Hicks Dome hosts breccias enriched in rare earth elements (REE), Y, Th, F, Ba, Ti, Nb, and Be, alongside spatially associated lamprophyre dikes (ca. 271 Ma). Hicks Dome is located within the Illinois–Kentucky Fluorspar District, which hosts fluorite, Pb–Zn, and barite resources. This study investigates the genetic relationships between Hicks Dome mineralization in breccias, alkaline magmatism, and Illinois–Kentucky Fluorspar District mineralization. Lamprophyre dikes are light REE–enriched with chondrite-normalized abundances decreasing from La to Lu. The Host Breccia exhibits middle and heavy REE–enriched patterns that mirror those of the principal REE–Th host minerals, including fluorapatite, xenotime, and thorite. Textural evidence suggests recrystallization of phosphates, sulfates, and Ti–Nb oxides in the Host Breccia. U–Pb geochronology constrains multiple mineralizing events, with ages of 277 ± 18 Ma from low-Th apatite interpreted as main-stage mineralization, and 121.6 ± 9.7 Ma from high-Th apatite indicating later overprinting. O–H–C stable isotope data provide evidence for multiple stages of fluid-rock interaction and fluid mixing: (1) early magmatic fluids dissolved limestone country rock, (2) mixing between magmatic fluids and basinal brines led to main-stage mineralization in the Host Breccia, and (3) late-stage mineralization occurred following mixing of meteoric water and basinal brine. These results indicate that heavy REEs, high field strength elements, and fluorine precipitated proximal to its alkaline magmatic source because of fluid–rock interactions and fluid mixing. Subsequent fluid mixing drove late-stage recrystallization and additional fluorite formation, a process that may be similar to mineralization in the Illinois-Kentucky Fluorspar District.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2026.107328","usgsCitation":"McIntosh, J.A., Andersen, A.K., Bennett, M.M., Thompson, J.M., Johnson, C.A., Hofstra, A.H., and Nuelle, L., 2026, Geochemical, mineralogical, and isotopic evidence for multi-stage genesis of the Hicks Dome REE + Y-HFSE-fluorite deposit, Illinois, USA: Ore Geology Reviews, v. 194, 107328, 23 p., https://doi.org/10.1016/j.oregeorev.2026.107328.","productDescription":"107328, 23 p.","ipdsId":"IP-180590","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":504815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2026.107328","text":"Publisher Index Page"},{"id":504772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Hicks Dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.383333,\n 37.55\n ],\n [\n -88.3,\n 37.55\n ],\n [\n -88.3,\n 37.466667\n ],\n [\n -88.383333,\n 37.466667\n ],\n [\n -88.383333,\n 37.55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"194","noUsgsAuthors":false,"publicationDate":"2026-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McIntosh, Julia A. 0000-0003-2819-8664","orcid":"https://orcid.org/0000-0003-2819-8664","contributorId":331662,"corporation":false,"usgs":true,"family":"McIntosh","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":962098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, Allen K. 0000-0002-6865-2561","orcid":"https://orcid.org/0000-0002-6865-2561","contributorId":217476,"corporation":false,"usgs":true,"family":"Andersen","given":"Allen","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":962099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Mitchell M. 0000-0001-9533-9557 mbennett@usgs.gov","orcid":"https://orcid.org/0000-0001-9533-9557","contributorId":199379,"corporation":false,"usgs":true,"family":"Bennett","given":"Mitchell","email":"mbennett@usgs.gov","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":962100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Jay M. 0000-0003-3322-0870","orcid":"https://orcid.org/0000-0003-3322-0870","contributorId":329664,"corporation":false,"usgs":true,"family":"Thompson","given":"Jay","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":962101,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":962102,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":962103,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nuelle, Laurence","contributorId":371609,"corporation":false,"usgs":false,"family":"Nuelle","given":"Laurence","affiliations":[{"id":88191,"text":"Hicks Dome LLC","active":true,"usgs":false}],"preferred":false,"id":962104,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70275747,"text":"sir20265010 - 2026 - Continuous and high-resolution longitudinal profiles of the water surface and riverbed elevation for 282 miles of the Colorado River from Lees Ferry to Pearce Ferry, Arizona, 2021","interactions":[],"lastModifiedDate":"2026-05-26T18:25:26.706081","indexId":"sir20265010","displayToPublicDate":"2026-05-26T10:00:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5010","displayTitle":"Continuous and High-Resolution Longitudinal Profiles of the Water Surface and Riverbed Elevation for 282 Miles of the Colorado River From Lees Ferry To Pearce Ferry, Arizona, 2021","title":"Continuous and high-resolution longitudinal profiles of the water surface and riverbed elevation for 282 miles of the Colorado River from Lees Ferry to Pearce Ferry, Arizona, 2021","docAbstract":"Longitudinal profiles of water surface and riverbed elevations capture key geomorphic characteristics that can be affected by water infrastructure and natural processes. Continuous water surface profiles of the Colorado River in Grand Canyon, a river influenced by two of the largest dams in the United States, have been measured infrequently. The water surface profile was first measured in 1923, 13 years before the completion of Hoover Dam, which impounded water into western Grand Canyon, and 40 years before the completion of Glen Canyon Dam, which affected streamflow and sediment supply for all of Grand Canyon. The water surface profile was next measured in 2000, 37 years after the completion of Glen Canyon Dam, although this profile did not include the segment affected by Hoover Dam. A continuous profile of riverbed elevations has never been published. Here, we present the first complete, coupled water surface and riverbed elevation profiles, collected in 2021 during a period of steady releases from Glen Canyon Dam. The profiles were constructed from positions and elevations measured by boat-based global navigation satellite systems and from bathymetry collected by multibeam sonar. Data collected by boat were supplemented by data from a photogrammetry-derived digital surface model that was created from concurrently collected aerial images. Independent measurements made by conventional total stations referenced to a common geodetic control network were used to evaluate accuracy of all measurements. The final water surface and riverbed elevation profiles improved the accuracy and precision reported for previous profiles. In this study, the mean absolute vertical accuracy of water surface elevations was 0.07 meter for 85 percent of river miles and 0.19 meter for 11 percent of river miles. For the remaining 4 percent of river miles, water surface elevations were interpolated between measured values. The profiles reported herein can be used for current assessment of Colorado River geomorphic conditions, quantification of changes in the river over time, and predictive modeling of river resources for potential future management scenarios.quantification of changes in the river over time, and predictive modeling of river resources for potential future management scenarios.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265010","usgsCitation":"Sartain, S.L., Kaplinski, M.A., Kohl, K., Chapman, K.A., Bransky, N.D., Sankey, J.B., and Grams, P.E., 2026, Continuous and high-resolution longitudinal profiles of the water surface and riverbed elevation for 282 miles of the Colorado River from Lees Ferry to Pearce Ferry, Arizona, 2021: U.S. Geological Survey Scientific Investigations Report 2026–5010, 40 p., https://doi.org/10.3133/sir20265010.","productDescription":"Report: vii, 40 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179784","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":504710,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119446.htm","linkFileType":{"id":5,"text":"html"}},{"id":504453,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5010/sir20265010.pdf","text":"Report","size":"6.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5010 PDF"},{"id":504457,"rank":2,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265010/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5010 HTML"},{"id":504458,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5010/sir20265010.XML","description":"SIR 2026-5010 XML"},{"id":504459,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5010/images"},{"id":504460,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5010/coverthb.jpg"},{"id":504461,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P135FNFM","text":"USGS data release","linkHelpText":"Continuous and high-resolution profiles of the water surface and riverbed elevation for 282 miles of the Colorado River from Lees Ferry to Pearce Ferry, AZ, 2021—Data"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.415697136473,\n 36.90189262731032\n ],\n [\n -114.01161104871596,\n 36.90189262731032\n ],\n [\n -114.01161104871596,\n 35.51758910449131\n ],\n [\n -111.415697136473,\n 35.51758910449131\n ],\n [\n -111.415697136473,\n 36.90189262731032\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
We measured the elevation of 282 miles of the water surface and riverbed of the Colorado River in Grand Canyon, from Lees Ferry, Arizona, to Pearce Ferry, Ariz. We collected water surface and riverbed elevations during a period of steady releases from Glen Canyon Dam in 2021. We used multiple, concurrent methods to measure the elevation of the water surface and assessed error for each measurement method to use the most accurate data possible in the final elevation profile. The final water surface profile is measured to the centimeter every river hundredth mile, with vertical uncertainty less than or equal to 0.07 meter for 85 percent of the river and less than or equal to 0.19 meter for the remainder of the river. We collected bathymetry of the river centerline everywhere possible, which did not include rapids and shallow areas. This study is the third measurement of a complete water surface profile; the first was collected in 1923, 40 years before Glen Canyon Dam was completed, and the second was collected in 2000, 37 years after Glen Canyon Dam was completed. A continuous riverbed profile had not been collected previously.
","publicationDate":"2026-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Sartain, Shannon L. 0000-0003-2395-6825","orcid":"https://orcid.org/0000-0003-2395-6825","contributorId":290222,"corporation":false,"usgs":true,"family":"Sartain","given":"Shannon","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaplinski, Matthew A. 0000-0001-6232-8325","orcid":"https://orcid.org/0000-0001-6232-8325","contributorId":333646,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kohl, Keith 0000-0001-6812-0373","orcid":"https://orcid.org/0000-0001-6812-0373","contributorId":371349,"corporation":false,"usgs":false,"family":"Kohl","given":"Keith","affiliations":[{"id":88119,"text":"NOAA, National Geodetic Survey, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":961629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapman, Katherine A. 0009-0009-1806-6474 kchapman@usgs.gov","orcid":"https://orcid.org/0009-0009-1806-6474","contributorId":345014,"corporation":false,"usgs":true,"family":"Chapman","given":"Katherine","email":"kchapman@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bransky, Nathaniel D. 0000-0003-3113-7491","orcid":"https://orcid.org/0000-0003-3113-7491","contributorId":305709,"corporation":false,"usgs":true,"family":"Bransky","given":"Nathaniel","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":212943,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961633,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276298,"text":"70276298 - 2026 - Indicators of mercury concentration in Lake Trout: Can fish location and appearance provide information to anglers to reduce their exposure?","interactions":[],"lastModifiedDate":"2026-05-27T14:38:46.85553","indexId":"70276298","displayToPublicDate":"2026-05-21T09:34:12","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Indicators of mercury concentration in Lake Trout: Can fish location and appearance provide information to anglers to reduce their exposure?","docAbstract":"People are exposed to mercury (Hg) through the consumption of fish. State and federal governments provide broad, often-generalized food safety guidance to reduce exposure; however, numerous rural fishing areas lack testing and location- or species-specific guidance. The aim of this study was to provide tangible, visible, or easily measured characteristics of Lake Trout Salvelinus namaycush that could convey information on Hg exposure to people harvesting and consuming fish where no location-specific guidance exists.
We investigated potential indicators of Lake Trout total Hg (THg) concentrations in muscle across 10 lakes in Alaska's national parks. Potential indicators, including lake, lake zone (i.e., littoral, pelagic, profundal), fish length, head size, body condition, and general appearance, were evaluated by competing linear mixed-effects models.
Lake Trout THg concentrations ranged widely from 22 to 1,306 ng/g wet weight. Much of the variation (48%) in THg concentrations was attributed to differences among individual lakes, but the interaction of the fish's lake zone, body length, and head size accounted for an additional 21%. Predicted THg concentrations increased with Lake Trout length and head : body proportion, but the rate of THg concentration increase with length varied by head : body proportion and lake zone.
Given the overwhelming evidence of high lake-to-lake variability in Lake Trout THg concentrations, we find support for use of lake-specific guidance when data are available. When lake-specific THg concentrations are not available, the best potential way to reduce exposure is to harvest and consume Lake Trout with mean predicted THg concentrations that are within state and federal safe consumption guidelines. This included Lake Trout from surface waters (i.e., pelagic or littoral zone) that are ≤70 cm in length; if harvesting fish from deep waters (i.e., profundal zone), lower THg concentrations were found in Lake Trout with heads ≤25% of their body length. The indicators—lake zone, length, and head size—of Lake Trout THg concentrations can provide harvesters with additional information in the absence of data for specific lakes.
Translocations have been widely used to restore and conserve bighorn sheep (Ovis canadensis) populations in North America. Some translocations have been successful, but many populations remain small and genetically isolated. Population structure can influence the viability and long-term success of reintroductions. Social ungulates often function as interconnected subpopulations (metapopulations); however, few studies evaluate subpopulation sizes, connectivity, and genetic diversity within metapopulations. To address this gap, we conducted a comprehensive study of a reintroduced Rocky Mountain bighorn sheep (Ovis canadensis canadensis) population in Dinosaur National Monument in Colorado and Utah, USA, between 2006–2020. We analyzed global positioning system (GPS) radio-collar data, genetic samples, and results of health testing to evaluate abundance, distribution, genetic structure and diversity, habitat use, movement and connectivity, and presence of or exposure to respiratory pathogens. We integrated these analyses to evaluate the outcomes of a reintroduction effort that began in 1952, over 70 years ago, and to inform management decisions in Dinosaur National Monument. We also provide a framework for evaluating metapopulation processes, including a non-invasive approach that links genetic structure with Bayesian spatial capture-recapture analyses to estimate subpopulation sizes. Despite models indicating continuous suitable habitat, we found a spatially structured population with at least 4 subpopulations with constrained connectivity. Evidence from step selection and density analyses suggested that movement among subpopulations may be limited by semi-permeable barriers including rivers and human disturbance, which could contribute to maintenance of spatial structure over time. In 2006, antibody to Mycoplasma ovipneumoniae was detected in all geographically and genetically distinct subpopulations. Widespread clinical signs of disease and a confirmed exposure to M. ovipneumoniae in 2019 indicate a long-term disease challenge. Proximity to domestic sheep creates repeated opportunities for introduction of new M. ovipneumoniae strains. We estimated abundance in 2019 at 109 (95% CrI = 87–133), composed of subpopulations ranging from 18–39 animals (95% CrIs from 11–50). Genetic diversity was relatively high compared to other reintroduced and native Rocky Mountain bighorn sheep populations, which is likely a consequence of multiple translocations from different sources. Three of 4 subpopulation centers generally aligned with the locations of original translocation release sites. Persistence in the presence of pathogens may be facilitated by metapopulation structure and moderately high genetic diversity. Conversely, metapopulation structure can also facilitate pathogen persistence. Our approach offers a path to advance understanding of the population ecology of reintroduced bighorn sheep and can inform effective conservation and management of their populations.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wmon.70011","usgsCitation":"Carroll, S., Flesch, E.P., Scoresby, S., Spencer, E., Crowhurst, R.S., Epps, C.W., Galloway, N., Janousek, W.M., and Graves, T., 2026, Ecology of reintroduced Rocky Mountain bighorn sheep in Dinosaur National Monument: Wildlife Monographs, https://doi.org/10.1002/wmon.70011.","ipdsId":"IP-170036","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":504813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wmon.70011","text":"Publisher Index Page"},{"id":504734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Dinosaur National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.68629167900906,\n 43.55694885042547\n ],\n [\n -104.42518255194071,\n 43.55694885042547\n ],\n [\n -104.42518255194071,\n 38.60536698151091\n ],\n [\n -110.68629167900906,\n 38.60536698151091\n ],\n [\n -110.68629167900906,\n 43.55694885042547\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Carroll, Sarah Louise 0000-0002-5391-7627","orcid":"https://orcid.org/0000-0002-5391-7627","contributorId":352227,"corporation":false,"usgs":true,"family":"Carroll","given":"Sarah Louise","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":961989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flesch, Elizabeth P 0000-0002-7592-8124","orcid":"https://orcid.org/0000-0002-7592-8124","contributorId":222685,"corporation":false,"usgs":false,"family":"Flesch","given":"Elizabeth","email":"","middleInitial":"P","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":961990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scoresby, Salix","contributorId":352228,"corporation":false,"usgs":false,"family":"Scoresby","given":"Salix","affiliations":[{"id":84134,"text":"Contractor, USGS (Northern Arizona University)","active":true,"usgs":false}],"preferred":false,"id":961991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spencer, Emily","contributorId":292165,"corporation":false,"usgs":false,"family":"Spencer","given":"Emily","email":"","affiliations":[],"preferred":false,"id":961992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crowhurst, Rachel S.","contributorId":198153,"corporation":false,"usgs":false,"family":"Crowhurst","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":961993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Epps, Clinton W.","contributorId":359530,"corporation":false,"usgs":false,"family":"Epps","given":"Clinton","middleInitial":"W.","affiliations":[{"id":85841,"text":"Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Nash Hall Room 104, Corvallis, OR, 97331, USA","active":true,"usgs":false}],"preferred":false,"id":961994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Galloway, Nathan L.","contributorId":271191,"corporation":false,"usgs":false,"family":"Galloway","given":"Nathan L.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":961995,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":961996,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":961997,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70275769,"text":"fs20263010 - 2026 - The Great Lakes Geologic Mapping Coalition—Working collaboratively to understand the geology of the Great Lakes Region","interactions":[],"lastModifiedDate":"2026-05-26T18:37:48.030145","indexId":"fs20263010","displayToPublicDate":"2026-05-20T13:25:18","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-3010","displayTitle":"The Great Lakes Geologic Mapping Coalition—Working Collaboratively to Understand the Geology of the Great Lakes Region","title":"The Great Lakes Geologic Mapping Coalition—Working collaboratively to understand the geology of the Great Lakes Region","docAbstract":"The Great Lakes Geologic Mapping Coalition (GLGMC), commonly referred to as the “Coalition,” is a partnership between the U.S. Geological Survey (USGS), the U.S. States of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin and the Canadian province of Ontario. The member States receive funding for geologic mapping work from the USGS National Cooperative Geologic Mapping Program (NCGMP), whereas Ontario participates as a nonfunded partner. The mission of the GLGMC is to produce three-dimensional (3D) geologic maps that depict unconsolidated sediments and near-surface bedrock in the Great Lakes region of North America. Geologic maps are the basis of most earth science investigations and help support resource exploration (energy, minerals, groundwater), natural hazard mitigation, infrastructure development, and land-use planning, all of which can be used to advance economic development and strengthen national security in the Great Lakes region.
During the last few million years, the Great Lakes region has experienced repeated glacial advances and retreats, leaving behind extensive sediments, abundant natural resources, and widespread effects on the underlying bedrock geology (Swezey and others, 2022). Linked by shared histories of past glaciations, industrial agriculture, and legacy automotive, coal, steel, and manufacturing industries, the GLGMC member States collaborate to improve the understanding of the 3D distribution of the sediments overlying the region’s bedrock (fig. 1). Developing a comprehensive subsurface 3D framework of this glaciated terrain can provide earth science data to policymakers at all levels. These insights facilitate informed decisions on the exploration, use, and protection of vital resources, such as critical minerals, industrial materials, and aquifers, thereby supporting economic prosperity and the well-being of the citizens of this region.
Since its inception in 1998, the Coalition has completed more than 100 geologic mapping projects across the Great Lakes region. Each project aims to deliver geologic maps, 3D datasets, and other information that improves understanding of the geology of the Great Lakes region, with an emphasis on economic and water resources. Key deliverables include 3D geologic maps and models typically portraying sediment thickness, often derived from top-of-bedrock and borehole data. These products are developed through a combination of fieldwork, subsurface modeling, and the collection and analysis of rock and sediment cores.
To support Coalition goals, member States collaborate with scientists working on related STATEMAP, EDMAP, and FEDMAP projects. Coalition scientists also engage with Tribal Nations in the Great Lakes region to ensure that Tribal interests pertaining to Coalition work are addressed. Through this collaboration, the Coalition unites the efforts of State, Federal, and Tribal Nation stakeholders to advance geologic data production and enhance understanding of the geologic resources of the Great Lakes region.
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This report describes the methodology used for the construction of a digital three-layer geologic model of the conterminous United States by mapping the altitude of three surfaces: land surface, the top of bedrock, and the top of basement. These surfaces are mapped through the compilation and synthesis of published stratigraphic horizons from numerous topical studies. The mapped surfaces create a three-layer geologic model with three geomaterial-based subdivisions: unconsolidated to weakly consolidated sediment; layered consolidated rock strata that constitute bedrock; and crystalline rocks that are described as “basement,” consisting of either igneous, metamorphic, or highly deformed rocks. The data compilation and synthesis are highly dependent on the definition of the informal terms “bedrock” and “basement,” which may describe different ages or types of rock in different parts of the conterminous United States. This report presents the conceptualization of the three mapped layers, describes the datasets used, and summarizes the decisions made while compiling the three-layer model from the various sources. This digital dataset was created as part of efforts by the U.S. Geological Survey to develop subsurface geologic data in geospatial form as part of a broad directive to develop two-dimensional and three-dimensional geologic information at detailed, national, and continental scales. This digital dataset partly fulfills the goal of the U.S. Geological Survey’s National Cooperative Geologic Mapping Program to construct a national-scale three-dimensional geologic model.
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Box 25046, Mail Stop 980
Denver, CO 80225
This report is a companion to a digital dataset created as part of U.S. Geological Survey National Cooperative Geologic Mapping Program efforts to develop subsurface geologic data in geospatial form at regional to national scales. The report describes data sources and methods used to construct a digital three-layer geologic model of the conterminous United States by mapping the altitude of three surfaces: land surface, top of bedrock, and top of basement.
","publicationDate":"2026-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Sweetkind, Donald S. 0000-0003-0892-4796","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":210808,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":959223,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70275743,"text":"sir20265012 - 2026 - Status and understanding of groundwater quality in the San Joaquin Valley Kern County subbasin domestic-supply aquifer study unit, 2022—California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2026-05-26T18:29:13.900279","indexId":"sir20265012","displayToPublicDate":"2026-05-19T10:38:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5012","displayTitle":"Status and Understanding of Groundwater Quality in the San Joaquin Valley Kern County Subbasin Domestic-Supply Aquifer Study Unit, 2022: California GAMA Priority Basin Project","title":"Status and understanding of groundwater quality in the San Joaquin Valley Kern County subbasin domestic-supply aquifer study unit, 2022—California GAMA Priority Basin Project","docAbstract":"The quality of water accessed by domestic wells (here referred to as domestic groundwater resources) in the San Joaquin Valley Kern County subbasin (basin number 5-022.14) was assessed as part of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project (GAMA-PBP), in cooperation with the California State Water Resources Control Board. Kern County is at the southern end of the San Joaquin Valley in California, and about 30,000 residents are estimated to use privately owned domestic wells for drinking water. Domestic wells typically draw from shallower parts of the aquifer system than public-supply wells and can be more vulnerable to effects from surface activities. Kern County is host to a highly productive agricultural industry, with Bakersfield as the main urban center. The Kern River runs through Bakersfield from the southern Sierra Nevada and intersects the Kern Water Bank, one of the largest groundwater banking operations in California, at the Kern River Intertie. The section of the Kern River running through the Kern Water Bank is dry most years. Kern County also encompasses some of the most productive oil and gas basins in California, with extensive underground and surface disposal of oil-field wastewater.
This study was based on data collected from 33 sites sampled by the U.S. Geological Survey for the GAMA-PBP in 2022. To provide context for the water quality assessment, measured concentrations were compared to regulatory and non-regulatory health-based and aesthetic benchmarks. A grid-based method was used to estimate the proportions of the groundwater resources used for domestic-supply wells that have water-quality constituents below (low relative concentration), approaching (moderate relative concentration), or above (high relative concentration) benchmark concentrations. At least one measured constituent with a regulatory benchmark was categorized as having a high relative concentration in 72 percent of the aquifer area used for domestic groundwater resources. Inorganic constituents were detected at high concentrations in 45 percent of the domestic groundwater resources, and the constituents detected above regulatory benchmarks were arsenic, nitrate, and uranium. At least one organic constituent was detected at high concentrations in 41 percent of the domestic groundwater resources, and the constituents exceeding regulatory benchmarks were the fumigants 1,2,3-trichloropropane (1,2,3-TCP), 1,2-dibromo-3-chloropropane (dibromochloropropane [DBCP]), 1,2-dibromoethane (EDB), and the per-and polyfluoroalkyl substance (PFAS) perfluorooctanesulfonate. The disinfection by-product chloroform, the fumigant 1,2-dichloropropane, the herbicides atrazine and hexazinone, and the herbicide degradates 2-chloro-6-ethylamino-4-amino-s-triazine, 2-chloro-4,6-diamino-s-triazine, 4-hydroxychlorothalonil, and metolachlor sulfonic acid were detected in more than 10 percent of domestic groundwater resources, but concentrations did not exceed regulatory benchmarks.
Land use, groundwater age (fraction of modern water and mean age), and geochemical environment (oxic or anoxic conditions, pH, alkalinity) were associated with the distribution of high relative concentrations of inorganic and organic constituents. Young, oxygenated water is recharged along the Kern River and adjacent recharge ponds, or as irrigation water in the agricultural areas. High concentrations of nitrate and volatile organic compounds occurred in the oxic water in urban and agricultural areas. The fumigants 1,2,3-TCP, DBCP, and EDB were reported throughout the agricultural areas, whereas chloroform, tetrachloroethene, and PFAS were associated with urban land use. High uranium concentrations were associated with young, modern groundwater in agricultural areas with low pH and high bicarbonate. Total dissolved solids increased with distance from the Kern River, as the contributions of fresh, oxic water decreased. High concentrations of arsenic were present in older anoxic or alkaline groundwater away from areas of recharge. Overall, groundwater age, redox conditions, and the source of recharge as a result of different land uses contribute to large aquifer-scale portions of domestic groundwater resources that exceed health-based benchmarks for nitrate, uranium, and fumigant concentrations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265012","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Harkness, J.S., Faulkner, K.E., and Jurgens, B.C., 2026, Status and understanding of groundwater quality\nin the San Joaquin Valley Kern County subbasin domestic- supply aquifer study unit, 2022—California\nGAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2026–5012, 53 p.,\nhttps://doi.org/10.3133/sir20265012.","productDescription":"Report: x, 53 p.; 3 Data Releases","numberOfPages":"53","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-169250","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":504711,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119448.htm","linkFileType":{"id":5,"text":"html"}},{"id":504430,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13WQA8P","text":"USGS data release","linkHelpText":"Potential explanatory variables for groundwater quality in the San Joaquin Valley Kern County subbasin domestic well study unit, 2022"},{"id":504429,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ISEGA","text":"USGS data release","linkHelpText":"Data for assessing the susceptibility of groundwater used for domestic- supply, California"},{"id":504425,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265012/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-5012 HTML"},{"id":504424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5012/sir20265012.pdf","text":"Report","size":"37.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-5012 PDF"},{"id":504423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5012/coverthb.jpg"},{"id":504426,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5012/sir20265012.XML","description":"OFR 2026-5012 XML"},{"id":504427,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5012/images"},{"id":504428,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GGNIQI","text":"USGS data release","linkHelpText":"Groundwater- quality data in the Kern County Domestic- Supply Aquifer Study Unit, 2022—Results from the California GAMA Priority Basin Project"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley Kern County subbasin study unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.2,\n 35.8\n ],\n [\n -118.5,\n 35.8\n ],\n [\n -118.5,\n 34.9\n ],\n [\n -120.2,\n 34.9\n ],\n [\n -120.2,\n 35.8\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
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6000 J Street, Placer Hall
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Acknowledgments
Abstract
Introduction
Hydrogeologic Setting
Methods
Status of Groundwater Quality
Factors that Affect Groundwater Quality
Summary
References Cited
The U.S. Geological Survey, in cooperation with the City of Lee’s Summit, Missouri, assessed flooding of the East Fork Little Blue River and tributaries for varying precipitation magnitudes and durations, varying antecedent runoff conditions, and projected climate-change conditions. The precipitation scenarios were used to develop a library of flood-inundation maps for a 2.95-mile reach of the East Fork Little Blue River and tributaries within the city.
A two-dimensional U.S. Army Corps of Engineers Hydrologic Engineering Center–River Analysis System (HEC–RAS; ver. 6.5) rain-on-grid model was calibrated to selected runoff events representing a range of antecedent runoff conditions and hydrologic responses. Lowest adjacent grades for structures within the nearby study area were incorporated into the terrain, and depth grids and water-surface elevation grids were developed for the study area. Simulated velocities at selected bridge locations were also developed from the model. The model was calibrated using water-surface elevation data collected from water-level loggers (pressure transducers) and streamflow measurements and water-surface elevation measurements made at a reference point during runoff events. The calibrated HEC–RAS model was used to simulate streamflows from design rainfall events of 15-minute to 24-hour durations and ranging from a 100- to 0.1-percent annual exceedance probability (1-year to 1,000-year recurrence intervals). Flood-inundation maps were produced for depths at a reference location of 3 to 16 feet, or a depth exceeding the 0.1-percent annual exceedance probability interval precipitation. The results of each precipitation duration-frequency value were represented by a 1-foot-increment inundation map based on the generated peak streamflow from that rainfall event and the corresponding water-surface elevation at the East Fork Little Blue River reference location.
Within the HEC–RAS model, 240 scenarios were developed from the design rainfall events with each of 3 antecedent conditions. Additional scenarios were created to simulate the effects of projected precipitation scenarios on the 100-year recurrence interval, 24-hour storm and the 100-year recurrence interval, 6-hour storm. All simulation results were assigned to a flood-inundation map condition based on the generated peak flow and corresponding water-surface elevation at the East Fork Little Blue River reference location.
The flood-inundation maps are shown on a web mapping application made available to the public through the City of Lee’s Summit (hyperlink will be added when available). The flood-inundation maps are tied to real-time precipitation data obtained from the Automated Surface Observing System weather station at the Lee’s Summit Municipal Airport, accessible at https://mesonet.agron.iastate.edu/request/download.phtml?network=MO_ASOS. The availability of these maps, along with information regarding observed rainfall, could help provide emergency management personnel and residents with information that is critical for flood-response activities, such as evacuations and road closures, and for postflood recovery efforts.
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1400 Independence Road
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The U.S. Geological Survey, in cooperation with the City of Lee’s Summit, Missouri, assessed flooding of the East Fork Little Blue River and tributaries for varying precipitation magnitudes and durations, varying antecedent runoff conditions, and projected climate-change conditions. The precipitation scenarios were used to develop a library of flood-inundation maps that included a 2.95-mile reach of the East Fork Little Blue River and tributaries within the city. The availability of these maps, along with information regarding observed rainfall, could help provide emergency management personnel and residents with information that is critical for flood-response activities, such as evacuations and road closures, and for postflood recovery efforts.
","publicationDate":"2026-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Atkinson, Allison A. 0009-0001-7572-0729 aatkinson@usgs.gov","orcid":"https://orcid.org/0009-0001-7572-0729","contributorId":330979,"corporation":false,"usgs":true,"family":"Atkinson","given":"Allison","email":"aatkinson@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961727,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70276240,"text":"70276240 - 2026 - Remote sensing enables basin-scale inventories of coal mine methane","interactions":[],"lastModifiedDate":"2026-05-20T14:51:11.392104","indexId":"70276240","displayToPublicDate":"2026-05-19T09:28:33","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing enables basin-scale inventories of coal mine methane","docAbstract":"Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.
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One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 9 safehold anomaly. On October 17, 2025, Landsat 9 experienced a Solar Array Drive Assembly potentiometer fault. The onboard fault response put both the Operational Land Imager sensor and the Thermal Infrared Sensor into safe mode. Additionally, the Thermal Infrared Sensor focal plane assembly was turned off, but the cryocooler remained on. On October 20, 2025, the Solar Array Drive Assembly recovery commanding was successfully performed to put the spacecraft into nadir viewing mode. The following day, Operational Land Imager activation and recovery started, including focal plane assembly warmup. After reaching nominal operational temperatures and achieving thermal stability, science imaging resumed on October 23, 2025. Additional information about the Landsat 9 safehold anomaly is here: https://www.usgs.gov/landsat-missions/news/landsat-9-returns-normal-operations-following-brief-safehold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261014","usgsCitation":"Haque, M.O., Hasan, M.N., Shrestha, A., Rengarajan, R., Lubke, M., Steinwand, D., Bresnahan, P., Shaw, J.L., Ruslander, K., Micijevic, E., Choate, M.J., Anderson, C., Clauson, J., Thome, K., Angal, A., Levy, R., Miller, J., and Teixeira Pinto, C., 2026, ECCOE Landsat quarterly calibration and validation report—Quarter 4, 2025 (ver.1.1, May 20, 2026: U.S. Geological Survey Open- File Report 2026–1014, 57 p., https://doi.org/10.3133/ofr20261014.","productDescription":"Report: viii; 57 p.; Dataset","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-186051","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":504443,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS Database","linkHelpText":"EarthExplorer"},{"id":504441,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1014/ofr20261014.XML","description":"OFR 2026-1014 XML"},{"id":504440,"rank":2,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261014/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1014 HTML"},{"id":504438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1014/coverthb2.jpg"},{"id":504572,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2026/1014/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":504573,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1014/ofr20261014.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1014 PDF"},{"id":504442,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1014/images"}],"edition":"Version 1.0: May 18, 2026; Version 1.1: May 20, 2026","contact":"Director, Earth Resources Observation and Science Center
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47914 252nd Street
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These reports present and detail the methodology and procedures for characterization; present technical and operational information about the Tanager hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
This report summarizes the sensor performance of the Tanager based on the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence system characterization process. In summary, we determined that the Tanager exhibits a band-to-band geometric error ranging from -0.074 to 0.097 pixels. Compared to the Landsat Operational Land Imager, geometric offsets ranged from -5.980 meters (-0.20 pixels) to 11.348 meters (0.40 pixels). Radiometric comparisons showed offsets between -0.004 and 0.056 with slopes from 0.830 to 1.066. Spectral shifts are found between 0.65 and 0.75 nanometers. Finally, spatial performance evaluation yielded a PSF full width at half maximum of 1.27 to 1.75 pixels, a relative edge response of 0.802 to 0.651, and a modulation transfer function at Nyquist of 0.488 to 0.253.
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47914 252nd Street
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The U.S. Army Corps of Engineers, Jacksonville District, deepened the St. Johns River channel in Jacksonville, Florida, to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection sites in the St. Johns River and its tributaries.
This report contains information collected during the 2023 water year, from October 2022 to September 2023. Data at each site were compared for the length of the project, 8 years so far, and on a yearly basis to show the annual variability of discharge and salinity.
The countywide annual rainfall for the 2023 water year was below the average yearly rainfall in four of the five counties. Annual mean discharge at 9 of the 10 tributary monitoring sites was lower for the 2023 water year than for the 2022 water year, and the annual mean flow at Broward River below Biscayne Boulevard near Jacksonville, Florida (USGS site number 02246751), was the lowest recorded at that site for the 8 years of data collection. The annual mean discharge for each of the main-stem sites was higher for the 2023 water year than for the 2022 water year and was above the average for the 8 years of data collected so far.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek above Buckhorn Bluff near Jacksonville, Fla. (USGS site number 302657081312400), the site closest to the Atlantic Ocean, and was lowest at Durbin Creek near Fruit Cove, Fla. (USGS site number 022462002), the site farthest from the ocean, for all years. Annual mean salinity data from the main-stem sites indicate that salinity decreased with distance upstream from the ocean, which was expected. Annual mean salinity for the 2023 water year was higher than or equal to that of the 2022 water year for all main-stem and tributary sites, except at St. Johns River at Dancy Point near Spuds, Fla. (USGS site number 294213081345300), which was lower. Three main-stem monitoring stations (USGS site numbers 295856081372301, 02245340, and 301057081414800) and six tributary monitoring stations (USGS site numbers 300803081354500, 022462002, 301204081434900, 02246459, 02246518, and 02246804) either had the highest annual mean salinities or tied with the highest annual mean salinities at their respective sites since data collection began.
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This report provides actionable guidance for scientists developing scientific tools that inform on-the-ground decision making. Scientific tools, in the context of this report, are technology or protocols that help practitioners collect and analyze their own data, and information products and web tools that practitioners could use to inform decisions. Engaging end-users and fellow experts is fundamental to the creation of useful scientific tools. Scientists can use clear and specific direction on action steps and activities to effectively engage with end-users and fellow experts during development. Our study explores lessons learned from six U.S. Geological Survey projects that designed and implemented engagement activities with end-users and experts to coproduce scientific tools for natural resource managers. U.S. Geological Survey teams engaged end-users and experts across the United States from Federal, State, and local governments; universities; Tribes; territories; and nongovernmental organizations in designing and developing scientific tools intended to support end-users in their work. An online survey with 98 participants measured satisfaction across several indicators of successful engagement, including engagement activity frequency, sufficient opportunities to provide feedback, feedback implementation, inclusion of necessary perspectives, and functionality of the tool for end-users. Semistructured interviews were held with project leads, during which the project leads reviewed a summary of the survey results. The project leads reflected on the engagement efforts used in their project, then described lessons learned from the engagement experience and participant feedback. Common themes for ensuring effective engagement identified through thematic analysis included engaging end-users during product conceptualization; establishing clear roles and expectations; considering who end-users are and how end-users may use the tool; recruiting participants through your network, boundary spanners, and leadership; understanding individual use cases; communicating how feedback was integrated into the product; and strategically using virtual meeting tools. This guide shares practical steps and exercises for planning and facilitating effective engagement based on lessons learned from project leads and case study summaries of each project.
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U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes substantially to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides substantial volumes of agricultural products not just for California but for the United States.
Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface-water and groundwater resources in the valley. This situation has resulted in water management challenges in the Salinas Valley that generally relate to the distribution of the water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. Historically, to deal with the distribution issue, water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface-water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface-water supplies are insufficient. The availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand for groundwater and surface-water resources throughout the Salinas Valley has resulted in undesirable effects from unsustainable water use, such as surface-water depletion, groundwater-level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface-water and groundwater resources. To meet water demands and reduce the undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and climate variability.
To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resources Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley hydrogeologic system called the Salinas Valley System Model. The geologic framework is known as the Salinas Valley Geologic Framework and was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The surface-water model is called the Salinas Valley Watershed Model and simulates the Salinas River watershed. Monthly surface-water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.
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California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Essential to pasture health, dung beetles (Coleoptera: Scarabaeidae) provide key ecosystem services across natural and managed rangeland habitats. Insecticide residues in livestock dung can negatively impact dung beetle populations, and synergized pyrethroid products are commonly used to combat resistant pest fly populations. Here, permethrin residues were measured by GC-MS/MS in fresh cattle feces on Days −2 (pretreatment), 4, 8, 16, and 30 after the label rate application of a formulated pour-on treatment (a.i. 5% permethrin, 5% piperonyl butoxide [PBO]). Mean (± SE) measured permethrin concentrations were the highest on Day 4 at 1400 ± 360 ng of permethrin/g of dung (dry weight) with a maximum concentration of 2200 ng/g. Approximately, 99% of applied permethrin was excreted by Day 16, with no detection by Day 30. Field-collected dung was used in a 48-hour toxicity test and with three treatment groups (control [Day −2], low risk [Day 16], and high risk [Day 4]). Two temperate dung beetle species were tested: Onthophagus pennsylvanicus Harold and Canthon chalcites Haldeman. Mean (± SE) mortality of O. pennsylvanicus was 28 ± 5% and 58 ± 13% for low and high risk treatments, respectively. Mean (± SE) mortality of C. chalcites was lower than O. pennsylvanicus with 10 ± 4% and 40 ± 10% for low and high risk treatments, respectively. PBO was detected on Days 4 and 8, and the permethrin:PBO ratio was 10:1 on Day 4, i.e., high risk treatment. Data presented highlight episodic risks of pour-on products and support threshold-based, integrated pest management approaches.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agee.2026.110511","usgsCitation":"Cavallaro, M.C., Hladik, M.L., Soares, R., Anderson, M., and Hoback, W.W., 2026, Toxicity of synergized permethrin residues in cattle dung to two temperate dung beetle species after application of common livestock pour-on treatment: Agriculture, Ecosystems, and Environment, v. 408, 110511, 8 p., https://doi.org/10.1016/j.agee.2026.110511.","productDescription":"110511, 8 p.","ipdsId":"IP-186435","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":504530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","county":"Lincoln County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-97.1428,35.9442],[-96.6228,35.9427],[-96.6228,35.7248],[-96.6233,35.6377],[-96.6247,35.5564],[-96.6253,35.4634],[-96.6254,35.4602],[-96.8274,35.4646],[-97.0381,35.4651],[-97.1437,35.4645],[-97.1452,35.6361],[-97.1436,35.7246],[-97.1438,35.8112],[-97.1433,35.8988],[-97.1405,35.8988],[-97.1409,35.9283],[-97.1428,35.9442]]]},\"properties\":{\"name\":\"Lincoln\",\"state\":\"OK\"}}]}","volume":"408","noUsgsAuthors":false,"publicationDate":"2026-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavallaro, Michael C.","contributorId":371379,"corporation":false,"usgs":false,"family":"Cavallaro","given":"Michael","middleInitial":"C.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":961744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soares, Rodrigo","contributorId":371380,"corporation":false,"usgs":false,"family":"Soares","given":"Rodrigo","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":961746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Mikaela","contributorId":371382,"corporation":false,"usgs":false,"family":"Anderson","given":"Mikaela","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":961747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoback, W. Wyatt","contributorId":371383,"corporation":false,"usgs":false,"family":"Hoback","given":"W.","middleInitial":"Wyatt","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":961748,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275667,"text":"sir20265023 - 2026 - Top Elevation of Glacial Till and Thickness of the Big Sioux Aquifer Delineated From Electrical Resistivity Tomography Surveys Near Sioux Falls, South Dakota, 2022 and 2025","interactions":[],"lastModifiedDate":"2026-05-15T17:44:04.18892","indexId":"sir20265023","displayToPublicDate":"2026-05-12T09:48:23","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5023","displayTitle":"Top Elevation of Glacial Till and Thickness of the Big Sioux Aquifer Delineated From Electrical Resistivity Tomography Surveys Near Sioux Falls, South Dakota, 2022 and 2025","title":"Top Elevation of Glacial Till and Thickness of the Big Sioux Aquifer Delineated From Electrical Resistivity Tomography Surveys Near Sioux Falls, South Dakota, 2022 and 2025","docAbstract":"The City of Sioux Falls, South Dakota, requested the U.S. Geological Survey perform electrical resistivity surveys on three parcels of land north of the city. Electrical resistivity data were collected along a total of 22 transects during March 14–18, 2022, and November 17–21, 2025. Results from electrical resistivity surveys were used to delineate the top of glacial till deposits for the purpose of characterizing the Big Sioux aquifer near the city. Delineating geologic contacts provides important information on groundwater storage, flow dynamics, well design and placement, contaminant transport, groundwater–surface-water interactions, and regional water modeling. The top elevation of glacial till and the thickness of the Big Sioux aquifer varied among the three survey areas. The interpreted top elevation of glacial till in the North survey area decreases from east to west toward a slough, with elevations ranging from 1,403 to 1,418 feet (ft). The estimated thickness of the Big Sioux aquifer in the North survey area increased from east to west, with thicknesses ranging from 23 to 38 ft. The top elevation of glacial till in the Well 72 survey area generally decreases from northwest to southeast. Top elevations of the glacial till in the Well 72 survey area ranged from 1,400 to 1,409 ft along the southern end of transect W72_2. The estimated thickness of the Big Sioux aquifer in the Well 72 survey area was greatest along a southeast to northwest trending channel, with thicknesses ranging from 28 to 40 ft. The top elevation of glacial till in the Nose survey area generally decreases west toward the Big Sioux River. Top elevations of the glacial till in the Nose survey area ranged from 1,362 to 1,395 ft. The estimated thickness of the Big Sioux aquifer in the Nose survey area ranged from 33 to 70 ft.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265023","collaboration":"Prepared in cooperation with City of Sioux Falls, South Dakota","usgsCitation":"Medler, C.J., and Anderson, T.M., 2026, Top elevation of glacial till and thickness of the Big Sioux aquifer delineated from electrical resistivity tomography surveys near Sioux Falls, South Dakota, 2022 and 2025: U.S. Geological Survey Scientific Investigations Report 2026–5023, 29 p., https://doi.org/10.3133/sir20265023.","productDescription":"Report: vi, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-183750","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":504431,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119412.htm","linkFileType":{"id":5,"text":"html"}},{"id":504116,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5023/sir20265023.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5023 XML"},{"id":504120,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P18XCLZT","text":"USGS data release","linkHelpText":"Electrical resistivity tomography (ERT) data collected March 14–18 and November 17–21 north of Sioux Falls, South Dakota"},{"id":504119,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5023/images"},{"id":504115,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265023/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5023 HTML"},{"id":504113,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5023/sir20265023.pdf","text":"Report","size":"18.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5023"},{"id":504112,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5023/coverthb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Big Sioux Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.783333,\n 43.58\n ],\n [\n -96.683333,\n 43.58\n ],\n [\n -96.683333,\n 43.666667\n ],\n [\n -96.783333,\n 43.666667\n ],\n [\n -96.783333,\n 43.8\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
This study was conducted by the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, to update the hydrogeologic framework and conceptual flow model for the panhandle and northwest parts of the High Plains (Ogallala) aquifer in Oklahoma, which together compose the Ogallala aquifer focus area. The study included the construction of a potentiometric surface, and available geologic and hydrologic data were used to evaluate saturated thickness of the aquifer. The water budget for the updated conceptual groundwater-flow model was based on estimated inflows and outflows for the 1998–2022 study period.
Saturated thickness of the Ogallala aquifer averaged 127 and 116 feet for the panhandle and northwest parts, respectively. Groundwater withdrawals from the Ogallala aquifer for 1998–2022 averaged 422,054 and 39,645 acre-feet per year (acre-ft/yr) for the panhandle and northwest parts, respectively. Recharge, the primary inflow, was estimated at 0.63 inch per year for the 1998–2022 study period, with the panhandle part of the Ogallala aquifer receiving 175,068 acre-ft/yr and the northwest part of the Ogallala aquifer receiving 49,376 acre-ft/yr. Additional inflows included irrigation return flows, estimated at 8,111 and 642 acre-ft/yr for the panhandle and northwest parts, respectively, of the Ogallala aquifer. Net lateral groundwater flows, considered to be aquifer outflows, were estimated to account for 31,908 acre-ft/yr for the Ogallala aquifer focus area. Streambed seepage, which was an outflow of 5,535 acre-ft/yr, was only present in the northwest part of the Ogallala aquifer. Vertical leakage and saturated-zone evapotranspiration were considered negligible outflows. These findings provide a revised conceptual groundwater-flow model water budget for the Ogallala aquifer focus area in Oklahoma.
The first quantitative mineral resource assessment for undiscovered lithium pegmatite deposits in the southern Appalachian region of the United States was conducted. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical and mineral occurrence data. Lithium pegmatite prospectivity of the tracts was ranked with simplified mappable criteria, including proximity to Paleozoic felsic intrusions and major lithotectonic structures, stream sediment geochemical anomalies, and pegmatite occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. These estimates were integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was applied to convert the probabilistic estimates of contained lithium into recoverable material. The identified lithium pegmatite resources for the Carolina Lithium and Kings Mountain deposits, North Carolina, contain 1589 thousand tons (kt) of Li2O. The median contained undiscovered resource for the southern Appalachian orogen was estimated to be 2240 kt Li2O. At 90% confidence, the region contains at least 130 kt Li2O, and 10,700 kt at 10% confidence. After applying economic filters, the median recoverable contained resource was 1430 kt Li2O, corresponding to approximately 201 years of current lithium imports for consumption in the United States. North and South Carolina are likely to contain most of these resources. Coarse data resolution and intra-state variations in the geological data contribute to uncertainty of undiscovered lithium pegmatite resources. Continued efforts to harmonize disparate geospatial datasets with updated or new information can improve the accuracy and precision of estimated undiscovered lithium pegmatite resources in the study area and at broader scales.
","language":"English","publisher":"Springer","doi":"/10.1007/s11053-026-10689-w","usgsCitation":"Rosera, J.M., Crocker, K., Pianowski, L., Murchek, J., Wiens, A.M., Sanders, M.M., Evart, L., DeAngelo, J., Lederer, G.W., and Coyan, J.A., 2026, Quantitative mineral resource assessment of lithium pegmatite deposits in the southern Appalachian orogen: Natural Resources Research, https://doi.org//10.1007/s11053-026-10689-w.","ipdsId":"IP-173525","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":504647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11053-026-10689-w","text":"Publisher Index Page"},{"id":504483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, Maryland, North Carolina, South Carolina, Virginia","otherGeospatial":"southern Appalachian orogen","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.0950383,\n 38.4437543\n ],\n [\n -75.7221382,\n 38.6381998\n ],\n [\n -75.7635716,\n 39.6663386\n ],\n [\n -77.5037717,\n 39.7619553\n ],\n [\n -78.1667051,\n 38.6705562\n ],\n [\n -79.3682719,\n 37.529411\n ],\n [\n -80.9427387,\n 37.3320007\n ],\n [\n -82.1443054,\n 36.2035478\n ],\n [\n -84.4231389,\n 34.8548403\n ],\n [\n -85.9561724,\n 33.449091\n ],\n [\n -87.4063392,\n 33.0332492\n ],\n [\n -85.4589723,\n 32.4057935\n ],\n [\n -82.6000721,\n 32.8941965\n ],\n [\n -81.232772,\n 32.4757285\n ],\n [\n -80.3626719,\n 32.5106757\n ],\n [\n -78.4981718,\n 33.8285365\n ],\n [\n -78.0009718,\n 33.8285365\n ],\n [\n -76.4679383,\n 34.8548403\n ],\n [\n -75.8878716,\n 35.565739\n ],\n [\n -76.1364716,\n 36.9024953\n ],\n [\n -76.177905,\n 38.2487836\n ],\n [\n -75.7221382,\n 38.6381998\n ],\n [\n -75.8050049,\n 38.7028981\n ],\n [\n -75.8464383,\n 38.6058287\n ],\n [\n -75.8464383,\n 38.6705562\n ],\n [\n -75.8050049,\n 38.6705562\n ],\n [\n -76.0950383,\n 38.4437543\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":961644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crocker, Kelsey Elizabeth 0000-0002-5919-5274","orcid":"https://orcid.org/0000-0002-5919-5274","contributorId":298791,"corporation":false,"usgs":true,"family":"Crocker","given":"Kelsey Elizabeth","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":961645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pianowski, Laura 0000-0002-5346-8251","orcid":"https://orcid.org/0000-0002-5346-8251","contributorId":218817,"corporation":false,"usgs":true,"family":"Pianowski","given":"Laura","email":"","affiliations":[],"preferred":true,"id":961646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murchek, Jacob T. 0009-0006-1765-5646","orcid":"https://orcid.org/0009-0006-1765-5646","contributorId":343990,"corporation":false,"usgs":true,"family":"Murchek","given":"Jacob T.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":961647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanders, Margaret M. 0000-0003-3505-874X","orcid":"https://orcid.org/0000-0003-3505-874X","contributorId":248709,"corporation":false,"usgs":true,"family":"Sanders","given":"Margaret","email":"","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":961649,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Evart, Lucas Leonidus 0000-0002-3442-0922","orcid":"https://orcid.org/0000-0002-3442-0922","contributorId":302525,"corporation":false,"usgs":true,"family":"Evart","given":"Lucas Leonidus","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":961650,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":961651,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":961652,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Coyan, Joshua A. 0000-0002-8450-7364 jcoyan@usgs.gov","orcid":"https://orcid.org/0000-0002-8450-7364","contributorId":197481,"corporation":false,"usgs":true,"family":"Coyan","given":"Joshua","email":"jcoyan@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":961653,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70276249,"text":"70276249 - 2026 - Accounting for emigration reveals high survival and bimodal size at departure from a loggerhead sea turtle (Caretta caretta) foraging area","interactions":[],"lastModifiedDate":"2026-05-20T14:57:35.282917","indexId":"70276249","displayToPublicDate":"2026-05-11T09:52:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Accounting for emigration reveals high survival and bimodal size at departure from a loggerhead sea turtle (Caretta caretta) foraging area","title":"Accounting for emigration reveals high survival and bimodal size at departure from a loggerhead sea turtle (Caretta caretta) foraging area","docAbstract":"The life history of hard-shelled sea turtles includes several ontogenetic shifts in habitat use and these complex permanent emigration patterns can impact estimates of stage-specific population rates, including survival. We developed several multistate mark recapture models to estimate survival of adult and juvenile loggerhead turtles from a coastal bay in the northern Gulf of America (also commonly referred to as the Gulf of Mexico) while, in some cases, accounting for permanent emigration and transient individuals. Our mark-recapture dataset consisted of 228 individual turtles with 37 total recaptures from 2011 to 2024. Of the models we fit, those that incorporated emigration produced higher estimates for annual survival than models that did not, and higher estimates than what is commonly seen in the literature for loggerheads. All models suggested a major permanent emigration pulse at the typical size of sexual maturity (70 cm straight carapace length) and another major pulse at > 90 cm. This bimodal pattern of departure may reflect differences in size at sexual maturity among loggerheads, possible genetic variability within the assemblage, or both. To assess the models’ ability to effectively recover true parameter values, we developed a simulation study of 50 randomly generated independent data sets under our specified models of similar sample size to our study dataset. Simulation results suggested that models that accounted for permanent emigration and transient individuals produced relatively unbiased estimates of survival, while models that did not often underestimated survival rates. Mark-recapture studies that may exhibit emigration and suffer from low recapture rates would benefit from auxiliary data collection such as acoustic telemetry detections to better estimate true rates of emigration and survival. Obtaining unbiased estimates of true survival by accounting for processes like emigration can support effective conservation of endangered long-lived species like loggerheads.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00227-026-04842-5","usgsCitation":"Blommel, C.M., Lamont, M., and Kendall, W.L., 2026, Accounting for emigration reveals high survival and bimodal size at departure from a loggerhead sea turtle (Caretta caretta) foraging area: Marine Biology, v. 173, no. 6, 95, 15 p., https://doi.org/10.1007/s00227-026-04842-5.","productDescription":"95, 15 p.","ipdsId":"IP-182417","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":504655,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00227-026-04842-5","text":"Publisher Index Page"},{"id":504575,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13E4PMT","text":"USGS data release","linkHelpText":"Mark recapture data for loggerhead sea turtles in St. Joseph Bay, FL from 2011-2024"},{"id":504551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St. Joseph Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.47559331382445,\n 29.90905541130931\n ],\n [\n -85.25446694849322,\n 29.90905541130931\n ],\n [\n -85.25446694849322,\n 29.64361905224979\n ],\n [\n -85.47559331382445,\n 29.64361905224979\n ],\n [\n -85.47559331382445,\n 29.90905541130931\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"173","issue":"6","noUsgsAuthors":false,"publicationDate":"2026-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Blommel, Caroline M. 0000-0002-1716-2706","orcid":"https://orcid.org/0000-0002-1716-2706","contributorId":371440,"corporation":false,"usgs":false,"family":"Blommel","given":"Caroline","middleInitial":"M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":961824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":206258,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":961825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":961826,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70275735,"text":"70275735 - 2026 - Variability and consistency in wildfire susceptibility: Insights from a national compilation","interactions":[],"lastModifiedDate":"2026-05-15T13:16:54.003888","indexId":"70275735","displayToPublicDate":"2026-05-11T09:19:29","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Variability and consistency in wildfire susceptibility: Insights from a national compilation","docAbstract":"Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear.
This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts.
We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale.
RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input.
Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs.
Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF25219","usgsCitation":"Russell, A., Bair, L., Meldrum, J.R., and Hawbaker, T., 2026, Variability and consistency in wildfire susceptibility: Insights from a national compilation: International Journal of Wildland Fire, v. 35, no. 5, WF25219, 14 p., https://doi.org/10.1071/WF25219.","productDescription":"WF25219, 14 p.","ipdsId":"IP-182497","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":504330,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":504378,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf25219","text":"Publisher Index Page"}],"country":"United States","volume":"35","issue":"5","noUsgsAuthors":false,"publicationDate":"2026-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Russell, Aaron Daniel 0000-0003-3980-827X","orcid":"https://orcid.org/0000-0003-3980-827X","contributorId":355854,"corporation":false,"usgs":true,"family":"Russell","given":"Aaron Daniel","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bair, Lucas 0000-0002-9911-3624","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":248714,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":961576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":222615,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":961577,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275703,"text":"70275703 - 2026 - Patterns of floodplain forest mortality and recruitment along the Upper Mississippi and Illinois Rivers: Associations with forest fragmentation and flood inundation","interactions":[],"lastModifiedDate":"2026-05-13T14:23:56.148281","indexId":"70275703","displayToPublicDate":"2026-05-11T09:18:04","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of floodplain forest mortality and recruitment along the Upper Mississippi and Illinois Rivers: Associations with forest fragmentation and flood inundation","docAbstract":"Different rates of floodplain forest recruitment and mortality can reveal important changes in ecosystem processes that drive forest dynamics, resulting in net changes in forest cover, thereby influencing a wide range of river habitat and morphological characteristics.
We evaluated characteristics of forest change areas in the Upper Mississippi River System.
An overlay technique was used to map patches of forest loss, gain, and persistence between 2010 and 2020 in relation to a series of explanatory variables.
We quantified a net decline in forest cover ranging from 3.2 to 16.8% in the uppermost five study reaches, and a net increase in forest cover ranging from 0.5 to 4.6% in the southernmost three reaches. Patches of forest loss and persistence were similarly tall (> 15 m), dense (> 90% cover), silver maple (Acer saccharinum) dominated forests, whereas forest gain patches were short (< 15 m), less dense (< 66% cover) and more likely to be dominated by willow (Salix) species. Both forest loss and gain patches were smaller than forest persistence patches and were typically found in areas with low neighborhood forest density (< 50% forested 10 ha neighborhood). Areas that experienced more than three flood events per growing season, more than 100 consecutive days of inundation during a single flood event, and more than 60 mean total days of inundation per growing season from 2011 to 2020 showed a net loss of forest cover in all study reaches. In contrast, net increases in forest cover were restricted to areas that experienced less than a single flood event per growing season, less than 40 consecutive days of inundation during a single flood event and less than 30 mean total days of inundation per growing season from 2011 to 2020.
Forest mortality along these river reaches is associated with forest fragmentation and an increasingly wetter hydrological regime.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-025-02286-8","usgsCitation":"De Jager, N.R., Rohweder, J.J., Van Appledorn, M., Weiss, S.A., Trumper, M., and Guyon, L.J., 2026, Patterns of floodplain forest mortality and recruitment along the Upper Mississippi and Illinois Rivers: Associations with forest fragmentation and flood inundation: Landscape Ecology, v. 41, 90, 25 p., https://doi.org/10.1007/s10980-025-02286-8.","productDescription":"90, 25 p.","ipdsId":"IP-180163","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":504372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-025-02286-8","text":"Publisher Index Page"},{"id":504300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi and Illinois Rivers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96,\n 46\n ],\n [\n -86,\n 46\n ],\n [\n -86,\n 36.633102878335635\n ],\n [\n -96,\n 36.633102878335635\n ],\n [\n -96,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2026-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":961442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":961443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":961444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiss, Shelby A.","contributorId":368922,"corporation":false,"usgs":false,"family":"Weiss","given":"Shelby","middleInitial":"A.","affiliations":[{"id":55549,"text":"National Great Rivers Research and Education Center","active":true,"usgs":false}],"preferred":false,"id":961445,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trumper, Matthew","contributorId":369810,"corporation":false,"usgs":false,"family":"Trumper","given":"Matthew","affiliations":[{"id":87852,"text":"Former Upper Midwest Environmental Sciences Employee","active":true,"usgs":false}],"preferred":false,"id":961446,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guyon, Lyle J.","contributorId":215690,"corporation":false,"usgs":false,"family":"Guyon","given":"Lyle","email":"","middleInitial":"J.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":961447,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70275694,"text":"70275694 - 2026 - Refinement of a framework for Moving Aircraft River Velocimetry (MARV) and application to particle tracking along Alaskan rivers","interactions":[],"lastModifiedDate":"2026-05-12T13:47:57.040645","indexId":"70275694","displayToPublicDate":"2026-05-11T08:46:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Refinement of a framework for Moving Aircraft River Velocimetry (MARV) and application to particle tracking along Alaskan rivers","docAbstract":"Information on river velocities enhances understanding flood hazards, evaluating habitat conditions, and predicting the transport of floating materials. In this follow-up study, we used data from two new sites, one with a more complex morphology and the other with a lower suspended sediment concentration, to provide further evidence that Moving Aircraft River Velocimetry (MARV) can yield accurate velocity estimates ( R2 up to 0.87 when compared to field measurements) for long segments of large, turbid rivers. The MARV workflow is packaged in freely available software and is robust to implementation details; neither buffering to mitigate edge effects nor a new approach to aggregating velocity vectors improved performance. MARV was not sensitive to parameters used to establish overlapping image sequences, but combining a long window with a short jump between consecutive windows was the optimal configuration. Although accuracy varied from one cross section to the next, agreement between remotely sensed velocities and those measured in the field was independent of position within a frame range. As an initial step toward application of the approach to help address practical problems, we showed how MARV can drive particle tracking models. Our first-order simulations suggest that channel morphology and flow velocity are the primary controls on travel time and particle fate, with diffusive processes playing a lesser role. Although MARV can be used to characterize an instantaneous flow field, a more comprehensive framework that accounts for other physical processes would be required to model specific types of events like oil spills.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR043181","usgsCitation":"Legleiter, C.J., Kinzel, P.J., Laker, M., and Conaway, J., 2026, Refinement of a framework for Moving Aircraft River Velocimetry (MARV) and application to particle tracking along Alaskan rivers: Water Resources Research, v. 62, no. 5, e2025WR043181, 36 p., https://doi.org/10.1029/2025WR043181.","productDescription":"e2025WR043181, 36 p.","ipdsId":"IP-184216","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":504369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr043181","text":"Publisher Index Page"},{"id":504278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tanana River, Yukon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.75570313334435,\n 65.91143177654979\n ],\n [\n -149.47674302069896,\n 65.91143177654979\n ],\n [\n -149.47674302069896,\n 65.84208480633984\n ],\n [\n -149.75570313334435,\n 65.84208480633984\n ],\n [\n -149.75570313334435,\n 65.91143177654979\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -145.77263488160432,\n 64.18041091114998\n ],\n [\n -145.87601297288305,\n 64.18041091114998\n ],\n [\n -145.87601297288305,\n 64.1422606892462\n ],\n [\n -145.77263488160432,\n 64.1422606892462\n ],\n [\n -145.77263488160432,\n 64.18041091114998\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"5","noUsgsAuthors":false,"publicationDate":"2026-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":961428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laker, Mark","contributorId":298315,"corporation":false,"usgs":false,"family":"Laker","given":"Mark","email":"","affiliations":[{"id":64530,"text":"U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":961430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conaway, Jeff 0000-0002-3036-592X","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":214226,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeff","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":961431,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275631,"text":"sir20265007 - 2026 - Regression models for estimating suspended sediment concentrations and loads and comparison with acoustic surrogate model on the Snake River, Weiser, Idaho, 1977–2022","interactions":[],"lastModifiedDate":"2026-05-11T17:06:06.542003","indexId":"sir20265007","displayToPublicDate":"2026-05-07T15:45:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5007","displayTitle":"Regression Models for Estimating Suspended Sediment Concentrations and Loads and Comparison With Acoustic Surrogate Model on the Snake River, Weiser, Idaho, 1977–2022","title":"Regression models for estimating suspended sediment concentrations and loads and comparison with acoustic surrogate model on the Snake River, Weiser, Idaho, 1977–2022","docAbstract":"The U.S. Geological Survey, in cooperation with Idaho Power, developed streamflow- based regression models to estimate suspended sediment concentration (SSC) and loads on the Snake River at Weiser, Idaho site (U.S. Geological Survey streamgage 13269000; hereafter referred to as “Snake at Weiser site”). This site sits upstream from the dams and reservoirs of the Hells Canyon Complex and the Hells Canyon National Recreation Area, where large sandbars along the Snake River that provide recreation and riparian habitat and host archaeological resources have declined since 1973. Analyses of samples from historical (1977- 2003) and modern (2017- 22) periods show that SSC has decreased over time, with median concentrations declining from 50 milligrams per liter (mg/L) to 28 mg/L. Mann- Kendall trend tests confirm statistically significant declines in total SSC and the fine and sand fractions of suspended sediment through the full period of record.
Regression models specific to each period outperformed models using the full dataset, suggesting changes in the sediment supply to this reach of the Snake River and highlighting the need for period- based approaches. Regression models for total SSC and fine sediment were more accurate than those for sand, which exhibited greater error and bias, likely reflecting a sand supply limited by upstream dams. The regression model for modern period total SSC and a previously developed acoustic surrogate model showed similar performance, indicating both methods are viable for estimating SSC and loads.
These findings help to better quantify suspended sediment concentrations and loads upstream of the Hells Canyon Complex and provide resource managers with tools to better quantify sediment loads affecting reservoir storage and the maintenance of sandbars in the Hells Canyon National Recreation Area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265007","collaboration":"Prepared in cooperation with Idaho Power","usgsCitation":"Kenworthy, M.K., 2026, Regression models for estimating suspended sediment concentrations and loads and comparison with acoustic surrogate model on the Snake River, Weiser, Idaho, 1977–2022: U.S. Geological Survey Scientific Investigations Report 2026–5007, 27 p., https://doi.org/10.3133/sir20265007.","productDescription":"Report: vi, 27 p.; 2 Data Releases","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-173970","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":504272,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119409.htm","linkFileType":{"id":5,"text":"html"}},{"id":504016,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14KZNMK","text":"USGS data release","linkHelpText":"Suspended sediment dataset for development of regression models to estimate suspended sediment concentration and loads for the Snake River at Weiser, Idaho, 1977–2022"},{"id":504011,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5007/sir20265007.pdf","size":"4.25 MB","description":"SIR 2026-5007 PDF"},{"id":504015,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YT1GIC","text":"USGS data release","linkHelpText":"Model Archive Summary for acoustic derived suspended- sediment concentration at 13269000 Snake River at Weiser, ID"},{"id":504014,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5007/images/"},{"id":504013,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5007/sir20265007.XML","description":"SIR 2026-5007 XML"},{"id":504012,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265007/full","description":"SIR 2026-5007 HTML"},{"id":504010,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5007/coverthb.jpg"}],"country":"United States","state":"Idaho, Nevada, Oregon, Utah","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119,\n 45.5\n ],\n [\n -113,\n 45.5\n ],\n [\n -113,\n 41\n ],\n [\n -119,\n 41\n ],\n [\n -119,\n 45.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd.
Boise, Idaho 83702-4520