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":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","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":70276934,"text":"70276934 - 2026 - Improved estimates of relative occurrence and abundance using opportunistic surveys and presence-only observations: A zero-inflated integrated species distribution model","interactions":[],"lastModifiedDate":"2026-06-29T16:01:32.498379","indexId":"70276934","displayToPublicDate":"2026-06-26T10:53:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16139,"text":"Ecological Modeling","active":true,"publicationSubtype":{"id":10}},"title":"Improved estimates of relative occurrence and abundance using opportunistic surveys and presence-only observations: A zero-inflated integrated species distribution model","docAbstract":"Modeling tools for estimating and forecasting shifts in species distributions are becoming increasingly valuable for conservation planning and response. This is especially true for wild bird populations, which have been declining across habitats and regions. Species distribution models (SDM) represent a diverse set of tools with options for addressing various sources of bias. Complex spatial processes associated with rare or clustered species can be accounted for using zero-inflated SDMs, whereas biased survey data can be integrated with additional data sources to improve estimates. Each option addresses an important and common source of bias, but the two SDM frameworks have not been implemented together previously. We present a novel zero-inflated extension of an integrated SDM framework for a Poisson regression (ZI-iSDM), allowing for the estimation of independent occurrence and abundance processes by integrating opportunistic survey and presence-only data. We validated performance of this ZI-iSDM using simulated datasets under different degrees of species rarity and density on the landscape as well as sampling bias in opportunistic datasets. We additionally applied this model to real survey data for multiple wild bird species using publicly available observation data combined with open-access environmental information to describe habitat associations. We found that integrating presence-only data, such as banding or harvest events, can compensate for potential deficiencies in opportunistic surveys by expanding sampling to be more representative of available and used habitat. Additionally, models that first differentiated occurrence and abundance using a ZI term were better suited for approximating distributions of spatially clustered species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2026.111712","usgsCitation":"Mullinax, J., Gonnerman, M.B., Sullivan, J.D., Kent, C.M., and Prosser, D., 2026, Improved estimates of relative occurrence and abundance using opportunistic surveys and presence-only observations: A zero-inflated integrated species distribution model: Ecological Modeling, v. 521, 111712, 11 p., https://doi.org/10.1016/j.ecolmodel.2026.111712.","productDescription":"111712, 11 p.","ipdsId":"IP-184595","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":506224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"521","noUsgsAuthors":false,"publicationDate":"2026-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Mullinax, Jennifer","contributorId":358744,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":963692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonnerman, Matthew Brandon 0000-0002-0791-9218","orcid":"https://orcid.org/0000-0002-0791-9218","contributorId":345802,"corporation":false,"usgs":true,"family":"Gonnerman","given":"Matthew","email":"","middleInitial":"Brandon","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":963688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":963689,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kent, Cody M.","contributorId":265823,"corporation":false,"usgs":false,"family":"Kent","given":"Cody","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":963690,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":963691,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276933,"text":"70276933 - 2026 - Geochemistry of the 2022 Mauna Loa eruption: A comparison with earlier historical summit reservoir eruptions, with implications for magma supply and recharge","interactions":[],"lastModifiedDate":"2026-06-29T14:32:36.026528","indexId":"70276933","displayToPublicDate":"2026-06-26T09:26:24","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry of the 2022 Mauna Loa eruption: A comparison with earlier historical summit reservoir eruptions, with implications for magma supply and recharge","docAbstract":"On November 28th, 2022, following a record historical repose period of 38 years, Mauna Loa erupted about 145 × 106 m3 of lava and tephra over a 15-day period. The eruption was confined to the summit caldera region and the upper Northeast Rift Zone and is remarkably homogeneous in composition in both time and space. In these respects, it is typical of prior shallow summit reservoir magma bodies, recently estimated to be at a depth of around 1–2 km beneath the caldera. In contrast with these earlier magma bodies, which typically contain 6.7–7.1% MgO and are perched at the low-MgO end of olivine-control trends, the 2022 lava and tephra are more evolved with 6.24 + / − 0.03% MgO. This implies a temperature difference of around 11 °C with the prior 1984 magma. The simplest explanation is that over 38 years, cooling and crystallization of the remaining 1984 magma body has significantly exceeded magma recharge, giving rise to the evolved 2022 magma. The problem with this model is that we know from a variety of geophysical observations that in those 38 years, Mauna Loa has been erratically inflating, with heightened periods since around 2000 attributed to magma recharge. To reconcile these differences, we suggest instead that the 1984 magma cooled and crystallized much more extensively, from 1166 °C to around 1106 °C, co-crystallizing plagioclase, clinopyroxene, pigeonite and subsequently enstatite instead of pigeonite. At this point, the residual 1984 magma would have an MgO content around 4.2% and been about 50% solidified. Subsequent recharge and mixing by dominantly reservoir magmas, derived from a deeper 3–4-km intermediate magma reservoir, eventually produced the 2022 magma.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-026-01993-7","usgsCitation":"Rhodes, J.M., Trusdell, F., Lynn, K.J., Downs, D.T., and Vollinger, M., 2026, Geochemistry of the 2022 Mauna Loa eruption: A comparison with earlier historical summit reservoir eruptions, with implications for magma supply and recharge: Bulletin of Volcanology, v. 88, 77, https://doi.org/10.1007/s00445-026-01993-7.","productDescription":"77","ipdsId":"IP-178801","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":506207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6429026434013,\n 19.64234577540033\n ],\n [\n -155.4392027817081,\n 19.64234577540033\n ],\n [\n -155.4392027817081,\n 19.43865485428765\n ],\n [\n -155.6429026434013,\n 19.43865485428765\n ],\n [\n -155.6429026434013,\n 19.64234577540033\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","noUsgsAuthors":false,"publicationDate":"2026-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Rhodes, J. Michael 0000-0001-9864-5269","orcid":"https://orcid.org/0000-0001-9864-5269","contributorId":372833,"corporation":false,"usgs":false,"family":"Rhodes","given":"J.","middleInitial":"Michael","affiliations":[{"id":49179,"text":"University of Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":963683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trusdell, Frank A. 0000-0002-0681-0528 trusdell@usgs.gov","orcid":"https://orcid.org/0000-0002-0681-0528","contributorId":754,"corporation":false,"usgs":true,"family":"Trusdell","given":"Frank A.","email":"trusdell@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":963684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":963685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":963686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vollinger, Michael 0000-0002-5679-7886","orcid":"https://orcid.org/0000-0002-5679-7886","contributorId":372834,"corporation":false,"usgs":false,"family":"Vollinger","given":"Michael","affiliations":[{"id":49179,"text":"University of Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":963687,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276741,"text":"fs20263015 - 2026 - Assessment of undiscovered conventional oil and gas resources in the Buda Limestone of Texas, 2025","interactions":[],"lastModifiedDate":"2026-06-25T17:04:41.491485","indexId":"fs20263015","displayToPublicDate":"2026-06-24T11:50:00","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":"2026-3015","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources in the Buda Limestone of Texas, 2025","title":"Assessment of undiscovered conventional oil and gas resources in the Buda Limestone of Texas, 2025","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 12 million barrels of oil and 184 billion cubic feet of gas in the Buda Limestone of Texas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20263015","programNote":"National and Global Petroleum Assessment","usgsCitation":"Lohr, C.D., Doolan, C.A., Merrill, M.D., Craddock, W.H., Gardner, R., Anderson, C.P., Le, P.A., Mercier, T.J., and Schenk, C.J., 2026, Assessment of undiscovered conventional oil and gas resources in the Buda Limestone of Texas, 2025: U.S. Geological Survey Fact Sheet 2026–3015, 4 p., https://doi.org/10.3133/fs20263015.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-184808","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":505912,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20263015/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3015"},{"id":505838,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2026/3015/fs20263015.xml"},{"id":505837,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2026/3015/images"},{"id":505702,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1SN76VY","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Buda Limestone of Texas—Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":505701,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2026/3015/fs20263015.pdf","text":"Report","size":"3.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3015"},{"id":505700,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2026/3015/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Buda Limestone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102,\n 34\n ],\n [\n -92,\n 34\n ],\n [\n -92,\n 26\n ],\n [\n -102,\n 26\n ],\n [\n -102,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Energy & Minerals Science Center
U.S. Geological Survey
954 National Center
Reston, VA 20192
Ultraviolet (UV) remote sensing is widely used to detect volcanic sulfur dioxide (SO₂) due to its high sensitivity and favorable spatial and temporal resolution. However, significant discrepancies have been reported between ground-based and satellite-based UV observations of dense volcanic plumes. A notable example is the 2018 lower East Rift Zone eruption of Kīlauea, where SO₂ emission rates derived from ground-based Differential Optical Absorption Spectroscopy (DOAS) measurements differed substantially from those obtained by the spaceborne Tropospheric Monitoring Instrument (TROPOMI). In this study, we investigate these differences by applying thermal infrared (TIR) satellite retrievals using a modified version of the SO₂-ALTA algorithm to Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The resulting TIR-derived SO₂ fluxes are compared with ground-based DOAS data, satellite UV observations, and petrological estimates of gas emissions. Our results show strong agreement between TIR-derived fluxes, ground-based DOAS measurements, and petrological estimates, particularly during the peak and plateau phases of the eruption. In contrast, satellite UV-derived SO₂ emissions are systematically lower. We find that TIR observations are more effective in quantifying high-concentration SO₂ plumes in the near-vent region, while UV measurements are more sensitive under lower-concentration conditions but more affected by scattering in optically dense plumes. These findings highlight the complementary strengths of UV and TIR remote sensing techniques and emphasize the importance of accounting for plume density and observation geometry when interpreting satellite SO₂ retrievals.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-026-02004-5","usgsCitation":"Gabrieli, A., Kern, C., Lerner, A., Realmuto, V.J., Carn, S., Nadeau, P.A., Wright, R., and Porter, J.N., 2026, Thermal infrared and ultraviolet remote sensing of sulfur dioxide gas emitted during the 2018 lower East Rift Zone eruption of Kilauea, Hawaiʻi: Bulletin of Volcanology, v. 88, 76, https://doi.org/10.1007/s00445-026-02004-5.","productDescription":"76","ipdsId":"IP-189503","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":505908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.4727625,\n 19.3686062\n ],\n [\n -155.2091918920762,\n 19.376341900270532\n ],\n [\n -155.2091918920762,\n 19.247549862007077\n ],\n [\n -155.2646912,\n 19.264299\n ],\n [\n -155.3661629,\n 19.2232172\n ],\n [\n -155.4768625205247,\n 19.247549862007077\n ],\n [\n -155.4727625,\n 19.3686062\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","noUsgsAuthors":false,"publicationDate":"2026-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Gabrieli, Andrea","contributorId":372801,"corporation":false,"usgs":false,"family":"Gabrieli","given":"Andrea","affiliations":[{"id":88423,"text":"Univ. of Hawaii Manoa","active":true,"usgs":false}],"preferred":false,"id":963586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":963587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lerner, Allan 0000-0001-7208-1493","orcid":"https://orcid.org/0000-0001-7208-1493","contributorId":229362,"corporation":false,"usgs":true,"family":"Lerner","given":"Allan","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":963588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Realmuto, Vincent J.","contributorId":372802,"corporation":false,"usgs":false,"family":"Realmuto","given":"Vincent","middleInitial":"J.","affiliations":[{"id":27923,"text":"NASA JPL","active":true,"usgs":false}],"preferred":false,"id":963589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carn, Simon","contributorId":344949,"corporation":false,"usgs":false,"family":"Carn","given":"Simon","affiliations":[],"preferred":false,"id":963590,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nadeau, Patricia A. 0000-0002-6732-3686","orcid":"https://orcid.org/0000-0002-6732-3686","contributorId":215616,"corporation":false,"usgs":true,"family":"Nadeau","given":"Patricia","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":963591,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, Robert","contributorId":174413,"corporation":false,"usgs":false,"family":"Wright","given":"Robert","affiliations":[],"preferred":false,"id":963592,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Porter, John N.","contributorId":372803,"corporation":false,"usgs":false,"family":"Porter","given":"John","middleInitial":"N.","affiliations":[{"id":88429,"text":"Univ of Hawaii Manoa","active":true,"usgs":false}],"preferred":false,"id":963593,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70276779,"text":"sim3548 - 2026 - Colored shaded-relief bathymetric and acoustic-backscatter maps of Jenkinson Lake with orthomosaic of the Sly Park Creek and Hazel Creek area, California","interactions":[],"lastModifiedDate":"2026-06-24T14:17:19.358294","indexId":"sim3548","displayToPublicDate":"2026-06-23T14:47:41","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3548","displayTitle":"Colored Shaded-Relief Bathymetric and Acoustic-Backscatter Maps of Jenkinson Lake with Orthomosaic of the Sly Park Creek and Hazel Creek Area, California","title":"Colored shaded-relief bathymetric and acoustic-backscatter maps of Jenkinson Lake with orthomosaic of the Sly Park Creek and Hazel Creek area, California","docAbstract":"The Caldor Fire was ignited on August 14, 2021, and burned almost 222,000 acres (898 square kilometers) in forested terrain of the central and western Sierra Nevada, California. During the subsequent two months, the fire burned nearly all of Sly Park Creek watershed in El Dorado County. The El Dorado Irrigation District manages the water supply for the area using storage in Jenkinson Lake, a 1.6-kilometer- (1.0-mile-) wide and 3.6-kilometer- (2.2-mile-) long reservoir, located south of the town of Pollock Pines. Several weeks after the fire, the U.S. Geological Survey began investigations into post-fire landscape responses, including sediment yield, by measuring new sediment deposition in Jenkinson Lake. This study focused on the collection and processing of bathymetric and acoustic-backscatter data, as well as onshore aerial imagery in and around Jenkinson Lake, to support wildfire science after the Caldor Fire. A colored shaded-relief bathymetric map (sheet 1) and an acoustic backscatter map (sheet 2) show the lake floor morphology and backscatter intensities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3548","usgsCitation":"Dartnell, P., Logan, J.B., East, A.E., Hatcher, G.A., Currie, J.E., Marcuson, R.K., Powers, D.C., Dal Ferro, P., and McKee, J.A., 2026, Colored shaded-relief bathymetric and acoustic-backscatter maps of Jenkinson Lake with orthomosaic of the Sly Park Creek and Hazel Creek area, California: U.S. Geological Survey Scientific Investigations Map 3548, 2 sheets, scale 1:6,000, https://doi.org/10.3133/sim3548.","productDescription":"2 Sheets: 34.84 x 26.78 inches; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-178309","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":505751,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14QWDYN","text":"USGS data release","description":"Logan, J.B. and East, A.E., 2024, Digital surface models and orthomosaic images from UAS surveys of Jenkinson Lake, El Dorado County, CA: U.S. Geological Survey data release, https://doi.org/10.5066/P14QWDYN.","linkHelpText":"Digital surface models and orthomosaic images from UAS surveys of Jenkinson Lake, El Dorado County, CA"},{"id":505749,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3548/sim3548_sheet2.pdf","text":"Sheet 2","size":"25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3548 Sheet 2"},{"id":505750,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13BSSDY","text":"USGS data release","description":"Dartnell, P., East, A.E., Logan, J., Hatcher, G.A., Currie, J.E., Marcuson, R.K., Powers, D.C., Dal Ferro, P., and McKee, J.A., 2024, Bathymetry and acoustic backscatter data for Jenkinson Lake, California collected during three USGS field activities, 2022-604-FA, 2022-649-FA, and 2023-634-FA: U.S. Geological Survey data release, https://doi.org/10.5066/P13BSSDY.","linkHelpText":"Bathymetry and acoustic backscatter data for Jenkinson Lake, California collected during three USGS field activities, 2022-604-FA, 2022-649-FA, and 2023-634-FA"},{"id":505748,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3548/sim3548_sheet1.pdf","text":"Sheet 1","size":"24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3548 Sheet 1"},{"id":505747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3548/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Jenkinson Lake, Sly Park Creek and Hazel Creek area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.5883,\n 38.75\n ],\n [\n -120.51,\n 38.75\n ],\n [\n -120.51,\n 38.7\n ],\n [\n -120.5883,\n 38.7\n ],\n [\n -120.5883,\n 38.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Digital flood-inundation maps for 35.5 miles of the Blue River, in and near Kansas City, Missouri, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Kansas City. Maps were also developed for a combined 7.3 miles of Brush Creek (4.4 miles) and Indian Creek (2.9 miles), two primary tributaries to the Blue River in the study reach. The flood-inundation maps, available through the USGS Flood Inundation Mapping Program website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding, depth of water above first-floor elevations in selected buildings, water velocity, water-surface elevations, and time of travel corresponding to selected water levels or gage heights (hereafter referred to as “stages”) at nine reference USGS streamgages—five on the Blue River (USGS station numbers 06893590, 06893578, 06893500, 06893150, and 06893100), two on Brush Creek (USGS station numbers 06893562 and 06893557), one on Indian Creek (USGS station number 06893390), and one on the Missouri River (USGS station number 06893000). Near-real-time stages at these streamgages may be obtained from USGS Water Data for the Nation at https://doi.org/10.5066/F7P55KJN or the National Weather Service National Water Prediction Service at http://water.noaa.gov/, which also forecasts flood hydrographs at seven of these sites (USGS station numbers 06893000, 06893590, 06893578, 06893500, 06893150, 06893557, and 06893390).
Flood profiles were computed for eight map reaches by means of two-dimensional hydraulic models. The models were calibrated using the USGS-developed stage–streamflow relations at each reference streamgage. Two map reaches on the lower Blue River also include the effects of backwater from the Missouri River on flood inundation extent and hydraulic characteristics.
The hydraulic models were used to compute water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datums. The profile stages ranged from the National Weather Service “Action Stage” or near bankfull to a stage exceeding the highest recorded water level at each streamgage. The simulated water-surface profiles were then combined with a digital elevation model (derived from light detection and ranging data having a nonvegetated vertical accuracy of a maximum 10-centimeter root-mean-square error) to delineate the area flooded at each water level and the associated hydraulic characteristics.
The availability of these maps, along with information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel, resource managers, and residents with information that could be critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265033","collaboration":"Prepared in cooperation with the City of Kansas City, Missouri","usgsCitation":"Heimann, D.C., Cigrand, C.V., High, J.L., Kostynick, R.P., Atkinson, A.A., and Rydlund, P.H., Jr., 2026, Flood-inundation maps of the Blue River and major tributaries in and near Kansas City, Missouri, 2023–25: U.S. Geological Survey Scientific Investigations Report 2026–5033, 26 p., https://doi.org/10.3133/sir20265033.","productDescription":"Report: viii, 26 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-182544","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":505633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5033/coverthb.jpg"},{"id":505637,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265033/full","description":"SIR 2026–5033 HTML"},{"id":505634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5033/sir20265033.pdf","text":"Report","size":"33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026–5033 PDF"},{"id":505635,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5033/sir20265033.XML","description":"SIR 2026–5033 XML"},{"id":505636,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5033/images/"},{"id":505638,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1NSJHXH","text":"USGS data release","linkHelpText":"Flood-inundation map products, travel time estimates, geospatial information, and hydraulic models of the Blue River and major tributaries, in and near Kansas City, Missouri, 2023–25"}],"country":"United States","state":"Kansas, Missouri","city":"Kansas City","otherGeospatial":"Blue River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.833,\n 39.1667\n ],\n [\n -94.4,\n 39.1667\n ],\n [\n -94.4,\n 38.75\n ],\n [\n -94.833,\n 38.75\n ],\n [\n -94.833,\n 39.1667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The U.S. Geological Survey (USGS) created a new set of flood-inundation maps for the Blue River and two of its tributaries, Brush Creek and Indian Creek, in and near Kansas City, Missouri. These maps show where flooding is likely to spread and how deep the water may get when the river rises to different water levels. The maps are based on water-level information measured at nine USGS streamgages in the area. Using computer simulations, the USGS estimated how water would move through river channels and across nearby land during floods. The results show the likely extent of flooding, areas where water may flow quickly, and places where the water might become deep enough to threaten buildings and roads. These maps can help residents, businesses, and emergency managers understand their flood risk and make informed decisions before and during flood events. Knowing which areas may flood at different river levels helps people better plan evacuation routes, road closures, and other safety measures.
","publicationDate":"2026-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cigrand, Charles V. 0000-0002-4177-7583","orcid":"https://orcid.org/0000-0002-4177-7583","contributorId":201575,"corporation":false,"usgs":true,"family":"Cigrand","given":"Charles","email":"","middleInitial":"V.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"High, Jason L. 0009-0009-1031-1439","orcid":"https://orcid.org/0009-0009-1031-1439","contributorId":372425,"corporation":false,"usgs":false,"family":"High","given":"Jason","middleInitial":"L.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":963077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kostynick, Robert P. 0009-0004-2801-1091","orcid":"https://orcid.org/0009-0004-2801-1091","contributorId":372426,"corporation":false,"usgs":true,"family":"Kostynick","given":"Robert","middleInitial":"P.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, Allison A. 0009-0001-7572-0729 aatkinson@usgs.gov","orcid":"https://orcid.org/0009-0001-7572-0729","contributorId":330979,"corporation":false,"usgs":true,"family":"Atkinson","given":"Allison","email":"aatkinson@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963079,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":963080,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70276820,"text":"70276820 - 2026 - Perceptions of parcel-level wildfire risk differ between homeowners and trained assessors in wildland-urban interface communities across the western United States","interactions":[],"lastModifiedDate":"2026-06-24T16:03:55.28622","indexId":"70276820","displayToPublicDate":"2026-06-23T10:56:48","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3300,"text":"Risk Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Perceptions of parcel-level wildfire risk differ between homeowners and trained assessors in wildland-urban interface communities across the western United States","docAbstract":"Wildfire risk mitigation on private property is central to reducing community wildfire vulnerability. Homeowners have control over many of the key factors that contribute to wildfire risk on their parcels, yet vulnerable conditions persist. One potential explanation is a misalignment between homeowners' and trained assessors' perceptions of parcel-level wildfire risk. Prior research has documented a “risk gap” in a single community wherein owners often underestimate their parcel-level wildfire risk; however, it is unclear whether such misalignments are widespread. This study replicates and expands previous research by examining the parcel-level wildfire risk gap in 38 wildland–urban interface (WUI) communities across the Western United States using paired data from household surveys and parcel-level wildfire risk assessments by trained assessors. We find that homeowners and assessors often perceive parcel characteristics differently. Homeowners may systematically mis-weight their importance, tending to underweight key controllable factors such as building materials and defensible space, leading to meaningful divergence from trained assessor ratings. Accordingly, we also find that homeowners generally underestimate overall parcel wildfire risk compared to trained assessors. These results suggest that even when homeowners recognize attributes on their parcels that contribute to wildfire risk, they may not fully grasp how much the attributes contribute to overall parcel risk, potentially failing to recognize the need to undertake meaningful mitigation actions. The findings from this study contribute to the broader natural hazards literature on expert-layperson risk perception gaps and offer insights for improving wildfire communication, education, and mitigation strategies in WUI communities.
","language":"English","publisher":"Wiley","doi":"10.1111/risa.70268","usgsCitation":"Wallace, K., Webster, G., Brenkert-Smith, H., Champ, P.A., Donovan, C., Wagner, C., Barth, C.M., Kuehn, J., Wittenbrink, S., and Meldrum, J.R., 2026, Perceptions of parcel-level wildfire risk differ between homeowners and trained assessors in wildland-urban interface communities across the western United States: Risk Analysis, v. 46, no. 7, e70268, 15 p., https://doi.org/10.1111/risa.70268.","productDescription":"e70268, 15 p.","ipdsId":"IP-183761","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":506080,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/risa.70268","text":"Publisher Index Page"},{"id":505834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Colorado, New Mexico, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.87193311450088,\n 61.38021349656111\n ],\n [\n -148.38408803583386,\n 61.38021349656111\n ],\n [\n -148.38408803583386,\n 59.42383348186476\n ],\n [\n -151.87193311450088,\n 59.42383348186476\n ],\n [\n -151.87193311450088,\n 61.38021349656111\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5996176,\n 43.7152618\n ],\n [\n -103.99309069449717,\n 43.7152618\n ],\n [\n -103.99309069449717,\n 33.721908765802056\n ],\n [\n -112.5996176,\n 33.721908765802056\n ],\n [\n -112.5996176,\n 43.7152618\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"7","noUsgsAuthors":false,"publicationDate":"2026-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wallace, Kelly","contributorId":355698,"corporation":false,"usgs":false,"family":"Wallace","given":"Kelly","affiliations":[{"id":84783,"text":"University of Colorado-Boulder, Institute of Behavioral Science","active":true,"usgs":false}],"preferred":false,"id":963448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webster, Grant","contributorId":355604,"corporation":false,"usgs":false,"family":"Webster","given":"Grant","affiliations":[{"id":84783,"text":"University of Colorado-Boulder, Institute of Behavioral Science","active":true,"usgs":false}],"preferred":false,"id":963449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":963450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champ, Patricia A. 0000-0003-1917-883X","orcid":"https://orcid.org/0000-0003-1917-883X","contributorId":360956,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","middleInitial":"A.","affiliations":[{"id":86128,"text":"U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":963451,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donovan, Colleen","contributorId":240586,"corporation":false,"usgs":false,"family":"Donovan","given":"Colleen","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":963452,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Carolyn","contributorId":240587,"corporation":false,"usgs":false,"family":"Wagner","given":"Carolyn","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":963453,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barth, Christopher M.","contributorId":372706,"corporation":false,"usgs":false,"family":"Barth","given":"Christopher","middleInitial":"M.","affiliations":[{"id":88412,"text":"USDA Forest Service, Washington Office, Fire and Aviation Management","active":true,"usgs":false}],"preferred":false,"id":963454,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kuehn, Josh","contributorId":269634,"corporation":false,"usgs":false,"family":"Kuehn","given":"Josh","email":"","affiliations":[{"id":56021,"text":"Colorado State Forest Service","active":true,"usgs":false}],"preferred":false,"id":963455,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wittenbrink, Suzanne","contributorId":333353,"corporation":false,"usgs":false,"family":"Wittenbrink","given":"Suzanne","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":963456,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":963457,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70276862,"text":"70276862 - 2026 - The path to FAIR research models: Lessons learned","interactions":[],"lastModifiedDate":"2026-06-24T15:42:13.815628","indexId":"70276862","displayToPublicDate":"2026-06-23T10:38:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"The path to FAIR research models: Lessons learned","docAbstract":"Numerical modeling of Earth surface processes emerged as an important scientific tool in the late 1960s to mid-1970s, driven by the development of finite element methods in computer science. These advancements, initially applied in civil engineering, enabled scientists to simulate complex geological phenomena. At that time, models were often only described in publications, access was limited to researchers with direct connections to the developers, and the code was rarely documented for reuse, limiting their application beyond the original research context. The FAIR principles (Findability, Accessibility, Interoperability, and Reusability) as applied to data began to take shape in the 21st century with the rise of open science, digital repositories, and standardized data sharing frameworks. In the late 2010s, grassroots movements began to apply some of the FAIRness goals to numerical models. Subsequently, more formalized FAIR model principles were developed that addressed the specific needs of the scientific modeling community, resulting in the formulation of the FAIR principles for research software (FAIR4RS).
In this study, we examine the development and implementation of strategies by two geoscience research infrastructures – the CSDMS (Community Surface Dynamics Modeling System) Model Repository and the U.S. Geological Survey Model Catalog – to enhance the FAIRness of models guided by FAIR4RS. Some of the development and implementation efforts described predate the formalization of FAIR and FAIR4RS principles, making this an ongoing and adaptive process. We evaluate the temporal progression towards increased FAIR4RS alignment across three phases of research infrastructure development: prototype, refinement, and growth and iteration. Although certain principles were more straightforward to implement early in prototypes of the catalog infrastructures, others required broader community collaboration during refinement, and some continue to pose practical challenges in the growth and iteration phase. By tracing these dynamics, our aim is to provide insights that can guide other modeling initiatives in effectively adopting FAIR4RS principles within their communities.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-19-5381-2026","usgsCitation":"Kettner, A., Hsu, L., and Serna, B., 2026, The path to FAIR research models: Lessons learned: Geoscientific Model Development, v. 19, no. 12, p. 5381-5399, https://doi.org/10.5194/gmd-19-5381-2026.","productDescription":"19 p.","startPage":"5381","endPage":"5399","ipdsId":"IP-179664","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":506077,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-19-5381-2026","text":"Publisher Index Page"},{"id":505828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"12","noUsgsAuthors":false,"publicationDate":"2026-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kettner, Albert 0000-0002-7191-6521","orcid":"https://orcid.org/0000-0002-7191-6521","contributorId":372774,"corporation":false,"usgs":false,"family":"Kettner","given":"Albert","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":963545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hsu, Leslie 0000-0002-5353-807X lhsu@usgs.gov","orcid":"https://orcid.org/0000-0002-5353-807X","contributorId":191745,"corporation":false,"usgs":true,"family":"Hsu","given":"Leslie","email":"lhsu@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":963546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Serna, Brandon 0000-0002-5284-6230 bserna@usgs.gov","orcid":"https://orcid.org/0000-0002-5284-6230","contributorId":5646,"corporation":false,"usgs":true,"family":"Serna","given":"Brandon","email":"bserna@usgs.gov","affiliations":[],"preferred":true,"id":963547,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276622,"text":"ofr20261022 - 2026 - The US XPD-24–200—An isokinetic suspended-sediment and water-quality collapsible-bag sampler with point- or depth-integrating sampling capabilities","interactions":[],"lastModifiedDate":"2026-06-22T21:29:05.096671","indexId":"ofr20261022","displayToPublicDate":"2026-06-22T11:10:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1022","displayTitle":"The US XPD-24–200: An Isokinetic Suspended-Sediment and Water-Quality Collapsible-Bag Sampler with Point- or Depth-Integrating Sampling Capabilities","title":"The US XPD-24–200—An isokinetic suspended-sediment and water-quality collapsible-bag sampler with point- or depth-integrating sampling capabilities","docAbstract":"Accurate collection of fluvial suspended‑sediment and water‑quality samples is essential for understanding transport processes, evaluating river health, quantifying loads, and supporting regulatory and management decisions. Since 1939, the Federal Interagency Sedimentation Project (FISP) has led the development and standardization of sediment‑sampling equipment and methods across Federal agencies. Although substantial advancements have been made, the most recent point‑integrating sampler developed in 2006 has notable limitations, including insufficient sample volume for low‑concentration analyses and a mechanically complex pressure‑equalization system required for a rigid-bottle sample container. To address these limitations, FISP collaborated with Carnet Technology to design, fabricate, and test a new collapsible‑bag sampler capable of collecting larger sample volumes and operating as either a point‑integrating or depth‑integrating sampler. The resulting sampler, the US XPD‑24‑200, was evaluated through controlled tow‑tank tests and field testing in a lake environment.
Results indicate that the US XPD‑24‑200 can collect a 5.5-fold increase in maximum sample volume than a pre-existing point sampler developed in 2006. The US XPD‑24‑200 performs isokinetically within the expected intake efficiency (IE) range under most conditions. Approximately 73 percent of IEs fell within the target range of 0.9–1.1. A mild bias was observed with IE values outside this range that were predominantly lower than 0.9 and occurred most frequently at the lower test velocities, whereas only 2 percent of IEs exceeded 1.1, primarily at the highest velocities tested. Tow‑tank tests produced tightly clustered IE values with low variability, demonstrating stable performance under controlled conditions. Lake towing tests exhibited more variability, reflecting natural environmental influences such as turbulence, temperature gradients, and unsteady inflow. Collectively, the results demonstrate that the US XPD‑24‑200 provides reliable IEs comparable to existing samplers while offering increased sample volume, reduced mechanical complexity, and enhanced operational flexibility.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261022","collaboration":"Prepared in cooperation with the Federal Interagency Sedimentation Project (FISP)","usgsCitation":"Groten, J.T., Rose, C.E., O’Neal, W., Simmons, L.B., Straub, T.D., and Diaz, P., Jr., 2026, The US XPD-24–200—An isokinetic suspended-sediment and water-quality collapsible-bag sampler with point- or depth-integrating sampling capabilities: U.S. Geological Survey Open-File Report 2026–1022, 13 p., https://doi.org/10.3133/ofr20261022.","productDescription":"Report: vi, 13 p.; Data Release; Project Site","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-185472","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":505435,"rank":7,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/fisp/","linkHelpText":"- Federal Interagency Sedimentation Project (FISP) website"},{"id":505434,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13AXK4I","text":"USGS data release","linkHelpText":"Intake efficiency testing data for the US XPD-24-200 isokinetic suspended sediment and water quality collapsible-bag sampler"},{"id":505433,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1022/images"},{"id":505432,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1022/ofr20261022.XML","description":"OFR 2026-1022 XML"},{"id":505431,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261022/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1022 HTML"},{"id":505430,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1022/coverthb2.jpg"},{"id":505429,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1022/ofr20261022.pdf","text":"Report","size":"7.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1022 PDF"}],"contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1992 Folwell Avenue
St. Paul, MN 55108
Groundwater quality is often affected by anthropogenic activities in urban settings. This study examines groundwater quality in and around the Santa Fe Springs Oil Field in Los Angeles County, California, where oil and gas production commonly intersects with high density industrial, commercial and residential land uses. Utilizing a combination of new and historical data, we evaluated potential pathways that would allow for oil field formation fluids to migrate into groundwater and whether mixing may have occurred based on the distribution of groundwater and oil field formation fluid tracers in samples. Samples were analyzed for a wide array of constituents including volatile organic compounds, light hydrocarbons, major ions, and various isotopic compositions. Despite evidence of oil field infrastructure providing potential pathways of migration via uncemented annular spaces, casing breaches and historical disposal of oil field formation water in surface ponds, the distribution and occurrence of stable isotopes of water, chloride, boron, and total dissolved solids do not indicate mixing of oil field formation water and groundwater. However, methane isotopic signatures and the presence of heavier alkanes suggest gas from oil-bearing formations have migrated from depth via oil field well infrastructure. Volatile organic compound detections were mainly from manufactured compounds unrelated to oil and gas production, with a relatively limited number of petroleum hydrocarbons also detected. Volatile organic compounds were generally found in wells tapping shallow, modern aged groundwater, indicating anthropogenic activities occurring at or near land surface as the source. Study results suggest that while oil field infrastructure provides migration pathways for oil field formation fluids to be introduced into groundwater, urban land uses not related to oil and gas production are the primary drivers of groundwater quality degradation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2026.181966","usgsCitation":"Wright, M., Davis, T.A., Landon, M.K., Land, M., Shimabukuro, D.H., Sowers, T.A., Schmer, M., Gannon, R., Kulongoski, J.T., Hunt, A., and Watson, E., 2026, Evaluating groundwater quality influences from oil field operations and other anthropogenic activities in an urban setting, Santa Fe Springs, California: Science of the Total Environment, v. 1045, 181966, 13 p., https://doi.org/10.1016/j.scitotenv.2026.181966.","productDescription":"181966, 13 p.","ipdsId":"IP-176374","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":506092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2026.181966","text":"Publisher Index Page"},{"id":505901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Fe Springs oil field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 34\n ],\n [\n -118.15,\n 34\n ],\n [\n -118.15,\n 33.9\n ],\n [\n -118,\n 33.9\n ],\n [\n -118,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1045","noUsgsAuthors":false,"publicationDate":"2026-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wright, Michael 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":151031,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Tracy A. 0000-0003-0253-6661","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":372816,"corporation":false,"usgs":false,"family":"Davis","given":"Tracy","middleInitial":"A.","affiliations":[{"id":38734,"text":"former employee","active":true,"usgs":false}],"preferred":false,"id":963614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Land, Michael 0000-0001-5141-0307 mtland@usgs.gov","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":171938,"corporation":false,"usgs":true,"family":"Land","given":"Michael","email":"mtland@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shimabukuro, David H. 0000-0002-6106-5284","orcid":"https://orcid.org/0000-0002-6106-5284","contributorId":208209,"corporation":false,"usgs":false,"family":"Shimabukuro","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":963617,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sowers, Theron A. 0000-0002-3208-5411","orcid":"https://orcid.org/0000-0002-3208-5411","contributorId":211482,"corporation":false,"usgs":false,"family":"Sowers","given":"Theron","email":"","middleInitial":"A.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":963618,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmer, Megan E 0009-0002-0010-0864","orcid":"https://orcid.org/0009-0002-0010-0864","contributorId":336792,"corporation":false,"usgs":true,"family":"Schmer","given":"Megan E","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963619,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gannon, Riley 0000-0002-1239-1083","orcid":"https://orcid.org/0000-0002-1239-1083","contributorId":205967,"corporation":false,"usgs":true,"family":"Gannon","given":"Riley","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963620,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963621,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hunt, Andrew G. 0000-0002-3810-8610","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":206197,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":963622,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Watson, Elise 0000-0003-2213-4707","orcid":"https://orcid.org/0000-0003-2213-4707","contributorId":206381,"corporation":false,"usgs":true,"family":"Watson","given":"Elise","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963623,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70276780,"text":"70276780 - 2026 - Evidence for a biological origin of uranium-rich carbon masses within the Ediacaran Salt Range Formation of Pakistan","interactions":[],"lastModifiedDate":"2026-06-23T17:52:09.53987","indexId":"70276780","displayToPublicDate":"2026-06-20T10:09:27","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for a biological origin of uranium-rich carbon masses within the Ediacaran Salt Range Formation of Pakistan","docAbstract":"Thucholites are unique organic structures found in igneous and sedimentary rocks composed of a U-C-rich interior enclosed by an organic outer shell. Their formation and occurrence have perplexed scientists for over 100 years. Typically, thucholites are sparse in sedimentary rocks but where found in abundance, they may be the result of rapid paleoecological disruptions, e.g., volcanic ashfall. Here, we evaluated thucholites from the Ediacaran Salt Range Formation of the Indus Basin in Pakistan using field emission scanning electron microscopy (FESEM) and nanoscale secondary ion mass spectroscopy (NanoSIMS) to propose a two-stage mechanism for thucholite development. NanoSIMS results suggest organic matter in thucholite cores formed by biological fractionation (represented by the presence of lighter 13C/12C and 34S/32S) while the outer organic mantle formed via radiolysis-induced polymerization. FESEM elemental analysis confirms compositional differences between the two thucholite components (core and mantle), further implying their contrasting origins. Dimensional comparison of thucholite cores and their U-bearing mineral morphologies to ancient and modern U-biomineralized microbes suggests that the thucholite cores formed from metal-biological interactions. The presence of volcanogenic biotite, alkali feldspar, and clay spherules (interpreted as devitrified volcanic glass) with thucholite suggests that the thucholite cores in the Salt Range Formation are biological responses to rapid paleoenvironmental change from volcanic eruption which preserved the fossilized morphologies of Proterozoic microorganisms.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2026.105226","usgsCitation":"Valentine, B., Hackley, P.C., Stokes, M., Bose, M., McAleer, R.J., and Khan, I., 2026, Evidence for a biological origin of uranium-rich carbon masses within the Ediacaran Salt Range Formation of Pakistan: Organic Geochemistry, v. 219, 105226, 10 p., https://doi.org/10.1016/j.orggeochem.2026.105226.","productDescription":"105226, 10 p.","ipdsId":"IP-171061","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":506063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.orggeochem.2026.105226","text":"Publisher Index Page"},{"id":505775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Pakistan","otherGeospatial":"Salt Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 73.07453958142958,\n 33.121150877165675\n ],\n [\n 71.59448375213682,\n 33.121150877165675\n ],\n [\n 71.59448375213682,\n 32.473531670424165\n ],\n [\n 73.07453958142958,\n 32.473531670424165\n ],\n [\n 73.07453958142958,\n 33.121150877165675\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"219","noUsgsAuthors":false,"publicationDate":"2026-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentine, Brett 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":209829,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":963358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":963359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":963360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bose, Maitrayee","contributorId":372639,"corporation":false,"usgs":false,"family":"Bose","given":"Maitrayee","affiliations":[{"id":64194,"text":"Arizona State University, School of Earth and Space Exploration","active":true,"usgs":false}],"preferred":false,"id":963361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":963362,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Khan, Imran","contributorId":372644,"corporation":false,"usgs":false,"family":"Khan","given":"Imran","affiliations":[{"id":84124,"text":"COMSATS Institute of Information and Technology, Abbottabad, Kpk, Pakistan","active":true,"usgs":false}],"preferred":false,"id":963363,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70276795,"text":"70276795 - 2026 - Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data","interactions":[],"lastModifiedDate":"2026-06-23T17:24:19.09444","indexId":"70276795","displayToPublicDate":"2026-06-19T12:07:38","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data","docAbstract":"Ecological models should account for uncertainty to be most effective and useful. Yet, uncertainty from model covariates—unlike that from other sources, such as sampling error or process variability—is seldom explicitly incorporated. This can cause underestimates of uncertainty to cascade through model parameter estimates, predictions, and downstream uses. Burner et al. proposed a method for quantifying uncertainty in covariates and incorporating it into models using informative Bayesian priors. This method was applied to stop-level Breeding Bird Survey (BBS) analyses, where land cover uncertainty at each stop arises from substantial stop location uncertainty. A limited validation of model-estimated land cover, using stops with known locations, indicated the method’s potential effectiveness, but it was not rigorously evaluated. We conduct a robust simulation-based test, generating stop locations, extracting land cover, and simulating bird communities across 210 BBS routes in the upper Midwest. We compare 3 models: a “known” model with true land cover, a “naive” model assuming consistent 800-m stop spacing, and a “full” model using informative priors to estimate land cover. Species parameter estimates and predicted prevalence patterns across gradients in land cover from the full model approached those of the known model and were substantially closer to the true values used in simulations relative to those from the naive model. Naive model parameters were more biased relative to the other models, and credible intervals of predicted species prevalence rarely included the true simulated values. The full model also produced land cover covariate estimates closer to true simulation values relative to the mean informative priors. Our results show that, for the BBS, informative priors enable more accurate stop-level analyses despite location uncertainty. In contrast, naive models that ignore this uncertainty yield poor inferences. More broadly, we demonstrate empirically the utility of informative priors to account for covariate uncertainty in ecological models.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/ornithapp/duag032","usgsCitation":"Burner, R.C., Hostetler, J.A., and Kirschbaum, A., 2026, Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data: Ornithological Applications, https://doi.org/10.1093/ornithapp/duag032.","ipdsId":"IP-182491","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":505772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconson","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-83.880387,41.720089],[-86.824828,41.76024],[-86.24971,42.480212],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.617955,43.768596],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-83.880387,41.720089]]],[[[-90.418136,46.566094],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192],[-90.614589,42.508053],[-91.078097,42.806526],[-91.177728,43.118733],[-91.062562,43.243165],[-91.217706,43.50055],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.418136,46.566094]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Michigan\",\"nation\":\"USA \"}}]}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Burner, Ryan C. 0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":304152,"corporation":false,"usgs":true,"family":"Burner","given":"Ryan","email":"","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":963398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":963399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kirschbaum, Alan","contributorId":344465,"corporation":false,"usgs":false,"family":"Kirschbaum","given":"Alan","affiliations":[{"id":82351,"text":"U.S. National Park Service (NPS)","active":true,"usgs":false}],"preferred":false,"id":963400,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276748,"text":"70276748 - 2026 - Osmium isotope constraints on Mauna Loa–Kilauea magmatic connectivity, Island of Hawai‘i","interactions":[],"lastModifiedDate":"2026-06-23T13:27:36.796451","indexId":"70276748","displayToPublicDate":"2026-06-19T09:34:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Osmium isotope constraints on Mauna Loa–Kilauea magmatic connectivity, Island of Hawai‘i","docAbstract":"The U.S. Geological Survey developed a two-dimensional hydraulic model for a 9.2-mile reach of the Kalamazoo River between the Trowbridge and Allegan City Dams. The model simulates streamflow conditions with spatial coverage and resolution that would be difficult or dangerous to document with field measurements, enabling assessments of habitat connectivity and substrate stability to support dam removal and restoration planning. The model was calibrated with surveyed water surface elevation (WSE) profiles, streamgage WSE time series, and measured depth-average velocities. Modeled WSE profiles had root mean square error (RMSE) values of 0.20 and 0.32 foot. Cross-sectional average velocities were slightly underpredicted, with RMSE of 0.28 and 0.30 foot per second (ft/s). Channel roughness varied with stage, and the high-flow model reproduced streamgage WSE time series with an RMSE of 0.04 foot. Quasi-steady simulations at 4,000 cubic feet per second (ft3/s), about the 50-percent annual exceedance probability streamflow, indicated that cross-sectional average velocities within 3.4 miles downstream from Trowbridge Dam were commonly between 3 and 4 ft/s, occasionally exceeding 4 ft/s. Farther downstream, velocities seldom exceeded 3 ft/s. Simulated shear stresses were used to estimate substrate stability in the reach. At 4,000 ft3/s, the minimum stable grain size along most of the main channel was predicted to be in the pebble range (4–64 millimeters), and sands and silts were predicted to be stable in the floodplain and backwaters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265026","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Great Lakes Restoration Initiative; the Michigan Department of Natural Resources; and the Michigan Department of Environment, Great Lakes, and Energy","usgsCitation":"Roland, C.J., Vaughan, A.A., Fitzpatrick, F.A., Broerman, H.M., and Lund, J.W., 2026, Development of a two-dimensional hydraulic model for the Kalamazoo River between the Trowbridge and Allegan City Dams, Michigan: U.S. Geological Survey Scientific Investigations Report 2026–5026, 54 p., https://doi.org/10.3133/sir20265026.","productDescription":"Report: vii, 54 p.; 2 Data Releases; Dataset","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-175614","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":505721,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119511.htm","linkFileType":{"id":5,"text":"html"}},{"id":505680,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96JBHF4","text":"USGS data release","linkHelpText":"Geomorphic reference reach data for the Kalamazoo River Basin, Michigan Area of Concern (ver. 2.0, October 2024)"},{"id":505679,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":505683,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265026/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5026 HTML"},{"id":505678,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13CPA5B","text":"USGS data release","linkHelpText":"Model application data release for a 2D hydraulic model (HEC–RAS) of the Kalamazoo River Trowbridge Dam to Allegan City Dam reach"},{"id":505677,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5026/images"},{"id":505681,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5026/sir20265026.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5026 XML"},{"id":505675,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5026/sir20265026.pdf","text":"Report","size":"14.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5026"},{"id":505673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5026/coverthb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Allegan City Dam, Kalamazoo River, Trowbridge Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.86167194105684,\n 42.533098\n ],\n [\n -85.7846387,\n 42.533098\n ],\n [\n -85.7846387,\n 42.47972309491453\n ],\n [\n -85.86167194105684,\n 42.47972309491453\n ],\n [\n -85.86167194105684,\n 42.533098\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1992 Folwell Avenue
St. Paul, MN 55108
The U.S. Geological Survey built a detailed computer model of how water moves through a 9.2-mile stretch of the Kalamazoo River between the Trowbridge and Allegan City Dams to support dam removal and river restoration planning. Model results were checked against field measurements of water levels and flow speeds, and the model matched water levels very closely (generally within a few inches). Flow speeds were slightly underpredicted, by an average of 0.28 foot per second. For a streamflow scenario of 4,000 cubic feet per second (a flow size expected in about half of all years), the model showed that in the first 3.4 miles below Trowbridge Dam, average flow speeds are often 3–4 feet per second and sometimes greater than 4 feet per second. Farther downstream, average speeds rarely exceed 3 feet per second. From the simulated bed shear stresses, the smallest riverbed material likely to stay in place at this flow is mostly pebbles (4–64 millimeters) in the main channel. Finer sands and silts are expected to remain stable in floodplain and backwater areas, where currents are slower. The model gives a high-resolution picture of water levels, currents, and sediment stability in places and at streamflow conditions that are hard to measure in the field. Those insights help decision makers understand habitat connectivity and bed stability as they plan dam removal and river restoration actions.
","publicationDate":"2026-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Collin J. 0000-0003-1004-0746","orcid":"https://orcid.org/0000-0003-1004-0746","contributorId":343660,"corporation":false,"usgs":true,"family":"Roland","given":"Collin","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vaughan, Angus A. 0000-0001-9900-4658","orcid":"https://orcid.org/0000-0001-9900-4658","contributorId":302333,"corporation":false,"usgs":true,"family":"Vaughan","given":"Angus","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":963177,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209191,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963178,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Broerman, Heidi M. 0009-0007-2475-5044","orcid":"https://orcid.org/0009-0007-2475-5044","contributorId":330645,"corporation":false,"usgs":true,"family":"Broerman","given":"Heidi M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":211157,"corporation":false,"usgs":true,"family":"Lund","given":"J.","email":"","middleInitial":"William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963180,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276720,"text":"ofr20251058 - 2026 - Preliminary geology of the North Meadow Creek Area, Tobacco Root Mountains, southwest Montana: The North Meadow Creek Fault","interactions":[],"lastModifiedDate":"2026-06-22T21:04:05.576851","indexId":"ofr20251058","displayToPublicDate":"2026-06-18T14:00:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1058","displayTitle":"Preliminary Geology of the North Meadow Creek Area, Tobacco Root Mountains, Southwest Montana: The North Meadow Creek Fault","title":"Preliminary geology of the North Meadow Creek Area, Tobacco Root Mountains, southwest Montana: The North Meadow Creek Fault","docAbstract":"This report documents a previously unmapped fault, informally referred to herein as the North Meadow Creek fault, on the east flank of the Tobacco Mountains of southwestern Montana. This fault has an apparently long and complex history, including Quaternary offset of an older alluvial terrace, offset of a debris flow of presumed Pleistocene age, offset of rhyolite lava flows of presumed Tertiary age from their presumed source several kilometers east, on the opposite side of the fault, and offset and possible rotation of blocks of Archean gneiss on northeast side of the fault. The western part of the fault is covered by glacial moraines of two apparent ages, both Pleistocene.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251058","usgsCitation":"Fuis, G.S., LeClair, P.J., and Ruleman, C.A., 2026, Preliminary geology of the North Meadow Creek Area, Tobacco Root Mountains, southwest Montana—The North Meadow Creek Fault: U.S. Geological Survey Open-File Report 2025–1058, 6 p., https://doi.org/10.3133/ofr20251058.","productDescription":"Report: iv, 6 p.; Data Release; 1 Supplemental Figure; 1 Excel file","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-158436","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":505722,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119512.htm","linkFileType":{"id":5,"text":"html"}},{"id":505651,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P146WVWS","text":"USGS data release","description":"Fuis, G.S., LeClair, P., and Ruleman, C., 2025, Preliminary Geology of the North Meadow Creek Area, Tobacco Root Mountains, Southwest Montana: Measurements along the North Meadow Creek Fault: U.S. Geological Survey data release, https://doi.org/10.5066/P146WVWS.","linkHelpText":"Preliminary Geology of the North Meadow Creek Area, Tobacco Root Mountains, Southwest Montana: Measurements along the North Meadow Creek Fault"},{"id":505746,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2025/1058/ofr20251058_FoliationData.xlsx","text":"Foliation Data","size":"12 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2025-1058 Foliation Data Table"},{"id":505650,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2025/1058/ofr20251058_fig3.pdf","text":"Numbered Foliation Map","size":"505 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1058 Supplemental Figure"},{"id":505648,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1058/coverthb.jpg"},{"id":505649,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1058/ofr20251058.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1058 PDF"}],"country":"United States","state":"Montana","otherGeospatial":"North Meadow Creek Area, Tobacco Root Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.88,\n 45.53\n ],\n [\n -111.74,\n 45.53\n ],\n [\n -111.74,\n 45.47\n ],\n [\n -111.88,\n 45.47\n ],\n [\n -111.88,\n 45.53\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
For more than a century, researchers have debated the route of the Snake River across the northern Cordillera and U.S. Pacific Northwest, including the associated incision history of Hells Canyon. Here, we use detrital zircon U-Pb provenance analysis of Miocene strata upstream and downstream of Hells Canyon to constrain the evolution in fluvial pathways over time. Downstream of Hells Canyon, we show that the ca. 10−6 Ma Clarkston Heights gravel was dominantly sourced from the nearby Salmon and Clearwater rivers but also with substantial input from drainages that now flow into the western Snake River Plain. These same western Snake River Plain drainages were contributing to time-equivalent Lake Idaho strata, upstream of Hells Canyon, indicating a Hells Canyon fluvial connection between the western Snake River Plain and Columbia basin before 6 Ma. Results from Lake Idaho strata suggest a two-phased lacustrine history in the western Snake River Plain: Before ca. 6.0 Ma, lake strata were derived from local tributaries, suggesting that the western Snake River Plain was isolated from the modern upper Snake River system. Between ca. 4.3 Ma and 2.2 Ma, the source area expanded to include eastern tributaries in conjunction with migration of high-standing topography of the Yellowstone hotspot. Our results challenge the long-held hypothesis of “capture” of the Snake River through Hells Canyon. Instead, we infer that Hells Canyon was a long-established route for outflow of lakes occupying the western Snake River Plain, possibly intermittently, during a ca. 10−2 Ma phase of slow regional incision, followed by rapid incision in Hells Canyon starting ca. 2 Ma in conjunction with erosion of the topographic barrier impounding Lake Idaho.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B39068.1","usgsCitation":"Staisch, L.M., O'Connor, J., Cannon, C.M., Holm-Denoma, C., and Schwid, M., 2026, Long-term intermittent connection between the western Snake River Plain and Columbia basin: A two-phased incision history of Hells Canyon: GSA Bulletin, https://doi.org/10.1130/B39068.1.","ipdsId":"IP-183235","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":505669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Hells Canyon, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.5,\n 45.5\n ],\n [\n -119.5,\n 45.5\n ],\n [\n -119.5,\n 42\n ],\n [\n -113.5,\n 42\n ],\n [\n -113.5,\n 45.5\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":963171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":963172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannon, Charles M. 0000-0003-4136-2350 ccannon@usgs.gov","orcid":"https://orcid.org/0000-0003-4136-2350","contributorId":247680,"corporation":false,"usgs":true,"family":"Cannon","given":"Charles","email":"ccannon@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":963173,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":219763,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher S.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":963174,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwid, Maxwel Fredrick 0000-0001-6193-2424","orcid":"https://orcid.org/0000-0001-6193-2424","contributorId":351221,"corporation":false,"usgs":true,"family":"Schwid","given":"Maxwel Fredrick","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":963175,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276735,"text":"70276735 - 2026 - Glacier fed deltas and new age constraints for glacial Lake Grand Gorge in the northern Catskill Mountains of New York State, USA","interactions":[],"lastModifiedDate":"2026-06-18T14:09:27.09568","indexId":"70276735","displayToPublicDate":"2026-06-17T09:01:11","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":24817,"text":"Quaternary","active":true,"publicationSubtype":{"id":10}},"title":"Glacier fed deltas and new age constraints for glacial Lake Grand Gorge in the northern Catskill Mountains of New York State, USA","docAbstract":"Ice-dammed lakes were common along the southern margin of the Laurentide Ice Sheet during deglaciation. In the Schoharie Valley of the northern Catskill Mountains, New York, a 171 km2 lake known as glacial Lake Grand Gorge formed in an interlobate area. Previous researchers suggested that deltas developed into this glacial lake from meltwater supplied by the adjacent Hudson Lobe during deglaciation. This study investigates stratigraphy and sedimentology of Pleistocene deltas and lake deposits to determine the source of meltwater and sediment. Detailed examination of stratigraphy from quarries, stream exposures, and new exploration borings was combined with radiocarbon and OSL geochronology to establish event stratigraphy. Sedimentologic and geomorphic data from deltas in the Manor Kill and Platter Kill Valleys demonstrates that braided outwash was supplied directly from the Westerlo Sublobe that crossed the northeastern escarpment of the Catskill Mountains. New geochronologic data indicates that the lake was established by 28 ka and likely persisted to at least 22 ka. Insects and twigs recovered from lake sediments complement the OSL data and indicate: (1) that the lake was present significantly earlier than previous deglacial models predict, and (2) that it existed in an ice-free area of the northern Catskill Mountains during the last glacial maximum of the MIS 2 glaciation.
","language":"English","publisher":"MDPI","doi":"10.3390/quat9030046","usgsCitation":"Kozlowski, A.L., Frieman, R.A., Backhaus, K.J., Forgeng, H., Feranec, R., and Mahan, S.A., 2026, Glacier fed deltas and new age constraints for glacial Lake Grand Gorge in the northern Catskill Mountains of New York State, USA: Quaternary, v. 9, 46, 41 p., https://doi.org/10.3390/quat9030046.","productDescription":"46, 41 p.","ipdsId":"IP-184993","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":506003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/quat9030046","text":"Publisher Index Page"},{"id":505666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.0633571745086,\n 42.742038204027864\n ],\n [\n -73.70023574382773,\n 42.742038204027864\n ],\n [\n -73.70023574382773,\n 42.08507645967336\n ],\n [\n -75.0633571745086,\n 42.08507645967336\n ],\n [\n -75.0633571745086,\n 42.742038204027864\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2026-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozlowski, Andrew L.","contributorId":372514,"corporation":false,"usgs":false,"family":"Kozlowski","given":"Andrew","middleInitial":"L.","affiliations":[{"id":88329,"text":"New York State Museum - Geological Survey, Albany, New York","active":true,"usgs":false}],"preferred":false,"id":963165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frieman, Richard A.","contributorId":372515,"corporation":false,"usgs":false,"family":"Frieman","given":"Richard","middleInitial":"A.","affiliations":[{"id":88329,"text":"New York State Museum - Geological Survey, Albany, New York","active":true,"usgs":false}],"preferred":false,"id":963166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Backhaus, Karl J.","contributorId":372516,"corporation":false,"usgs":false,"family":"Backhaus","given":"Karl","middleInitial":"J.","affiliations":[{"id":88329,"text":"New York State Museum - Geological Survey, Albany, New York","active":true,"usgs":false}],"preferred":false,"id":963167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forgeng, Hailey","contributorId":372517,"corporation":false,"usgs":false,"family":"Forgeng","given":"Hailey","affiliations":[{"id":88329,"text":"New York State Museum - Geological Survey, Albany, New York","active":true,"usgs":false}],"preferred":false,"id":963168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feranec, Robert 0000-0002-6523-6562","orcid":"https://orcid.org/0000-0002-6523-6562","contributorId":372518,"corporation":false,"usgs":false,"family":"Feranec","given":"Robert","affiliations":[{"id":88330,"text":"New York State Museum - Research and Collections Division, Albany, New York","active":true,"usgs":false}],"preferred":false,"id":963169,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":963170,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70276619,"text":"fs20263006 - 2026 - The 3D Elevation Program—Supporting North Dakota's economy","interactions":[],"lastModifiedDate":"2026-06-22T17:08:36.574777","indexId":"fs20263006","displayToPublicDate":"2026-06-17T05:20:00","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":"2026-3006","displayTitle":"The 3D Elevation Program—Supporting North Dakota’s Economy","title":"The 3D Elevation Program—Supporting North Dakota's economy","docAbstract":"As the northernmost Great Plains State encompassing two geomorphological areas divided by the Missouri River, North Dakota has varied needs for high-resolution elevation data. The top industry in North Dakota is agriculture and related products, and the fastest growing sector is natural resources led by oil and gas extraction and mining, all of which contribute to the State’s economy (U.S. Department of Agriculture, National Agricultural Statistics Service, 2024b). Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP; refer to sidebar) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better (table 1) to meet the many needs of the Nation and North Dakota. The status of available and in-progress 3DEP baseline lidar data in North Dakota is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification 2025 Rev. A (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment (Dewberry, 2012) identified user requirements and conservatively estimated that availability of lidar data would result in at least $12.39 million in new benefits annually to the State. The top nine North Dakota business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20263006","collaboration":"Prepared in cooperation with the North Dakota Department of Water Resources, Federal Emergency Management Agency, and Natural Resources Conservation Service","usgsCitation":"Guidero, E., 2026, The 3D Elevation Program—Supporting North Dakota's economy: U.S. Geological Survey Fact Sheet 2026-3006, 2 p., https://doi.org/10.3133/fs20263006.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-177779","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":505723,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119510.htm","linkFileType":{"id":5,"text":"html"}},{"id":505654,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2026/3006/fs20263006.xml","description":"FS 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Dakota\",\"nation\":\"USA \"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Florida is covered by flat-lying sedimentary strata of the Atlantic and Gulf Coastal Plains. These strata have accumulated since Middle Jurassic time. The pre-Middle Jurassic, or basement, rocks that underlie the Coastal Plain in Florida are known only from drill cores and cuttings recovered from a relatively small number of boreholes. This data report presents petrographic observations and the results of X-ray diffraction analyses of basement rocks from 18 boreholes across Florida in support of the identification, discrimination, and correlation of units for a subcrop geologic map of pre-Middle Jurassic rocks composing Florida’s sub-Coastal Plain geology.
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Release"},"url":"https://doi.org/10.5066/P133DRW5","text":"USGS data release","linkHelpText":"Mineral abundances of selected pre-Middle Jurassic basement rocks beneath the Atlantic and Gulf Coastal Plains in Florida and Alabama from whole-rock powder X-ray diffraction analysis and the Rietveld method"},{"id":500394,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13NBKKC","text":"USGS data release","linkHelpText":"Geochemical data from selected pre-Middle Jurassic basement rocks beneath the Atlantic and Gulf Coastal Plains in Florida and Alabama"},{"id":500398,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3543","text":"USGS Scientific Investigations Map 3543","linkHelpText":"- Geologic Map of Pre-Middle Jurassic Basement Rocks Beneath the Atlantic and Gulf Coastal Plains in Florida"},{"id":500397,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VBO427","text":"USGS data 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\"}}]}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 926A
Reston, VA 20192
Much of the southeastern United States, including all of Florida, is covered by flat-lying sedimentary strata of the Atlantic and Gulf Coastal Plains which have accumulated since Middle Jurassic time. The pre-Middle Jurassic rocks that underlie these coastal plains in Florida, here collectively referred to as “basement,” are known only from a relatively small number of boreholes. This scientific investigations map presents an interpretation of the basement geology in a 1:1,000,000-scale subsurface geologic map with supporting text, data, and figures. The subsurface mapping methodology integrates petrographic, geochronological, thermochronological, geochemical, and mineralogical analyses of drill cores and cuttings in the context of regional geophysical data.
The pre-Middle Jurassic rocks of Florida consist of the Gondwanan (West African) Suwannee terrane which was accreted to Laurentia during the Alleghanian orogeny and subsequently intruded by Permian granites, superposed by early Mesozoic rift basins, and partially overlain by bimodal Jurassic volcanic rocks. The younger basement components, specifically the Southwest Florida volcanic province, North Florida tholeiites, early Mesozoic rift basins, and Alleghanian granitoids, have correlative and contemporaneous units throughout the Appalachian orogen. In contrast, Florida’s older basement rocks, including Paleozoic siliciclastic strata of the Suwannee basin, North Florida volcanic series, Osceola and Gaskin intrusive complexes, and the St. Lucie Metamorphic Complex, have neither surface exposures nor unequivocal correlates. Major structures include early Mesozoic normal faults and northwest-striking transfer zones such as the Jay fault. Many of these faults define the boundaries of subbasins within the South Georgia rift system. Top-of-basement structure contours show gentle arches and embayments that are also recognized in overlying coastal plain strata.
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\"}}]}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 926A
Reston, VA 20192
The Landsat program has provided over 54 years of multispectral imagery, contributing vital information for agricultural and forestry scientific research and operational activities. Freely available Landsat data have enabled scientists to analyze land use patterns, assess ecological impacts, and develop strategies for sustainable management. We explored Landsat’s pivotal role through the lens of the United States Group on Earth Observations 2023 Earth Observation Assessment (EOA). The EOA included comprehensive surveys of more than 2000 federally supported Earth observation data products. We subsequently analyzed how Landsat satellite data and derived products support agricultural and forestry-related priorities compared to other Earth observation inputs. We evaluated both direct and indirect applications of the data, identifying key users across federal agencies and assessing how Landsat data contribute to critical products, services, and objectives. The results indicate that Landsat provides key information to support diverse activities across agriculture and forestry sectors, such as enhancing food supply, improving resilience to disaster and disturbance events, maximizing ecosystem productivity and conservation, and supporting regulatory requirements and decision-making. The Landsat OLI and TIRS sensors ranked 4th and 10th, respectively, out of 1171 Earth observation inputs identified in the study, underscoring their value to agriculture and forestry.
","language":"English","publisher":"MDPI","doi":"10.3390/rs18122003","usgsCitation":"Wengert, E., Rowe, J., Ramaseri Chandra, S.N., Vanderhoof, M.K., Garthwaite, I., Wu, Z., Snyder, G., Casey, K., Straub, C.L., Opstal, D.W., and Hinkley, E., 2026, Quantifying Landsat’s contributions to U.S. agricultural and forestry applications: Remote Sensing, v. 18, no. 12, 2003, 25 p., https://doi.org/10.3390/rs18122003.","productDescription":"2003, 25 p.","ipdsId":"IP-187199","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":86069,"text":"National Land Imaging","active":true,"usgs":true}],"links":[{"id":506061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18122003","text":"Publisher Index Page"},{"id":505773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"12","noUsgsAuthors":false,"publicationDate":"2026-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Wengert, Ellen","contributorId":348198,"corporation":false,"usgs":false,"family":"Wengert","given":"Ellen","affiliations":[{"id":83320,"text":"KBR Inc., contractor to the US Geological Survey, Reston, VA.","active":true,"usgs":false}],"preferred":false,"id":963387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowe, Jordan","contributorId":348199,"corporation":false,"usgs":false,"family":"Rowe","given":"Jordan","affiliations":[{"id":83320,"text":"KBR Inc., contractor to the US Geological Survey, Reston, VA.","active":true,"usgs":false}],"preferred":false,"id":963388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramaseri Chandra, Shankar N.","contributorId":372677,"corporation":false,"usgs":false,"family":"Ramaseri Chandra","given":"Shankar","middleInitial":"N.","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":963389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":5044,"text":"National Research Program - 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2026 - Assessing the state of hydrologic science in the Upper Klamath Basin—A comprehensive review of data, tools, and models","interactions":[],"lastModifiedDate":"2026-06-24T01:49:41.620498","indexId":"sir20265139","displayToPublicDate":"2026-06-16T09:40:00","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":"2026-5139","displayTitle":"Assessing the State of Hydrologic Science in the Upper Klamath Basin—A Comprehensive Review of Data, Tools, and Models","title":"Assessing the state of hydrologic science in the Upper Klamath Basin—A comprehensive review of data, tools, and models","docAbstract":"Water demand in the Upper Klamath Basin (UKB) from various stakeholders and ecological needs often outstrips available supply, leading to persistent management challenges. This study reviews the state of hydrologic science within the UKB as of 2025—specifically, the tools, data, and models available for assessing five key components of the water system: (1) surface water; (2) precipitation; (3) evapotranspiration; (4) groundwater; and (5) water use. The UKB water supply is critical for Native American communities, regional agriculture, and federally listed fishes and faces challenges from competing needs, climate variability, and operational/regulatory requirements. We assess existing datasets, regional and national models, and historical studies to understand the available resources and identify gaps that may hinder integrated water assessments and management. Our findings indicate areas where improvements in data collection and model precision could improve the accuracy of water-availability forecasts and support water-management practices. This review can inform near-term forecasting, assist in optimizing water-resource data collection and management strategies, and support regional water-availability assessments of the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265139","programNote":"Water Resources Mission Area—Water Availability and Use Science Program","usgsCitation":"Stonewall, A.J., Harden, T.M., Reale, J.K., and Cameron, C.R., 2026, Assessing the state of hydrologic science in the Upper Klamath Basin—A comprehensive review of data, tools, and models: U.S. Geological Survey Scientific Investigations Report 2026–5139, 56 p., https://doi.org/10.3133/sir20265139.","productDescription":"ix, 56 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-172128","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":505322,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5139/images"},{"id":505321,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5139/sir20265139.XML","description":"SIR 2026-5139 XML"},{"id":505316,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265139/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5139 HTML"},{"id":505315,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5139/sir20265139.pdf","text":"Report","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5139 PDF"},{"id":505314,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5139/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.56735919450429,\n 43.22749799340821\n ],\n [\n -120.5,\n 43.22749799340821\n ],\n [\n -120.5,\n 42.04358684993929\n ],\n [\n -122.56735919450429,\n 42.04358684993929\n ],\n [\n -122.56735919450429,\n 43.22749799340821\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, Oregon 97204
The Upper Klamath Basin (UKB), located in southern Oregon, includes Upper Klamath Lake and its tributaries. Upper Klamath Lake forms the headwaters of the Klamath River, which flows into northern California. The UKB is essential to the region’s ecology and serves as the main water source for the surrounding area. The water resources of the UKB are used in various ways, including irrigation for agriculture, domestic and industrial use, and commercial and recreational fishing. Over time, these competing demands have contributed to increased water stress in the UKB, complicating water allocation and contributing to more variable lake levels. Accurate lake-level forecasting is needed to inform management of lake water, but these competing demands also complicate efforts to forecast lake levels. This report offers an overview of the historical and current tools and methods used to monitor and forecast hydrological conditions in the UKB. The report highlights key factors affecting water availability, such as groundwater and surface-water dynamics, climate-related effects, precipitation patterns, and evapotranspiration (the combined water loss to the atmosphere through evaporation from surfaces and transpiration from plants). The tools and methods used to monitor the UKB include statistical techniques, computer modeling, field measurements, and high-tech instrumentation, and the report highlights their strengths and weaknesses. This analysis of the state of science in the UKB offers a synthesis of existing tools, models and data to inform future research, data collection, and water-management decisions. The objectives of this analysis are to (1) facilitate the availability of high-quality data to water managers, (2) aid water-management decision-making and UKB stewardship programs, and (3) improve the accuracy of water supply forecasting.
","publicationDate":"2026-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Stonewall, Adam J. 0000-0002-3277-8736 stonewal@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-8736","contributorId":139097,"corporation":false,"usgs":true,"family":"Stonewall","given":"Adam","email":"stonewal@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harden, Tessa M. 0000-0001-9854-1347","orcid":"https://orcid.org/0000-0001-9854-1347","contributorId":85690,"corporation":false,"usgs":false,"family":"Harden","given":"Tessa M.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":962770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reale, Justin K. 0000-0003-3523-4782","orcid":"https://orcid.org/0000-0003-3523-4782","contributorId":366407,"corporation":false,"usgs":true,"family":"Reale","given":"Justin","middleInitial":"K.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962771,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cameron, Cortney R. 0000-0001-7362-2810","orcid":"https://orcid.org/0000-0001-7362-2810","contributorId":372104,"corporation":false,"usgs":false,"family":"Cameron","given":"Cortney","middleInitial":"R.","affiliations":[{"id":34888,"text":"Oregon Water Resources Department","active":true,"usgs":false}],"preferred":false,"id":962772,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70276715,"text":"70276715 - 2026 - Continental-scale prediction of hydrologic signatures and processes","interactions":[],"lastModifiedDate":"2026-06-17T14:40:48.757748","indexId":"70276715","displayToPublicDate":"2026-06-16T09:32:56","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":24816,"text":"Hydrology and Earth System Sciences (HESS)","active":true,"publicationSubtype":{"id":10}},"title":"Continental-scale prediction of hydrologic signatures and processes","docAbstract":"Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures.
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Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1008","displayTitle":"Field Methods, Quality-Assurance, and Data Management Plan for Water-Quality Activities and Water-Level Measurements, Idaho National Laboratory, Idaho","title":"Field methods, quality-assurance, and data management plan for water-quality activities and water-level measurements, Idaho National Laboratory, Idaho","docAbstract":"Water-quality activities and water-level measurements conducted by the U.S. Geological Survey (USGS) Idaho National Laboratory (INL) Project Office coincide with the USGS mission of evaluating the quantity and quality of the Nation’s water resources. The activities are conducted in cooperation with the U.S. Department of Energy’s (DOE) Idaho Operations Office. Results of water-quality and hydraulic head research efforts are presented in various USGS and scientific journal publications (refer to Fisher, 2022). These data are stored internally in the Aquarius Time Series and Aquarius Samples databases and are publicly accessible through National Water Quality Monitoring Council (2025) and U.S. Geological Survey (2025). Data collected from our studies are used by researchers, Federal and State agencies, water management and regulatory organizations, as well as the public.
This quality assurance plan (QAP) describes the methods and processes for field methods, data collection, data management, data auditing, and equipment management for both the water-quality and water-level programs at the USGS INL Project Office (hereto referred to as INL Project Office). A comprehensive quality assurance (QA) plan ensures that the processes defined in this document will guide the program staff to collect and publish reliable, useful, and defensible data products for stakeholders. This QAP supersedes previous versions of this document and is intended to complement the Quality Assurance and Data Management (QADM) Plan for the Idaho Water Science Center (IDWSC; Christopher Mebane and Lauren Zinsser, written commun., 2024).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261008","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Treinen, K.C., Trcka, A.R., Zingre, J.A., and Wehnke, A.J., 2026, Field methods, quality-assurance, and data management plan for water-quality activities and water-level measurements, Idaho National Laboratory, Idaho: U.S. Geological Survey Open-File Report 2026–1008, 51 p., https://doi.org/10.3133/ofr20261008.","productDescription":"viii, 51 p.","onlineOnly":"Y","ipdsId":"IP-172087","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":505579,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261008/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1008"},{"id":505310,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1008/ofr20261008.xml"},{"id":505309,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1008/images"},{"id":505301,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1008/ofr20261008.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1008"},{"id":505300,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1008/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd.
Boise, ID 83702-4520