Environmental decision-support tools are increasingly being used to serve both expert and non-expert audiences. Many existing tools are primarily expert-focused, and redesigning them can be challenging because experts and non-experts interact with tools differently, existing users may be resistant to changes, and there is little guidance on how to prioritize redesign efforts and demonstrate their efficacy. In this report, we present a case study of a user-centered redesign of an established environmental decision-support tool—the U.S. Geological Survey WaterWatch. WaterWatch supports flood, drought, and other water resource management decisions through the display of water levels at gages across the United States. Using a participatory process, we identified a functional change (replacing the existing rainbow colormap), created an alternative design, and tested the alternative’s usability through two general public surveys. The results showed that replacing the rainbow colormap with a more intuitive diverging colormap improves usability, regardless of the audience’s subjective preference for the rainbow color scheme. In addition, we demonstrated the importance of using legends to improve the audience’s understanding of the map symbols. This study demonstrates how user-centered design approaches can be used to inform the design of high-profile products and tools.
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U.S. Geological Survey
1 Gifford Pinchot Dr
Madison, WI 53726
Potash, potassium-bearing water-soluble salt, is the primary global economic source of potassium. Potash is recognized as a critical mineral in Canada as it is the largest source of potassium used in fertilizers. It is essential for global agricultural productivity and food security. Canada is the world’s largest potash exporter with vast deposits in the widely mined Prairie Evaporite of Saskatchewan, which formed in the epicontinental Elk Point Basin during the Middle Devonian. Potash is also found in the Windsor Group of Atlantic Canada where it formed in a series of tectonically active basins during the Mississippian that have undergone substantial post-depositional subsurface alteration and deformation. Potash deposits were mined in New Brunswick up until 2016. Both deposits are salt giants, recording times in the geologic record of extensive and long-lasting evaporite genesis under arid conditions in restricted seas. This paper reviews the geological and economic significance of Canadian potash, including (1) the genesis of each deposit, (2) diagenetic, erosional, and tectonic modification, and (3) exploration and mining in each basin. Underdeveloped regions, possible undiscovered resources, environmental considerations, and the importance of sustainable practices in light of climate change and socioeconomic risks are also addressed.
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E.","contributorId":365587,"corporation":false,"usgs":false,"family":"Snyder","given":"M.","middleInitial":"E.","affiliations":[{"id":87157,"text":"Dept. of Earth and Environmental Science, Acadia University","active":true,"usgs":false}],"preferred":false,"id":954402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Craig","contributorId":365588,"corporation":false,"usgs":false,"family":"Funk","given":"Craig","affiliations":[{"id":87158,"text":"Geoservices, Nutrien Canada","active":true,"usgs":false}],"preferred":false,"id":954403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boehner, R.","contributorId":365589,"corporation":false,"usgs":false,"family":"Boehner","given":"R.","affiliations":[{"id":38268,"text":"independent","active":true,"usgs":false}],"preferred":false,"id":954404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yang, Chaowei 0000-0001-7768-4066","orcid":"https://orcid.org/0000-0001-7768-4066","contributorId":362010,"corporation":false,"usgs":false,"family":"Yang","given":"Chaowei","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":954405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicolas, M.P.B.","contributorId":365590,"corporation":false,"usgs":false,"family":"Nicolas","given":"M.P.B.","affiliations":[{"id":87159,"text":"Manitoba Geological Survey","active":true,"usgs":false}],"preferred":false,"id":954406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kruger, N. W.","contributorId":365591,"corporation":false,"usgs":false,"family":"Kruger","given":"N.","middleInitial":"W.","affiliations":[{"id":65569,"text":"North Dakota Geological Survey","active":true,"usgs":false}],"preferred":false,"id":954407,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273213,"text":"sir20255095 - 2025 - Assessment of treated wastewater infiltration in Bright Angel Wash and the potential for contaminants of emerging concern influencing spring water quality along the South Rim of the Grand Canyon in Grand Canyon National Park, Arizona","interactions":[],"lastModifiedDate":"2026-02-04T14:21:30.576365","indexId":"sir20255095","displayToPublicDate":"2025-12-22T10:55:16","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5095","displayTitle":"Assessment of Treated Wastewater Infiltration in Bright Angel Wash and the Potential for Contaminants of Emerging Concern Influencing Spring Water Quality Along the South Rim of the Grand Canyon in Grand Canyon National Park, Arizona","title":"Assessment of treated wastewater infiltration in Bright Angel Wash and the potential for contaminants of emerging concern influencing spring water quality along the South Rim of the Grand Canyon in Grand Canyon National Park, Arizona","docAbstract":"In April 2021, a synoptic study conducted by the U.S. Geological Survey (USGS) and National Park Service (NPS) identified wastewater-related contaminants of emerging concern (CECs) in springs along the South Rim of the Grand Canyon. These springs are located north of Bright Angel Wash, an ephemeral channel that receives treated effluent from the South Rim Wastewater Treatment Plant (SRWTP). Although water flows southwest and away from the canyon, there is evidence that treated wastewater is finding a flow path along fractures associated with the Bright Angel Fault back to water sources along the South Rim.
The CECs identified during the April 2021 sampling included several per- and polyfluoroalkyl substances (PFAS) and pharmaceutical compounds. The PFAS compounds detected only consisted of perfluoroalkyl acids, and these were only detected at Bright Angel Wash (treated wastewater), Monument Spring, and upper Horn Bedrock Spring. The other five sampled springs (the Salt Creek, Horn East Alluvium, Garden, Pumphouse, and Pipe Springs) had no detections of PFAS compounds. The five perfluoroalkyl acids detected at Monument Spring (in descending order of concentration) were perfluorobutanesulfonic acid (PFBS), perfluoropentanoic acid, perfluorooctanoic acid, perfluorohexanoic acid, and perfluorooctanesulfonic acid. Only the short-chained PFBS and perfluorobutanoic acid compounds were detected at the upper Horn Bedrock Spring. All the same perfluoroalkyl acids were found at Bright Angel Wash, except for PFBS.
Monument Spring was the only spring to have detections of pharmaceuticals. The two pharmaceuticals detected at the highest concentrations at Monument Spring were diphenhydramine (antihistamine) and carbamazepine (anticonvulsant or anti-epileptic drug). The other detected pharmaceuticals included (in descending order of concentration) fluconazole (antifungal), sulfamethoxazole (antibiotic), metformin (diabetes drug), tramadol (opioid analgesic), and venlafaxine (antidepressant and nerve pain medication). The same pharmaceuticals were detected in the wastewater at Bright Angel Wash but in greater concentrations. No CEC concentrations measured at Monument Spring exceeded any drinking water standards or human health benchmarks; however, most of the compounds detected have no regulatory standards. Studies of the ecological effects of these compounds show that some of the compounds detected can have endocrine and physiological effects, but generally, effects were observed at concentrations multiple orders of magnitude greater than what was measured during the April 2021 study.
Data from 1980 through 2022 retrieved from the Water Quality Portal were combined with data from the one-time synoptic sampling in April 2021 to assess the usefulness of other analytes for identifying a wastewater connection to South Rim springs. Most of the historical water chemistry data showed a statistical difference between samples collected within and east of the Garden Creek watershed and samples collected from locations in watersheds to the west of Garden Creek, including the Horn Creek, Salt Creek, Monument Creek, and Hermit Creek watersheds, which roughly align with the Bright Angel Fault. Most of the historical analytes were inconclusive as potential wastewater tracers, but nitrate, chloride, and gadolinium data possibly support the historical contribution of wastewater to Monument Spring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255095","collaboration":"Prepared in cooperation with the National Park Service, Grand Canyon National Park","usgsCitation":"Paretti, N.V., Beisner, K.R., and Shepherd, S.J.R., 2025, Assessment of treated wastewater infiltration in Bright Angel Wash and the potential for contaminants of emerging concern influencing spring water quality along the South Rim of the Grand Canyon in Grand Canyon National Park, Arizona (ver. 1.1, 2026): U.S. Geological Survey Scientific Investigations Report 2025–5095, 59 p., https://doi.org/10.3133/sir20255095.","productDescription":"ix, 59 p.","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-159478","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":499495,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119152.htm","linkFileType":{"id":5,"text":"html"}},{"id":499484,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5095/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2025-5095 Version History"},{"id":497774,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5095/sir20255095.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5095 XML"},{"id":497773,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255095/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5095 HTML"},{"id":497772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5095/sir20255095.pdf","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5095 PDF"},{"id":497775,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5095/images/"},{"id":497771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5095/coverthb2.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Bright Angel Wash, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.25,\n 36.1\n ],\n [\n -112.25,\n 35.94693133579284\n ],\n [\n -112,\n 35.94693133579284\n ],\n [\n -112,\n 36.1\n ],\n [\n -112.25,\n 36.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: December 29, 2025; Version 1.1: February 3, 2026","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue, Suite 221
Tucson, AZ 85719
Identifying suspended-sediment (SS) sources, seasonal variability, and phosphorus (P) transported with SS is critical information for basin managers, although there may be concerns about comparability between flow-integrated SS samples used for sediment fingerprinting and discrete samples used for concentrations and loads in basins where SS is mostly silt + clay and(or) one land-use predominates. Objectives were to determine if (1) sample-collection method and (2) source consideration influenced apportionment of the largest SS source.
Concurrent-replicate, SS samples were collected during 2022 from the East River, Wisconsin using an automated sampler, commonly used for water-quality sampling, and passive samplers, frequently used for SS fingerprinting. Samples were evaluated for differences in physical and chemical characteristics that may affect source apportionment. Considered sources included three upland land-use (cropland, forest, and roads), two in-channel (streambank and streambed sediment), and one that connects uplands to the stream channel (gullies). Source apportionment used established methods in the SedSAT tool. Source scenarios included land-use + streambank (4src), 4src + gully, 4src + streambed, and 4src + gully + streambed (6src).
There were no statistically significant differences in median grain size, organic carbon, or sediment-bound P as a function of collection method. In-channel sources were the largest proportional SS source, regardless of season, hydrologic condition, collection method, or source scenario. Source verification highlighted which source fingerprints were most accurately defined and implications for SS target apportionment.
Varying the source scenarios for sediment fingerprinting indicated that improved management of hydrologic connectivity between upland land use and the stream channel has the potential to mitigate SS loads.
","language":"English","publisher":"Springer","doi":"10.1007/s11368-025-04155-y","usgsCitation":"Williamson, T.N., Blount, J.D., Broerman, H., Fitzpatrick, F., Mevis, I., Hoefling, D.J., Pace, S.M., Komiskey, M.J., and Kreiling, R., 2025, Evaluating uncertainties with sample-collection method and source selection in sediment fingerprinting: an example from a Great Lakes tributary: Journal of Soils and Sediments, v. 25, p. 4140-4163, https://doi.org/10.1007/s11368-025-04155-y.","productDescription":"24 p.","startPage":"4140","endPage":"4163","ipdsId":"IP-174726","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":498457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11368-025-04155-y","text":"Publisher Index Page"},{"id":498344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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snow spectra","docAbstract":"Seasonal snow is an integral component of global hydrological systems, global energy budget and Earth's climate. As an important part of many Earth systems, seasonal snow is also an essential source of water for many human populations and ecosystems around the world. As such, the measurement of seasonal snow and characterization of uncertainty in those measurements is crucial. To elucidate potential uncertainty attributable to commonly used field spectrometers (and to a lesser extent imaging spectrometers) and associated reference panels, this work presents results from an intercalibration experiment conducted synchronously with the NASA 2023 Snow Experiment (SnowEx) Albedo campaign near Fairbanks, Alaska USA. Three sets of experiments were carried out under controlled laboratory conditions to characterize the radiometric and spectral wavelength consistency of the instruments as well as the white reference panels used to calculate reflectance from field measurements. Although there was generally good agreement between the instruments, panels, and the references, there were also some notable differences. One instrument showed an average − 74 % change from the reference for radiance, and multiple instruments exceeded the suggested 0.5 nm threshold for spectral wavelength scale. The Discussion section highlights how some of these findings and their implications could improve future field campaigns and general use/maintenance of these high-precision scientific instruments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coldregions.2025.104800","usgsCitation":"Roberts-Pierel, B.M., Crawford, C., Brown, S.W., Kokaly, R.F., Gleason, K.E., Nolin, A.W., Bair, E.H., Wilder, B.A., Surunis, A.J., Skiles, S.K., Meyer, J., Fitts, A.E., Johnston, J.M., Hunsaker, A.G., Steufer, M., and Løke, T., 2025, A laboratory-based spectrometer intercomparison for the measurement of snow spectra: Cold Regions Science and Technology, v. 245, 104800, 16 p., https://doi.org/10.1016/j.coldregions.2025.104800.","productDescription":"104800, 16 p.","ipdsId":"IP-182042","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499970,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pdxscholar.library.pdx.edu/esm_fac/430","text":"External Repository"},{"id":499172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.93176636317207,\n 64.88847731461294\n ],\n [\n -147.93176636317207,\n 64.76084697844067\n ],\n [\n -147.5919038491945,\n 64.76084697844067\n ],\n [\n -147.5919038491945,\n 64.88847731461294\n ],\n [\n -147.93176636317207,\n 64.88847731461294\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"245","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts-Pierel, Benjamin M. 0000-0002-1486-7903","orcid":"https://orcid.org/0000-0002-1486-7903","contributorId":365679,"corporation":false,"usgs":false,"family":"Roberts-Pierel","given":"Benjamin","middleInitial":"M.","affiliations":[{"id":87187,"text":"Earth Space Technology Service","active":true,"usgs":false}],"preferred":false,"id":954604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":954605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Steven W.","contributorId":365680,"corporation":false,"usgs":false,"family":"Brown","given":"Steven","middleInitial":"W.","affiliations":[{"id":25356,"text":"National Institute of Standards and Technology","active":true,"usgs":false}],"preferred":false,"id":954606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":954607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gleason, Kelly E.","contributorId":365681,"corporation":false,"usgs":false,"family":"Gleason","given":"Kelly","middleInitial":"E.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":954608,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nolin, Anne W.","contributorId":365682,"corporation":false,"usgs":false,"family":"Nolin","given":"Anne","middleInitial":"W.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":954609,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bair, Edward H.","contributorId":365683,"corporation":false,"usgs":false,"family":"Bair","given":"Edward","middleInitial":"H.","affiliations":[{"id":87188,"text":"Leidos, Inc.","active":true,"usgs":false}],"preferred":false,"id":954610,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilder, Brenton A.","contributorId":365684,"corporation":false,"usgs":false,"family":"Wilder","given":"Brenton","middleInitial":"A.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":954611,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Surunis, Anton J.","contributorId":365685,"corporation":false,"usgs":false,"family":"Surunis","given":"Anton","middleInitial":"J.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":954612,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Skiles, S. McKenzie K.","contributorId":365686,"corporation":false,"usgs":false,"family":"Skiles","given":"S. McKenzie","middleInitial":"K.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":954613,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Meyer, Joachim","contributorId":365687,"corporation":false,"usgs":false,"family":"Meyer","given":"Joachim","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":954614,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Fitts, Allyson E.","contributorId":365688,"corporation":false,"usgs":false,"family":"Fitts","given":"Allyson","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":954615,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Johnston, Jeremy M.","contributorId":365689,"corporation":false,"usgs":false,"family":"Johnston","given":"Jeremy","middleInitial":"M.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":954616,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hunsaker, Adam G.","contributorId":365690,"corporation":false,"usgs":false,"family":"Hunsaker","given":"Adam","middleInitial":"G.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":954617,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Steufer, Martin","contributorId":365691,"corporation":false,"usgs":false,"family":"Steufer","given":"Martin","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":954618,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Løke, Trond","contributorId":365692,"corporation":false,"usgs":false,"family":"Løke","given":"Trond","affiliations":[{"id":87189,"text":"Norsk Elektro Optikk AS","active":true,"usgs":false}],"preferred":false,"id":954619,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70273104,"text":"sir20255073 - 2025 - Hydrogeologic characterization of the Cahuilla Valley and Terwilliger Valley Groundwater Basins, Riverside County, California","interactions":[],"lastModifiedDate":"2026-02-03T17:01:22.100586","indexId":"sir20255073","displayToPublicDate":"2025-12-19T15:32:50","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5073","displayTitle":"Hydrogeologic Characterization of the Cahuilla Valley and Terwilliger Valley Groundwater Basins, Riverside County, California","title":"Hydrogeologic characterization of the Cahuilla Valley and Terwilliger Valley Groundwater Basins, Riverside County, California","docAbstract":"The relation between the groundwater and the amount of natural recharge to the Cahuilla Valley and Terwilliger Valley groundwater basins is not well understood. During the 20th century, the reliance on groundwater near Anza, California, used for agricultural, domestic, and municipal reasons has increased, and there is the potential for changes in groundwater availability related to climate change. Several types of existing data were evaluated, and new data were collected for this study, with the goal of characterizing the region’s hydrogeology. The study’s scope included constructing a geologic framework model to show where the groundwater-bearing units are present and their relation to each other, estimating the major components of the groundwater budget, and understanding local short-term and regional long-term groundwater flow and how that has changed since the early 1900s.
Two electrical resistivity tomography surveys were done in the Durasno Valley about 2,150 feet apart to identify the thickness of the alluvium, its horizontal extent, and the depth-to-basement along two profiles perpendicular to Cahuilla Creek. The subsurface sediments were mostly horizontally layered and the transitional boundary between the alluvium and basement was thinner and shallower along the upgradient profile where the depth-to-basement was about 70 feet below land surface; the depth-to-basement at the downgradient profile was more than about 140 feet below land surface. The results from the surveys were used to place four monitoring wells at two sites along the survey profiles. Artesian flow from the deepest well at the downgradient site indicated that the decomposed and competent basement likely contributed some groundwater to the overlying alluvium, laterally, from below, or both.
A digital three-dimensional geologic framework model was constructed using EarthVision software to represent the subsurface geometry of the alluvium, decomposed basement, and competent basement. Maps and cross sections of the modeled thicknesses of the alluvium and decomposed basement, and the modeled elevation of the top of the competent basement, were made to show the subsurface geometry of vertical faults, selected wells, and the groundwater-bearing units.
Because natural recharge is related to the variable cycles of precipitation, estimates are difficult to quantify. Recharge and runoff have extreme interannual variability in the study area; recharge and runoff can be sporadic, and a substantive amount may not occur in some years. Estimates of recharge from a previous study and the regional-scale Basin Characterization Model for California for four different periods ranged from 3,800 acre-feet/year for 1897–1947 to 5,900 acre-feet/year for 1971–2000. Potential recharge from the disposal of domestic septic systems may have been as much as 500 acre-feet in 2020. It was estimated that between about 400 and 2,400 acre-feet/year of groundwater is lost through evapotranspiration by vegetation and evaporation from open water bodies, but the main source of discharge is through pumpage, mainly used for agriculture from the alluvium in the Cahuilla Valley and Terwilliger Valley groundwater basins. The estimated total pumpage for 1991–2021 ranged from about 1,140 acre-feet in 2019 to about 3,450 acre-feet in 1994. When summed, the cumulative amount of estimated pumpage between 1991 and 2021 was about 81,400 acre-feet.
The general direction of groundwater flow is from the northeast along the San Jacinto fault zone at the headwaters of Cahuilla and Hamilton Creeks, to the surface-water outlets at the west and southeast parts of the study area. Groundwater-level data from the 1950s and earlier indicate that there was a natural groundwater divide between the Cahuilla Valley and Terwilliger Valley groundwater basins, but the changing magnitude and extent of the groundwater depressions caused by pumping since about 1950 indicate that the location of the natural groundwater boundary between the Cahuilla Valley and Terwilliger Valley groundwater basins has migrated over time.
Flow from the upper to the lower parts of the Cahuilla Valley groundwater basin roughly follows the course of Cahuilla Creek through the narrow Durasno Valley where an estimated volume of flow in April 2019 was about 10–150 acre-feet/year. Short-term trends in groundwater levels, particularly in wells where groundwater is shallow and in the basement unit, show how some areas respond quickly to recharge and discharge. Wells located further to the east within the Cahuilla Valley groundwater basin in the alluvium show much less of a response to recharge events; areas of sustained pumpage from the alluvium, primarily for agriculture, show long-term declines in groundwater levels and generally do not show the effects of storm events or recent runoff. Groundwater levels in wells that are farthest from where most of the recharge occurs and where pumping has been the greatest, had some of the largest long-term groundwater-level declines at a rate of about 0.8 foot/year between 1971 and 2021.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255073","collaboration":"Prepared in cooperation with the Ramona Band of Cahuilla","usgsCitation":"Stamos, C.L., Christensen, A.H., Cromwell, G., Dick, M.C., Ely, C.P., Jachens, E.R., Ogle, S.E., and Shepherd, M.M., 2025, Hydrogeologic characterization of the Cahuilla Valley and Terwilliger Valley Groundwater Basins,\nRiverside County, California: U.S. Geological Survey Scientific Investigations Report 2025–5073, 65 p., https://doi.org/10.3133/sir20255073.","productDescription":"Report: ix, 65 p., 3 Data Releases","onlineOnly":"Y","ipdsId":"IP-116466","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":497529,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93KA4IG","text":"USGS data release","description":"USGS data release","linkHelpText":"Select borehole data for Anza Valley, Anza, CA"},{"id":497531,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5073/images"},{"id":497875,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119059.htm","linkFileType":{"id":5,"text":"html"}},{"id":497532,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5073/sir20255073.XML"},{"id":497530,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DJLSOV","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic data from the Cahuilla Valley and Terwilliger Valley groundwater basins, Riverside County, California, 2022 (ver. 2.0, August 2025)"},{"id":497528,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LCEHD7","text":"USGS data release","description":"USGS data release","linkHelpText":"Electrical resistivity tomography in the Anza-Terwilliger Valley, Riverside County, California 2018"},{"id":497527,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255073/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5073"},{"id":497526,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5073/sir20255073.pdf","text":"Report","size":"15.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5073"},{"id":497525,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5073/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cahuilla Valley and Terwilliger Valley groundwater basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.5,\n 33.8\n ],\n [\n -117.5,\n 33\n ],\n [\n -115.8,\n 33\n ],\n [\n -115.8,\n 33.8\n ],\n [\n -117.5,\n 33.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The Mississippi Sound, an estuarine environment located between the mainland and barrier islands bordering the northern Gulf of America (formerly the Gulf of Mexico), serves as a vital ecosystem for the States of Mississippi and Alabama. Spanning approximately 100 kilometers from east to west and covering 1,400 square kilometers, the sound is home to marine industry and ports, and its shallow and brackish waters sustain a diverse array of marine life. Barrier islands along the southern edge of the sound separate the microtidal estuary from the Gulf of America. This protection from gulf wave action mediates current flow within the sound, resulting in predominantly fine-grained sediment deposition along the seafloor. This study, conducted by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers, provides insight on fluvial and tidal processes spanning the past 5,000 years. The report synthesizes existing research to provide a comprehensive overview of the sound geology, from Pleistocene origins to present-day morphology, and utilizes high-resolution single channel seismic profiles and sediment data to identify and map sedimentary deposits and morphologic features at and below the seafloor. Despite its ecological significance, the Mississippi Sound faces environmental challenges, including water-quality issues, habitat degradation, storm-induced erosion, and the ongoing threats of sea-level rise and environmental changes. This study uses the present-day understanding of the sound's geology to inform coastal management decisions, hazard assessment, and potential mineral resources.
Contact Us- USGS Publications Warehouse
Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Blue Mesa Reservoir, in the Curecanti National Recreation Area, is the largest storage reservoir in Colorado and consists of three distinct basins: Iola (the shallowest), Cebolla, and Sapinero. After algal toxins were first documented in Iola basin in 2018, the U.S. Geological Survey began a study in cooperation with the National Park Service, Colorado River Water Conservation District, Upper Gunnison River Water Conservancy District, Gunnison County, Project 7 Water Authority, and Uncompahgre Valley Water Users Association to better understand occurrence of toxic cyanobacteria harmful algal blooms (cyanoHABs) and identify possible causal mechanisms to potentially inform management strategies.
Toxic cyanoHABS occurred when the algal toxin microcystin exceeded a concentration of 8 micrograms per liter primarily in Iola basin in 2018 and 2020–22, years having some of the lowest reservoir water-level elevations (reservoir levels) since 1984. The toxic cyanoHABs started in mid-September and continued through the fall months. Algal abundance was greatest in Iola basin compared to Cebolla and Sapinero basins, with Aphanizomenon, a toxin-producing cyanobacterium, being the most abundant. During blooms, enhanced algal photosynthesis caused elevated pH and dissolved oxygen concentrations especially in Iola basin. Continuous monitor data in Iola basin indicated peaks in phycocyanin fluorescence, pH, and dissolved oxygen concentration that preceded the onset of toxic cyanoHABs by about 2 weeks potentially indicating a useful early warning monitoring strategy for future response to toxic cyanoHABs. Long-term trends showed increases in mean air and surface-water temperatures and chlorophyll-a concentrations in the reservoir but no change in nutrient inputs from major tributaries. In Iola basin, reservoir level was positively correlated with Secchi disk depth and inversely correlated with total phosphorus concentration. Because of its shallow depth, the effect of low reservoir levels may disproportionately affect Iola basin compared to other basins, resulting in algal blooms and toxin production especially at reservoir levels below about 7,470 feet above North American Vertical Datum of 1988. Elevated phosphorus at low reservoir level likely was primarily phosphorus contained in algal tissue.
This report indicates that the main driver for recent toxic cyanoHABs in Iola basin is low reservoir level that likely causes favorable conditions (shallow and warm) for algal growth and increased recruitment of algae from bottom sediments such as during wind-driven turbulence. Control of external nutrients to the reservoir is unlikely to help control algal blooms because Aphanizomenon fixes nitrogen from the atmosphere, and there is an abundant geogenic source of phosphorus. Maintenance of reservoir levels greater than about 7,470 feet might help minimize the occurrence of toxic cyanoHABs. Additional data could help better understand how the timing and duration of reservoir levels below 7,470 feet contribute to toxic cyanoHABs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255109","collaboration":"Prepared in cooperation with the National Park Service, Colorado River Water Conservation District, Upper Gunnison River Water Conservancy District, Gunnison County, Project 7 Water Authority, and Uncompahgre Valley Water Users Association","usgsCitation":"Walton-Day, K., Day, N.K., Mast, M.A., Gidley, R.G., Gohring, E.J., King, T.V., Day, W.C., Gibney, N.D., and Bauch, N.J., 2025, Environmental characterization of Blue Mesa Reservoir and potential causes of and management strategies for harmful algal blooms, 1970 through 2023, Curecanti National Recreation Area, Colorado: U.S. Geological Survey Scientific Investigations Report 2025–5109, 64 p., https://doi.org/10.3133/sir20255109.","productDescription":"Report: ix, 64 p.; 8 Linked Appendix Tables; Data Release; Dataset","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-175517","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":497594,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5109/sir20255109.pdf","text":"Report","size":"9.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5109"},{"id":497593,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5109/coverthb.jpg"},{"id":497595,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5109/sir20255109.XML"},{"id":497597,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5109/images"},{"id":497596,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255109/full"},{"id":497601,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14VZMGQ","text":"USGS data release","linkHelpText":"Phytoplankton, algal toxin, and water-quality data for Blue Mesa Reservoir, Colorado, 1970–2023"},{"id":497600,"rank":8,"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":497599,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2025/5109/downloads/sir20255109_appendix2_tables.zip","text":"Appendix 2","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 2.1 to 2.3"},{"id":497598,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2025/5109/downloads/sir20255109_appendix1_tables.zip","text":"Appendix 1","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 1.1 to 1.5"}],"country":"United States","state":"Colorado","otherGeospatial":"Blue Mesa Reservoir, Curecanti National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.33792466715349,\n 38.52947110278791\n ],\n [\n -107.33792466715349,\n 38.44323521066457\n ],\n [\n -107.054272974311,\n 38.44323521066457\n ],\n [\n -107.054272974311,\n 38.52947110278791\n ],\n [\n -107.33792466715349,\n 38.52947110278791\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
Blue Mesa Reservoir (Blue Mesa), in the Curecanti National Recreation Area, is the largest storage reservoir in Colorado and consists of three distinct basins: Iola (the shallowest), Cebolla, and Sapinero. After algal toxins were first documented in Iola basin in 2018, the U.S. Geological Survey began a study to better understand occurrence of toxic harmful algal blooms (HABs) and identify possible causal mechanisms to potentially inform management strategies. Harmful algal blooms occurred in Blue Mesa when concentration of a toxic substance produced by dying algae was greater than health advisory levels, prompting no contact warnings for humans and their pets in Blue Mesa. This condition occurred starting in September and lasted as late as early November in Iola basin in 2018 and 2020–22. These years had some of the lowest recorded reservoir water-level elevations since 1984. Iola basin had the greatest amount of algae compared to Cebolla and Sapinero Basins, and a type of algae that could produce toxins was the most abundant. Multiple climate and water-quality indicators were examined in the reservoir and its tributaries to determine the causes of toxic HABs in Blue Mesa. The results indicate that the main cause for recent toxic HABs in Iola basin may be low reservoir level that likely causes favorable conditions (shallow and warm) for algal growth and increased release of algae from bottom sediments, for example, during wind-driven turbulence. Control of external nutrients to the reservoir is unlikely to help control algal blooms because the toxin-producing algae can use nitrogen from the atmosphere, and there are abundant geologic sources of phosphorus providing that nutrient to Blue Mesa. Maintenance of reservoir water-level elevation greater than about 7,470 feet might help minimize the occurrence of toxic HABs in Blue Mesa.
","publicationDate":"2025-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Walton-Day, Katherine 0000-0002-9146-6193","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":336569,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mast, M. Alisa 0000-0001-6253-8162","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":211054,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gidley, Rachel G. 0000-0002-9840-8252","orcid":"https://orcid.org/0000-0002-9840-8252","contributorId":259315,"corporation":false,"usgs":true,"family":"Gidley","given":"Rachel","email":"","middleInitial":"G.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gohring, Evan J. 0000-0002-2229-9512","orcid":"https://orcid.org/0000-0002-2229-9512","contributorId":315496,"corporation":false,"usgs":true,"family":"Gohring","given":"Evan","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"King, Tyler V. 0000-0002-5785-3077","orcid":"https://orcid.org/0000-0002-5785-3077","contributorId":292424,"corporation":false,"usgs":true,"family":"King","given":"Tyler","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":952458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gibney, Nicole D.","contributorId":364297,"corporation":false,"usgs":false,"family":"Gibney","given":"Nicole","middleInitial":"D.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":952459,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bauch, Nancy J. 0000-0002-0302-2892","orcid":"https://orcid.org/0000-0002-0302-2892","contributorId":364298,"corporation":false,"usgs":false,"family":"Bauch","given":"Nancy","middleInitial":"J.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":952460,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70273088,"text":"fs20253054 - 2025 - Assessment of undiscovered oil and gas resources in the Haynesville Formation within the onshore United States and State waters of the Gulf Coast Basin, 2024","interactions":[],"lastModifiedDate":"2026-02-03T16:57:11.180664","indexId":"fs20253054","displayToPublicDate":"2025-12-17T11:55:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3054","displayTitle":"Assessment of Undiscovered Oil and Gas Resources in the Haynesville Formation Within the Onshore United States and State Waters of the Gulf Coast Basin, 2024","title":"Assessment of undiscovered oil and gas resources in the Haynesville Formation within the onshore United States and State waters of the Gulf Coast Basin, 2024","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 152 million barrels of oil and 47.9 trillion cubic feet of gas in reservoirs of the Haynesville Formation within the onshore United States and State waters of the Gulf Coast Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253054","usgsCitation":"Gardner, R., Flaum, J.A., Birdwell, J.E., Kinney, S.A., Pitman, J.K., Paxton, S.T., French, K.L., Mercier, T.J., Leathers-Miller, H.M., and Schenk, C.J., 2025, Assessment of undiscovered oil and gas resources in the Haynesville Formation within the onshore United States and State waters of the Gulf Coast Basin, 2024: U.S. Geological Survey Fact Sheet 2025–3054, 4 p., https://doi.org/10.3133/fs20253054.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-170936","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":497815,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119056.htm"},{"id":497508,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1AQ879T","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Gulf Coast Mesozoic Province, Haynesville Formation—Assessment Unit Boundaries, Assessment Input Tables, and Fact Sheet Data Tables"},{"id":497639,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3054/images/"},{"id":497638,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3054/fs20253054.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3054 XML"},{"id":497637,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253054/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3054 HTML"},{"id":497506,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3054/coverthb.jpg"},{"id":497507,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3054/fs20253054.pdf","text":"Report","size":"2.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3054 PDF"}],"country":"United States","state":"Alabama, Arkansas, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf Coast basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102,\n 34\n ],\n [\n -102,\n 28\n ],\n [\n -85.5,\n 28\n ],\n [\n -85.5,\n 34\n ],\n [\n -102,\n 34\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Urban runoff containing high amounts of nutrients like phosphorus (P) is a well-established driver of surface water eutrophication. In residential areas, a primary source of nutrients is derived from leaf litter. P contained in leaves is leached and transported by stormwater from source to stream. The majority of P leached from leaf litter is in the dissolved phase, which can be difficult to remove using conventional treatment practices, leaving source control as the most viable option. Additional tools are needed to help forecast how different tree species may improve or hinder contributions of nutrients to runoff. For this reason, ten street tree species that are common throughout the contiguous U.S. were chosen to evaluate the effect of species on leachable P from tree leaves using laboratory experiments. After 48 h of exposure to water, the amount of P released ranged from 2.16 mg P g−1 leaf for Silver Maple to 0.03 mg P g−1 leaf for Hackberry. More than half of the P was lost in the first 12 h for eight of the ten tree species, making guided source control important to reduce inputs to surface water from key locations. Results were used to identify ‘hotspots’ of P leaching in Madison, WI and can be used to assess current street tree inventories that can then guide management to areas with the highest nutrient reduction potential and inform urban foresters who may wish to tailor future planting scenarios that minimize nutrients in runoff.
","language":"English","publisher":"Springer","doi":"10.1007/s11270-025-08858-3","collaboration":"U.S. Forest Service, University of Wisconsin-Madison","usgsCitation":"Collin Klaubauf, Anita Thompson, Selbig, W.R., and Laxmir Prasad, 2025, Quantifying leachable phosphorus from the leaves of common midwest urban street trees and implications for stormwater management: Water, Air, & Soil Pollution, v. 237, 269, 19 p., https://doi.org/10.1007/s11270-025-08858-3.","productDescription":"269, 19 p.","ipdsId":"IP-174216","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11270-025-08858-3","text":"Publisher Index Page"},{"id":497680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Madison","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.18404405740438,\n 43.22776059386794\n ],\n [\n -89.64470062715654,\n 43.22776059386794\n ],\n [\n -89.64470062715654,\n 42.95864817099735\n ],\n [\n -89.18404405740438,\n 42.95864817099735\n ],\n [\n -89.18404405740438,\n 43.22776059386794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"237","noUsgsAuthors":false,"publicationDate":"2025-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Collin Klaubauf","contributorId":364361,"corporation":false,"usgs":false,"family":"Collin Klaubauf","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":952590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anita Thompson","contributorId":364362,"corporation":false,"usgs":false,"family":"Anita Thompson","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":952591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laxmir Prasad","contributorId":364364,"corporation":false,"usgs":false,"family":"Laxmir Prasad","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":952593,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273105,"text":"fs20253056 - 2025 - Assessing streams in the Chesapeake Bay Watershed to guide conservation and restoration activities","interactions":[],"lastModifiedDate":"2026-02-03T16:56:23.055037","indexId":"fs20253056","displayToPublicDate":"2025-12-16T16:33:29","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3056","displayTitle":"Assessing Streams in the Chesapeake Bay Watershed to Guide Conservation and Restoration Activities","title":"Assessing streams in the Chesapeake Bay Watershed to guide conservation and restoration activities","docAbstract":"Freshwater streams in the Chesapeake Bay watershed are home to numerous aquatic organisms (like fish, amphibians, mussels, and insects) and provide drinking water and recreational opportunities to people living in or visiting the watershed. Land-use changes, such as urban development and increased activities in certain agricultural sectors, have degraded water quality and altered conditions in these streams, thereby affecting their health and function. The U.S. Geological Survey (USGS) is working with Federal, State, and local partners to develop modeled assessments of stream health in freshwater streams and rivers within the Chesapeake Bay watershed. The USGS compiled large datasets for multiple stream health indicators, including instream stressors (salinity, water temperature, physical habitat, and streambank erosion) and living resources (macroinvertebrates and fish communities; fig. 1). These datasets were used by USGS scientists to develop models to predict stream health conditions across the entire region, including areas with little or no monitoring data. Collectively, these stream health assessments provide critical information to natural resource managers who implement restoration and conservation activities in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253056","issn":"2327-6932","isbn":"2327-6916","usgsCitation":"Maloney, K.O., Fanelli, R.M., Cashman, M.J., Boyle, L.J., Gordon, S.E., Gressler, B.P., Katoski, M.P., Kiser, A.H., Metes, M.J., Noe, G.B., Sekellick, A.J., Sussman, A., and Young, J.A., 2025, Assessing streams in the Chesapeake Bay Watershed to guide conservation and restoration activities: U.S. Geological Survey Fact Sheet 2025–3056, 4 p., https://doi.org/10.3133/fs20253056.","productDescription":"3 p.","onlineOnly":"N","ipdsId":"IP-180465","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":497539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3056/fs20253056.pdf","text":"Report","size":"39.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3056 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U.S. Geological Survey
12100 Beech Forest Rd., Ste 4039
Laurel, MD 20708
An evaluation of sediment deposition rates and volume of impounded sediments in Pahranagat Wash behind Arrow Canyon dam in southeastern Nevada was done between 2016 and 2022. Data were collected and interpreted to address concerns by the Moapa Band of Paiutes and local historical preservation groups regarding the burial of culturally important sites by the impounded sediment deposited behind the dam. Sediment cores from two wells, drilled to depths that reflect the original stream-channel profile, and a third site drilled and sampled at a finer resolution, were analyzed radiometrically for lead-210 (210Pb) and cesium-137 (137Cs) isotopes. The analysis of the 210Pb data yielded an overall estimated sediment deposition rate of 2.4 inches per year (in/yr). Using the 137Cs data, the sediment deposition rate declined from 9.4 in/yr from 1934 to 1951 to 4.2 in/yr from 1951 to 1964 to 1.0 in/yr between 1964 and 2019.
Sediment volume was determined by defining boundaries using a 1-foot contour map generated using Unmanned Aerial Survey datasets and field observations. The volume calculation involved segmenting the study area based on the availability of sediment thickness data. The average sediment thickness in each segment was multiplied by the surface area of each segment to obtain the total sediment volume of 4.3×107 cubic feet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255106","collaboration":"Prepared in cooperation with the Bureau of Land Management","programNote":"Water Resources Mission Area","usgsCitation":"Wilson, J.W., Poff, B., and Fuller, C.C., 2025, Sediment accumulation rates and volume in Pahranagat Wash above Arrow Canyon Dam in northern Moapa Valley, Nevada: U.S. Geological Survey Scientific Investigations Report 2025–5106, 14 p., https://doi.org/10.3133/sir20255106.","productDescription":"Report: vi, 14 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-154187","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":497609,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5106/images"},{"id":497607,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P9Q1A8","text":"USGS data release","description":"USGS data release","linkHelpText":"Radiometric analysis (cesium-137 and lead-210) at selected depth intervals from borehole core of impounded sediments in Pahranagat Wash behind Arrow Canyon Dam, northern Clark County, Nevada"},{"id":497606,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255106/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5106"},{"id":497605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5106/sir20255106.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5106"},{"id":497604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5106/coverthb.jpg"},{"id":497610,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5106/sir20255106.XML"},{"id":497608,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C4DRI5","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data for impounded sediments in Pahranagat Wash above Arrow Canyon Dam, in northern Moapa Valley, Nevada"},{"id":497813,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119055.htm"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahranagat Wash above Arrow Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.8667,\n 36.7667\n ],\n [\n -114.8667,\n 36.7333\n ],\n [\n -114.75,\n 36.7333\n ],\n [\n -114.75,\n 36.7667\n ],\n [\n -114.8667,\n 36.7667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road, Suite 3
Carson City, Nevada 89701
U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas:
The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.
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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Cyanobacterial toxicity, cyanotoxins, and their impact on aquatic ecosystems and human health are well documented. In comparison, less is known about bloom-associated bacterial communities. Co-occurring bacteria can influence bloom development, physiology and collapse, and may also provide a niche for pathogenic bacteria. Existing research focuses on the cyanosphere of Microcystis-dominated blooms, despite the increasing prevalence of filamentous genera (Aphanizomenon and Planktothrix). This pilot study aimed to broaden our understanding of the bacterial consortia attached to morphologically distinct cyanobacteria (coccoid and filamentous) dominating phytoplankton communities and to explore their potential roles in amplifying the impacts of cyanobacterial blooms. We investigated four shallow freshwater bodies across three continents and two climate zones: an urban pond in the USA, a dammed reservoir and a natural lake in Poland, and an urban water body in Singapore. Amplicon sequencing (16S rRNA gene) was used to characterize bacterial communities, while shotgun metagenomics identified nitrogen- and phosphorus-cycling genes to infer potential eco-physiological functions. Cyanobacteria dominated bacterioplankton assemblages at all sites (>35.6%), with bloom composition influencing toxigenic profiles. A mixed bloom of Microcystis, Snowella, and Aphanizomenon had the broadest range of cyanotoxin synthetase genes (mcyE, cyrJ, anaF and sxtA). Microcystis blooms correlated with increased Roseomonas, while Planktothrix co-occurred with Flavobacterium – both bacteria likely contribute to nutrient-cycling within blooms and represent potential opportunistic pathogens for aquatic organisms and humans. The Microcystis cyanosphere exhibited the highest number of significant positive correlations with bacteria (19 relations), compared to Planktothrix and Aphanizomenon (11 and 2 relations, respectively). Non-diazotrophic blooms of Microcystis and Planktothrix showed greater abundances of nitrogen – (ureB, glnA, narB, and narHZ) and phosphorus-cycling genes (phoBHPR and ppk1), indicating a strong dependence on associated bacteria for nutrient acquisition compared to diazotrophic Aphanizomenon. These findings suggest that Aphanizomenon-dominated blooms may be sustained by simpler microbiomes. Our results provide preliminary evidence of cyanosphere heterogeneity potentially shaped by the dominance or coexistence of three morphologically and eco-physiologically distinct genera of cyanobacteria. A comprehensive knowledge of the taxonomy and functional roles of bloom-associated microbiomes is therefore essential to understand bloom activity, evaluate the environmental threat, and develop effective strategies for prevention and mitigation.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmicb.2025.1655370","usgsCitation":"Mankiewicz-Boczek, J., Font Nájera, A., Gin, K.Y., Graham, J.L., Strapagiel, D., Gorney, R.M., Kok, J.W., Te, S.H., Kluska, M., Skóra, M., Seweryn, M., and Hun, F.J., 2025, Bacterial community diversity and potential eco-physiological roles in toxigenic blooms composed of Microcystis, Aphanizomenon or Planktothrix: Frontiers in Microbiology, v. 16, 1655370, 15 p., https://doi.org/10.3389/fmicb.2025.1655370.","productDescription":"1655370, 15 p.","ipdsId":"IP-179083","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":497747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2025.1655370","text":"Publisher Index 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1987 to 2017","interactions":[],"lastModifiedDate":"2026-01-07T17:45:08.410713","indexId":"70273185","displayToPublicDate":"2025-12-15T10:49:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"The US EPA’s National Nutrient Inventory: Critical shifts in US nutrient pollution sources from 1987 to 2017","docAbstract":"Efforts to constrain the negative environmental impacts of excess nitrogen (N) and phosphorus (P) are costly and challenging, due in part to inconsistent reporting of nutrient sources at temporal and spatial scales relevant for local decision making. To meet this challenge, the U.S. Environmental Protection Agency’s National Nutrient Inventory provides estimates of major agricultural, urban, atmospheric, and natural nutrient fluxes for the contiguous United States at county and HUC12 scales annually from 1987 (from 1950 for agriculture) to 2017. Since the late 1980s, total N emissions and atmospheric N deposition have declined 22% and 15%, respectively, despite increased agricultural emissions. Over the same period, municipal wastewater N and P loads remained largely stable, despite population increases, through wastewater treatment upgrades and the phaseout of phosphorus-containing detergents. Improved agricultural efficiency allowed for dramatic increases in agricultural production and crop harvest since 1987 (∼25% for N and P), with little change in surplus nutrients left on fields. Overall, a combination of innovative technologies and management has stemmed or even decreased major sources of nutrient pollution to the environment over the last several decades, representing an important shift that, if continued, may contribute to improved air, land, and water quality and human health.
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data through weakly supervised deep learning","docAbstract":"Monitoring the extent of surface water features (hydrography), accurately storing them in databases, and representing them on topographic maps are essential for various applications such as navigation and policy-making for legislative boundaries and permitting. In this context, hydrographic data includes features that generally have water present or image data showing signs that water is forming a terrain channel, and which would be included in 1:24,000 or larger scale topographic maps. In addition, reliable hydrographic data play a critical role to help manage environmental risks such as droughts, floods, fires, and landslides, as well as monitoring biological resources and pollutants. Inaccuracies in hydrography data can lead to modelling inaccuracies, resulting in economic, social, and environmental risks. However, generating sufficiently accurate high-resolution (HR) hydrography and terrain data for these purposes remains a substantial challenge primarily because of complex surface water dynamics and data handling limitations.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Abstracts of the International Cartographic Association","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Cartographic Association","doi":"10.5194/ica-abs-10-275-2025","usgsCitation":"Stanislawski, L., Qin, R., Liu, J., Shavers, E.J., Wang, S., Jaroenchai, N., and Thiem, P.T., 2025, Multi-temporal surface water mapping with high-resolution elevation and image data through weakly supervised deep learning, in Abstracts of the International Cartographic Association, v. 7, no. 10, 275, 3 p., https://doi.org/10.5194/ica-abs-10-275-2025.","productDescription":"275, 3 p.","ipdsId":"IP-179538","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":498917,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ica-abs-10-275-2025","text":"Publisher Index Page"},{"id":498745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"7","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qin, Rongjun","contributorId":333939,"corporation":false,"usgs":false,"family":"Qin","given":"Rongjun","email":"","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":947788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Jung-Kuan 0000-0001-8461-8200","orcid":"https://orcid.org/0000-0001-8461-8200","contributorId":333940,"corporation":false,"usgs":true,"family":"Liu","given":"Jung-Kuan","email":"","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Shaowen","contributorId":198966,"corporation":false,"usgs":false,"family":"Wang","given":"Shaowen","email":"","affiliations":[],"preferred":false,"id":947791,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jaroenchai, Nattapon","contributorId":267318,"corporation":false,"usgs":false,"family":"Jaroenchai","given":"Nattapon","email":"","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":947792,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947793,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273108,"text":"70273108 - 2025 - Efficacy of oblique bubble screen deterrents on redirecting live eggs and larvae of grass carp (Ctenopharyngodon idella) at different developmental stages","interactions":[],"lastModifiedDate":"2025-12-16T15:19:23.792373","indexId":"70273108","displayToPublicDate":"2025-12-13T09:18:20","publicationYear":"2025","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}},"displayTitle":"Efficacy of oblique bubble screen deterrents on redirecting live eggs and larvae of grass carp (Ctenopharyngodon idella) at different developmental stages","title":"Efficacy of oblique bubble screen deterrents on redirecting live eggs and larvae of grass carp (Ctenopharyngodon idella) at different developmental stages","docAbstract":"Invasive carp have severely damaged aquatic ecosystems in the USA, particularly in the Mississippi River Basin. Behavioral deterrents have been developed in the last few decades to control population expansion into new ecosystems. However, none of these deterrents are capable of controlling early-life stage carp, which have limited or no mobility during their drifting stage in rivers. Capturing eggs and larvae in large numbers warrants new methods due to their distinct physical and biological properties as well as their lack of behavioral response. We tested a novel method to redirect downstream drifting eggs and larvae for their efficient removal in streams using an oblique bubble screen (OBS) deterrent. We investigated the effects of mean water velocity and airflow rate on redirection of eggs, pre-gas bladder inflation (GBI) larvae, near-GBI larvae, and dead larvae. Although similar OBS configurations had shown high efficacy redirecting plastic spheres (egg surrogates) in previous studies, they underperform redirecting live eggs and larvae. However, distinct patterns were identified for eggs, pre-GBI, near-GBI, and dead larvae. A detailed hydrodynamic analysis showed that eggs closely follow the larger scales of motions created by the OBS, and that larvae can actively respond to turbulence cues. This study yielded new insights into the movement of early-life stage grass carp in a turbulent flow with strong recirculation, and provided important data to improve the design of bubble screen dispersal barriers for invasive carp management and population control.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR039967","usgsCitation":"Prasad, V., Andrade Ramos, J.M., Suski, C., Jackson, P.R., George, A.E., Chapman, D.C., Fischer, J.R., Stahlschmidt, B.H., and Tinoco, R.O., 2025, Efficacy of oblique bubble screen deterrents on redirecting live eggs and larvae of grass carp (Ctenopharyngodon idella) at different developmental stages: Water Resources Research, v. 61, no. 12, e2025WR039967, 26 p., https://doi.org/10.1029/2025WR039967.","productDescription":"e2025WR039967, 26 p.","ipdsId":"IP-172992","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497725,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr039967","text":"Publisher Index Page"},{"id":497568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-12-13","publicationStatus":"PW","contributors":{"authors":[{"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":952356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrade Ramos, Juan Martin 0009-0003-8610-5574","orcid":"https://orcid.org/0009-0003-8610-5574","contributorId":364205,"corporation":false,"usgs":false,"family":"Andrade Ramos","given":"Juan","middleInitial":"Martin","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":952357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suski, Cory 0000-0001-8280-873X","orcid":"https://orcid.org/0000-0001-8280-873X","contributorId":364207,"corporation":false,"usgs":false,"family":"Suski","given":"Cory","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":952358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":952359,"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":952360,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Duane C. 0000-0002-1086-8853","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":364209,"corporation":false,"usgs":false,"family":"Chapman","given":"Duane","middleInitial":"C.","affiliations":[{"id":86770,"text":"USGS-CERC (retired)","active":true,"usgs":false}],"preferred":false,"id":952361,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":952362,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":952363,"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":952364,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274191,"text":"70274191 - 2025 - Post-wildfire sediment fluxes and turbidity plumes in a coastal-draining watershed","interactions":[],"lastModifiedDate":"2026-03-04T22:30:06.144695","indexId":"70274191","displayToPublicDate":"2025-12-12T15:20:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Post-wildfire sediment fluxes and turbidity plumes in a coastal-draining watershed","docAbstract":"Coastal watersheds impacted by wildfires experience higher erosion resulting in increased sediment delivery to the ocean that alters limiting factors (i.e., light) for marine organisms. With increasing wildfire magnitude and severity, it is critical to explore changes in riverine discharges to the ocean to assess cascading hazards associated with wildfires. In situ data, remotely sensed turbidity data, and hydrological model (Soil and Water Assessment Tool “SWAT”) simulations have been adapted to capture and investigate fire-related land use change impacts on Malibu Creek, California, USA. Modifying SWAT land cover inputs using burn severity data had minimal impact on simulations, requiring additional parameterization for acceptable model performance. Remotely sensed turbidity, in situ discharge, rating curve sediment loads, and SWAT simulated discharge and sediment loads increased following the Woolsey Fire. When compared to in situ and rating curve data in similar non-fire water years, the 2019 Woolsey Fire water year in situ discharge was 1.8 times higher, SWAT simulated discharges were 1.4–1.7 times higher, and rating curve sediment load was 1.3 times higher. However, the SWAT simulated sediment loads were slightly lower (0.8–0.9 times) than rating curve sediment loads in similar non-fire water years. Mean coastal turbidity increased to 18.2 Formazin Nephelometric Unit (FNU) during the first storm post-fire (mean background value of 4.3 FNU). Synergies between methods demonstrated rapid coastal sediment exports (remote sensing) and ongoing erosion post-fire (SWAT). These data are essential to understanding fire-related marine ecological changes and implementing effective management and conservation initiatives.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024ea003843","usgsCitation":"Lopez, A.M., Meshesha, T.W., Lee, C.M., Mohammed, I.N., Hestir, E.L., Harmon, T.C., and Avouris, D., 2025, Post-wildfire sediment fluxes and turbidity plumes in a coastal-draining watershed: Earth and Space Science, v. 12, no. 12, e2024EA003843, 23 p., https://doi.org/10.1029/2024ea003843.","productDescription":"e2024EA003843, 23 p.","ipdsId":"IP-157846","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500850,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024ea003843","text":"Publisher Index Page"},{"id":500768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Malibu","otherGeospatial":"Santa Monica Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.80683049274855,\n 34.13442907849944\n ],\n [\n -118.80683049274855,\n 34.01851549973419\n ],\n [\n -118.63307632018143,\n 34.01851549973419\n ],\n [\n -118.63307632018143,\n 34.13442907849944\n ],\n [\n -118.80683049274855,\n 34.13442907849944\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Lopez, Amanda M.","contributorId":367167,"corporation":false,"usgs":false,"family":"Lopez","given":"Amanda","middleInitial":"M.","affiliations":[{"id":27923,"text":"NASA JPL","active":true,"usgs":false}],"preferred":false,"id":956879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meshesha, Tesfa W.","contributorId":367168,"corporation":false,"usgs":false,"family":"Meshesha","given":"Tesfa","middleInitial":"W.","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":956880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Christine M.","contributorId":367169,"corporation":false,"usgs":false,"family":"Lee","given":"Christine","middleInitial":"M.","affiliations":[{"id":27923,"text":"NASA JPL","active":true,"usgs":false}],"preferred":false,"id":956881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mohammed, Ibrahim N.","contributorId":367170,"corporation":false,"usgs":false,"family":"Mohammed","given":"Ibrahim","middleInitial":"N.","affiliations":[{"id":87588,"text":"Kalifa University","active":true,"usgs":false}],"preferred":false,"id":956882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hestir, Erin L.","contributorId":367171,"corporation":false,"usgs":false,"family":"Hestir","given":"Erin","middleInitial":"L.","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":956883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harmon, Thomas C.","contributorId":367172,"corporation":false,"usgs":false,"family":"Harmon","given":"Thomas","middleInitial":"C.","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":956884,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Avouris, Dulcinea Marie 0000-0001-5797-3960","orcid":"https://orcid.org/0000-0001-5797-3960","contributorId":335170,"corporation":false,"usgs":true,"family":"Avouris","given":"Dulcinea Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956885,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272812,"text":"ofr20251042 - 2025 - Assessment of dragonfly and damselfly (Odonata) occupancy and habitat suitability at −12 Mile Slough, Glen Canyon National Recreation Area, Arizona","interactions":[],"lastModifiedDate":"2026-02-03T16:52:15.723938","indexId":"ofr20251042","displayToPublicDate":"2025-12-12T11:15:36","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1042","displayTitle":"Assessment of Dragonfly and Damselfly (Odonata) Occupancy and Habitat Suitability at −12 Mile Slough, Glen Canyon National Recreation Area, Arizona","title":"Assessment of dragonfly and damselfly (Odonata) occupancy and habitat suitability at −12 Mile Slough, Glen Canyon National Recreation Area, Arizona","docAbstract":"Management practices that enhance habitat complexity in dam tailwaters often aim to increase biodiversity and improve ecosystem health. However, in other instances, management practices may simplify habitat features to help minimize the establishment of invasive species. These tradeoffs are complex, particularly in the face of drought and warming water temperatures. In Glen Canyon National Recreation Area, a backwater known as −12 Mile Slough (henceforth the Slough), located 5-kilometers downstream from Glen Canyon Dam, is being considered for removal to reduce breeding habitat for warmwater nonnative fishes. In this report, the habitat suitability for and occupancy of dragonflies and damselflies (Odonata) at the Slough are assessed. U.S. Geological Survey staff conducted three site visits to the Colorado River in Glen Canyon, the Slough, and another backwater (“Frogwater”) on September 11–13, and 26, 2024. The physical habitat of the sampling sites was characterized by recording water temperatures, specific conductance, dissolved oxygen, turbidity, flow, depth, and benthic substratum size distribution. We sampled aquatic macroinvertebrates and riparian macroinvertebrates using benthic and aerial collection methods, respectively. We describe three distinct benthic aquatic invertebrate communities in and around the Slough, two of which contained Odonata. We found no Odonata larvae in the mainstem, at Frogwater, or in the Lower Slough. Using historic specimen data from the Museum of Northern Arizona, we report 8 species of damselflies from one family (Coenagrionidae) and 8 species of dragonflies from three families (Aeshnidae, Gomphidae, and Libellulidae) in Glen Canyon between 1985 and 2024. We discuss the habitat requirements of Odonata larvae known to occur in the Slough, as well as their cultural and recreational values. We conclude that channelization of the Slough to cool water temperatures may reduce larval Odonata habitat locally but is unlikely to affect their diversity and abundance on a regional scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251042","collaboration":"National Park Service, Bureau of Reclamation, Springs Stewardship Institute","usgsCitation":"Metcalfe, A.N., Ford, M.A., Stevens, L.E., and Kennedy, T.A., 2025, Assessment of dragonfly and damselfly (Odonata) occupancy and habitat suitability at −12 Mile Slough, Glen Canyon National Recreation Area, Arizona: U.S. Geological Survey Open-File Report 2025–1042, 15 p., https://doi.org/10.3133/ofr20251042.","productDescription":"Report, ix, 15 p.; Data Release","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-173051","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497289,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1042/images"},{"id":497288,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1042/ofr20251042.XML","description":"OFR 2025-1042 XML"},{"id":497291,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1042/coverthb2.jpg"},{"id":497286,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1042/ofr20251042.pdf","text":"Report","size":"7.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1042 PDF"},{"id":497287,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251042/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1042 HTML"},{"id":497290,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1EJXMAO","text":"USGS Data Release","linkHelpText":"Aquatic Invertebrate and Habitat Assessment in Glen Canyon and Associated Backwaters, September 2024"}],"country":"United States","state":"Arizona","otherGeospatial":"12 Mile Slough, Glen Canyon National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.49179778654118,\n 36.90754527885582\n ],\n [\n -111.57073960910685,\n 36.90754527885582\n ],\n [\n -111.57073960910685,\n 36.8586991785957\n ],\n [\n -111.49179778654118,\n 36.8586991785957\n ],\n [\n -111.49179778654118,\n 36.90754527885582\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Southwest Biological Science Center
Grand Canyon Monitoring and Research Center
U.S. Geological Survey
2255 N Gemini Drive
Flagstaff, AZ 86001
Disassociating the independent effects of flow and water quality on the ecology of flowing waters is an overarching goal in water resource science needed to improve the efficacy of watershed management. However, the interrelatedness of these gradients and their subsequent alteration due to land use change has constrained progress made on this front. The objective of this study was to use benthic macroinvertebrate and fish assemblage data to characterize flow-ecology relationships that were unchanged by water quality impacts across two southeastern landscapes in the USA to help detect ecological change driven by flow alteration. General linear latent models were used to identify taxa that were responsive to high or low flow metrics and water quality gradients. Bayesian hierarchical generalized additive models were then developed using these indicator taxa and three biological metrics to identify flow-specific relationships that were unaffected by water quality impacts. Three low flow-specific relationships were identified, illustrating how potential agricultural or urban impacts to hydrology reduced stream biological health. Importantly, flow-ecology relationships developed using indicator taxa in this study effectively captured hydrology-specific impacts while biological metrics typical of state monitoring and assessment programs did not. Therefore, developing flow-specific biological metrics is a critical step when developing management strategies targeting flow alteration. Implementing standardized frameworks such as the one characterized here can limit contradictory findings and improve streamflow enhancement and restoration project efficacy. These low flow-specific relationships will enhance managers' capacity to develop environmental flow standards, monitor their success, and better understand urban and agricultural impacts on stream assemblages.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.70129","usgsCitation":"Hubbell, J., 2025, Streamflow as a stressor: Disentangling hydrology and water quality impacts to characterize flow-ecology relationships for two stream assemblages across two southeastern landscapes: Ecohydrology, v. 18, no. 8, e70129, 19 p., https://doi.org/10.1002/eco.70129.","productDescription":"e70129, 19 p.","ipdsId":"IP-170276","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":499585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"18","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Hubbell, Joshua Paul 0000-0002-5455-8451","orcid":"https://orcid.org/0000-0002-5455-8451","contributorId":347668,"corporation":false,"usgs":true,"family":"Hubbell","given":"Joshua Paul","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955110,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70273156,"text":"70273156 - 2025 - Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects","interactions":[],"lastModifiedDate":"2025-12-17T15:40:56.415479","indexId":"70273156","displayToPublicDate":"2025-12-10T09:35:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23101,"text":"npj Artificial Intelligence","active":true,"publicationSubtype":{"id":10}},"title":"Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects","docAbstract":"Machine learning (ML) models are often based on complex black-box architectures that are difficult to interpret. This interpretability problem can hinder the use of ML in fields like medicine, ecology, and insurance, and has boosted research in interpretable machine learning (IML). Here, we propose a novel approach for the functional decomposition of black-box predictions, which is a core concept of IML. This approach replaces the prediction function with a surrogate model consisting of simpler subfunctions, providing insights into the direction and strength of the main feature contributions and their interactions. Our method is based on a concept termed “stacked orthogonality”, which ensures that the main effects capture as much functional behavior as possible. To compute the subfunctions, we combine neural additive modeling with an efficient post-hoc orthogonalization procedure. Our method yielded plausible results in an analysis of stream biological condition in the Chesapeake Bay watershed (United States).
","language":"English","publisher":"Nature","doi":"10.1038/s44387-025-00033-7","usgsCitation":"Kohler, D., Rügamer, D., Boyle, L.J., Maloney, K.O., and Schmid, M., 2025, Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects: npj Artificial Intelligence, v. 1, 34, 13 p., https://doi.org/10.1038/s44387-025-00033-7.","productDescription":"34, 13 p.","ipdsId":"IP-168406","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s44387-025-00033-7","text":"Publisher Index Page"},{"id":497636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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Learning","active":true,"usgs":false}],"preferred":false,"id":952511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyle, Lindsey J. 0009-0007-8825-5700","orcid":"https://orcid.org/0009-0007-8825-5700","contributorId":334493,"corporation":false,"usgs":true,"family":"Boyle","given":"Lindsey","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":952512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmid, Matthias","contributorId":236855,"corporation":false,"usgs":false,"family":"Schmid","given":"Matthias","affiliations":[{"id":47552,"text":"University of Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":952514,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273055,"text":"70273055 - 2025 - Longer exposure to warm water increases subsequent thermal tolerance of brook trout in cold water: Acclimation timing and physiology","interactions":[],"lastModifiedDate":"2025-12-15T14:14:31.875055","indexId":"70273055","displayToPublicDate":"2025-12-10T09:34:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Longer exposure to warm water increases subsequent thermal tolerance of brook trout in cold water: Acclimation timing and physiology","docAbstract":"Climate change has resulted in increased incidence and variability of warming episodes in cold-water streams that support salmonids. The capacity to acclimate to warm temperatures may allow cold-water fish to persist in spite of changing thermal regimes, but accurately predicting fish performance under fluctuating stream temperatures also requires understanding re-acclimation to cool water, which is less well understood. We tested how thermal acclimation to warm temperatures and re-acclimation to cool water affected thermal tolerance and physiological endpoints in juvenile brook trout (Salvelinus fontinalis). We show that an initial thermal exposure (22°C, ΔT = 7°C) of 3, 7 and 14 days (but not 1 day) improved critical thermal maximum (CTmax) after a 14-day re-acclimation to cooler temperatures (15°C). Fish growth during the re-acclimation period decreased with increasing duration of initial thermal exposure (22°C). Physiological parameters associated with thermal acclimation (cortisol, glucose, haematocrit and haemoglobin) were lower at 15°C re-acclimation temperature than at the initial thermal treatment (22°C) and in some cases, lower than the 15°C control. Muscle HSP70 protein increased early (1 day) as part of the warm acclimation process and remained elevated at lower levels for up to 14 days. During re-acclimation to 15°C, HSP70 decreased relative to initial measures at 22°C. Fish exposed to the longest thermal treatment (22°C for 14 days) maintained elevated CTmax after 30 days of re-acclimation to 15°C without observed differences in the measured physiological endpoints but returned to control levels after 42 days at 15°C. This work shows that high-temperature acclimation effects in brook trout are retained for up to 30 days following re-acclimation to cool temperatures, and that isolated warming events may be expected to temporarily enhance thermal tolerance in subsequent thermal challenges.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coaf082","usgsCitation":"Regish, A.M., O’Donnell, M., Letcher, B., Lambert, T., Hall, D.J., and McCormick, S.D., 2025, Longer exposure to warm water increases subsequent thermal tolerance of brook trout in cold water: Acclimation timing and physiology: Conservation Physiology, v. 13, no. 1, coaf082, 21 p., https://doi.org/10.1093/conphys/coaf082.","productDescription":"coaf082, 21 p.","ipdsId":"IP-176771","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497702,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coaf082","text":"Publisher Index Page"},{"id":497470,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Matthew 0000-0002-9089-2377 mjodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":167315,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Matthew","email":"mjodonnell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lambert, Timothy 0000-0002-9309-7782","orcid":"https://orcid.org/0000-0002-9309-7782","contributorId":364028,"corporation":false,"usgs":true,"family":"Lambert","given":"Timothy","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":952183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Daniel J. 0000-0003-2490-1535","orcid":"https://orcid.org/0000-0003-2490-1535","contributorId":244103,"corporation":false,"usgs":true,"family":"Hall","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCormick, Stephen D. 0000-0003-0621-6200","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":364030,"corporation":false,"usgs":false,"family":"McCormick","given":"Stephen","middleInitial":"D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":952185,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272787,"text":"ofr20251055 - 2025 - Rapid structured decision making for Hypomesus transpacificus (delta smelt) summer–fall freshwater outflow management","interactions":[],"lastModifiedDate":"2026-02-03T16:50:11.545344","indexId":"ofr20251055","displayToPublicDate":"2025-12-09T16:20:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1055","displayTitle":"Rapid Structured Decision Making for Hypomesus Transpacificus (Delta Smelt) Summer–Fall Freshwater Outflow Management","title":"Rapid structured decision making for Hypomesus transpacificus (delta smelt) summer–fall freshwater outflow management","docAbstract":"Managers of the Central Valley Project (CVP) and State Water Projects (SWP) in California are confronted with difficult tradeoffs between water uses and associated values affected by water management decisions. These decisions involve altering the timing and magnitude of water releases from dams and reservoirs, which can affect habitats for economically important and Federally and State-listed endangered fish species, water deliveries for agriculture or municipalities, and water quality. In this report, we describe the results of a rapid structured decision-making process used to assist management agencies in evaluating tradeoffs while gathering input from cooperating agencies, rightsholders, or interested parties (hereafter participants) through facilitated workshops in spring 2025. Consideration of alternative water management actions was initiated by the continued decline of Hypomesus transpacificus (delta smelt) populations and the issuance of a new biological opinion for the CVP and SWP long-term operations on the effects on delta smelt and other Endangered Species Act-listed species in November 2024. An Executive Order was also issued in January 2025, directing the Bureau of Reclamation to maximize water deliveries. Participants, led by the U.S. Geological Survey and cooperating agencies, identified 8 fundamental values (hereafter objectives) and 11 alternative water management scenarios (or “alternative management actions” based on the PrOACT model). Using multicriteria decision analysis, we evaluated performance (or “consequences” based on a consequence table analysis) and analyzed tradeoffs of alternative water management actions to the fundamental objectives. We ranked the alternative water management actions based on four participants’ objective weights and composite utility scores calculated using a linear value function. The three highest ranking alternative water management actions had the poorest performance for delta smelt but performed best for CVP and SWP water exports and objectives related to coldwater pool operations for salmonids. An optimum strategy that could prevent the extinction of delta smelt was not determined for this study. However, insights gained from our rapid decision analysis suggested nonflow scenarios could benefit the delta smelt population, including in drier years, and could be considered to avoid curtailment of water exports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251055","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation, the Metropolitan Water District of Southern California, and the California Department of Water Resources","usgsCitation":"Healy, B.D., Phillis, C.C., Mahardja, B., Koizumi, C., Pien, C., Parker, N., Conrad, J.L., Ekstrom, J., Leimbach, J., Silberblatt, R., Fischer, T., and Ehlo, C., 2025, Rapid structured decision making for Hypomesus transpacificus (delta smelt) summer–fall freshwater outflow management: U.S. Geological Survey Open-File Report 2025–1055, 36 p., https://doi.org/10.3133/ofr20251055.","productDescription":"Report: viii, 36 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179521","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1055/ofr20251055.pdf","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1055 PDF"},{"id":497240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1055/coverthb.jpg"},{"id":497244,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1055/images/"},{"id":497245,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13BBC7D","text":"USGS data release","linkHelpText":"Multicriteria decision analysis scores for rapid delta smelt decision analysis"},{"id":497242,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251055/full","description":"OFR 2025-1055 HTML"},{"id":497243,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1055/ofr20251055.XML","description":"OFR 2025-1055 XML"}],"contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Decisions on how to store and distribute water in California’s Central Valley are made considering the use of water resources by people, fish and wildlife, and the effects on water quality. Water is stored behind dams throughout the Central Valley for later release into rivers and canals for distribution to meet different water needs. Declining water availability and increasing human demands for water over recent decades have made these decisions increasingly difficult, especially because different uses of water resources often conflict. This report summarizes a facilitated decision-making process, led by the U.S. Geological Survey, involving water, fish, wildlife managers, and those that have an interest in how water is used (interest holders) in the Central Valley. This process provides information for water managers to consider when deciding how to distribute water resources to meet the needs for endangered Hypomesus transpacificus (delta smelt), different runs of Oncorhynchus tshawytscha (Chinook salmon), and Oncorhynchus mykiss (Central Valley steelhead), while maximizing water deliveries for human use and maintaining water quality standards.
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$21B
Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B.
$25.6B
in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS.
$13.5B
in annual benefits is generated by the USGS's 3D Elevation Program.
44%
USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation.
29.4B
barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments.
$424B
in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk.
USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption.
$4.5B
is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property.
$3.1B
The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list.
$21B
in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation.
USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone.
$45B
USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy.
$4.1T
Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued.
45,000 metric tons
Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply.
$70.2B
USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production.
$11.8B
USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry.
1Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.
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12201 Sunrise Valley Drive
Reston, VA 20192