In unconventional petroleum reservoirs hydrocarbon fluids are hosted by both mineral and organic matter pores. These pores can have diameters that range from microns to less than a single nanometer and, for unconventional reservoirs, there is evidence that small pores ( <20 nm diameter) may constitute a large proportion of the available space. Understanding subsurface volumes and how fluids behave in them can be helpful for predicting hydrocarbon production and storage in the subsurface. One area with knowledge gaps regarding hydrocarbon behavior in small pores is the possibility for mixtures to fractionate (i.e., unmix) based on pore size or pore type. Mixture fractionation as a function of pore size could impact recovery of hydrocarbons, drive compositional shifts during production, and limit fluid storage within candidate reservoirs. To investigate natural gas fractionation in small geologic pores, we applied total neutron scattering to probe methane-ethane mixtures at reservoir pressures (up to ≈30 MPa) and temperature (60°C) within a sample from the Upper Cretaceous Niobrara Formation. Neutron scattering data reveal only minor fractionation occurs between methane and ethane in 20-nm diameter sample mesopores. Increased fractionation is observed for sample micropores, with up to 72% (±1% at 1-sigma) methane found in 2 nm diameter pores following injection of a 50%-50% methane-ethane mixture. These data provide rarely available direct experimental observations of hydrocarbon mixture behavior under nanoconfinement in a sample from an important unconventional petroleum reservoir. Our results are discussed in the context of evaluating hydrocarbon resources in unconventional reservoir meso- and micropores, reconciling observed gas composition changes during production, and more broadly, understanding subsurface pore volumes within an energy storage framework.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fuel.2026.140015","usgsCitation":"Jubb, A., Birdwell, J.E., Ruppert, L., Stokes, M., Wiens, A.M., Headen, T., and Youngs, T.G., 2027, Neutron scattering reveals fractionation of natural gas mixtures in unconventional petroleum reservoir pores: Perspectives on energy resource recovery and storage: Fuel, v. 427, no. Part E, 140015, 9 p., https://doi.org/10.1016/j.fuel.2026.140015.","productDescription":"140015, 9 p.","ipdsId":"IP-178718","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":505040,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fuel.2026.140015","text":"Publisher Index Page"},{"id":504908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"427","issue":"Part E","noUsgsAuthors":false,"publicationDate":"2026-05-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":962160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":962161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":242600,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie F.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":962162,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stokes, Martha 0000-0002-2838-8380","orcid":"https://orcid.org/0000-0002-2838-8380","contributorId":269608,"corporation":false,"usgs":true,"family":"Stokes","given":"Martha","email":"","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":962163,"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":962164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Headen, Thomas","contributorId":239572,"corporation":false,"usgs":false,"family":"Headen","given":"Thomas","affiliations":[],"preferred":false,"id":962165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Youngs, Tristan G. A.","contributorId":202502,"corporation":false,"usgs":false,"family":"Youngs","given":"Tristan","email":"","middleInitial":"G. A.","affiliations":[{"id":36465,"text":"Disordered Materials Group (ISIS), STFC Rutherford Appleton Laboratory, U.K.","active":true,"usgs":false}],"preferred":false,"id":962166,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276486,"text":"dr1225 - 2026 - Distribution, abundance, and breeding activities of Southwestern Willow Flycatchers (Empidonax traillii extimus) on the San Dieguito River and upper San Luis Rey River, San Diego County, California—2025 data summary","interactions":[],"lastModifiedDate":"2026-06-08T19:44:05.407687","indexId":"dr1225","displayToPublicDate":"2026-06-08T12:31:05","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1225","displayTitle":"Distribution, Abundance, and Breeding Activities of Southwestern Willow Flycatchers (Empidonax traillii extimus) on the San Dieguito River and Upper San Luis Rey River, San Diego County, California—2025 Data Summary","title":"Distribution, abundance, and breeding activities of Southwestern Willow Flycatchers (Empidonax traillii extimus) on the San Dieguito River and upper San Luis Rey River, San Diego County, California—2025 data summary","docAbstract":"We surveyed for Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at the San Dieguito River and the upper San Luis Rey River in 2025. Surveys were completed at five locations: one along the San Dieguito River (San Dieguito [SD]), which was last surveyed in 2016, and four along the upper San Luis Rey River, including three downstream from Lake Henshaw that have been surveyed annually since 2015 (Rey River Ranch [RRR], Cleveland National Forest [CNF], Vista Irrigation District [VID]), and one upstream at VID Lake Henshaw (VLH) that has been surveyed annually since 2018. There was a minimum of 57 territorial flycatchers (22 male, 35 female) and 3 transient flycatchers of unknown subspecies detected at 1 location (VLH). In total, 37 territories were established, containing 35 pairs (20 males and 35 females) and 2 male flycatchers of undetermined breeding status. Of the 35 pairs, 12 were monogamous pairings, and 23 were polygynous pairings consisting of 3 males each pairing with 2 different females [6 pairs], 3 males each pairing with 3 different females [9 pairs], and 2 males each pairing with 4 different females [8 pairs]).
No territorial flycatchers were detected downstream from Lake Henshaw or along the San Dieguito River. Brown-headed Cowbirds (Molothrus ater; cowbird) were detected at all five survey locations. No banded flycatchers were detected during surveys.
Flycatchers used only one habitat type at VLH, mixed willow riparian. All flycatcher locations were in habitat characterized as mixed willow riparian dominated by Goodding’s black willow (Salix gooddingii), and 93 percent were in habitat with greater than 95-percent native plant cover.
We monitored flycatcher nests at VLH to collect baseline data on nest success, productivity, and cowbird parasitism rate. There were 33 completed nests monitored in 26 territories; 10 were successful (30 percent). Of the 23 failed nests, 14 were depredated, 5 failed for unknown reasons, and 4 failed because of cowbird parasitism. There were 33 fledglings confirmed in monitored territories, yielding a seasonal productivity of 1.3 young/pair (33 young/26 monitored pairs). One additional fledgling was confirmed in an unmonitored territory during surveys at VLH. Based on 31 nests in which the contents were observed during the egg stage, 23 percent of nests in 2025 were parasitized. In two additional territories where nests were not located, adult flycatchers were observed feeding a cowbird fledgling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1225","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2026, Distribution, abundance, and breeding activities of Southwestern Willow Flycatchers (Empidonax traillii extimus) on the San Dieguito River and upper San Luis Rey River, San Diego County,\nCalifornia—2025 data summary: U.S. Geological Survey Data Report 1225, 14 p., https://doi.org/10.3133/dr1225.","productDescription":"Report: vi, 14 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-184457","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":505191,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96VC5Y4","text":"USGS data release","linkHelpText":"Southwestern Willow Flycatcher (Empidonax traillii extimus) Surveys and Nest Monitoring in San Diego County, California (ver. 5.0, December 2025)"},{"id":505113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1225/coverthb.jpg"},{"id":505114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1225/dr1225.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1225 PDF"},{"id":505115,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1225/full","linkFileType":{"id":5,"text":"html"},"description":"DR 1225 HTML"},{"id":505116,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1225/dr1225.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1225 XML"},{"id":505117,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1225/images"}],"contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The U.S. Geological Survey evaluated the stability of water-sample chemical analysis of nutrient, alkalinity, and acid-neutralizing capacity constituents with respect to the duration between sample collection and laboratory analysis, also known as the sample holding time. A study began in the spring of 2023 to evaluate the sample stability, between 2 and 180 days after sample collection, of the chemical properties and chemical constituents of alkalinity as calcium carbonate, filtered; acid-neutralizing capacity as calcium carbonate, unfiltered; total ammonia as nitrogen, filtered; total ammonia plus organic nitrogen as nitrogen, filtered and unfiltered; nitrite as nitrogen, filtered; nitrate plus nitrite as nitrogen, filtered; total nitrogen, filtered and unfiltered; orthophosphate as phosphorous, filtered; and total phosphorus as phosphorus (filtered and unfiltered) in water. Both surface water and groundwater matrices were represented.
Sample instability varied by observed property and matrix; therefore, providing general guidance for sample holding time is not possible based on matrices alone. No correlations between field measurements of sample characteristics and sample instability were observed. Although observations for some properties indicate sample stability that exceeds the recognized U.S. Geological Survey National Water Quality Laboratory method holding times, this is not necessarily the case for matrices and seasonal characteristics that were not investigated.
Based on the limited number of six sample sources used in this study, some patterns emerge for the 12 observed properties studied. Five observed properties generally indicate stability for as many as 180 days after sampling (total nitrogen as nitrogen, both filtered and unfiltered; orthophosphate as phosphorus, filtered; and phosphorus as phosphorus, both filtered and unfiltered). Other observed properties indicate stability for as many as 180 days for some matrices, but not for others. Finally, some observed properties indicate instability well before 180 days.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20265014","usgsCitation":"Struzeski, T.M., Wetherbee, G.A., and Morrison, J., 2026, Evaluation of nutrient, alkalinity, and acid-neutralizing capacity stabilities in water samples analyzed by the U.S. Geological Survey National Water Quality Laboratory, 2023–24: U.S. Geological Survey Scientific Investigations Report 2026–5014, 36 p., https://doi.org/10.3133/sir20265014.","productDescription":"Report: vi, 36 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-175990","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":504314,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5014/sir20265014.xml"},{"id":504313,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5014/images"},{"id":504312,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1BRC2GJ","text":"USGS data release","description":"SIR 2026-5014 data release","linkHelpText":"Data for Evaluation of Nutrient, Alkalinity, and Acid Neutralizing Capacity Stabilities in Water Samples Analyzed by the National Water Quality Laboratory -- 2023-2024"},{"id":504311,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5014/sir20265014.pdf","text":"Report","size":"5.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5014"},{"id":505176,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119485.htm","linkFileType":{"id":5,"text":"html"}},{"id":504310,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5014/coverthb.jpg"},{"id":505170,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265014/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5014"}],"contact":"Chief, Quality Systems Branch
U.S. Geological Survey
Box 25046, Mail Stop 401
Denver, CO 80225
In 2023–24, the U.S. Geological Survey (USGS) studied how long different chemical measurements in water samples remain reliable if analysis is delayed after collection. This question became important after the National Water Quality Laboratory (NWQL) experienced a large backlog of sample analyses causing many samples to be analyzed outside the timeframe required by the NWQL, which affected many USGS studies, some of which were being done for regulatory purposes (such as to meet requirements set by the Environmental Protection Agency). There are specific time frames in place to ensure that analyte concentrations do not change significantly between sampling and the time of analysis. The study focused on those water‑quality measurements that tend to be most affected by delayed analysis including forms of nitrogen and phosphorus (nutrients), alkalinity, and acid‑neutralizing capacity. Because the type of water can affect sample stability, samples used in the study were collected from six separate locations (five streams and one well) from across the United States. Samples were analyzed repeatedly for periods ranging from two days to 180 days after collection. The study found that sample stability depends on what is being measured and on the type of water the measurement comes from. Overall, the study found that some analyses performed after the required timeframe can still be useful, but data quality depends on the specific chemical measurement, the water type, and the intended use of the data.
","publicationDate":"2026-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Struzeski, Tedmund M. 0009-0007-4598-6263","orcid":"https://orcid.org/0009-0007-4598-6263","contributorId":331350,"corporation":false,"usgs":true,"family":"Struzeski","given":"Tedmund M.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":961519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":202919,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory A.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":961520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, Jonathan 0000-0002-1756-4609","orcid":"https://orcid.org/0000-0002-1756-4609","contributorId":241080,"corporation":false,"usgs":true,"family":"Morrison","given":"Jonathan","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961521,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276445,"text":"sir20265019 - 2026 - Spatial and temporal trends of mercury in fish from Duck Valley Reservation Reservoirs, southwestern Idaho and northern Nevada, 2007–24","interactions":[],"lastModifiedDate":"2026-06-08T16:38:33.093469","indexId":"sir20265019","displayToPublicDate":"2026-06-08T11:51:31","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":"2026-5019","displayTitle":"Spatial and Temporal Trends of Mercury in Fish from Duck Valley Reservation Reservoirs, Southwestern Idaho and Northern Nevada, 2007–24","title":"Spatial and temporal trends of mercury in fish from Duck Valley Reservation Reservoirs, southwestern Idaho and northern Nevada, 2007–24","docAbstract":"The Shoshone-Paiute (Sho-Pai) Tribes of the Duck Valley Reservation, Nevada, manage reservoirs that support commercial and recreational activities, including robust Oncorhynchus mykiss (rainbow trout) fisheries that attract anglers year-round. Reservoirs are common environments for methylation and bioaccumulation of mercury, which is a potent neurotoxin when elevated levels are consumed. The U.S. Geological Survey (USGS), in cooperation with the Sho-Pai Tribes, measured total mercury concentrations in the muscle tissue of rainbow trout from three Reservation reservoirs in Idaho and Nevada in 2007, 2009, 2013, and 2024. This report highlights spatial and temporal trends of mercury concentrations in rainbow trout in the Duck Valley Reservation reservoirs from 2007 through 2024, and presents limited data on other commonly consumed species, specifically Perca flavescens (yellow perch), Micropterus dolomieu (smallmouth bass), and Micropterus salmoides (largemouth bass). Mercury data are also presented for nearby sites and lower trophic level species. In 2024, two fish sampling methods were used and compared: biopsy muscle plugs and muscle fillets. Results show good agreement between mercury concentrations of biopsy and fillet muscle samples taken from the same fish, with most sample pairs differing by less than 20 percent, though biopsied fish had an unexpectedly high mortality rate. Mercury concentrations increased in Sheep Creek Reservoir during the study period, but no significant trend was observed in Mountain View Reservoir or Lake Billy Shaw. Only 1 rainbow trout out of 160 sampled in the Reservation reservoirs during the study period exceeded the U.S. Environmental Protection Agency’s recommended methylmercury criterion of 0.3 milligram per kilogram of wet weight (mg/kg ww). Largemouth bass, smallmouth bass, and yellow perch had higher mercury concentrations than rainbow trout and may pose a greater risk to consumers. Mercury concentrations in largemouth bass exceeded 0.3 mg/kg ww, although only two fish were sampled, both from Sheep Creek Reservoir. Fish consumption advisories on Tribal lands are determined by the Tribes, and these results may help Sho-Pai managers determine the mercury exposure risk to Tribal members and visiting anglers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265019","collaboration":"Prepared in cooperation with Shoshone-Paiute Tribes of the Duck Valley Reservation","usgsCitation":"Murray, E.M., 2026, Spatial and temporal trends of mercury in fish from Duck Valley Reservation Reservoirs, southwestern Idaho and northern Nevada, 2007–24: U.S. Geological Survey Scientific Investigations Report 2026–5019, 19 p., https://doi.org/10.3133/sir20265019.","productDescription":"Report: ix, 19 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-167114","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":505034,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P143FH5Q","text":"USGS Data Release","linkHelpText":"Mercury concentrations in fish and macroinvertebrates from the Duck Valley Reservation and nearby waters, southwestern Idaho and northern Nevada, 2007–2024"},{"id":505033,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5019/images"},{"id":505025,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5019/coverthb2.jpg"},{"id":505030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5019/sir20265019.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5019 PDF"},{"id":505031,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265019/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5019 HTML"},{"id":505032,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5019/sir20265019.XML","description":"SIR 2026-5019 XML"}],"country":"United States","state":"Idaho, Nevada","otherGeospatial":"Duck Valley Reservation reservoirs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116,\n 42.15\n ],\n [\n -116.35,\n 42.15\n ],\n [\n -116.35,\n 41.8\n ],\n [\n -116,\n 41.8\n ],\n [\n -116,\n 42.15\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd.
Boise, Idaho 83702-4520
Flood-frequency analysis is based on records of annual maximum instantaneous flows observed at long-term streamgages with 10 years or more of operation. Since the last flood-frequency analysis in Nebraska, an additional 30 years of annual peak-flow data have become available, and new flood-frequency analysis techniques have been developed. Moreover, the Elkhorn River Basin in north-central and eastern Nebraska has experienced two of the three highest magnitude floods on record in 2010 and 2019. The U.S. Geological Survey, in cooperation with the Nebraska Department of Transportation, analyzed flow frequency at streamgages in the Elkhorn River Basin in Nebraska.
Flow data from the U.S. Geological Survey and the Nebraska Department of Water, Energy, and Environment annual hydrographic reports were utilized to analyze peak flows. The Peak flow FreQuency (PeakFQ) software was used to perform a flood-frequency and nonstationarity analysis on the selected streamgages in the Elkhorn River Basin in Nebraska. Results of the peak-flow nonstationarity analysis indicate that, of the 23 streamgages analyzed for peak-flow frequency, 4 showed trends that were likely increasing for annual peak flows, whereas 3 indicated trends that were somewhat likely to be increasing. For 11 streamgages, the trend was categorized as about as likely as not, meaning there is less than a 70-percent chance of the trend being either upward or downward. Additionally, 2 streamgages exhibited trends that were somewhat likely to be decreasing, and 3 streamgages showed trends that were likely decreasing.
Low-flow streamflows and nonstationarity in the Elkhorn River Basin were analyzed for low flow periods representing the 1-day, 7-day, and 30-day flows at 21 streamgages using the Hydrologic Toolbox software. Spatially, the nonstationarity analysis results indicated likely increasing or somewhat increasing trend likelihoods for the 1-day, 7-day, and 30-day low flows for many of the Elkhorn streamgages downstream from the Elkhorn River at Ewing, Nebr., streamgage (U.S. Geological Survey station 06797500) and on eastern tributaries during the period of record.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265004","collaboration":"Prepared in cooperation with Nebraska Department of Transportation","usgsCitation":"Strauch, K.R., and Dietsch, B.J., 2026, Magnitude and frequency of peak and low flows in the Elkhorn River Basin, Nebraska, 1881–2022: U.S. Geological Survey Scientific Investigations Report 2026–5004, 17 p., https://doi.org/10.3133/sir20265004.","productDescription":"Report: iv, 17 p.; 2 Appendix Tables; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-156799","costCenters":[{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":505177,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119486.htm","linkFileType":{"id":5,"text":"html"}},{"id":504752,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5004/images/"},{"id":504751,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SLKHD1","text":"USGS data release","linkHelpText":"Data in support of flow frequency report—Magnitude and frequency of peak and low flows in the Elkhorn River Basin, Nebraska, 1881–2022"},{"id":504750,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2026/5004/downloads/","text":"Tables 1.1 and 1.2","linkFileType":{"id":7,"text":"csv"}},{"id":504749,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265004/full","description":"SIR 2026–5004 HTML"},{"id":504748,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5004/sir20265004.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026–5004 XML"},{"id":504747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5004/sir20265004.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026–5004 PDF"},{"id":504746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5004/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Elkhorn River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100,\n 43\n ],\n [\n -96,\n 43\n ],\n [\n -96,\n 41\n ],\n [\n -100,\n 41\n ],\n [\n -100,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Plains Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
This study compared the efficacy of a benthic mat alone with carbon dioxide infusion under a mat for killing Dreissena polymorpha (Pallas, 1771) (zebra mussel). Three sites were selected in Loon Lake, Sleeping Bear Dunes National Lakeshore, Benzie County, Michigan, for replication of reference, benthic mat, and carbon dioxide mat treatments. Within a site, three 4-meter (m) x 4-m plots were delineated for each treatment and a reference. Pretreatment samples were collected to estimate zebra mussel density and macroinvertebrate community composition in reference plots. Zebra mussels (about 360) from outside of the treatment plots were caged and placed in the plots before treatment. Benthic mats (4.25 m x 4.25 m; polyethylene with a vinyl coating) were anchored on the lake bottom with sandbags and weights. Carbon dioxide was infused under a mat of the same material to a maximum of 200 milligrams per liter (mg/L; pH=6.13) every 2–4 hours, for about 12 hours. Benthic and carbon dioxide mats were deployed for 5 days. One day after mat removal, we assessed mortality of resident and sentinel caged zebra mussels and macroinvertebrate community abundance and diversity in each plot. Average pH (as a proxy for carbon dioxide) under the carbon dioxide mats was between 6.38 and 6.80, equivalent to 170.5 and 103.0 mg/L carbon dioxide, respectively. In the posttreatment survey, few zebra mussels were observed in the benthic mat and carbon dioxide treatment plots compared to the reference plots; survival was lowest in the carbon dioxide plots. Mortality of sentinel caged mussels was greater than 80 percent in carbon dioxide treatments compared to mean mortalities of 20.6 percent and 12.7 percent in the benthic mat and reference plots, respectively. Macroinvertebrate community total abundance was lower in both mat treatments compared to reference plots, but diversity was comparable among all treatments. Our study demonstrated that carbon dioxide treatment near 200 mg/L could produce greater than 80-percent mortality of zebra mussels within 5 days. Refinement of the carbon dioxide mat and delivery system could increase spatial coverage of the treatment and broaden its use to other habitats.
","largerWorkTitle":"USGS Open-File Report","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261019","collaboration":"Prepared in cooperation with the National Park Service, U.S. Environmental Protection Agency, and Invasive Mussel Collaborative","usgsCitation":"Waller, D.L., Erickson, R.A., Wise, J.K., Meulemans, M.J., Morris, B.E.C., Severson, T.J., and Barbour, M.T., 2026, Open water control of invasive mussels using benthic mats—Part 1, short-term infusion of carbon dioxide under a mat: U.S. Geological Survey Open-File Report 2026–1019, 22 p., https://doi.org/10.3133/ofr20261019.","productDescription":"Report: viii; 22 p.; Data Release; Software Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-178968","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":504978,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1019/ofr20261019.pdf","text":"Report","size":"2.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1019"},{"id":504976,"rank":5,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P13JUBYH","text":"USGS software release","linkHelpText":"- Analysis of open water control of invasive mussels using benthic mats. Part 1—Short-term infusion of carbon dioxide under a mat"},{"id":504971,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1019/images"},{"id":505124,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13NC3TU","text":"USGS data release","linkHelpText":"Evaluation of benthic barrier layers/tarps for open water control of invasive mussels in 2024 in Loon Lake, Benzie Co., Michigan, USA"},{"id":504969,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1019/ofr20261019.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1019 XML"},{"id":504966,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1019/coverthb.jpg"},{"id":504968,"rank":2,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261019/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1019 HTML"}],"country":"United States","state":"Michigan","county":"Benzie County","otherGeospatial":"Loon Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.1304036738387,\n 44.70904195515499\n ],\n [\n -86.12565959497928,\n 44.70904195515499\n ],\n [\n -86.12565959497928,\n 44.70471858100336\n ],\n [\n -86.1304036738387,\n 44.70471858100336\n ],\n [\n -86.1304036738387,\n 44.70904195515499\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Quantifying and projecting the downstream benefits of water stored in lakes and wetlands (SWstorage) requires watershed hydrologic models, which often parameterize surface water storage in topographic depressions using static digital elevation model (DEM) data. Calibration and validation of modeled SWstorage dynamics using external data sets is uncommon, particularly across major river basins, with model calibration typically focused on observed discharge. Here, we develop and assess a novel remote sensing-based (RS) SWstorage data set (Sentinel-1 and Sentinel-2) for verifying simulated SWstorage estimates from a Soil and Water Assessment Tool (SWAT) model of the Upper Mississippi River Basin (UMRB; ∼440,000 km2). Our results suggest that static DEM-based parameterization as well as model calibration based solely on discharge do not adequately capture spatial and temporal SWstorage dynamics in the UMRB. Mean SWstorage as estimated by SWAT was 74% ± 122% (mean ± standard deviation) higher than RS SWstorage, where SWstorage in SWAT was underestimated in wetland-rich subbasins and overestimated in agricultural, tile-drained subbasins. Time series of SWAT SWstorage and RS SWstorage were positively correlated in only 38.8% of subbasins. As RS SWstorage is also vulnerable to error, storage estimates were compared to bathymetric data in select small wetlands. While uncertainty remains in the conversion from extent to storage for RS SWstorage, the method and data set presented here are a promising option for improved parameterization and calibration of SWstorage processes in SWAT and other process-based hydrologic models. Further consideration of these storage processes can potentially improve the accuracy of simulated streamflow in wetland-rich model domains.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040206","usgsCitation":"Dolan, W., Vanderhoof, M.K., Christensen, J.R., Golden, H.E., Lane, C.R., Rajib, A., Keenan, W., Zheng, Q., and Khare, A., 2026, Remotely sensed surface water storage shows distinct patterns from SWAT-simulated data: Water Resources Research, v. 62, no. 6, e2025WR040206, 22 p., https://doi.org/10.1029/2025WR040206.","productDescription":"e2025WR040206, 22 p.","ipdsId":"IP-175550","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":505244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, South Dakota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.9088108,\n 44.6284877\n ],\n [\n -86.7385234,\n 41.587393\n ],\n [\n -89.9700712,\n 38.3215153\n ],\n [\n -95.2047886,\n 42.7793981\n ],\n [\n -97.7322805,\n 45.1743925\n ],\n [\n -95.1189109,\n 47.5157703\n ],\n [\n -93.9118523,\n 46.800896\n ],\n [\n -89.1539577,\n 44.8972483\n ],\n [\n -91.2125251,\n 43.1136036\n ],\n [\n -91.4028634,\n 43.1633275\n ],\n [\n -91.4813002,\n 43.3107314\n ],\n [\n -95.9088108,\n 44.6284877\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"6","noUsgsAuthors":false,"publicationDate":"2026-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Dolan, Wayana 0000-0001-8405-4302","orcid":"https://orcid.org/0000-0001-8405-4302","contributorId":354442,"corporation":false,"usgs":true,"family":"Dolan","given":"Wayana","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":962658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":962659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Jay R. 0000-0003-4961-6132","orcid":"https://orcid.org/0000-0003-4961-6132","contributorId":372019,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","middleInitial":"R.","affiliations":[{"id":88243,"text":"EPA Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":962660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Golden, Heather E.","contributorId":364787,"corporation":false,"usgs":false,"family":"Golden","given":"Heather","middleInitial":"E.","affiliations":[{"id":13226,"text":"U.S. Environmental Protection Agency, Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":962661,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, Charles R. 0000-0003-0066-8919","orcid":"https://orcid.org/0000-0003-0066-8919","contributorId":372020,"corporation":false,"usgs":false,"family":"Lane","given":"Charles","middleInitial":"R.","affiliations":[{"id":88243,"text":"EPA Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":962662,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rajib, Adnan","contributorId":365158,"corporation":false,"usgs":false,"family":"Rajib","given":"Adnan","affiliations":[{"id":50034,"text":"University of Texas, Arlington","active":true,"usgs":false}],"preferred":false,"id":962663,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keenan, William","contributorId":365156,"corporation":false,"usgs":false,"family":"Keenan","given":"William","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":962664,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zheng, Qianjin 0000-0002-9535-472X","orcid":"https://orcid.org/0000-0002-9535-472X","contributorId":372022,"corporation":false,"usgs":false,"family":"Zheng","given":"Qianjin","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":962665,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Khare, Arushi","contributorId":366982,"corporation":false,"usgs":false,"family":"Khare","given":"Arushi","affiliations":[{"id":50034,"text":"University of Texas, Arlington","active":true,"usgs":false}],"preferred":false,"id":962666,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70276562,"text":"70276562 - 2026 - PFAS remediation in a bioelectrochemical system inoculated with the west branch consortium (WBC-2)","interactions":[],"lastModifiedDate":"2026-06-09T15:12:13.615374","indexId":"70276562","displayToPublicDate":"2026-06-08T08:07:57","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":24805,"text":"Journal of Water Process Engineering","active":true,"publicationSubtype":{"id":10}},"title":"PFAS remediation in a bioelectrochemical system inoculated with the west branch consortium (WBC-2)","docAbstract":"Groundwater contamination by per- and polyfluoroalkyl substances (PFAS) poses a persistent environmental and public health concern. This study evaluates a two-chambered bioelectrochemical system (BES) inoculated with the West Branch Consortium (WBC-2) for PFAS remediation. Under an applied cathodic potential of −450 mV (versus Ag/AgCl), the BES with active WBC-2 achieved >99.0% perfluorooctanesulfonic acid (PFOS) removal within 21 days in deionized water with culture medium and > 98.9% removal of PFOS, perfluorooctanoic acid (PFOA), perfluorohexanoic acid (PFHxA), and perfluorohexanesulfonic acid (PFHxS) in contaminated groundwater after 102 days. Intermediate formation (e.g., PFOA, 6:2 fluorotelomer sulfonate (6:2 FTS), perfluoropropionic acid (PFPrA), perfluorobutanoic acid (PFBA)) and background-corrected fluoride release were consistent with PFOS transformation under anaerobic reducing conditions potentially involving defluorination. Following repeated PFOS spikes (100 μg/L on Days 0, 50, and 399), PFOA, PFPrA, and PFBA accumulated over 664 days. Despite being the dominant accumulated compound, PFOA accounted for <1.8% of the total spiked PFOS mass. Minimal PFOS transformation occurred in controls without active WBC-2, highlighting the importance of microbial metabolism. Biofilm analysis revealed dense colonization of rod-shaped bacteria on carbon fiber brushes. Enrichment of Bacillus, Agrobacterium, and other low-abundance taxa suggests selective adaptation to BES and PFAS conditions. These findings highlight BES driven by electrochemically stimulated microbial activity as a promising strategy for PFAS remediation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jwpe.2026.110325","usgsCitation":"Yang, H., Lorah, M.M., Bender, K.S., Xia, C., Sun, J., and Liu, J., 2026, PFAS remediation in a bioelectrochemical system inoculated with the west branch consortium (WBC-2): Journal of Water Process Engineering, v. 89, 110325 , 14 p., https://doi.org/10.1016/j.jwpe.2026.110325.","productDescription":"110325 , 14 p.","ipdsId":"IP-179739","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":505233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yang, Haoran 0009-0008-7388-9214","orcid":"https://orcid.org/0009-0008-7388-9214","contributorId":372037,"corporation":false,"usgs":false,"family":"Yang","given":"Haoran","affiliations":[{"id":85556,"text":"Southern Illinois University Carbondale","active":true,"usgs":false}],"preferred":false,"id":962674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":216751,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bender, Kelly S. 0000-0002-0025-2166","orcid":"https://orcid.org/0000-0002-0025-2166","contributorId":372039,"corporation":false,"usgs":false,"family":"Bender","given":"Kelly","middleInitial":"S.","affiliations":[{"id":85556,"text":"Southern Illinois University Carbondale","active":true,"usgs":false}],"preferred":false,"id":962676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xia, Chunjie 0000-0002-2497-1907","orcid":"https://orcid.org/0000-0002-2497-1907","contributorId":372040,"corporation":false,"usgs":false,"family":"Xia","given":"Chunjie","affiliations":[{"id":15309,"text":"University of Maryland Baltimore County","active":true,"usgs":false}],"preferred":false,"id":962677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Jiasi 0000-0003-4282-2988","orcid":"https://orcid.org/0000-0003-4282-2988","contributorId":372041,"corporation":false,"usgs":false,"family":"Sun","given":"Jiasi","affiliations":[{"id":35028,"text":"Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":962678,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Jia","contributorId":194205,"corporation":false,"usgs":false,"family":"Liu","given":"Jia","affiliations":[{"id":26877,"text":"Southern Illinois University, Carbondale, IL","active":true,"usgs":false}],"preferred":false,"id":962679,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70276356,"text":"pp1890R - 2026 - High-resolution magnetic survey using an unoccupied aerial vehicle to constrain buried lava flow geometry, volume, and eruptive history of Little Cones, Crater Flat, Nevada","interactions":[{"subject":{"id":70276356,"text":"pp1890R - 2026 - High-resolution magnetic survey using an unoccupied aerial vehicle to constrain buried lava flow geometry, volume, and eruptive history of Little Cones, Crater Flat, Nevada","indexId":"pp1890R","publicationYear":"2026","noYear":false,"chapter":"R","displayTitle":"High-Resolution Magnetic Survey Using an Unoccupied Aerial Vehicle to Constrain Buried Lava Flow Geometry, Volume, and Eruptive History of Little Cones, Crater Flat, Nevada","title":"High-resolution magnetic survey using an unoccupied aerial vehicle to constrain buried lava flow geometry, volume, and eruptive history of Little Cones, Crater Flat, Nevada"},"predicate":"IS_PART_OF","object":{"id":70259456,"text":"pp1890 - 2024 - Distributed volcanism—Characteristics, processes, and hazards","indexId":"pp1890","publicationYear":"2024","noYear":false,"title":"Distributed volcanism—Characteristics, processes, and hazards"},"id":1}],"isPartOf":{"id":70259456,"text":"pp1890 - 2024 - Distributed volcanism—Characteristics, processes, and hazards","indexId":"pp1890","publicationYear":"2024","noYear":false,"title":"Distributed volcanism—Characteristics, processes, and hazards"},"lastModifiedDate":"2026-06-08T17:27:26.618433","indexId":"pp1890R","displayToPublicDate":"2026-06-05T14:42:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1890","chapter":"R","displayTitle":"High-Resolution Magnetic Survey Using an Unoccupied Aerial Vehicle to Constrain Buried Lava Flow Geometry, Volume, and Eruptive History of Little Cones, Crater Flat, Nevada","title":"High-resolution magnetic survey using an unoccupied aerial vehicle to constrain buried lava flow geometry, volume, and eruptive history of Little Cones, Crater Flat, Nevada","docAbstract":"Magnetic surveys are an important tool used to augment geologic mapping in distributed volcanic fields. Using magnetic anomalies, it is possible to model the geometry of shallowly buried volcanic features, such as conduits, sills, and lava flows. This subsurface mapping is important for understanding eruption dynamics and emplacement of lava flows, and it sometimes reveals buried volcanoes no longer visible at the surface. These data are critical to better interpret the numbers, styles, and magnitudes of eruptions in distributed volcanic fields and their associated volcanic hazards. New advances in unoccupied aerial vehicles (UAVs) offer an attractive middle range of resolution and aerial coverage between ground-based magnetic surveys and aeromagnetic surveys.
Here, we present the results of a UAV fluxgate magnetic survey of the Little Cones, Nevada, scoria cones, which have been the target of previous ground and aeromagnetic surveys. The magnetic anomalies at Little Cones are of interest because the surrounding alluvium conceals lava flows that erupted from Little Cones, making it very difficult to understand the volume and morphology of lava flows from geologic mapping alone. Nonlinear inversion of UAV-collected magnetic data were used to model the thickness and morphology of buried Little Cones’ lava flows with higher precision than achieved previously. The sequence of events and calculated flow characteristics are then interpreted. The total volume of Little Cones, including concealed lava flows, is approximately 0.016 cubic kilometer, and the initial sheet flow erupted in less than 24 hours. The findings presented herein demonstrate that UAV-based magnetic surveys are a reliable method of data collection and an efficient alternative to other survey methods, facilitating development of a three-dimensional perspective of distributed volcanic fields.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1890R","usgsCitation":"Van Alphen, R., Rodgers, M., Malservisi, R., Connor, C.B., Bakowski, R., and Berkey, T., 2026, High-resolution magnetic survey using an unoccupied aerial vehicle to constrain buried lava flow geometry, volume, and eruptive history of\nLittle Cones, Crater Flat, Nevada, chap. R of Poland, M.P., Ort, M.H., Stovall, W.K., Vaughan, R.G., Connor, C.B., and Rumpf, M.E., eds., Distributed volcanism—Characteristics, processes, and hazards: U.S. Geological Survey\nProfessional Paper 1890, 28 p., https://doi.org/10.3133/pp1890R.","productDescription":"Report: vii, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-156146","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":505174,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119484.htm","linkFileType":{"id":5,"text":"html"}},{"id":504935,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.17632/zdcsk3rz9z.1","text":"Data release","linkHelpText":"Data and codes utilized for the study of the lava flow of Little Cones, Nevada, USA, using UAV magnetic data (ver. 1)"},{"id":504931,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1890/r/pp1890R.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Professional Paper 1890-R PDF"},{"id":504930,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1890/r/coverthb.jpg"},{"id":504933,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/pp/1890/r/pp1890R.XML","linkFileType":{"id":8,"text":"xml"},"description":"Professional Paper 1890-R XML"},{"id":504932,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/pp1890R/full","linkFileType":{"id":5,"text":"html"},"description":"Professional Paper 1890-R HTML"},{"id":504934,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/pp/1890/r/images"}],"country":"United States","state":"Nevada","otherGeospatial":"Crater Flat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.663,\n 36.92\n ],\n [\n -116.44,\n 36.92\n ],\n [\n -116.44,\n 36.684\n ],\n [\n -116.663,\n 36.684\n ],\n [\n -116.663,\n 36.92\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Volcano Science Center
U.S. Geological Survey
1300 SE Cardinal Court Bldg. 10
Vancouver, WA 98683
Wildfires abruptly change landscapes by altering soil properties and vegetation cover. These changes are thought to reduce soil infiltration capacity, making landscapes susceptible to runoff and erosion. However, post-fire soil response is complex and likely varies across locations and time.
Here, we aim to understand regional post-fire soil response and recovery by tracking changes across different northern California (USA) lithology and vegetation types.
We conducted repeat in situ soil infiltration tests for 3 years post-fire at 31 burned and 10 unburned sites spanning the 2021 Dixie, 2020 LNU Lightning Complex, 2020 Walbridge and 2020 Glass fires.
Our two main findings are: (1) burned chaparral soils have increased hydraulic conductivity compared with unburned sites, and (2) infiltration rates return to pre-fire conditions within 3 years across most lithologies and vegetations.
Recovery might be generalizable by vegetation and lithology but differ regionally, making it important to identify meaningful hydrologic response units (HRUs). Multi-year studies with paired burned and unburned measurements can constrain the recovery timeline and provide information missed by observations solely of burned soils.
Understanding where, and for how long, soil remains susceptible to runoff and erosion can help prioritize areas and time periods most in need of mitigation.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF25141","usgsCitation":"Cerovski-Darriau, C., Perkins, K., Creamer, C., Prancevic, J.P., and Stock, J.D., 2026, Post-fire soil hydrologic response and recovery in northern California (USA): International Journal of Wildland Fire, v. 35, no. 6, WF25141, 18 p., https://doi.org/10.1071/WF25141.","productDescription":"WF25141, 18 p.","ipdsId":"IP-178685","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":505149,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"northern California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.25,\n 39\n ],\n [\n -122,\n 39\n ],\n [\n -122,\n 38.25\n ],\n [\n -123.25,\n 38.25\n ],\n [\n -123.25,\n 39\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.75,\n 40.5\n ],\n [\n -120.25,\n 40.5\n ],\n [\n -120.25,\n 39.75\n ],\n [\n -121.75,\n 39.75\n ],\n [\n -121.75,\n 40.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"6","noUsgsAuthors":false,"publicationDate":"2026-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cerovski-Darriau, Corina 0000-0002-0543-0902","orcid":"https://orcid.org/0000-0002-0543-0902","contributorId":221159,"corporation":false,"usgs":true,"family":"Cerovski-Darriau","given":"Corina","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":962505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":962506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":962507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prancevic, Jeff P. 0000-0003-1890-7551","orcid":"https://orcid.org/0000-0003-1890-7551","contributorId":371877,"corporation":false,"usgs":false,"family":"Prancevic","given":"Jeff","middleInitial":"P.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":962508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stock, Jonathan D. 0000-0001-8565-3577","orcid":"https://orcid.org/0000-0001-8565-3577","contributorId":371878,"corporation":false,"usgs":false,"family":"Stock","given":"Jonathan","middleInitial":"D.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":962509,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276446,"text":"70276446 - 2026 - Global pegmatite-hosted lithium, cesium, and rubidium resources: A dataset for grade and tonnage modeling","interactions":[],"lastModifiedDate":"2026-06-05T13:59:55.653198","indexId":"70276446","displayToPublicDate":"2026-06-04T08:57:22","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Global pegmatite-hosted lithium, cesium, and rubidium resources: A dataset for grade and tonnage modeling","docAbstract":"Quantitative mineral resource assessments of potential undiscovered deposits can inform future mineral supply scenarios, but their accuracy is conditional on building robust grade and tonnage models of known deposits. This study presents an up-to-date global compilation and analysis of recently discovered and original, in-situ pegmatite-hosted Li, Cs, and Rb resources prior to historic production. Our analysis yields a median tonnage of 21.2 million tons (Mt) and grade of 1.12% Li2O, respectively, for global Li pegmatite deposits (n = 73). The grades and tonnages of Li pegmatite resources vary depending on the age of the bedrock host domain, pegmatite crystallization age, and primary ore mineralogy. Lithium pegmatite resources hosted in Archean to transitional Archean-Paleoproterozoic domains have the largest median tonnage (29.8 Mt; n = 38), and those hosted in Paleoproterozoic to Mesoproterozoic domains have smaller median tonnages (6.5 Mt; n = 16). Cesium deposits where pollucite is the primary ore mineral have a bimodal grade distribution, with modes of 2.40 and 0.035 wt% Cs2O for high- and low-grade deposits, respectively, while Rb deposits are more unimodal with a median grade of 0.247 wt% Rb2O. Pegmatite-hosted Cs and Rb resources have median tonnages of 7.6 and 6.3 Mt, respectively. Covariation between ore mineralogy and the degree of crustal enrichment in pegmatite-hosted deposits is diagnostic of petrogenetic differences, including melt source characteristics, magma evolution, or variable degrees of volatile solubility. The Li pegmatite compilation is suitable for fitting robust numerical models to support quantitative assessments. More well-defined Rb and Cs pegmatite resources are required for quantitative assessments, but these data provide useful information about original in-place resources for framing supply discussions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2026.107360","usgsCitation":"Rosera, J.M., McCaffrey, D.M., and Wintzer, N.E., 2026, Global pegmatite-hosted lithium, cesium, and rubidium resources: A dataset for grade and tonnage modeling: Ore Geology Reviews, v. 194, 107360, 16 p., https://doi.org/10.1016/j.oregeorev.2026.107360.","productDescription":"107360, 16 p.","ipdsId":"IP-184418","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":505087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"194","noUsgsAuthors":false,"publicationDate":"2026-06-04","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":962405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCaffrey, Dalton M. 0000-0002-2539-4865","orcid":"https://orcid.org/0000-0002-2539-4865","contributorId":298840,"corporation":false,"usgs":true,"family":"McCaffrey","given":"Dalton","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":962406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wintzer, Niki E. 0000-0003-3085-435X nwintzer@usgs.gov","orcid":"https://orcid.org/0000-0003-3085-435X","contributorId":5297,"corporation":false,"usgs":true,"family":"Wintzer","given":"Niki","email":"nwintzer@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":962407,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276398,"text":"fs20263002 - 2026 - Arizona Water Science Center activities at Lees Ferry, Arizona","interactions":[],"lastModifiedDate":"2026-06-08T17:29:10.55739","indexId":"fs20263002","displayToPublicDate":"2026-06-03T14:15:00","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":"2026-3002","displayTitle":"Arizona Water Science Center Activities at Lees Ferry, Arizona","title":"Arizona Water Science Center activities at Lees Ferry, Arizona","docAbstract":"In 1921, the U.S. Geological Survey (USGS) established a streamgage on the Colorado River at Lees Ferry, Arizona, to monitor the river’s flow and level as it enters Grand Canyon. The following year, the seven States encompassing the Colorado River Basin (Arizona, California, Colorado, Nevada, New Mexico, Utah, and Wyoming) negotiated the 1922 Colorado River Compact to regulate distribution of the river’s waters between them. The compact divided the basin into two regions—the Upper Basin and the Lower Basin—and established the dividing point between them about one mile downstream from Lees Ferry, just below the confluence of the Colorado and Paria Rivers.
The Colorado River at Lees Ferry streamgage (USGS station 09380000) is one of the most important streamgages in the United States because it is used to measure how much water passes from the Upper Basin to the Lower Basin through Glen Canyon Dam. The dam, constructed between 1956 and 1966, generates hydropower and stores water in Lake Powell reservoir, which is used to provide Upper and Lower Basin states with the water allotted to them by the compact. Lower Basin states depend on releases from the dam to receive their allotments. The Lees Ferry streamgage, located less than 16 miles downstream from Glen Canyon Dam, produces publicly available, real-time water data that allows the Colorado River’s streamflow below the dam to be monitored.
Most years, the Colorado River runs dry before reaching its historical terminus at the Gulf of California in Mexico, so measuring and monitoring the river at Lees Ferry is critical for the Lower Basin ecosystems, agricultural resources, and municipal industries that rely on the river’s every drop. Additionally, Grand Canyon river guides and recreationalists depend on water level data from the Lees Ferry streamgage to determine when to run rapids and camp on sandbars. Streamflow and water-quality data collected at Lees Ferry are also important for monitoring the health of the Colorado River’s aquatic life because some species, including fish and macroinvertebrates, require certain water conditions to survive, reproduce, and spawn.
The Arizona Water Science Center is responsible for maintaining and collecting water data from the Lees Ferry streamgage. The Arizona Water Science Center is a branch of the USGS dedicated to providing high quality, impartial water data to resource managers and the public for their use in understanding and managing critical water resources in Arizona and the Southwest.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20263002","usgsCitation":"Cooney, K., 2026, Arizona Water Science Center activities at Lees Ferry, Arizona: U.S. Geological Survey Fact Sheet 2026–3002, 4 p., https://doi.org/10.3133/fs20263002.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-168012","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":505175,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119483.htm","linkFileType":{"id":5,"text":"html"}},{"id":504982,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2026/3002/fs20263002.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2026–3002 XML"},{"id":504981,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20263002/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2026–3002 HTML"},{"id":504983,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2026/3002/images"},{"id":504980,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2026/3002/fs20263002.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2026–3002 PDF"},{"id":504979,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2026/3002/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Lees Ferry","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.37564572779584,\n 36.99849467623304\n ],\n [\n -111.65910481382933,\n 36.99849467623304\n ],\n [\n -111.65910481382933,\n 36.827943533328465\n ],\n [\n -111.37564572779584,\n 36.827943533328465\n ],\n [\n -111.37564572779584,\n 36.99849467623304\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue, Suite 221
Tucson, AZ 85719
The U.S. Geological Survey monitors a suite of intertidal black abalone (Haliotis cracherodii) sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential effect of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, typically annually or biennially. Monitoring resumed in 2001 and has been completed annually thereafter. Since 2018, the work has been carried out by the U.S. Geological Survey Western Ecological Research Center. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome (Candidatus Xenohaliotis californiensis), was first observed on San Nicolas Island in 1992 and over the next few years, withering syndrome reduced the black abalone population on San Nicolas Island by more than 99 percent. In 2009, the black abalone subsequently was listed as endangered under the Endangered Species Act.
The subject of this report is the 2023 survey of the sites and the status of the measured population in comparison to long-term patterns (based on data collected since 1981) at San Nicolas Island. Between the years 2000 and 2023, the total monitored black abalone population at the island has grown from roughly 200 to more than 2,500 abalone following disease-related decline. Since it was first consistently measured in 2005, the average distance between adjacent black abalone has decreased substantially from approximately 50 centimeters to less than 15 centimeters, indicating that abalone are sufficiently close together at several of the sites to reproduce successfully. The total abalone count in 2023 was 2,570, which was 19.2 percent higher than in 2022 and the highest count since 1993. All nine sites had higher counts in 2023 than in the previous year. Over 25 percent of the black abalone counted in 2023 were classified as recruits, defined as having a shell length of 3 centimeters or less.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261015","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2026, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2023 annual report: U.S. Geological Survey Open- File Report 2026–1015, 39 p., https://doi.org/10.3133/ofr20261015.","productDescription":"viii, 39 p","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166956","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":504926,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1015/ofr20261015.pdf","text":"Report","size":"10.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1015 PDF"},{"id":504929,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1015/images"},{"id":504928,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1015/ofr20261015.XML","description":"OFR 2026-1015 XML"},{"id":504927,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261015/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1015 HTML"},{"id":504925,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1015/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base Ventura County, San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.58614016989262,\n 33.29639489260616\n ],\n [\n -119.41438488619465,\n 33.29639489260616\n ],\n [\n -119.41438488619465,\n 33.201948055912865\n ],\n [\n -119.58614016989262,\n 33.201948055912865\n ],\n [\n -119.58614016989262,\n 33.29639489260616\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The 2023 monitoring of black abalone at San Nicolas Island shows strong signs of population recovery following the severe declines caused by withering syndrome in the 1990s. The island-wide summed count from the study sites reached 2,570 individuals—the highest since 1993—and increased nearly 20 percent from 2022, with higher numbers recorded at all nine study sites. Recruitment was particularly strong, with over a quarter of individuals classified as young abalone, and densities and spacing between individuals indicate increasing likelihood of successful reproduction. Although one historically important transect at Site 8 continues to show reduced numbers of larger adults despite high recruitment, the overall population trend across the island remains positive. Continued monitoring is important to track long-term recovery, habitat conditions, and potential risks.
","publicationDate":"2026-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":962194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":962195,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70276287,"text":"sir20255018B - 2026 - Summaries of goals, actions, and information needs by management entity","interactions":[],"lastModifiedDate":"2026-06-03T16:05:30.771038","indexId":"sir20255018B","displayToPublicDate":"2026-06-02T16:30:00","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":"2025-5018","chapter":"B","displayTitle":"Summaries of Goals, Actions, and Information Needs by Management Entity","title":"Summaries of goals, actions, and information needs by management entity","docAbstract":"The grasslands in the North Central region are managed by a diverse group of Federal, State, and Tribal agencies; nongovernmental organizations; partnerships; and private landowners. This chapter highlights these various grassland management entities, provides background information on their mission and organizational structure, and describes some of their key grassland management activities, including the way in which each entity engages private landowners in grassland management. Each section also describes emerging challenges and opportunities and high-level information needs. The review and synthesis of grassland management-related documents identified specific information needs, which are listed in an appendix to provide additional detail for anyone looking to collaborate with grassland management entities on shared interests in grassland management or research.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255018B","collaboration":"Prepared in cooperation with the University of Colorado Boulder","programNote":"Climate Adaptation Science Centers","usgsCitation":"Miller Hesed, C.D., and Yocum, H.M., eds., 2026, Summaries of goals, actions, and information needs by management entity, chap. B of Grassland management priorities for the North Central region: U.S. Geological Survey Scientific Investigations Report 2025–5018–B, 151 p., https://doi.org/10.3133/sir20255018B.","productDescription":"Report: xviii, 151 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-154862","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":504886,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20255018A","text":"SIR 2025-5018-A","linkHelpText":"Background, Methods, Goals, Challenges, Opportunities, and Information Needs"},{"id":504714,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5018/B/coverthb.jpg"},{"id":504715,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5018/B/sir20255018-B.pdf","text":"Report","size":"61.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5018-B"},{"id":504716,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PCQHA2","text":"USGS data release","description":"SIR 2025-5018-B data release","linkHelpText":"Broadly Shared Information Needs Among Grassland Managers in the North Central Region"}],"contact":"Regional Administrator, North Central Climate Adaptation Science Center
U.S. Geological Survey
University of Colorado - Boulder
Sustainability, Energy and Environment Community
4001 Discovery Dr., Suite 348
Boulder, CO 80303
Changing rainfall patterns and intensifying rainfall extremes affect urban infrastructure and can increase flash-flood risk. Understanding how climate change has altered rainfall can support state and local agencies as they adapt and build resiliency. In this study, rainfall data from 23 weather stations in Florida were used to examine temporal and spatial trends over the period 1990–2022. Subdaily to daily rainfall events of durations 1, 2, 3, 6, 12, and 24 h were examined. A variety of statistical methods were applied to examine annual and seasonal trends, including quantile regression, extreme value analysis, run theory using the Mann–Kendall test, Sen–Theil slope, and Poisson and negative binomial tests, and threshold exceedance rates using generalized additive models. Using subdaily rainfall data posed challenges, including equipment failures, limited documentation of the quality assurance and control process, and potential measurement interferences. Results indicated that over 1990–2022, there was a decrease in hourly rainfall extremes but an increase at moderate quantiles. Overall, the number of rainfall events increased, particularly at shorter durations, but the mean total rainfall per event decreased. Additionally, the annual number of daily rainfall extremes showed more decreases than increases.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-25-0112.1","usgsCitation":"Haider, S., Irizarry-Ortiz, M.M., Obeysekera, J.T., Maran, A.C., Solaiman, T., and Johnston, B.D., 2026, Trends in subdaily to daily rainfall in Florida, 1990–2022: Journal of Hydrometeorology, v. 27, no. 6, p. 847-865, https://doi.org/10.1175/JHM-D-25-0112.1.","productDescription":"19 p.","startPage":"847","endPage":"865","ipdsId":"IP-175860","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":505091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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We developed a transferable workflow to evaluate geothermal district systems that pair ground heat exchangers with seasonal underground thermal energy storage. Using standardized hourly loads for seven commercial buildings and a uniform cost framework, we simulated ten U.S. cities with a physics-based ground heat exchanger model, subsurface storage simulations, and economic assessment to isolate the roles of climate and hydrogeology. In cooling-dominated cities, underground thermal energy storage supplied the majority of annual cooling, cutting electricity use and summer peaks substantially while achieving levelized costs comparable to or below conventional chiller-boiler plants. In cooler climates, the storage share shrunk, required borefield size and costs rose, and levelized cost of energy increased nearly linearly with declining underground thermal energy storage fraction, indicating storage fraction as the primary economic lever. Sensitivity analysis showed capital risk dominated by borefield drilling and surface heating, ventilation, and air-conditioning and piping, with underground thermal energy storage costs secondary. This workflow provides a transparent foundation for site-specific design and screening of next-generation geothermal district energy systems.
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communities","interactions":[],"lastModifiedDate":"2026-06-01T13:56:29.395433","indexId":"70276343","displayToPublicDate":"2026-05-29T08:51:15","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Co-occurrence of pesticides and pharmaceuticals and personal care products (PPCPs) across Zostera marina (common eelgrass) communities","title":"Co-occurrence of pesticides and pharmaceuticals and personal care products (PPCPs) across Zostera marina (common eelgrass) communities","docAbstract":"Anthropogenic pressures are driving changes in eelgrass communities, which are altering baseline conditions in estuarine environments. Field detections have validated the transport of land-sourced pollutants to aquatic systems; however, studies rarely sample concurrently for pesticides, and pharmaceuticals and personal care products (PPCPs) across environmental compartments. Moreover, studies on contaminant uptake by eelgrass and associated species are even more limited. In collaboration with the Confederated Tribes of the Coos, Lower Umpqua and Siuslaw Indians (CTCLUSI), this study collected samples of water, eelgrass, clams, and sediment at sites of Tribal significance in Southern Oregon to test for organic contaminants (i.e., herbicides and pharmaceuticals). Paired sampling was conducted for analysis by the CTCLUSI in tandem with the United States Geological Survey (USGS) in order for the Tribe to develop analytical standards for future sampling efforts. Ten pesticides and eight pharmaceuticals were detected across the four sites, with the highest number of overall detections (27) at the Florence Marina site. The insecticide bifenthrin was most frequently detected across all media (0.012–1.565 μg/g organic carbon in sediment, 2.7–30 ng/g in organismal tissue) and the anti-diabetic agent metformin was the most detected PPCP in clam tissues (1.33–3.78 ng/g). Pesticides and PPCPs were observed to co-occur in eelgrass habitats, with numerous pesticide detections across media types. These findings demonstrate numerous routes of exposure for estuarine organisms which could be addressed with pharmaceutical disposal strategies or pesticide use restrictions near these habitats.
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The objective of this study was to complete range-wide surveys to locate extant AGS colonies and to quantify the number of AGS observed at each location. From 2021–24, 284 surveys were done in 25 unique (that is, distinct) counties in 8 States in the Eastern United States — Maryland, Michigan, New York, North Carolina, Ohio, Pennsylvania, Virginia, and West Virginia. We found AGS in only two counties: Alleghany County, Virginia, and Greenbrier County, West Virginia. AGS were observed 180 times in these two counties. Our results can inform U.S. Fish and Wildlife decisions about where and how future AGS conservation efforts can be implemented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261017","collaboration":"Maryland Department of Natural Resources; Michigan State University Extension; New Jersey Department of Environmental Protection; New York Natural Heritage Program; North Carolina Department of Natural and Cultural Resources; Ohio Department of Natural Resources; Western Pennsylvania Conservancy; U.S. Fish and Wildlife Service; Virginia Department of Conservation and Recreation; West Virginia Division of Natural Resources","usgsCitation":"Vyas, N.B., Selfridge, J., Cuthrell, D., Somes, R., White, E., Ratcliffe, J., Lynch, J., Hamon, L., Wyza, E., Leppo, B., Woods, P., Tur, A., Drummey, D., Nolan, K., Orcutt, E., Rapp, A., Card, L., Goldner, J., and Olcott, S., 2026, Range-wide relative abundance of the Appalachian grizzled skipper (Pyrgus centaureae wyandot) in the Eastern United States: U.S. Geological Survey Open-File Report 2026–1017, 57 p., 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U.S. Geological Survey
12100 Beech Forest Rd., Ste 4039
Laurel, MD 20708-4039
Prescribed fire is a common approach to reduce fuels and mitigate fire hazards. The accumulation of live and dead fuels following initial treatment means that repeated application of prescribed fire could be used to maintain this benefit. However, the effect of repeated prescribed fires is not well documented in many dry coniferous forests in the western United States. Here, we present observations of changes in live trees and surface fuels following two prescribed fires in dry coniferous forests in national parks of California.
Changes in forest structure and accumulation of surface fuels were similar over time following initial-entry and second-entry fires. An exception was that repeated fires were associated with substantial reductions in stem density. There were smaller changes in live tree basal area and stem biomass.
Our results indicate that following initial-entry fires, subsequent burning maintained reductions in surface fuel loads without major inadvertent losses of live tree basal area and stem biomass, implying the survival of large trees.
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Box 1713, Klamath Falls, OR 97601, USA","active":true,"usgs":false}],"preferred":false,"id":962224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engber, Eamon","contributorId":202777,"corporation":false,"usgs":false,"family":"Engber","given":"Eamon","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":962225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McClure, Emma J. 0009-0007-1285-4977","orcid":"https://orcid.org/0009-0007-1285-4977","contributorId":352134,"corporation":false,"usgs":false,"family":"McClure","given":"Emma J.","affiliations":[{"id":84121,"text":"National Park Service, Redwood National and State Parks","active":true,"usgs":false}],"preferred":false,"id":962226,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caprio, Anthony C.","contributorId":35863,"corporation":false,"usgs":false,"family":"Caprio","given":"Anthony C.","affiliations":[],"preferred":false,"id":962227,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keifer, MaryBeth","contributorId":194887,"corporation":false,"usgs":false,"family":"Keifer","given":"MaryBeth","email":"","affiliations":[],"preferred":false,"id":962228,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276457,"text":"70276457 - 2026 - Future water constraints on United States lithium mining under climate change","interactions":[],"lastModifiedDate":"2026-06-05T13:48:19.979755","indexId":"70276457","displayToPublicDate":"2026-05-28T08:43:26","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Future water constraints on United States lithium mining under climate change","docAbstract":"Lithium is necessary for low-carbon technologies that combat climate change, but lithium extraction is water-intensive. Changes in temperature and precipitation arising from climate change are altering water distribution, which could further strain supplies for new mines and industry, farms, and households. Here we explored how climate change, water use, and mining siting could impact lithium mining in the United States. We analyzed whether there would be sufficient water available to support the single existing and 22 proposed U.S. lithium mines at mid-century under four socioeconomic-climate scenarios and five climate models. Though dependent on socioeconomic-climate scenario, climate model, and lithium deposit type, available water supply in most subbasins would likely be unable to support new mines’ water demands, or even non-mining water demands from other sectors. Water scarcity could hinder the ability of the United States to produce enough lithium to meet domestic demand thereby necessitating higher imports.
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Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":962434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Jennifer B. 0000-0002-2065-5106","orcid":"https://orcid.org/0000-0002-2065-5106","contributorId":371832,"corporation":false,"usgs":false,"family":"Dunn","given":"Jennifer","middleInitial":"B.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":962435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276319,"text":"70276319 - 2026 - Geochemical, mineralogical, and isotopic evidence for multi-stage genesis of the Hicks Dome REE + Y-HFSE-fluorite deposit, Illinois, USA","interactions":[],"lastModifiedDate":"2026-05-28T14:13:31.247592","indexId":"70276319","displayToPublicDate":"2026-05-27T09:02:02","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical, mineralogical, and isotopic evidence for multi-stage genesis of the Hicks Dome REE + Y-HFSE-fluorite deposit, Illinois, USA","docAbstract":"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":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"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}],"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":70276326,"text":"70276326 - 2026 - Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2025","interactions":[],"lastModifiedDate":"2026-05-29T13:52:57.889658","indexId":"70276326","displayToPublicDate":"2026-05-27T08:46:24","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2025","docAbstract":"Fall bottom trawl (fall BT) and lakewide acoustic (AC) surveys are conducted annually to generate indices of pelagic and benthic prey fish densities in Lake Michigan. The fall BT survey has been conducted each fall since 1973 using 12-m trawls at depths ranging from 9 to 110 m at fixed locations distributed across seven transects; this survey estimates densities of seven prey fish species [i.e., Alewife (Alosa pseudoharengus), Bloater (Coregonus hoyi), Rainbow Smelt (Osmerus mordax), Deepwater Sculpin (Myoxocephalus thompsonii), Slimy Sculpin (Cottus cognatus), Round Goby (Neogobius melanostomus), Ninespine Stickleback (Pungitius pungitius)]. The AC survey has been conducted each late summer/early fall since 2004 (except 2020). The 2025 AC survey consisted of 26 transects [470 km total (292 miles)] covering bottom depths ranging from 5 to 259 m and 44 midwater trawl tows at 1.4 to 82.4 m fishing depth; this survey estimates densities of three prey fish species (i.e., Alewife, Bloater, and Rainbow Smelt). The data generated from these surveys are used to estimate various population parameters that are, in turn, used by state and tribal agencies in managing Lake Michigan fish stocks.
For the AC survey, total biomass density of prey fish equaled 9.3 kg/ha, continuing a recent trend of index values above the long-term average of 5.4 kg/ha. For the fall BT, total biomass density of prey fish equaled 3.4 kg/ha, close to values observed since 2014 and well below historic numbers and those observed earlier in the 2000s. Over the period both surveys have been conducted (2004-2025), the total biomass density index had trended downward in the fall BT through the mid-2010s and appears to have stabilized at low values, while the AC survey biomass density index has remained relatively stable over the time series.
Mean biomass of yearling and older (YAO) Alewife was 4.3 kg/ha in the AC survey and 0.45 kg/ha in the fall BT. Since 2014, annual survey results suggest that the catchability of YAO Alewife for the fall BT is substantially lower than the AC survey. The 2025 AC survey YAO Alewife biomass density estimate was 57% higher than the average from 2004-2024. The Alewife population of Lake Michigan appears to be composed mostly of young fish and the proportion of age-4 and older Alewife was ~5% in both surveys. Age-0 Alewife numeric density from the AC survey was 259 fish/ha in 2025, lower than the long-term mean (487 fish/ha). Biomass density of large (≥120 mm) Bloater was 3.5 kg/ha in the AC survey and 1.9 kg/ha in the fall BT. The density of small (<120 mm) Bloater was 540 fish/ha in the AC survey, the second highest value in the time series. Meanwhile, small Bloater density estimated in the fall BT was only 6.1 fish/ha. Biomass density of large Rainbow Smelt (≥90 mm) was 0.69 kg/ha in the AC survey and 0.04 kg/ha in the fall BT survey. Numeric density of small (<90 mm) Rainbow Smelt was 541 fish/ha in the AC survey, the highest value in the time series, and 41 fish/ha in the fall BT. All four prey fish species indexed only by the fall BT had below-average biomass densities. Deepwater Sculpin biomass density was 0.21 kg/ha, which makes 15 of the past 16 years with biomass <1 kg/ha. Slimy Sculpin was estimated to be 0.03 kg/ha, an order of magnitude lower than the long-term average from the fall BT. Round Goby biomass density was 0.44 kg/ha and Ninespine Stickleback density was 0.20 kg/ha, the highest value since 2007.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Tingley, R.W., O’Brien, T.P., Madenjian, C.P., Esselman, P., Dieter, P., Phillips, K., Turschak, B., Hanson, D., and Farha, S.A., 2026, Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2025, 26 p.","productDescription":"26 p.","ipdsId":"IP-189835","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":504865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":504860,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://glfc.org/publication-media-search.php"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.6436767578125,\n 45.69083283645816\n ],\n [\n 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In response to the increased number of earthquakes in this region, rapid and accurate characterization of earthquake sources is necessary to understand the evolution of seismic activity and level of seismic hazard associated with these earthquakes. This study re-evaluates earthquake magnitudes, estimating moment magnitude (MW) for small earthquakes in the Delaware Basin using 1) moment-rate spectra derived from S-wave coda envelopes, and 2) a relative magnitude method that relies exclusively on the ratio of waveform amplitudes between highly correlated waveform pairs. The coda-envelope method produces accurate MW estimates for small earthquakes (M 1.5 – 3) that are consistent with independent, waveform modeled moment magnitudes for events with MW > 3. Using the relative amplitudes method to extend these MW magnitudes to many other events, we successfully provide relative moment magnitude (MW,rel) values for 81% of the Texas Seismological Network catalog in the Delaware Basin region, and 45% of the USGS Induced Seismicity Project’s catalog of events in southeast New Mexico. The adoption and integration of the calibrated MW,rel method with current magnitude estimation methods offers valuable insights into the relationships between local and moment magnitude and will contribute to improved characterization of widespread induced seismicity.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220250246","usgsCitation":"Gable, S., Huang, Y., Shelly, D.R., and Rubinstein, J.L., 2026, Moment magnitude for small earthquakes in the Delaware basin of west Texas and southeast New Mexico, USA: Seismological Research Letters, 13 p., https://doi.org/10.1785/0220250246.","productDescription":"13 p.","ipdsId":"IP-183105","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":505047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220250246","text":"Publisher Index Page"},{"id":504950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"southeast New Mexico, west Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.50900660650426,\n 32.93869833342073\n ],\n [\n -102.78073180819358,\n 32.861136118194196\n ],\n [\n -102.84970324032894,\n 30.88089004482086\n ],\n [\n -106.51434494246497,\n 30.96526183674557\n ],\n [\n -106.50900660650426,\n 32.93869833342073\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Gable, Sydney","contributorId":371633,"corporation":false,"usgs":false,"family":"Gable","given":"Sydney","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":962204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Yihe","contributorId":276214,"corporation":false,"usgs":false,"family":"Huang","given":"Yihe","email":"","affiliations":[{"id":56937,"text":"Univ Michigan","active":true,"usgs":false}],"preferred":false,"id":962205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":962206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":215341,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":962207,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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":70276454,"text":"70276454 - 2026 - Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems","interactions":[],"lastModifiedDate":"2026-06-05T13:55:33.458167","indexId":"70276454","displayToPublicDate":"2026-05-26T08:49:06","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems","docAbstract":"Water is essential for life on Earth, supporting ecosystems, human health, and economic activities. Hydrology relies on observational data, and this paper discusses regional and national datasets for the conterminous United States (CONUS) publicly available as of 2023, focusing on headwaters, defined as first- and second-order streams at 1:24000 scale. It identifies 72 primary and secondary datasets and 11 repositories and argues how better integration and accessibility of hydrological data can improve research. The paper distinguishes between datasets where streamflow was the primary data collection objective and those where it was secondary. This distinction highlights opportunities to consider data from efforts peripheral to hydrology but is still useful for understanding hydrologic conditions. The analysis reveals that out of about 118 000 active and inactive stream observation sites, about 6.6% and 25% are located on first- and second-order streams, respectively. This indicates a substantial data gap for headwater systems, which account for over 77% of stream length in CONUS. Federal agencies manage 72% of hydrologic monitoring sites across all stream orders, but only 34% of these are in headwater systems. Academic institutions operate about 2% of sites, with almost half (48%) in headwater systems, focusing on ecosystem research. State agencies also operate about 2% of sites, primarily on larger systems, with 19% on headwaters. Additionally, 23% of sites are managed by multiple agencies. Spatial patterns further reveal pronounced disparities among physiographic regions. Eastern and coastal provinces show relatively dense monitoring, while central and western regions show sparse coverage. These gaps reflect historical priorities, logistical constraints, funding limitations, and the high cost of continuous instrumentation. To address biases in monitoring networks, data collection could be enhanced with low-cost monitoring, community science, and remote sensing technologies. This study also notes the benefits of long-term monitoring and prioritizing retention of streamgages with longer records.
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