Many communities and ecosystems in the United States that are dependent on groundwater are potentially adversely affected by groundwater drought. We computed yearly groundwater-drought metrics and mean groundwater levels at well locations across the conterminous United States (CONUS), using data from wells and remotely sensed and modeled Gravity Recovery and Climate Experiment Drought Monitor Data Assimilation (GRACE-DADM). We also modeled the probability of low or high human impact at each well location. The spatial distribution of groundwater-drought duration and severity from 2001 to 2020 for 1,510 wells shows longer maximum duration and higher maximum severity events in drier regions like the Southwest than in wetter regions like the Northeast. Based on 613 wells in CONUS from 1981 to 2020, there are many significant decreases in drought duration and severity in the Northeast and many significant increases in annual-mean groundwater levels. In contrast, there are many significant increases in drought metrics and decreases in mean water levels in parts of the Southeast. There are major differences in trends from 2001 to 2020 between well-based and GRACE-DADM-based groundwater metrics in some CONUS regions and a very low correlation between trends at individual locations across CONUS. A potential reason for this disparity is the low GRACE-DADM resolution (∼12 km) and the potential for a large amount of groundwater variation at the local scale. Also, GRACE-DADM represents shallow, unconfined aquifers which may not match the screened interval of the monitoring wells we evaluated. Large spatial gaps in long-term, high frequency, and quality-assured groundwater-well monitoring data present a challenge for understanding groundwater-drought variability across CONUS. Remote sensing tools such as GRACE can help but cannot fully replace well monitoring, as highlighted by our study results. Substantially more long-term monitoring wells would more accurately represent groundwater-drought trends and spatial variability across CONUS, particularly in western regions.
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0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":451,"text":"National Water Quality Assessment 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origin","interactions":[],"lastModifiedDate":"2026-03-13T14:29:50.599041","indexId":"70274211","displayToPublicDate":"2026-03-11T09:20:41","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin","docAbstract":"Per- and polyfluoroalkyl substances (PFAS) are a class of widespread, environmentally persistent compounds that pose a potential threat to wildlife and human health. Despite recent efforts to reduce the use of long-chain PFAS in industrial practices and commercial/consumer products, the persistence and solubility of PFAS have led to their detection in wildlife on a global scale. Osprey (Pandion haliaetus) have long been used as a sentinel species with an extensive history of serving as an effective bioindicator of contamination. Here we report on a large-scale evaluation of PFAS and potential health effects in osprey from the Chesapeake and Delaware Bays, USA. In 2011 and 2015, we collected plasma samples from osprey nestlings throughout the Chesapeake and Delaware Bay watersheds. We quantified 40 PFAS congeners in osprey plasma via liquid chromatography-mass spectrometry and analyzed plasma for indicators of immune and thyroid function, and plasma biochemistry. In all birds, perfluorooctanesulfonic acid (PFOS) was the most commonly detected PFAS, followed by perfluoroundecanoic acid, (PFUnA) and perfluorodecanoic acid (PFDA). In nestling plasma from Chesapeake Bay, PFOS tended to be a higher average contributor to PFAS profiles compared to samples from Delaware Bay. In contrast, long-chain perfluoroalkyl carboxylic acids (PFCAs) such as PFUnA and PFDA comprised larger percentages of total PFAS in osprey plasma from Delaware Bay relative to Chesapeake Bay. While some PFAS concentrations were associated with plasma health indicators, the proportion of variation explained was low. Overall, our study provides a more thorough understanding of PFAS presence in the Chesapeake and Delaware Bays and is one of the first to examine whether PFAS exposure is associated with adverse health effects in wildlife.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgag055","usgsCitation":"Karouna-Renier, N., Haskins, D., Schultz, S.L., Akresh, M., and Rattner, B., 2026, Accumulation of per- and polyfluoroalkyl substances (PFAS) and their association with immune parameters in nestling ospreys (Pandion haliaetus) from Chesapeake and Delaware Bays, USA: Environmental Toxicology and Chemistry, https://doi.org/10.1093/etojnl/vgag055.","ipdsId":"IP-183725","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501383,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70274236/images"},{"id":501382,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70274236/70274236.XML"},{"id":501381,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70274236/full"},{"id":501230,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake and Delaware Bays","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.61761223029669,\n 39.86211116682409\n ],\n [\n -76.93592404163553,\n 39.86211116682409\n ],\n [\n -76.93592404163553,\n 36.61322897844552\n ],\n [\n -74.61761223029669,\n 36.61322897844552\n ],\n [\n -74.61761223029669,\n 39.86211116682409\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haskins, David Lee 0000-0002-6692-3225","orcid":"https://orcid.org/0000-0002-6692-3225","contributorId":357996,"corporation":false,"usgs":true,"family":"Haskins","given":"David Lee","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":957121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, Sandra L. 0000-0003-3394-2857 sschultz@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-2857","contributorId":5966,"corporation":false,"usgs":true,"family":"Schultz","given":"Sandra","email":"sschultz@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Akresh, Michael E.","contributorId":355344,"corporation":false,"usgs":false,"family":"Akresh","given":"Michael E.","affiliations":[{"id":83385,"text":"Antioch University","active":true,"usgs":false}],"preferred":false,"id":957123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rattner, Barnett 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":221814,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957124,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274632,"text":"70274632 - 2026 - Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution","interactions":[],"lastModifiedDate":"2026-04-02T18:44:26.919721","indexId":"70274632","displayToPublicDate":"2026-03-10T11:32:48","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution","title":"Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution","docAbstract":"Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence Micropterus dolomieu (Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2026.181562","usgsCitation":"Sorensen, S.F., Fox, J.T., and Magoulick, D.D., 2026, Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution: Science of the Total Environment, v. 1025, 181562, 9 p., https://doi.org/10.1016/j.scitotenv.2026.181562.","productDescription":"181562, 9 p.","ipdsId":"IP-176491","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":502098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2026.181562","text":"Publisher Index Page"},{"id":502032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark-Ouachita Interior Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.06835076729865,\n 37.54392591075137\n ],\n [\n -95.58753725694291,\n 35.616131979244244\n ],\n [\n -96.86430792379102,\n 34.30485408838467\n ],\n [\n -95.13839254168458,\n 34.13182914589751\n ],\n [\n -93.02844126052034,\n 33.84485206480821\n ],\n [\n -91.20526644252189,\n 35.93662462412837\n ],\n [\n -90.46426221649432,\n 38.03635872039271\n ],\n [\n -95.06835076729865,\n 37.54392591075137\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1025","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sorensen, Sarah F.","contributorId":369126,"corporation":false,"usgs":false,"family":"Sorensen","given":"Sarah","middleInitial":"F.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, J. Tyler","contributorId":369127,"corporation":false,"usgs":false,"family":"Fox","given":"J.","middleInitial":"Tyler","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958497,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274195,"text":"sim3545 - 2026 - Water use permits as of July 2024 and reported water use near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023","interactions":[],"lastModifiedDate":"2026-03-13T16:57:02.210512","indexId":"sim3545","displayToPublicDate":"2026-03-09T11:44:43","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":"3545","displayTitle":"Water Use Permits as of July 2024 and Reported Water Use Near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023","title":"Water use permits as of July 2024 and reported water use near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023","docAbstract":"Starting in the early 2000s, increasing oil and gas development in western North Dakota created a need for additional water resources from surface-water and groundwater sources near the North Unit of Theodore Roosevelt National Park. To summarize the use of water in that area, the U.S. Geological Survey, in cooperation with the National Park Service, developed a map of surface-water and groundwater resources, aquifers, and water-use diversions, and plotted water-use trends from 1980 to 2023. Reported water used from permits in the map area has more than doubled since 2020, increasing from about 750 acre-feet in 2020 to about 2,300 acre-feet in 2022 and 2,000 acre-feet in 2023. Surface water provided the primary source of reported water used for the study period with an average of about 410 acre-feet per year from 1980 through 2017 and about 1,330 acre-feet per year from 2018 through 2023. After 2011, groundwater sourced from the Little Missouri River, Tobacco Garden Creek, Fox Hills, Fort Union, and Dakota aquifers became a larger portion of total annual reported water use from permits in the map area. From 1980 through 2015, water use for irrigation averaged 86 percent of the total annual reported surface-water and groundwater use in the map area. Starting in 2011, however, industrial uses became a proportionally larger total use of water, and in 2015, became the highest reported volume of water use in the map area. From 2011 to 2023, industrial use designated for water depots increased from 50 acre-feet to about 1,370 acre-feet, accounting for about 70 percent of total reported water use in the map area in 2023.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3545","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Anderson, T.M., and Medler, C.J., 2026, Water use permits as of July 2024 and reported water use near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023: U.S. Geological Survey Scientific Investigations Map 3545, 1 p., scale 1:75,000, https://doi.org/10.3133/sim3545.","productDescription":"1 Sheet: 51.96 x 32.00 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-180137","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":501164,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119300.htm","linkFileType":{"id":5,"text":"html"}},{"id":500796,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3545/sim3545.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3545"},{"id":500795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3545/coverthb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"North Unit of Theodore Roosevelt National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.68187232257335,\n 47.72042516981429\n ],\n [\n -103.68187232257335,\n 47.454023726420644\n ],\n [\n -103.19621849492077,\n 47.454023726420644\n ],\n [\n -103.19621849492077,\n 47.72042516981429\n ],\n [\n -103.68187232257335,\n 47.72042516981429\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
This map shows the location of water permits and graphs of the reported amount of water used from those permits from rivers, streams, and wells as of July 2024, near Theodore Roosevelt National Park in North Dakota. Total water use in the map area more than doubled from 2020 to 2023. From 1980 through 2023, water from rivers and streams was used more than water from wells, but water use from wells began to increase starting in 2011. From 1980 through 2015, most water was used for irrigation, but after 2015, most water was used for industrial purposes.
","publicationDate":"2026-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Todd M. 0000-0001-8971-9502","orcid":"https://orcid.org/0000-0001-8971-9502","contributorId":218978,"corporation":false,"usgs":true,"family":"Anderson","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medler, Colton J. 0000-0001-6119-5065","orcid":"https://orcid.org/0000-0001-6119-5065","contributorId":201463,"corporation":false,"usgs":true,"family":"Medler","given":"Colton","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956900,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274560,"text":"70274560 - 2026 - Estimating discharge from undular hydraulic jumps: Feasibility assessment based on flume experiments","interactions":[],"lastModifiedDate":"2026-03-30T15:40:22.34149","indexId":"70274560","displayToPublicDate":"2026-03-07T10:28:17","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating discharge from undular hydraulic jumps: Feasibility assessment based on flume experiments","docAbstract":"Rapids are common in steep rivers, often forming where flow transitions from supercritical (Froude number, Fr > 1) to subcritical (Fr < 1) through a hydraulic jump. When upstream Fr is supercritical but close to 1, this transition may occur as an undular hydraulic jump, exhibiting a train of stationary waves downstream of the jump toe. Previous studies proposed a method to estimate discharge using only UHJ wave spacing and channel width combined with a wave dispersion equation for large water depths relative to the UHJ wavelength. This method is based on the hypotheses that, by their presence, UHJs indicate near-critical flow conditions (Fr ≈ 1) and that wave celerity c is equal to and opposite the cross-sectionally averaged flow velocity U. However, these hypotheses have not been thoroughly tested. We used data from published UHJ flume experiments to test the hypotheses that Fr ≈ 1 and c = U, compare the deep-water and general wave dispersion equations, and evaluate the accuracy of discharge estimates. In these experiments, the stationary waves exhibited shallow depths relative to wavelength and flow was subcritical (Fr < 1) when averaged across multiple wavelengths. Additionally, wave celerity more closely approximated the surface flow velocity than U. By using a Fr representative of actual conditions and applying a coefficient to correct for c ≠ U , the accuracy of the discharge estimates improved. This finding suggests that the critical flow-based method is robust and can produce reliable streamflow estimates if the remotely observed wave trains are correctly interpreted as UHJs, without requiring in situ measurements.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040997","usgsCitation":"White, D., Yager, E., Legleiter, C.J., Grant, G., Hempel, L.A., Leonard, C.M., Adler, K., Harlan, M.E., and Fasth, B., 2026, Estimating discharge from undular hydraulic jumps: Feasibility assessment based on flume experiments: Water Resources Research, v. 62, no. 3, e2025WR040997, 19 p., https://doi.org/10.1029/2025WR040997.","productDescription":"e2025WR040997, 19 p.","ipdsId":"IP-172038","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":502062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr040997","text":"Publisher Index Page"},{"id":501815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Daniel C. 0000-0001-8376-8469","orcid":"https://orcid.org/0000-0001-8376-8469","contributorId":347543,"corporation":false,"usgs":false,"family":"White","given":"Daniel C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":958310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Elowyn 0000-0002-3382-2356","orcid":"https://orcid.org/0000-0002-3382-2356","contributorId":347542,"corporation":false,"usgs":false,"family":"Yager","given":"Elowyn","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":958311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":958312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grant, Gordon","contributorId":349384,"corporation":false,"usgs":false,"family":"Grant","given":"Gordon","affiliations":[{"id":83479,"text":"US Forest Service, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":958314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leonard, Christina M. 0000-0002-5096-8103","orcid":"https://orcid.org/0000-0002-5096-8103","contributorId":360578,"corporation":false,"usgs":false,"family":"Leonard","given":"Christina","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":958315,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Adler, Katherine","contributorId":369026,"corporation":false,"usgs":false,"family":"Adler","given":"Katherine","affiliations":[],"preferred":false,"id":958316,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harlan, Merritt Elizabeth 0000-0002-4019-4888","orcid":"https://orcid.org/0000-0002-4019-4888","contributorId":302672,"corporation":false,"usgs":true,"family":"Harlan","given":"Merritt","email":"","middleInitial":"Elizabeth","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":958317,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fasth, Becky","contributorId":349390,"corporation":false,"usgs":false,"family":"Fasth","given":"Becky","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":958318,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274666,"text":"70274666 - 2026 - Development and assessment of fluorescent-dyed, preserved invasive grass carp (Ctenopharyngodon idella) eggs as surrogates for live eggs in transport and dispersal control experiments","interactions":[],"lastModifiedDate":"2026-04-03T15:31:04.627511","indexId":"70274666","displayToPublicDate":"2026-03-07T10:24:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Development and assessment of fluorescent-dyed, preserved invasive grass carp (Ctenopharyngodon idella) eggs as surrogates for live eggs in transport and dispersal control experiments","title":"Development and assessment of fluorescent-dyed, preserved invasive grass carp (Ctenopharyngodon idella) eggs as surrogates for live eggs in transport and dispersal control experiments","docAbstract":"Invasive species such as grass carp (Ctenopharyngodon idella) pose substantial ecological threats to North American freshwater ecosystems. Understanding their early life stage behavior is critical for management efforts. From spawning to hatching, invasive carp eggs must remain suspended in the water column while drifting downstream for the best chance of survival. This highly vulnerable life stage is a potential target for population control to reduce recruitment. However, studying egg transport and potential dispersal control techniques is challenging, because the availability of live eggs and time period for experimentation are extremely limited. Additionally, accurately replicating the physical characteristics and transport mechanisms of fish eggs using surrogates in laboratory and field studies is not trivial. This study presents a novel method to create fluorescein-dyed, preserved grass carp eggs as surrogates for live eggs in transport and dispersal control experiments. This technique enables year-round studies of grass carp egg transport, offering managers a reliable tool for developing and testing dispersal control and passive sampling methods for invasive carp eggs. In this study, we rehydrate and dye preserved grass carp eggs in varying concentrations of aqueous fluorescein for a range of rehydration times, evaluate dye retention and egg visibility under ultraviolet light (UV-A), and measure diameters and settling velocities for comparison with live eggs. Eggs rehydrated in 0.100 g per liter fluorescein for 30 min maintain adequate brightness for up to 40 min in mixed conditions and exhibit mean settling velocities and densities similar to live eggs, making them ideal for laboratory experiments using quantitative imaging techniques.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.70124","usgsCitation":"Doyle, H.F., Stahlschmidt, B.H., Herndon, A.M., Prasad, V., George, A.E., Fischer, J.R., Jackson, P.R., Cory D. Suski, and Tinoco, R.O., 2026, Development and assessment of fluorescent-dyed, preserved invasive grass carp (Ctenopharyngodon idella) eggs as surrogates for live eggs in transport and dispersal control experiments: River Research and Applications, https://doi.org/10.1002/rra.70124.","ipdsId":"IP-172670","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Doyle, Henry F. 0000-0001-9942-8602","orcid":"https://orcid.org/0000-0001-9942-8602","contributorId":369222,"corporation":false,"usgs":false,"family":"Doyle","given":"Henry","middleInitial":"F.","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":958621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stahlschmidt, Benjamin H. 0000-0001-6197-662X","orcid":"https://orcid.org/0000-0001-6197-662X","contributorId":211250,"corporation":false,"usgs":true,"family":"Stahlschmidt","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herndon, Anne Marie 0000-0002-7057-0303","orcid":"https://orcid.org/0000-0002-7057-0303","contributorId":332776,"corporation":false,"usgs":true,"family":"Herndon","given":"Anne","email":"","middleInitial":"Marie","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prasad, Vindhyawasini 0000-0003-0585-7217","orcid":"https://orcid.org/0000-0003-0585-7217","contributorId":296287,"corporation":false,"usgs":false,"family":"Prasad","given":"Vindhyawasini","email":"","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":958624,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958625,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fischer, Jesse Robert 0000-0002-9071-7931","orcid":"https://orcid.org/0000-0002-9071-7931","contributorId":329677,"corporation":false,"usgs":true,"family":"Fischer","given":"Jesse","email":"","middleInitial":"Robert","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958626,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":958627,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cory D. Suski","contributorId":369224,"corporation":false,"usgs":false,"family":"Cory D. Suski","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":958628,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tinoco, Rafael O.","contributorId":211779,"corporation":false,"usgs":false,"family":"Tinoco","given":"Rafael","email":"","middleInitial":"O.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":958629,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274277,"text":"70274277 - 2026 - Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach","interactions":[],"lastModifiedDate":"2026-03-24T17:12:07.583859","indexId":"70274277","displayToPublicDate":"2026-03-07T10:02:44","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach","docAbstract":"Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2026.114741","usgsCitation":"Norman, L., Petrakis, R.E., Wilson, N.R., Middleton, B.R., Villarreal, M.L., Pollock, M., Minckley, T.A., and Hendrickson, D., 2026, Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach: Ecological Indicators, v. 184, 114741, 16 p., https://doi.org/10.1016/j.ecolind.2026.114741.","productDescription":"114741, 16 p.","ipdsId":"IP-179305","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":501684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2026.114741","text":"Publisher Index Page"},{"id":501477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, New Mexico","otherGeospatial":"Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.05152972005978,\n 33.0768867725987\n ],\n [\n -112.05152972005978,\n 29.88732922369421\n ],\n [\n -108.36301240182003,\n 29.88732922369421\n ],\n [\n -108.36301240182003,\n 33.0768867725987\n ],\n [\n -112.05152972005978,\n 33.0768867725987\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Natalie R. 0000-0001-5145-1221 nrwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":214982,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie","email":"nrwilson@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, Barry R.","contributorId":367728,"corporation":false,"usgs":false,"family":"Middleton","given":"Barry","middleInitial":"R.","affiliations":[{"id":36921,"text":"Ret. USGS","active":true,"usgs":false}],"preferred":false,"id":957550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":214980,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pollock, Michael","contributorId":367729,"corporation":false,"usgs":false,"family":"Pollock","given":"Michael","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":957552,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Minckley, Thomas A.","contributorId":367730,"corporation":false,"usgs":false,"family":"Minckley","given":"Thomas","middleInitial":"A.","affiliations":[{"id":87617,"text":"University of Wyoming, Department of Geology and Geophysics, Laramie, WY 82071-2000","active":true,"usgs":false}],"preferred":false,"id":957553,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hendrickson, Dean","contributorId":367731,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Dean","affiliations":[{"id":87618,"text":"University of Texas at Austin, College of Natural Sciences, Austin, TX 78712","active":true,"usgs":false}],"preferred":false,"id":957554,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70274196,"text":"ofr20261063 - 2026 - Evaluation of turbidity corrections for EXO fluorescent dissolved organic matter (fDOM) sensors","interactions":[],"lastModifiedDate":"2026-03-06T21:45:10.353284","indexId":"ofr20261063","displayToPublicDate":"2026-03-06T11:20:00","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":"2026-1063","displayTitle":"Evaluation of Turbidity Corrections for EXO Fluorescent Dissolved Organic Matter (fDOM) Sensors","title":"Evaluation of turbidity corrections for EXO fluorescent dissolved organic matter (fDOM) sensors","docAbstract":"The use of field-deployable fluorescence sensors to better understand dissolved organic matter concentrations and composition has grown immensely in recent years. Applications of these sensors to critical monitoring efforts have also grown, encompassing post-fire monitoring, wastewater tracking, and use as a proxy for various contaminants. Despite the growth, it is well known that these sensors require corrections for temperature (Watras and others, 2011) and are subject to many light-field interferences caused by both scattering and absorbance due to dissolved and particulate substances (Downing and others, 2012; Lee and others, 2015; Booth and others, 2023). The most common fluorescence sensors used by the U.S. Geological Survey (USGS) include those targeting fluorescent dissolved organic matter (fDOM) and chlorophylls. Because fDOM sensors primarily measure fluorescence in the dissolved to colloidal phases, corrections to the interferences caused by particulates can be made relatively easily. By the end of 2024, the USGS had 69 fDOM sensors deployed within official water quality monitoring networks included on the USGS National Water Dashboard (https://dashboard.waterdata.usgs.gov/app/nwd/en/) and numerous others used in surveys and research applications across the Nation.
Although temperature corrections are widely applicable across sensor models, interference corrections can be model specific due to differences in design specifications across manufacturers and models (Booth and others, 2023). The corrections are also potentially subject to changes in manufacturing within a specific sensor model. Recently, USGS staff obtained information regarding possible changes in the manufacturing of its most widely-used fDOM sensor model, raising concerns about data consistency and quality in the USGS fDOM sensor networks.
Furthermore, changes in turbidity sensors since the corrections guidance was performed may also affect the performance of the corrections. The turbidity sensor used in the original experiments (Downing and others, 2012) was determined to have a signal output approximately 1.3 times higher than the output of the turbidity sensor currently used in an extensive field comparison study (Messner and others, 2023). With these changes, it is imperative that the corrections be reevaluated to maintain data consistency and continuity across the USGS.
In this study, we evaluated turbidity corrections for fDOM sensors over a range of serial numbers covering manufacturing dates 2015 through 2022 and turbidity serial numbers covering the range 2013 through 2022. The goal was to determine whether reported changes in the manufacturing process of the fDOM and turbidity sensors affected the correction approach developed by Downing and others (2012) such that additional guidance would be required to address this manufacturing change. To evaluate, we repeated a laboratory-based test similar to that performed by Downing and others (2012) in which a series of tank experiments with multiple sensors were deployed in a suspension of Elliot Silt Loam (ESL). High turbidities of the ESL suspension were maintained throughout the tank by turbulent recirculation using submersible pumps. Particulates were removed using a recirculated line equipped with a capsule filter (0.45 micron). Measurements were collected throughout the filtration until turbidities reached approximately 5 formazin nephelometric units (FNU; data available in Baxter and others, 2023). Each experimental run included a mixture of unique sensor combinations to account for variability imposed by the turbidity and temperature sensors. The fDOM correction factor was calculated for each combination of fDOM and turbidity sensors included in the test.
We observed no systematic change in fDOM correction coefficients across serial numbers representing manufacturing years 2015 through 2022. However, the results highlighted questions raised about the corrections for high-turbidity samples, as noted in USGS Techniques and Methods (Booth and others, 2023). Applying the inverse of the commonly-used fDOM ratio with a quadratic fit performed better than the exponential fits when correcting fDOM data for turbidity in the ESL laboratory filtration test and generated a simple scale factor correction equation. This approach also served as a better indicator of data quality than the exponential fit approach. Similar to fDOM, more rigorous quality assurance measures may be necessary to evaluate turbidity sensor calibrations and performance. Sensors exceeding a certain age may need to be replaced despite passing quality assurance checks during calibration. Further testing of the turbidity corrections for different sediment and water types is warranted to better understand the variations in the fits and correctable ranges of turbidity in different systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261063","programNote":"Water Resources Mission Area","usgsCitation":"Fleck, J.A., Baxter, T.J., and Hansen, A.M., 2026, Evaluation of turbidity corrections for fluorescent dissolved organic matter (fDOM) sensors: U.S. Geological Survey Open-File Report 2026–1063, 30 p., https://doi.org/10.3133/ofr20261063.","productDescription":"Report: vi, 30 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-171907","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1063/coverthb.jpg"},{"id":500843,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1063/ofr20261063.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1063 PDF"},{"id":500844,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261063/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1063 HTML"},{"id":500845,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1063/ofr20261063.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1063 XML"},{"id":500846,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1063/images"},{"id":500847,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OB430E","text":"USGS data release","linkHelpText":"Fluorescence sensor measurements in sediment suspensions to evaluate turbidity corrections"}],"contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The San Francisco Bay supports thousands of breeding waterbirds annually and hosts large populations of American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), and Forster’s terns (Sterna forsteri). These three species have relied largely on former commercial salt ponds in south San Francisco Bay, which provide wetland foraging habitat and island nesting habitat. The South Bay Salt Pond Restoration Project is in the process of restoring as much as 15,100 acres of these former salt ponds to tidal marsh and tidal mudflats. Although this restoration is expected to have numerous benefits, including providing habitat for tidal wetland-dependent species, improving water quality, buffering against storm surge, and protecting inland areas from sea level rise, the reduction in former salt-pond habitat and nesting islands may negatively affect breeding waterbirds. To address the reduction in former salt-pond habitat available to waterbirds, the South Bay Salt Pond Restoration Project will maintain some pond habitat for wildlife and provide enhancements such as the construction of new islands for nesting. The South Bay Salt Pond Restoration Project follows an adaptive management plan in which waterbird response to the changing landscape is monitored over time to ensure that existing breeding waterbird populations are maintained.
In this report, we provide results of waterbird nest monitoring in south San Francisco Bay during the 2024 breeding season and present these results in the context of annual nest monitoring in south San Francisco Bay since 2005. Overall, Forster’s tern nest abundance in 2024 (1,808 nests) was the highest recorded between 2005 and 2024, and it maintained the high abundance first observed in 2022 (1,727 nests), which reversed the historically low abundance observed during 2015–17. In contrast, nest abundance remained at or near 20-year lows for American avocets (222 nests) and black-necked stilts (126 nests) in 2024, but both species had small increases in their nesting population sizes compared to 2022. In 2024, there were only 3 Forster’s tern, 5 American avocet, and 3 black-necked stilt major colony nesting sites, which is down from the annual averages of 6.6, 12.4, and 6.6 observed during 2005–09. Nest success (73 percent for American avocets, 54 percent for black-necked stilt, and 64 percent for Forster’s terns) increased compared to 2022 (30 percent for American avocets, 29 percent for black-necked stilt, and 53 percent for Forster’s terns) and during 2005–10 (37 percent for American avocets, 24 percent for black-necked stilt, and 61 percent for Forster’s terns). Nest success in 2024 was above (American avocets and black-necked stilts) or slightly below (Forster’s terns) baseline values established for the South Bay Salt Pond Restoration Project. Average egg-hatching success was lower for American avocets (86 percent) and Forster’s terns (86 percent) and similar for black-necked stilts (96 percent) than the values observed during 2005–10. Average clutch sizes for American avocets (3.87 eggs), black-necked stilts (3.88 eggs), and Forster’s terns (2.73 eggs) were greater than what was observed in 2022 and during 2005–10. Average nest-initiation dates in 2024 were substantially earlier among all three species (April 19 for American avocets, April 25 for black-necked stilts, and May 12 for Forster’s terns) than in 2022 (May 4 for American avocets, May 13 for black-necked stilts, and May 20 for Forster’s terns) and during 2005–10 (May 15 for American avocets, May 3 for black-necked stilts, and May 30 for Forster’s terns). Finally, the enhanced managed ponds with newly constructed islands (Ponds A16 and SF2) supported 52 percent of American avocet nests, 47 percent of black-necked stilt nests, and 94 percent of all the Forster’s tern nests recorded in south San Francisco Bay in 2024.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261064","collaboration":"Prepared in cooperation with the California State Coastal Conservancy, California Wildlife Foundation, California Department of Fish and Wildlife, U.S. Fish and Wildlife Service, and South Bay Salt Pond Restoration Project","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Ackerman, J.T., Hartman, C.A., and Herzog, M., 2026, Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2024 breeding season: U.S. Geological Survey Open-File Report 2026–1064, 27 p., https://doi.org/10.3133/ofr20261064.","productDescription":"Report: vi, 27 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-177737","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":500738,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13VVTPR","text":"USGS data release","linkHelpText":"Waterbird nest abundance in south San Francisco Bay"},{"id":500737,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1064/images"},{"id":500736,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1064/ofr20261064.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1064 XML"},{"id":500733,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1064/coverthb.jpg"},{"id":500734,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1064/ofr20261064.pdf","text":"Report","size":"4.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1064 PDF"},{"id":500735,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261064/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1064 HTML"}],"country":"United States","state":"California","otherGeospatial":"south San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.25,\n 37.667\n ],\n [\n -122.25,\n 37.4167\n ],\n [\n -121.9,\n 37.4167\n ],\n [\n -121.9,\n 37.667\n ],\n [\n -122.25,\n 37.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Following a heavy, multiday rainfall event that took place between June 20 and June 22, 2024, widespread flooding occurred in parts of northwestern Iowa. Ten U.S. Geological Survey (USGS) streamgages with periods of record ranging from 56 to 99 years in length experienced new peaks of record, three of which were more than double the previous peak-of-record: 06483500 (Rock River near Rock Valley, Iowa), 06605850 (Little Sioux River at Linn Grove, Iowa), and 06606600 (Little Sioux River at Correctionville, Iowa). A Presidential declaration of a major disaster for the State of Iowa was approved on June 24, 2024, and the cost of the flooding is estimated at over $310 million. The severity of this flooding prompted the USGS, in cooperation with the Iowa Department of Transportation, to summarize the meteorological and hydrological conditions preceding the flooding, compile estimates of the magnitude of peak flows resulting from the flooding, and update estimates of peak-flow frequency for selected USGS streamgages. Of the 33 streamgages analyzed, a peak streamflow occurred that corresponded to an annual exceedance probability of less than 4 percent at 13 streamgages, an annual exceedance probability of less than 1 percent at 6 streamgages, and an annual exceedance probability of less than 0.2 percent at 1 streamgage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261066","collaboration":"Prepared in cooperation with the Iowa Department of Transportation","usgsCitation":"Marti, M.K., and O’Shea, P.S., 2026, Floods of June 2024 in northwestern Iowa: U.S. Geological Survey Open-File Report 2026–1066, 16 p., https://doi.org/10.3133/ofr20261066.","productDescription":"Report: vi, 16 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-175807","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500762,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261066/full"},{"id":500761,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1066/images/"},{"id":500760,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1066/ofr20261066.XML"},{"id":500759,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1066/ofr20261066.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1066"},{"id":500758,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1066/coverthb.jpg"},{"id":501165,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119301.htm","linkFileType":{"id":5,"text":"html"}},{"id":500763,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1JFCNSZ","text":"USGS data release","linkHelpText":"Peak-flow frequency analysis for U.S. Geological Survey streamgages in northwestern Iowa, based on data through water year 2024"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.667,\n 43.6\n ],\n [\n -96.667,\n 41.667\n ],\n [\n -93,\n 41.667\n ],\n [\n -93,\n 43.6\n ],\n [\n -96.667,\n 43.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, Iowa 52240
A new oceanographic radar instrument package was developed by the U.S. Geological Survey (USGS) to measure storm waves and water levels in the nearshore, capable of being deployed rapidly and transmitting data in near real-time. To test the performance and accuracy of the sensor, multiple years of data were collected over various hydrodynamic conditions and compared to long-term monitoring data collected at the U.S. Army Corps of Engineers (USACE) Field Research Facility in Duck, North Carolina, USA. The oceanographic radars were highly reliable, with less than 1% of the record being erroneous spikes or missing data points. At the end of the pier, the radar was highly accurate, with nearly perfect agreement in water level (r2 = 0.997) compared to a nearby National Oceanic and Atmospheric Administration (NOAA) tide gauge, and good agreement in significant wave height (r2 = 0.98) and peak wave period (r2 = 0.65) compared to a nearby USACE sensor. This work demonstrates the potential of the USGS radar for rapid response storm deployments and collecting reliable and accurate hydrodynamic measurements in the nearshore for validating coastal impact models.
","conferenceTitle":"Coastal Dynamics 2025","conferenceDate":"April 7-11, 2025","conferenceLocation":"Aveiro, Portugal","language":"English","publisher":"Springer","doi":"10.1007/978-3-032-15473-6_106","usgsCitation":"Brown, J., McClenney, B.J., and Dickhudt, P., 2026, Measuring storm waves and water levels from a fixed structure with a rapidly deployable oceanographic radar, Coastal Dynamics 2025, Aveiro, Portugal, April 7-11, 2025, p. 696-702, https://doi.org/10.1007/978-3-032-15473-6_106.","productDescription":"7 p.","startPage":"696","endPage":"702","ipdsId":"IP-174186","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":500987,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501099,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-032-15473-6_106","text":"Publisher Index Page"}],"country":"United States","state":"North Carolina","city":"Duck","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Jenna A. 0000-0003-3137-7073","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":208564,"corporation":false,"usgs":true,"family":"Brown","given":"Jenna A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":956978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McClenney, Bryce J 0009-0007-6454-2078","orcid":"https://orcid.org/0009-0007-6454-2078","contributorId":367183,"corporation":false,"usgs":true,"family":"McClenney","given":"Bryce","middleInitial":"J","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickhudt, Patrick J. ","contributorId":169593,"corporation":false,"usgs":false,"family":"Dickhudt","given":"Patrick J. ","affiliations":[{"id":25562,"text":"(former) Woods Hole Coastal and Marine Science Center employee","active":true,"usgs":false}],"preferred":false,"id":956980,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274219,"text":"70274219 - 2026 - Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States","interactions":[],"lastModifiedDate":"2026-03-13T15:02:27.64804","indexId":"70274219","displayToPublicDate":"2026-03-04T09:37:40","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States","docAbstract":"In arid and semi-arid regions, groundwater sustains vegetation through subsurface water access, yet the responses of groundwater-dependent ecosystems (GDEs) to changing hydroclimate and groundwater availability are relatively understudied. This study investigates seasonal and spatial patterns in vegetation greenness using Landsat Enhanced Vegetation Index (EVI) values across riparian and upland zones in the semi-arid Upper San Pedro (USP) watershed, southern Arizona, which experiences a bimodal precipitation regime. We paired 25 years (2000–2024) of EVI and depth to groundwater (DTG) data from 89 wells and climate metrics (precipitation and vapour pressure deficit) to quantify the sensitivity of vegetation to subsurface moisture as well as atmospheric moisture supply and demand. Vegetation at wells near the USP riparian area showed strong associations between EVI and DTG anomalies during the monsoon season, indicating sustained groundwater use even during this wet period when summer precipitation is abundant. In contrast, upland vegetation that lacked access to groundwater showed minimal sensitivity in EVI to DTG and was generally less responsive to vapour pressure deficit. Interestingly, the riparian GDEs were not decoupled from precipitation and climate variability. These results underscore the importance of groundwater for maintaining riparian productivity and highlight the utility of remote sensing in identifying vegetation-climate-groundwater linkages across heterogeneous dryland landscapes.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70405","usgsCitation":"Bromley, F., Borxton, P., Zhang, J., van Leeuwen, W.J., Nagler, P., and Hu, J., 2026, Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States: Hydrological Processes, v. 40, no. 3, e70405, 18 p., https://doi.org/10.1002/hyp.70405.","productDescription":"e70405, 18 p.","ipdsId":"IP-180542","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70405","text":"Publisher Index Page"},{"id":501145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Upper San Pedro watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.31987279028372,\n 31.82228360728554\n ],\n [\n -110.31987279028372,\n 31.379497469636988\n ],\n [\n -109.98150823782808,\n 31.379497469636988\n ],\n [\n -109.98150823782808,\n 31.82228360728554\n ],\n [\n -110.31987279028372,\n 31.82228360728554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Bromley, Fern 0000-0003-0596-1487","orcid":"https://orcid.org/0000-0003-0596-1487","contributorId":367222,"corporation":false,"usgs":false,"family":"Bromley","given":"Fern","affiliations":[{"id":36671,"text":"School of Natural Resources and the Environment, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":957082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borxton, Patrick 0000-0002-2665-6820","orcid":"https://orcid.org/0000-0002-2665-6820","contributorId":248510,"corporation":false,"usgs":false,"family":"Borxton","given":"Patrick","email":"","affiliations":[{"id":49935,"text":"2University of Arizona, School of Natural Resources and the Environment","active":true,"usgs":false}],"preferred":false,"id":957083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Jiaqi","contributorId":202467,"corporation":false,"usgs":false,"family":"Zhang","given":"Jiaqi","email":"","affiliations":[{"id":36453,"text":"University of Texas, Arlington, TX, USA","active":true,"usgs":false}],"preferred":false,"id":957084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Leeuwen, Willem J.D. 0000-0002-3188-7172","orcid":"https://orcid.org/0000-0002-3188-7172","contributorId":191856,"corporation":false,"usgs":false,"family":"van Leeuwen","given":"Willem","middleInitial":"J.D.","affiliations":[],"preferred":false,"id":957085,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagler, Pamela L. 0000-0003-0674-103X","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":363777,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","middleInitial":"L.","affiliations":[],"preferred":true,"id":957086,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hu, Jia","contributorId":367226,"corporation":false,"usgs":false,"family":"Hu","given":"Jia","affiliations":[],"preferred":false,"id":957087,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273889,"text":"70273889 - 2026 - Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA","interactions":[],"lastModifiedDate":"2026-03-23T14:02:07.561392","indexId":"70273889","displayToPublicDate":"2026-03-04T08:59:53","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA","docAbstract":"Large magnitude snow avalanches (destructive size ≥ D3) impact settlements, transportation corridors, and public safety worldwide. In Colorado, United States, avalanches have killed more people than any other natural hazard since 1950. In March 2019, a large magnitude avalanche cycle occurred throughout the entire mountainous portion of Colorado resulting in more than 1000 reported avalanches during a two-week period. Nearly 200 of these avalanches were size D4 or larger with at least three D5 avalanches. However, placing this 2019 large magnitude avalanche cycle in historic context requires data prior to the instrumental record. Here, we paired tree disturbance data from dendrochronology (1698 to 2020) with meteorological data from the modeled and instrumental record (1901 to 2020) to understand the frequency and climate drivers of large magnitude snow avalanche cycles. The extensive number of downed trees from the 2019 avalanche cycle allowed us to collect 1,188 cross-sections and cores from 1023 individual trees within 24 avalanche paths across the state. From these samples we identified 4135 avalanche-related growth disturbances. We employed a strategic nested sampling design to spatially aggregate avalanche frequency from individual avalanche paths, to counties, to three major sub-regions (i.e., north, central, and south), and across the entire region (i.e., state of Colorado). Over a period spanning more than three centuries (1698 to 2020), we identified 76 avalanche years within 24 individual avalanche paths. Large magnitude avalanche event frequency varied across paths and sub-regions with several notable region-wide avalanche cycles. Both tree-ring and historical written records highlighted 1899 as a year with widespread and large magnitude avalanche activity similar to the March 2019 avalanche cycle. Since the early-20th century (1900 to 2020) regional avalanche probability declined significantly in parallel with decreasing snowpack throughout Colorado. Similarly, dominant avalanche regimes shifted from large magnitude regional cycles driven by above average snowfall years over most of the record, to regional avalanche cycles occurring more commonly in average to low snow years since 1988. In recent decades, a lack of December precipitation and above average March precipitation characterized years with regional large magnitude avalanche activity. Even with declining snow water equivalent, truly extreme regional large magnitude avalanche cycles remain possible – as demonstrated by the 2019 cycle. This underscores that rare but high-impact events are not eliminated by long-term trends. Understanding the changing snow and weather drivers and subsequent behavior of large magnitude avalanche cycles across multiple spatial scales may improve avalanche forecasting and the products and mitigations strategies developed by structural engineers to mitigate avalanche danger. This can decrease the avalanche risk to the public and improve infrastructure design in avalanche terrain.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/nhess-26-1059-2026","usgsCitation":"Peitzsch, E.H., Martin, J.T., Greene, E.M., Eckert, N., Favillier, A., Konigsberg, J., Kichas, N., Stahle, D.K., Birkeland, K.W., Elder, K., and Pederson, G.T., 2026, Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA: Natural Hazards and Earth System Sciences, v. 26, p. 1059-1074, https://doi.org/10.5194/nhess-26-1059-2026.","productDescription":"16 p.","startPage":"1059","endPage":"1074","ipdsId":"IP-175486","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501654,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-26-1059-2026","text":"Publisher Index Page"},{"id":499809,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.129166385724,\n 41.04962213955744\n ],\n [\n -109.129166385724,\n 36.99334376580887\n ],\n [\n -102.04655644997314,\n 36.99334376580887\n ],\n [\n -102.04655644997314,\n 41.04962213955744\n ],\n [\n -109.129166385724,\n 41.04962213955744\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","noUsgsAuthors":false,"publicationDate":"2026-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":202576,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science 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Nicolas","contributorId":330971,"corporation":false,"usgs":false,"family":"Eckert","given":"Nicolas","email":"","affiliations":[{"id":27334,"text":"Universite Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":955443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Favillier, Adrien","contributorId":330970,"corporation":false,"usgs":false,"family":"Favillier","given":"Adrien","email":"","affiliations":[{"id":66013,"text":"University of Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":955444,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Konigsberg, Jason","contributorId":330955,"corporation":false,"usgs":false,"family":"Konigsberg","given":"Jason","email":"","affiliations":[{"id":40054,"text":"Colorado Avalanche Information Center","active":true,"usgs":false}],"preferred":false,"id":955445,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kichas, Nickolas","contributorId":366210,"corporation":false,"usgs":false,"family":"Kichas","given":"Nickolas","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":955446,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stahle, Daniel K.","contributorId":210004,"corporation":false,"usgs":true,"family":"Stahle","given":"Daniel","middleInitial":"K.","affiliations":[],"preferred":false,"id":955447,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Birkeland, Karl W.","contributorId":173366,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","middleInitial":"W.","affiliations":[{"id":27213,"text":"USDA Forest Service National Avalanche Center, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":955448,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Elder, Kelly","contributorId":346220,"corporation":false,"usgs":false,"family":"Elder","given":"Kelly","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":955449,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":955450,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70274161,"text":"ofr20261065 - 2026 - Evaluation of pathogen risks and testing considerations for Chinook salmon egg movements between New Zealand and California","interactions":[],"lastModifiedDate":"2026-03-04T15:20:21.949375","indexId":"ofr20261065","displayToPublicDate":"2026-03-03T12:16:41","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":"2026-1065","displayTitle":"Evaluation of Pathogen Risks and Testing Considerations for Chinook Salmon Egg Movements Between New Zealand and California","title":"Evaluation of pathogen risks and testing considerations for Chinook salmon egg movements between New Zealand and California","docAbstract":"Oncorhynchus tshawytscha (Walbaum in Artedi, 1792; Chinook salmon) were historically abundant in the McCloud River but are now extirpated from this tributary owing to dam construction and lack of passage. Planning efforts to restore populations above Shasta and Keswick Dams are currently underway, including an evaluation of potential source populations. One potential source is New Zealand Chinook salmon, which are believed to have originated from tributaries of the Sacramento River. These fish could be returned to California if reintroduction risks, including risks of pathogen introduction, could be sufficiently mitigated. The U.S. Geological Survey was contracted to provide scientific support for reintroduction efforts, including evaluating the risks of pathogen transmission via the movement of Chinook salmon eggs from New Zealand to the McCloud River. This report estimates pathogen risks associated with egg movement and considers epidemiological and biosecurity measures to minimize these risks.
Pathogen risks associated with the movement of Chinook salmon eggs from New Zealand were evaluated based on pathogen virulence, transmission route, and geographic distribution. These criteria identified 14 moderate- and high-risk pathogens out of the 30 pathogens evaluated. Pathogen species and strains were considered high risk if they have the potential for vertical transmission (that is, transmission from parent to offspring), are moderately or highly virulent, and are exotic to the Sacramento River Basin. According to these criteria, we identified the following pathogens as high risk:
Strategic use of testing and biosecurity measures can minimize pathogen risks associated with the movement of eggs. The most effective measures include iodophor treatment of eggs to remove external pathogens, testing of all the adult fish from which gametes are obtained, and a quarantine period after transport to confirm pathogen testing results. Additional measures to enhance biosecurity could include testing the quarantined fish following emergence and (or) developing a fish health history of the source population through pathogen monitoring.
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\"}}]}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
5501- A Cook Underwood Road
Cook, Washington 98605-9717
This report presents the results of a cooperative study by the U.S. Geological Survey and Missouri Department of Natural Resources to quantify sediment transport source contributions in the Medicine Creek drainage basin. Understanding relative source contributions provides valuable information for selecting the conservation practices that may be most effective in reducing sediment and sediment-associated nutrient transport in the Medicine Creek drainage basin and similar areas of the Lower Grand River drainage basin. Sediment samples were collected from potential contributing areas (source samples) and from fluvial-transported samples (target samples). Source sample types included streambanks, row crop fields, and a combined pastures and forests category. Samples were analyzed for particle size and quantity of carbon, nitrogen, stable isotopes of carbon and nitrogen, and 49 mineral elements as potential tracers. Results for the carbon stable isotope ratio of carbon-13/carbon-12 (δ13C) and concentrations of total carbon, total nitrogen, calcium, potassium, and copper were selected by discriminant function analysis as the best combination of multiple tracers to differentiate each source type. The discriminant function analysis poorly differentiated pastures and forests, so these source types were combined. The sources defined by the discriminant function analysis were then used in an unmixing model to apportion sources for each target sample.
In the study area, transported sediment was predominantly bank sediment, with an overall average of 86.9 percent of suspended-sediment samples and depositional streambed samples attributed to bank material. Suspended-sediment samples from the mainstem of Medicine Creek were dominated by bank sediments (average of 95.8 percent), and depositional streambed samples from throughout the drainage basin had more variable source contributions with an average of 71.1 percent attributed to bank material. The relative importance of upland sources (row crop fields and the combined pastures and forests category) varied seasonally and with streamflow but was not related to land use or drainage basin size. Relative contributions from upland sources were greater in the summer through winter rather than spring and during lower streamflow, though this may be driven by the seasonality of streamflow. These results indicate management practices that reduce bank erosion could be effective strategies for managing the dominant source of sediment and sediment-associated phosphorus.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265121","collaboration":"Prepared in cooperation with Missouri Department of Natural Resources","usgsCitation":"Garrett, J.D., 2026, Stream sediment sources in Medicine Creek, northern Missouri and southern Iowa: U.S. Geological Survey Scientific Investigations Report 2026–5121, 11 p., https://doi.org/10.3133/sir20265121.","productDescription":"Report: vi, 11 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164057","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501166,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119303.htm","linkFileType":{"id":5,"text":"html"}},{"id":500681,"rank":7,"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":500680,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13EN5TA","text":"USGS data release","linkHelpText":"Chemical and physical data for sediment source and fluvial target samples for fingerprinting of suspended and bed sediment in Medicine Creek, Missouri and Iowa"},{"id":500679,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265121/full"},{"id":500678,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5121/images/"},{"id":500677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5121/sir20265121.XML"},{"id":500676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5121/sir20265121.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5121"},{"id":500675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5121/coverthb.jpg"}],"country":"United States","state":"Iowa, Missouri","otherGeospatial":"Medicine Creek drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.1667,\n 40.75\n ],\n [\n -93.5,\n 40.75\n ],\n [\n -93.5,\n 40\n ],\n [\n -93.1667,\n 40\n ],\n [\n -93.1667,\n 40.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
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Naegleria fowleri is a thermophilic free-living amoeba (FLA) and the causative agent of primary amoebic meningoencephalitis, posing public health risks in warm freshwater environments. This multiyear, multiagency study surveyed 40 thermally impacted recreational waters across five western United States national parks and recreation areas–Yellowstone National Park, Grand Teton National Park, Olympic National Park, Newberry National Volcanic Monument, and Lake Mead National Recreation Area–to assess N. fowleri presence, concentration, and associated environmental conditions. A total of 185 water samples were analyzed by qPCR and Sanger sequencing, revealing widespread detection of N. fowleri in 34% of samples with positive detections from Lake Mead, Yellowstone, and Grand Teton hot springs and thermally impacted waters, with concentrations ranging from 4.9 to 115.7 cells/L. Multiple codetections of N. fowleri with nonpathogenic species including Naegleria australiensis were identified, suggesting they may inhabit similar ecological niches in the natural systems in contrast to engineered systems. These findings indicate that N. fowleri is present in thermally impacted areas across the western United States and underscore the use of enhanced monitoring, public awareness, and risk management strategies in thermally influenced recreational waters.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acsestwater.5c01243","usgsCitation":"Shikany, J.I., Banks, M.M., Barnhart, E.P., Kinsey, S., Wright, P.R., Kageyama, S.A., Merkes, C.M., Kulesza, N., Wylie, J., Halonen, S., Ortega-Villa, A.M., Long, C.M., Peyton, B.M., and Puzon, G., 2026, Detection of Naegleria fowleri in thermally impacted recreational waters of western United States national parks: ACS ES&T Water, v. 6, no. 3, p. 1704-1715, https://doi.org/10.1021/acsestwater.5c01243.","productDescription":"12 p.","startPage":"1704","endPage":"1715","ipdsId":"IP-184597","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":502067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsestwater.5c01243","text":"Publisher Index 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Service","active":true,"usgs":false}],"preferred":false,"id":958021,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274497,"text":"70274497 - 2026 - Understanding flooding and channel dynamics along the Taiya River: Providing context for resource management","interactions":[],"lastModifiedDate":"2026-03-27T17:08:43.02844","indexId":"70274497","displayToPublicDate":"2026-03-01T12:05:40","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":691,"text":"Alaska Park Science","printIssn":"1545- 496","active":true,"publicationSubtype":{"id":10}},"title":"Understanding flooding and channel dynamics along the Taiya River: Providing context for resource management","docAbstract":"Flooding and channel change in the Taiya River Basin in recent decades have directly affected\npark infrastructure and cultural resources. The complexities of flooding and channel change are compounded by the changing sediment and flow regime from a changing climate and\nshrinking glaciers, which will continue to drive dynamic riverine change. Streamflow data and\ngeomorphic interpretation helped us place these events in context to inform decision making that\ntakes dynamic natural processes into account.","language":"English","publisher":"National Park Service","usgsCitation":"Curran, J.H., 2026, Understanding flooding and channel dynamics along the Taiya River: Providing context for resource management: Alaska Park Science, v. 24, no. 1, p. 26-35.","productDescription":"10 p.","startPage":"26","endPage":"35","ipdsId":"IP-182307","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":501726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501705,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2317596"}],"country":"United Statesq","state":"Alaska","otherGeospatial":"Taiya River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -135.40358674059615,\n 59.43440777292025\n ],\n [\n -135.16293100255444,\n 59.465315065891104\n ],\n [\n -135.17678488217464,\n 59.63505469200757\n ],\n [\n -135.48037695028358,\n 59.796116294791744\n ],\n [\n -135.80292468090636,\n 59.69771870037559\n ],\n [\n -135.45205191120436,\n 59.41808754397522\n ],\n [\n -135.40358674059615,\n 59.43440777292025\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Curran, Janet H. 0000-0002-3899-6275 jcurran@usgs.gov","orcid":"https://orcid.org/0000-0002-3899-6275","contributorId":690,"corporation":false,"usgs":true,"family":"Curran","given":"Janet","email":"jcurran@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":958013,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70274284,"text":"70274284 - 2026 - Hyperspectral retrieval of phytoplankton absorption and community composition from NASA’s PACE-OCI in estuarine–coastal waters using a hybrid framework combining mixture-of-experts and Variational Autoencoder","interactions":[],"lastModifiedDate":"2026-03-24T17:58:00.328721","indexId":"70274284","displayToPublicDate":"2026-02-28T10:36:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Hyperspectral retrieval of phytoplankton absorption and community composition from NASA’s PACE-OCI in estuarine–coastal waters using a hybrid framework combining mixture-of-experts and Variational Autoencoder","docAbstract":"Retrieving the phytoplankton absorption coefficient (aphy; m−1), one of the most spectrally rich inherent optical properties, remains challenging in optically complex coastal waters worldwide. Leveraging NASA's new hyperspectral mission, PACE, we introduce Hyper-MoE-VAE, a deep-learning architecture that integrates a Mixture-of-Experts with a Variational Autoencoder to retrieve high-dimensional aphy and subsequent estimation of phytoplankton community composition (PCC) from PACE-OCI hyperspectral remote sensing reflectance (Rrs). Pre-trained on global hyperspectral bio-optical datasets and fine-tuned using regional field Rrs–aphy pairings from inland– estuarine–coastal waters, Hyper-MoE-VAE demonstrated strong transferability and effective adaptation across regions. Validation with in-situ Rrs showed accurate aphy retrievals in Lake Erie (NRMSE = 0.12, ε = 17.10), Lake Pontchartrain (NRMSE = 0.11, ε = 37.12), and the Barataria–Terrebonne Estuary (NRMSE = 0.14, ε = 38.89). Using same-day PACE-OCI Level 2 Rrs, the model achieved comparable performance in Lake Erie (NRMSE = 0.19, ε = 55.19), Lake Pontchartrain (NRMSE = 0.14, ε = 51.39), and the Barataria–Terrebonne Estuary (NRMSE = 0.17, ε = 47.92). Hyper-MoE-VAE derived PACE-OCI hyperspectral aphy was further decomposed against mass-specific absorption spectra to estimate group-specific contributions to total chlorophyll a. The resulting PCC showed strong agreement with HPLC–CHEMTAX in Lake Erie (R2= 0.692) and Gulf estuarine–coastal systems (R2 = 0.732). Monte Carlo noise experiments further revealed group-dependent sensitivities, with diatoms and dinoflagellates showing moderate susceptibility to noise, while cyanobacteria and cryptophytes exhibited narrow uncertainty distributions. These results demonstrate Hyper-MoE-VAE's capability for regional, operational water-quality monitoring with PACE-OCI and its adaptability to current and future hyperspectral missions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2026.115327","usgsCitation":"Bai, X., Liu, B., Li, J., Xiong, Y., D'Sa, E.J., Baustian, M.M., Zhang, X., Grunert, B.K., Emeghiebo, C.O., Glasspie, C., and Yuan, X., 2026, Hyperspectral retrieval of phytoplankton absorption and community composition from NASA’s PACE-OCI in estuarine–coastal waters using a hybrid framework combining mixture-of-experts and Variational Autoencoder: Remote Sensing of Environment, v. 337, 115327, 21 p., https://doi.org/10.1016/j.rse.2026.115327.","productDescription":"115327, 21 p.","ipdsId":"IP-183464","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":501687,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2026.115327","text":"Publisher Index 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Lafayette","active":true,"usgs":false}],"preferred":false,"id":957612,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Glasspie, Cassie","contributorId":367744,"corporation":false,"usgs":false,"family":"Glasspie","given":"Cassie","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":957613,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yuan, Xu","contributorId":367734,"corporation":false,"usgs":false,"family":"Yuan","given":"Xu","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":957614,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70274263,"text":"70274263 - 2026 - Mercury cycling across a U.S. semi-arid mountain ecosystem elevation gradient","interactions":[],"lastModifiedDate":"2026-03-24T14:10:42.104231","indexId":"70274263","displayToPublicDate":"2026-02-28T09:05:05","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9326,"text":"JGR Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Mercury cycling across a U.S. semi-arid mountain ecosystem elevation gradient","docAbstract":"Mountains comprise ∼30% of the Earth's surface, but mercury (Hg) cycling in these regions remains understudied, particularly in the semi-arid western U.S. where strong climatic and ecological gradients in mountainous landscapes influence Hg deposition, retention, and bioaccumulation. In this study, we quantified growing season inputs, storage, and bioaccumulation of Hg along a ∼2,000 m elevation gradient in the Colorado Rocky Mountains, spanning the plains to the alpine. We measured Hg in atmospheric deposition, vegetation, soil, and 12-day-old chickadees. Accounting for percent canopy cover, open precipitation was the largest component of atmospheric deposition at all elevations, followed by throughfall and litterfall fluxes. Atmospheric Hg fluxes peaked at mid-elevations, likely due to cloud-cap dynamics and denser canopy cover. Total gaseous Hg and precipitation fluxes were highest at low elevations, likely reflecting local emissions and meteorological pooling. Surface soil Hg storage was more strongly predicted by organic matter content (R2 = 0.49; p < 0.01) and water retention (R2 = 0.45; p < 0.01) than by elevation (R2 = 0.21; p < 0.05). Alpine soils (66.3 ± 25.3 ng g−1) had significantly higher total Hg concentrations than lower elevations (<41.0 ± 12.7 ng g−1; p < 0.01), likely reflecting slower organic matter turnover. Soils on north-facing slopes also retained significantly higher pools of Hg in surface soils compared with south- and east-facing slopes. Vegetation Hg pools were greatest in the alpine region, likely due to long-lived plant species. Methylmercury (MeHg) concentrations in chickadee feathers peaked at mid-elevations (205 ± 155 ng g−1), corresponding to higher ecosystem Hg inputs via throughfall. Our results show that deposition, canopy cover, and meteorological conditions—not elevation alone—predict Hg retention and bioaccumulation.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JG009556","usgsCitation":"Miller, H.R., Janssen, S., Taylor, S.A., Gerson, J.R., McIntosh, T.L., and Hinckley, E.S., 2026, Mercury cycling across a U.S. semi-arid mountain ecosystem elevation gradient: JGR Biogeosciences, v. 131, no. 3, e2025JG009556, 19 p., https://doi.org/10.1029/2025JG009556.","productDescription":"e2025JG009556, 19 p.","ipdsId":"IP-177248","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"headwaters of the Boulder Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.58,\n 40.06\n ],\n [\n -105.58,\n 39.98\n ],\n [\n -105.27,\n 39.98\n ],\n [\n -105.27,\n 40.06\n ],\n [\n -105.58,\n 40.06\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"131","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Hannah R.","contributorId":367690,"corporation":false,"usgs":false,"family":"Miller","given":"Hannah","middleInitial":"R.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":957444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Scott A.","contributorId":367691,"corporation":false,"usgs":false,"family":"Taylor","given":"Scott","middleInitial":"A.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":957446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerson, Jacqueline R.","contributorId":367692,"corporation":false,"usgs":false,"family":"Gerson","given":"Jacqueline","middleInitial":"R.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":957447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntosh, Tyler L.","contributorId":367693,"corporation":false,"usgs":false,"family":"McIntosh","given":"Tyler","middleInitial":"L.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":957448,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hinckley, Eve-Lyn S.","contributorId":367694,"corporation":false,"usgs":false,"family":"Hinckley","given":"Eve-Lyn","middleInitial":"S.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":957449,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274197,"text":"70274197 - 2026 - Terrestrial ecosystem response to changing temperature and seasonality in the Paleocene-Eocene Thermal Maximum: Shallow marine records from the Salisbury Embayment, USA","interactions":[],"lastModifiedDate":"2026-03-10T13:41:31.319054","indexId":"70274197","displayToPublicDate":"2026-02-28T08:12:37","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Terrestrial ecosystem response to changing temperature and seasonality in the Paleocene-Eocene Thermal Maximum: Shallow marine records from the Salisbury Embayment, USA","docAbstract":"The Paleocene-Eocene thermal maximum (PETM, ∼56 Ma) is marked by a massive and rapid rise in atmospheric CO2 and ∼5°C of global warming. It is globally characterized by a negative carbon isotope excursion (CIE), and, at least locally, is preceded by a pre-onset excursion (POE). We present palynological and bioclimatic analyses from stratigraphically expanded marginal marine sediment sections from the eastern United States. Late Paleocene forests were dominated by needle-leaved gymnosperms and broad-leaved angiosperms characteristic of warm climates. The POE is marked by a minor expansion of angiosperms and pteridophytes, warmer winters, and altered seasonal precipitation, followed by a return to pre-POE conditions. Increased terrestrial palynomorph concentrations before the CIE are suggestive of increased fluvial discharge before the PETM. Early PETM assemblages are characterized by dominance of ferns, loss of conifers, and expansion of broad-leaved angiosperm forests. Bioclimatic analyses indicate warmer mean atmospheric temperatures in early PETM time, driven primarily by winter warming of ∼3°C. A shift in seasonality, associated with increased severity of storms and floods that scoured the late Paleocene floodplain, facilitated establishment of riparian fern communities at the CIE onset. These flooding events persisted through the early part of the PETM and were severe enough to transport Westphalian-age (Middle Pennsylvanian) reworked material from the central Appalachian Basin and flush large amounts of terrestrial material and carbon onto the continental shelf, resulting in decreased salinity, increased productivity, and water-column stratification.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025PA005278","usgsCitation":"Willard, D., Nelissen, M., Sluijs, A., Brinkhuis, H., Reichgelt, T., Robinson, M., and Self-Trail, J., 2026, Terrestrial ecosystem response to changing temperature and seasonality in the Paleocene-Eocene Thermal Maximum: Shallow marine records from the Salisbury Embayment, USA: Paleoceanography and Paleoclimatology, v. 41, no. 3, e2025PA005278, 19 p., https://doi.org/10.1029/2025PA005278.","productDescription":"e2025PA005278, 19 p.","ipdsId":"IP-171569","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":501095,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025pa005278","text":"Publisher Index Page"},{"id":500858,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, Virginia","otherGeospatial":"Salisbury Embayment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74,\n 40\n ],\n [\n -77,\n 40\n ],\n [\n -77,\n 37\n ],\n [\n -74,\n 37\n ],\n [\n -74,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Willard, Debra A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":269840,"corporation":false,"usgs":true,"family":"Willard","given":"Debra A.","affiliations":[],"preferred":true,"id":956904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelissen, Mei","contributorId":362170,"corporation":false,"usgs":false,"family":"Nelissen","given":"Mei","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":956905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sluijs, Appy","contributorId":215371,"corporation":false,"usgs":false,"family":"Sluijs","given":"Appy","email":"","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":956906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brinkhuis, Henk","contributorId":328591,"corporation":false,"usgs":false,"family":"Brinkhuis","given":"Henk","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":956907,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reichgelt, Tammo","contributorId":215367,"corporation":false,"usgs":false,"family":"Reichgelt","given":"Tammo","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":956908,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, Marci M. 0000-0002-9200-4097","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":261664,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":956909,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":956910,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274266,"text":"70274266 - 2026 - Extreme precipitation variability and soil texture controls on water-table response","interactions":[],"lastModifiedDate":"2026-03-24T16:31:28.917628","indexId":"70274266","displayToPublicDate":"2026-02-27T09:28:04","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Extreme precipitation variability and soil texture controls on water-table response","docAbstract":"Extreme precipitation events (EPEs), a key class of hydrometeorological extremes, are intensifying globally under climate change; however, their effects on water-table dynamics across varying soil textures remain poorly understood. To better understand the impacts of EPEs, we conducted one-dimensional modeling to evaluate water-table response time, displacement, recession time, and total recharge under EPEs of 0.20 m, 0.40 m, and 0.60 m amounts, applied over 1-, 7-, and 20-day durations across twelve soil textures. The results show that coarse soils (i.e., sand) respond within days, while fine soils (i.e., clay) may take over 200 days. Water-table displacement ranged from 0.30 to 1.64 m and increased with EPE magnitude. The time it took for water tables to recede ranged from 1.2 to 3.0 years. A first-order estimate of total possible recharge, calculated from porosity and displacement, ranged from 17% (clay) to 97% (sand), averaging ~63% across soil textures. These findings highlight that recharge is primarily governed by EPE magnitude and soil properties, not event duration. This modeling effort provides new insight into how soil texture modulates groundwater response to extreme precipitation, informing future water budget and resilience assessments.
","language":"English","publisher":"MDPI","doi":"10.3390/w18050587","usgsCitation":"Corona, C.R., Ge, S., Anderson, S.P., and Dickinson, J.E., 2026, Extreme precipitation variability and soil texture controls on water-table response: Water, v. 18, no. 5, 587, 20 p., https://doi.org/10.3390/w18050587.","productDescription":"587, 20 p.","ipdsId":"IP-160684","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":501680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w18050587","text":"Publisher Index Page"},{"id":501472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"5","noUsgsAuthors":false,"publicationDate":"2026-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Corona, Claudia R.","contributorId":152548,"corporation":false,"usgs":false,"family":"Corona","given":"Claudia","middleInitial":"R.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":957469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ge, Shemin","contributorId":203465,"corporation":false,"usgs":false,"family":"Ge","given":"Shemin","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":957470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Suzanne P. 0000-0002-6796-6649","orcid":"https://orcid.org/0000-0002-6796-6649","contributorId":172732,"corporation":false,"usgs":false,"family":"Anderson","given":"Suzanne","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":957471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957472,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}