecting acceptance of water reuse for public supply. The book is useful to water resource, regulatory, and public health professionals interested in the history of successful and unsuccessful attempts to conserve, recycle, and reuse treated municipal wastewater as a public resource. The book is timely given the extended drought conditions throughout much of the American southwest and the almost one billion gallons of water available daily for reuse in southern California alone (Ding, 2022).","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13243","usgsCitation":"Izbicki, J.A., 2022, The Water Recycling Revolution: Tapping into the future: Groundwater, v. 60, no. 5, p. 581-582, https://doi.org/10.1111/gwat.13243.","productDescription":"2 p.","startPage":"581","endPage":"582","ipdsId":"IP-143606","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":405681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":849582,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70259623,"text":"70259623 - 2022 - High-resolution marine seismic imaging of the Seattle fault zone: Near surface insights into fault zone geometry, Quaternary deformation, and long-term evolution","interactions":[],"lastModifiedDate":"2024-10-17T12:00:47.133274","indexId":"70259623","displayToPublicDate":"2022-08-19T06:59:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution marine seismic imaging of the Seattle fault zone: Near surface insights into fault zone geometry, Quaternary deformation, and long-term evolution","docAbstract":"The Seattle fault zone (SFZ) is a north‐directed thrust fault system that underlies the greater Seattle metropolitan area. Evidence of past land level changes, landslides, liquefaction, and a local tsunami indicate that this 70‐km‐long fault system can host up to M 7–7.5 earthquakes. Both the geometry and earthquake recurrence of the SFZ are debated and surveys of the shallow subsurface have not yet been incorporated into deeper crustal‐scale structural interpretations, especially where the SFZ cuts across marine portions of the Puget Lowland. Here we use a new high‐resolution marine seismic reflection dataset to image fault‐related deformation in Quaternary sediments and Tertiary bedrock throughout Puget Sound and Lake Washington. We use this perspective of shallow geology as a link between existing crustal‐scale geophysical insights into fault geometry at depth and paleoseismological observations of faulting at the surface and propose a refined structural model for the SFZ. We interpret that our new seismic reflection data in the Rich Passage area of Puget Sound images evidence of an inactive, south‐dipping strand of the SFZ, which is overprinted by Quaternary folding and slip along north‐dipping backthrusts within the hanging wall of a blind, south‐dipping fault located 6 km farther north. To explain these results, we propose that the SFZ is a normal sequence fault propagation fold that has stepped northward through time, and we show the plausibility of this model through trishear forward modeling. Growth strata and faulting imaged in Quaternary sediments in Lake Washington and Rich Passage are consistent with the spatial distribution of folding and backthrusting that occurred during an M 7–7.5 earthquake in A.D. 900–930, corroborating existing evidence that the SFZ has been active throughout the Quaternary.
Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns. We highlight micropollutants to be prioritized due to their high occurrence and critical concentration levels compared to environmental quality standards. These top-listed micropollutants include contaminants from all chemical classes (pesticides, heavy metals, polycyclic aromatic hydrocarbons, personal care products, pharmaceuticals, and industrial and household chemicals). Analysis of over 30,000 event mean concentrations shows a large fraction of measurements (> 50%) were below the limit of quantification, stressing the need for reliable, standard monitoring procedures. High variability was observed among events and sites, with differences between micropollutant classes. The number of events required for a reliable estimate of site mean concentrations (error bandwidth of 1 around the “true\" value) depends on the individual micropollutant. The median minimum number of events is 7 for CSO (2 to 31, 80%-interquantile) and 6 for SWO (1 to 25 events, 80%-interquantile). Our analysis indicates the minimum number of sites needed to assess global pollution levels and our data collection and analysis can be used to estimate the required number of sites for an urban catchment. Our data-driven analysis demonstrates how future wet-weather monitoring programs will be more effective if the consequences of high variability inherent in urban wet-weather discharges are considered.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2022.118968","usgsCitation":"Mutzner, L., Furrer, V., Castebrunet, H., Dittmer, U., Fuchs, S., Gernjak, W., Gromaire, M., Matzinger, A., Mikkelsen, P.S., Selbig, W.R., and Vezzaro, L., 2022, A decade of monitoring micropollutants in urban wet-weather flows: What did we learn?: Water Research, v. 223, 118968, 14 p., https://doi.org/10.1016/j.watres.2022.118968.","productDescription":"118968, 14 p.","ipdsId":"IP-140246","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":446726,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2022.118968","text":"Publisher Index Page"},{"id":407377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"223","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mutzner, Lena","contributorId":296932,"corporation":false,"usgs":false,"family":"Mutzner","given":"Lena","email":"","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":852914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Furrer, Viviane","contributorId":296933,"corporation":false,"usgs":false,"family":"Furrer","given":"Viviane","email":"","affiliations":[{"id":64243,"text":"Swiss Federal Institute of Aquatic Science and Technology","active":true,"usgs":false}],"preferred":false,"id":852915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castebrunet, Helene","contributorId":296934,"corporation":false,"usgs":false,"family":"Castebrunet","given":"Helene","email":"","affiliations":[{"id":13426,"text":"University of Lyon","active":true,"usgs":false}],"preferred":false,"id":852916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dittmer, Ulrich","contributorId":296935,"corporation":false,"usgs":false,"family":"Dittmer","given":"Ulrich","email":"","affiliations":[{"id":64244,"text":"Technical University Kaiserslautern","active":true,"usgs":false}],"preferred":false,"id":852917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuchs, Stephan","contributorId":296936,"corporation":false,"usgs":false,"family":"Fuchs","given":"Stephan","email":"","affiliations":[{"id":64245,"text":"Karlsruhe Institute of Technology (KIT)","active":true,"usgs":false}],"preferred":false,"id":852918,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gernjak, Wolfgang","contributorId":296937,"corporation":false,"usgs":false,"family":"Gernjak","given":"Wolfgang","email":"","affiliations":[{"id":64246,"text":"ICRA, Catalan Institute for Water Research","active":true,"usgs":false}],"preferred":false,"id":852919,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gromaire, Marie-Christine","contributorId":296938,"corporation":false,"usgs":false,"family":"Gromaire","given":"Marie-Christine","email":"","affiliations":[{"id":64247,"text":"Leesu, École des Ponts ParisTech","active":true,"usgs":false}],"preferred":false,"id":852920,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Matzinger, Andreas","contributorId":296939,"corporation":false,"usgs":false,"family":"Matzinger","given":"Andreas","email":"","affiliations":[{"id":64248,"text":"Kompetenzzentrum Wasser Berlin (KWB)","active":true,"usgs":false}],"preferred":false,"id":852921,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mikkelsen, Peter Steen","contributorId":296940,"corporation":false,"usgs":false,"family":"Mikkelsen","given":"Peter","email":"","middleInitial":"Steen","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":852922,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852923,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vezzaro, Luca","contributorId":296941,"corporation":false,"usgs":false,"family":"Vezzaro","given":"Luca","email":"","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":852924,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70239339,"text":"70239339 - 2022 - Second round of an interlaboratory comparison of SARS-CoV2 molecular detection assays used by 45 veterinary diagnostic laboratories in the United States","interactions":[],"lastModifiedDate":"2023-01-09T20:26:08.76894","indexId":"70239339","displayToPublicDate":"2022-08-18T14:20:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2492,"text":"Journal of Veterinary Diagnostic Investigation","active":true,"publicationSubtype":{"id":10}},"title":"Second round of an interlaboratory comparison of SARS-CoV2 molecular detection assays used by 45 veterinary diagnostic laboratories in the United States","docAbstract":"The COVID-19 pandemic presents a continued public health challenge. Veterinary diagnostic laboratories in the United States use RT-rtPCR for animal testing, and many laboratories are certified for testing human samples; hence, ensuring that laboratories have sensitive and specific SARS-CoV2 testing methods is a critical component of the pandemic response. In 2020, the FDA Veterinary Laboratory Investigation and Response Network (Vet-LIRN) led an interlaboratory comparison (ILC1) to help laboratories evaluate their existing RT-rtPCR methods for detecting SARS-CoV2. All participating laboratories were able to detect the viral RNA spiked in buffer and PrimeStore molecular transport medium (MTM). With ILC2, Vet-LIRN extended ILC1 by evaluating analytical sensitivity and specificity of the methods used by participating laboratories to detect 3 SARS-CoV2 variants (B.1; B.1.1.7 [Alpha]; B.1.351 [Beta]) at various copy levels. We analyzed 57 sets of results from 45 laboratories qualitatively and quantitatively according to the principles of ISO 16140-2:2016. More than 95% of analysts detected the SARS-CoV2 RNA in MTM at ≥500 copies for all 3 variants. In addition, for nucleocapsid markers N1 and N2, 81% and 92% of the analysts detected ≤20 copies in the assays, respectively. The analytical specificity of the evaluated methods was >99%. Participating laboratories were able to assess their current method performance, identify possible limitations, and recognize method strengths as part of a continuous learning environment to support the critical need for the reliable diagnosis of COVID-19 in potentially infected animals and humans.
","language":"English","publisher":"Sage Publications","doi":"10.1177/10406387221115702","usgsCitation":"Deng, K., Uhlig, S., Goodman, L.B., Ip, H., Killiam, M.L., Nemser, S., Ulaszek, J., Kiener, S., Kmet, M., Frost, K., Hettwer, K., Colson, B., Nichani, K., Schlierf, A., Tkachenko, A., Oyinloye, M.M., Andrew, S., Reddy, R., and Tyson, G.H., 2022, Second round of an interlaboratory comparison of SARS-CoV2 molecular detection assays used by 45 veterinary diagnostic laboratories in the United States: Journal of Veterinary Diagnostic Investigation, v. 34, no. 5, p. 825-834, https://doi.org/10.1177/10406387221115702.","productDescription":"10 p.","startPage":"825","endPage":"834","ipdsId":"IP-137189","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":446729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/10406387221115702","text":"Publisher Index Page"},{"id":411582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Deng, Kaiping","contributorId":264930,"corporation":false,"usgs":false,"family":"Deng","given":"Kaiping","email":"","affiliations":[{"id":54585,"text":"U.S. Food and Drug Administration, Division of Food Processing Science and Technology, 6502 S. Archer Road, Bedford Park, IL 60501","active":true,"usgs":false}],"preferred":false,"id":861168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uhlig, Steffen","contributorId":264931,"corporation":false,"usgs":false,"family":"Uhlig","given":"Steffen","email":"","affiliations":[{"id":54586,"text":"2QuoData – Quality & Statistics, Prellerstr. 14, 01309, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":861169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodman, Laura B.","contributorId":300693,"corporation":false,"usgs":false,"family":"Goodman","given":"Laura","email":"","middleInitial":"B.","affiliations":[{"id":65232,"text":"College of Veterinary Medicine, Cornell University, Ithaca, NY, USA","active":true,"usgs":false}],"preferred":false,"id":861170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ip, Hon S. 0000-0003-4844-7533","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":126815,"corporation":false,"usgs":true,"family":"Ip","given":"Hon S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":861171,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Killiam, Mary Lea","contributorId":300694,"corporation":false,"usgs":false,"family":"Killiam","given":"Mary","email":"","middleInitial":"Lea","affiliations":[{"id":65233,"text":"National Animal and Plant Health Inspection Service Laboratories, Veterinary Services, U.S. Department of Agriculture, Ames, IA, USA","active":true,"usgs":false}],"preferred":false,"id":861172,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nemser, Sarah","contributorId":264933,"corporation":false,"usgs":false,"family":"Nemser","given":"Sarah","affiliations":[{"id":54587,"text":"U.S. Food and Drug Administration, Center for Veterinary Medicine, 8401 Muirkirk Rd., Laurel, MD 20708","active":true,"usgs":false}],"preferred":false,"id":861173,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ulaszek, Jodie","contributorId":264934,"corporation":false,"usgs":false,"family":"Ulaszek","given":"Jodie","email":"","affiliations":[{"id":54588,"text":"Illinois Institute of Technology, Institute for Food Safety and Health, 6502 South Archer Road, Bedford Park, IL 60501","active":true,"usgs":false}],"preferred":false,"id":861174,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kiener, Shannon","contributorId":300695,"corporation":false,"usgs":false,"family":"Kiener","given":"Shannon","email":"","affiliations":[{"id":65234,"text":"Division of Food Processing Science and Technology, U.S. Food and Drug Administration, Bedford Park, IL, USA","active":true,"usgs":false}],"preferred":false,"id":861175,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kmet, Matthew","contributorId":264937,"corporation":false,"usgs":false,"family":"Kmet","given":"Matthew","email":"","affiliations":[{"id":54585,"text":"U.S. Food and Drug Administration, Division of Food Processing Science and Technology, 6502 S. Archer Road, Bedford Park, IL 60501","active":true,"usgs":false}],"preferred":false,"id":861176,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Frost, Kirstin","contributorId":300696,"corporation":false,"usgs":false,"family":"Frost","given":"Kirstin","email":"","affiliations":[{"id":65235,"text":"QuoData – Quality & Statistics, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":861177,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hettwer, Karina","contributorId":264939,"corporation":false,"usgs":false,"family":"Hettwer","given":"Karina","email":"","affiliations":[{"id":54586,"text":"2QuoData – Quality & Statistics, Prellerstr. 14, 01309, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":861178,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Colson, Bertrand","contributorId":264940,"corporation":false,"usgs":false,"family":"Colson","given":"Bertrand","email":"","affiliations":[{"id":54586,"text":"2QuoData – Quality & Statistics, Prellerstr. 14, 01309, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":861179,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nichani, Kapil","contributorId":264941,"corporation":false,"usgs":false,"family":"Nichani","given":"Kapil","email":"","affiliations":[{"id":54586,"text":"2QuoData – Quality & Statistics, Prellerstr. 14, 01309, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":861180,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schlierf, Anja","contributorId":300697,"corporation":false,"usgs":false,"family":"Schlierf","given":"Anja","email":"","affiliations":[{"id":65235,"text":"QuoData – Quality & Statistics, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":861181,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tkachenko, Andriy","contributorId":264943,"corporation":false,"usgs":false,"family":"Tkachenko","given":"Andriy","email":"","affiliations":[{"id":54587,"text":"U.S. Food and Drug Administration, Center for Veterinary Medicine, 8401 Muirkirk Rd., Laurel, MD 20708","active":true,"usgs":false}],"preferred":false,"id":861183,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Oyinloye, Mothomang Mlalazi","contributorId":300699,"corporation":false,"usgs":false,"family":"Oyinloye","given":"Mothomang","email":"","middleInitial":"Mlalazi","affiliations":[{"id":65237,"text":"Center for Veterinary Medicine, U.S. Food and Drug Administration, Laurel, MD, USA","active":true,"usgs":false}],"preferred":false,"id":861184,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Andrew, Scott","contributorId":300698,"corporation":false,"usgs":false,"family":"Andrew","given":"Scott","email":"","affiliations":[{"id":65236,"text":"Integrated Consortium of Laboratory Networks, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":861182,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Reddy, Ravinder","contributorId":264944,"corporation":false,"usgs":false,"family":"Reddy","given":"Ravinder","email":"","affiliations":[{"id":54585,"text":"U.S. Food and Drug Administration, Division of Food Processing Science and Technology, 6502 S. Archer Road, Bedford Park, IL 60501","active":true,"usgs":false}],"preferred":false,"id":861185,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Tyson, Gregory H.","contributorId":300700,"corporation":false,"usgs":false,"family":"Tyson","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":65238,"text":"); Center for Veterinary Medicine, U.S. Food and Drug Administration, Laurel, MD, USA","active":true,"usgs":false}],"preferred":false,"id":861186,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70235898,"text":"70235898 - 2022 - Collateral damage: Anticoagulant rodenticides pose threats to California condors","interactions":[],"lastModifiedDate":"2022-08-25T15:53:53.204495","indexId":"70235898","displayToPublicDate":"2022-08-18T10:41:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Collateral damage: Anticoagulant rodenticides pose threats to California condors","docAbstract":"Anticoagulant rodenticides (ARs) are widespread environmental contaminants that pose risks to scavenging birds because they routinely occur within their prey and can cause secondary poisoning. However, little is known about AR exposure in one of the rarest avian scavengers in the world, the California condor (Gymnogyps californianus). We assessed AR exposure in California condors and surrogate turkey vultures (Cathartes aura) to gauge potential hazard to a proposed future condor flock by determining how application rate and environmental factors influence exposure. Additionally, we examined whether ARs might be correlated with prolonged blood clotting time and potential mortality in condors. Only second-generation ARs (SGARs) were detected, and exposure was detected in all condor flocks. Liver AR residues were detected in 42% of the condors (27 of 65) and 93% of the turkey vultures (66 of 71). Although concentrations were generally low (<10 ng/g ww), 48% of the California condors and 64% of the turkey vultures exposed to ARs exceeded the 5% probability of exhibiting signs of toxicosis (>20 ng/g ww), and 10% and 13% exceeded the 20% probability of exhibiting signs toxicosis (>80 ng/g ww). There was evidence of prolonged blood clotting time in 16% of the free-flying condors. For condors, there was a relationship between the interaction of AR exposure index (legal use across regions where condors existed) and precipitation, and the probability of detecting ARs in liver. Exposure to ARs may complicate recovery efforts of condor populations within their current range and in the soon to be established northern California experimental population. Continued monitoring of AR exposure using plasma blood clotting assays and residue analysis would allow for an improved understanding of their hazard to condors, particularly if paired with recent movement data that could elucidate exposure sources on the landscape occupied by this endangered species.
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Because sediment transport varies non-linearly with flow rates, discharge modeled from daily total precipitation distributed evenly over 24-hrs may significantly underestimate actual bedload transport capacity. In this study, we assume bedload transport capacity determined from a hydrograph resulting from the use of hourly (1-h) precipitation is a close approximation of actual transport capacity and quantify the error introduced into a network-scale bedload transport model driven by daily precipitation at channel network locations varying from lowland pool-riffle channels to upland colluvial channels in a watershed where snow accumulation and melt can affect runoff processes. Transport capacity is determined using effective stresses and the Wilcock and Crowe (2003) equations and expressed in terms of transport capacity normalized by the bankfull value. We find that, depending on channel network location, cumulative error can range from 10 - 20% to more than two orders of magnitude. Surprisingly, variation in flow rates due to differences in hillslope and channel runoff do not seem to dictate the network locations where the largest errors in predicted bedload transport capacity occur. Rather, spatial variability of the magnitude of the effective-bankfull-excess shear stress and changes in runoff due to snow accumulation and melt exert the greatest influence. These findings have implications for flood-hazard and aquatic habitat models that rely on modeled sediment transport driven by coarse-temporal-resolution climate data.","language":"English","publisher":"Wiley","doi":"10.1029/2021WR030358","usgsCitation":"Keck, J., Istanbulluoglu, E., Lundquist, J., Bandaragoda, C., Jaeger, K.L., Mauger, G.S., and Horner-Devine, A., 2022, How does precipitation variability control bedload response across a mountainous channel network in a maritime climate?: Water Resources Research, v. 58, no. 8, e2021WR030358, 28 p., https://doi.org/10.1029/2021WR030358.","productDescription":"e2021WR030358, 28 p.","ipdsId":"IP-142534","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":405308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Sauk River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.66671752929688,\n 47.89148526708789\n ],\n [\n -120.69030761718749,\n 47.89148526708789\n ],\n [\n -120.69030761718749,\n 48.47565256743914\n ],\n [\n -121.66671752929688,\n 48.47565256743914\n ],\n [\n -121.66671752929688,\n 47.89148526708789\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"58","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Keck, Jeffrey 0000-0002-0646-8574","orcid":"https://orcid.org/0000-0002-0646-8574","contributorId":295347,"corporation":false,"usgs":false,"family":"Keck","given":"Jeffrey","email":"","affiliations":[{"id":63850,"text":"University of Washington; Washington State Dept of Natrual Resources","active":true,"usgs":false}],"preferred":false,"id":849240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Istanbulluoglu, Erkan 0000-0001-9453-4676","orcid":"https://orcid.org/0000-0001-9453-4676","contributorId":295348,"corporation":false,"usgs":false,"family":"Istanbulluoglu","given":"Erkan","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":849241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundquist, Jessica 0000-0003-2193-5633","orcid":"https://orcid.org/0000-0003-2193-5633","contributorId":295349,"corporation":false,"usgs":false,"family":"Lundquist","given":"Jessica","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":849242,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bandaragoda, Christina 0000-0003-1617-1288","orcid":"https://orcid.org/0000-0003-1617-1288","contributorId":295350,"corporation":false,"usgs":false,"family":"Bandaragoda","given":"Christina","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":849243,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":849244,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mauger, Guillaume S.","contributorId":138608,"corporation":false,"usgs":false,"family":"Mauger","given":"Guillaume","email":"","middleInitial":"S.","affiliations":[{"id":12463,"text":"Climate Impacts Group, College of the Environment, University of Washington","active":true,"usgs":false}],"preferred":false,"id":849245,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Horner-Devine, Alex 0000-0003-2323-7150","orcid":"https://orcid.org/0000-0003-2323-7150","contributorId":295351,"corporation":false,"usgs":false,"family":"Horner-Devine","given":"Alex","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":849246,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70235762,"text":"70235762 - 2022 - Natural infrastructure in dryland streams (NIDS) can establish regenerative wetland sinks that reverse desertification and strengthen climate resilience","interactions":[],"lastModifiedDate":"2022-08-18T14:51:15.245065","indexId":"70235762","displayToPublicDate":"2022-08-18T09:43:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Natural infrastructure in dryland streams (NIDS) can establish regenerative wetland sinks that reverse desertification and strengthen climate resilience","docAbstract":"In this article we describe the natural hydrogeomorphological and biogeochemical cycles of dryland fluvial ecosystems that make them unique, yet vulnerable to land use activities and climate change. We introduce Natural Infrastructure in Dryland Streams (NIDS), which are structures naturally or anthropogenically created from earth, wood, debris, or rock that can restore implicit function of these systems. This manuscript further discusses the capability of and functional similarities between beaver dams and anthropogenic NIDS, documented by decades of scientific study. In addition, we present the novel, evidence-based finding that NIDS can create wetlands in water-scarce riparian zones, with soil organic carbon stock as much as 200 to 1400 Mg C/ha in the top meter of soil. We identify the key restorative action of NIDS, which is to slow the drainage of water from the landscape such that more of it can infiltrate and be used to facilitate natural physical, chemical, and biological processes in fluvial environments. Specifically, we assert that the rapid drainage of water from such environments can be reversed through the restoration of natural infrastructure that once existed. We then explore how NIDS can be used to restore the natural biogeochemical feedback loops in these systems. We provide examples of how NIDS have been used to restore such feedback loops, the lessons learned from installation of NIDS in the dryland streams of the southwestern United States, how such efforts might be scaled up, and what the implications are for mitigating climate change effects. Our synthesis portrays how restoration using NIDS can support adaptation to and protection from climate-related disturbances and stressors such as drought, water shortages, flooding, heatwaves, dust storms, wildfire, biodiversity losses, and food insecurity.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.157738","usgsCitation":"Norman, L., Lal, R., Wohl, E., Fairfax, E., Gellis, A.C., and Pollock, M.M., 2022, Natural infrastructure in dryland streams (NIDS) can establish regenerative wetland sinks that reverse desertification and strengthen climate resilience: Science of the Total Environment, v. 849, 157738, 20 p., https://doi.org/10.1016/j.scitotenv.2022.157738.","productDescription":"157738, 20 p.","ipdsId":"IP-137646","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science 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Chiropterologica","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal activity patterns of bats in high-elevation conifer sky islands","docAbstract":"In the southern Appalachian Mountains of the southeastern USA, bat communities in high-elevation habitats tend to be relatively under-surveyed. High-elevation habitats may provide important habitat to certain species (i.e., migratory tree bats), and may serve as climate refugia during droughts or high temperatures. We conducted an opportunistic acoustic survey of bat communities in ten survey areas in high elevation (1,585–1,920 m a.s.l.) montane Picea rubens (red spruce)-Abies fraseri (Fraser fir) forest in the southern Appalachian Mountains of western North Carolina. In each survey area, we randomly placed three full spectrum acoustic detectors (N = 30) during three seasons (spring, summer and fall) in 2015. We deployed each detector for two five-day periods during each season (n = 900 survey nights). Although we detected seven bat species/groups during the surveys, 73% of echolocation files were attributed to Lasiurus cinereus (hoary bat) and Lasionycteris noctivagans (silver-haired bat). Generally rare in the Appalachians and typically present only at low densities in the summer at mid- and low-elevations, both species were detected at all sites during all seasons. Overall, mean nightly activity of bats was higher in the summer than the spring or fall. We observed 3.7–5 times greater activity of L. cinereus in spruce-fir forests during the summer compared to spring and fall, whereas L. noctivagans had 1.3–5 times more activity in the summer compared to other seasons. After accounting for precipitation events, our finite mixture models showed that season, temperature, elevation, and canopy height influenced L. cinereus activity, whereas season and temperature affected L. noctivagans activity. Our observations suggest that high-elevation spruce-fir forests are providing summer foraging and possibly day-roosting habitat of tree bats not previously documented this far south in North America.
","language":"English","publisher":"Museum and Institute of Zoology at the Polish Academy of Sciences","doi":"10.3161/15081109acc2022.24.1.007","usgsCitation":"Diggins, C., and Ford, W., 2022, Seasonal activity patterns of bats in high-elevation conifer sky islands: Acta Chiropterologica, v. 24, no. 1, p. 91-101, https://doi.org/10.3161/15081109acc2022.24.1.007.","productDescription":"11 p.","startPage":"91","endPage":"101","ipdsId":"IP-121634","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467168,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/111935","text":"External Repository"},{"id":465988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.01925096181063,\n 36.1284749704932\n ],\n [\n -83.75535293883529,\n 36.1284749704932\n ],\n [\n -83.75535293883529,\n 35.0263131090354\n ],\n [\n -82.01925096181063,\n 35.0263131090354\n ],\n [\n -82.01925096181063,\n 36.1284749704932\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Diggins, Corinne A.","contributorId":270602,"corporation":false,"usgs":false,"family":"Diggins","given":"Corinne A.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":922940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":922939,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}