Urban runoff from streets and parking lots carries pollutants that degrade receiving waters. Green infrastructure, such as biofilters, is increasingly used to treat this runoff by mimicking natural hydrologic processes. The U.S. Geological Survey, in cooperation with the Milwaukee Metropolitan Sewerage District, evaluated a biofilter receiving roadway runoff from an industrial area in Milwaukee, Wisconsin, over a 3-year period (2022–24). Paired inlet and outlet samples were analyzed for changes in runoff volume, peak discharge, and concentrations of solids, nutrients, major ions, and metals. The biofilter reduced runoff volume by 86 percent and peak discharge by 92 percent, with substantial reductions in total suspended solids (99 percent), total phosphorus (86 percent), and particulate metals (greater than 80 percent for most analytes). However, dissolved constituents showed variable performance; dissolved phosphorus and several metals exhibited net export, likely influenced by media composition, redox conditions, and winter road salt inputs. Sodium export, despite stable chloride loads, suggests cation exchange and seasonal release dynamics. These findings highlight limitations of conventional biofilter designs for dissolved pollutants and underscore the need for improved media, vegetation management, and consideration of winter deicing practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265143","collaboration":"Prepared in cooperation with the Milwaukee Metropolitan Sewerage District","usgsCitation":"Selbig, W.R., and Romano, J., 2026, Urban stormwater treatment using biofiltration—Variable performance across solids, nutrients, major ions, and metals: U.S. Geological Survey Scientific Investigations Report 2026–5143, 27 p., https://doi.org/10.3133/sir20265143.","productDescription":"Report: vii, 27 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179736","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5143/coverthb.jpg"},{"id":500780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5143/sir20265143.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5143"},{"id":500781,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5143/sir20265143.XML"},{"id":500782,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5143/images/"},{"id":500783,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265143/full"},{"id":500784,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13E8BMK","text":"USGS data release","linkHelpText":"Water quality concentration and load data for a biofilter at Green Tech Station in Milwaukee, Wisconsin, 2022–24"}],"country":"United States","state":"Wisconsin","city":"Milwaukee","otherGeospatial":"Green Tech Station stormwater plaza","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.95385389802549,\n 43.092593420276046\n ],\n [\n -87.95385389802549,\n 43.09035056067961\n ],\n [\n -87.9520609229932,\n 43.09035056067961\n ],\n [\n -87.9520609229932,\n 43.092593420276046\n ],\n [\n -87.95385389802549,\n 43.092593420276046\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Urban stormwater runoff can carry sediment, nutrients, salts, and metals into nearby rivers and lakes, contributing to flooding and water-quality problems. To reduce these impacts, communities are increasingly using shallow, planted systems called biofilters to capture and soak up runoff. This study evaluates how well a biofilter in Milwaukee, Wisconsin, performed over three years and what its results mean for managing stormwater in urban areas.
The biofilter was highly effective at managing stormwater volume and flow. On average, it reduced the amount of runoff leaving the site by 86 percent and reduced peak flow rates by 92 percent. These reductions help lower the risk of flooding downstream, especially during heavy rain.
The biofilter also worked very well at removing pollutants attached to soil and debris. Nearly all suspended sediment was removed, and total phosphorus was reduced by more than 80 percent. Most metals attached to sediment, such as lead and copper, were also greatly reduced. These results show that biofilters are reliable tools for controlling particulate forms of pollutants from roads, even when sediment loads are high.
However, the biofilter was less effective at treating dissolved phase pollutants. For example, dissolved phosphorus and several dissolved metals, including iron and manganese, were often higher in water leaving the biofilter than in water entering it. Sodium, a major component of road salt, was also released from the system at times. Export of dissolved phase pollutants from the biofilter likely reflects interactions between runoff, organic material in the soil, and winter deicing practices. Improving soil mixtures, managing vegetation, and reducing salt inputs may help biofilters better protect urban water quality in the future.
","publicationDate":"2026-03-18","publicationStatus":"PW","contributors":{"authors":[{"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":956897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romano, James 0000-0002-1885-2178","orcid":"https://orcid.org/0000-0002-1885-2178","contributorId":366936,"corporation":false,"usgs":true,"family":"Romano","given":"James","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956898,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274272,"text":"70274272 - 2026 - Regreening, restoring, and reconnecting a southwestern wetland ecosystem – the Zeedyk wetland","interactions":[],"lastModifiedDate":"2026-03-24T15:18:17.947836","indexId":"70274272","displayToPublicDate":"2026-03-18T08:08:57","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5098,"text":"Remote Sensing Applications: Society and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Regreening, restoring, and reconnecting a southwestern wetland ecosystem – the Zeedyk wetland","docAbstract":"Alluvial wetland ecosystems are vital as biodiversity hotspots but are increasingly threatened by anthropogenic stressors and drought. These pressures are especially acute in arid and semi-arid regions, where eco-hydrologic connectivity is fragile and recovery is slow. This study quantifies the efficacy of nature-based solutions, particularly the ‘Zeedyk approach,’ which employs low-tech Natural Infrastructure in Dryland Streams (NIDS)—including rock detention structures—to slow surface water, raise groundwater tables, and restore wetland function at a spring-fed wetland in Cebolla Canyon, New Mexico, U.S.A. Our results depict a Restoration Feedback Loop that captures stages of change from a healthy wetland in 1935, altered by 20th-century agriculture and grazing, to the re-establishment of the historical flow regime by 2024 documented through an 89-year archive of aerial imagery (1935–2024). By the end of our study period, the Spring-Fed Wetland had expanded by roughly 229% of the original 1935 area, to 4.13 ha. Using 40 years of satellite data, we assess changes in vegetation and hydrology with remote sensing indices. Spatial and temporal analyses reveal significant increases in vegetation greenness and wetness, particularly in an Expanded Wetland subregion, which exhibited ∼3.5x higher wetness and ∼1.5x higher greenness trends compared to adjacent areas. Monthly metrics highlight seasonal variability, with increases in greenness linked to monsoonal rainfall and lateral water redistribution, indicating that restoration impacts extend beyond the primary wetland. This study demonstrates the utility of cloud-based platforms like Google Earth Engine and USGS EarthExplorer for long-term monitoring of wetland restoration, while quantifying the efficacy of the ‘Zeedyk approach’ and demonstrating its potential as a scalable method to restore and conserve wetland meadows in other arid and semi-arid landscapes.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rsase.2026.101964","usgsCitation":"Petrakis, R.E., Norman, L., McGraw, M., Carson, S., Sponholtz, C., Weber, C., and Zeedyk, B.D., 2026, Regreening, restoring, and reconnecting a southwestern wetland ecosystem – the Zeedyk wetland: Remote Sensing Applications: Society and Environment, v. 42, 101964, 25 p., https://doi.org/10.1016/j.rsase.2026.101964.","productDescription":"101964, 25 p.","ipdsId":"IP-181171","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":501673,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rsase.2026.101964","text":"Publisher Index Page"},{"id":501451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Cebolla Creek Restoration Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.02529096003872,\n 35.144508927313936\n ],\n [\n -108.02529096003872,\n 34.9960395169455\n ],\n [\n -107.84876055969504,\n 34.9960395169455\n ],\n [\n -107.84876055969504,\n 35.144508927313936\n ],\n [\n -108.02529096003872,\n 35.144508927313936\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGraw, Maryann","contributorId":367703,"corporation":false,"usgs":false,"family":"McGraw","given":"Maryann","affiliations":[{"id":87604,"text":"New Mexico Environment Department","active":true,"usgs":false}],"preferred":false,"id":957503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carson, Steve","contributorId":367704,"corporation":false,"usgs":false,"family":"Carson","given":"Steve","affiliations":[{"id":87605,"text":"Rangeland Hands, Inc.","active":true,"usgs":false}],"preferred":false,"id":957504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sponholtz, Craig","contributorId":367705,"corporation":false,"usgs":false,"family":"Sponholtz","given":"Craig","affiliations":[{"id":87606,"text":"Watershed Artisans, Inc.","active":true,"usgs":false}],"preferred":false,"id":957505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weber, Cameron","contributorId":367706,"corporation":false,"usgs":false,"family":"Weber","given":"Cameron","affiliations":[{"id":87607,"text":"Rio Grande Return","active":true,"usgs":false}],"preferred":false,"id":957506,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zeedyk, Bill D.","contributorId":367707,"corporation":false,"usgs":false,"family":"Zeedyk","given":"Bill","middleInitial":"D.","affiliations":[{"id":87608,"text":"Zeedyk Ecological Consulting, LLC","active":true,"usgs":false}],"preferred":false,"id":957507,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274216,"text":"70274216 - 2026 - Groundwater drought in the United States: Spatial and temporal variability","interactions":[],"lastModifiedDate":"2026-03-13T15:11:23.354627","indexId":"70274216","displayToPublicDate":"2026-03-11T10:03:16","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater drought in the United States: Spatial and temporal variability","docAbstract":"Many communities and ecosystems in the United States that are dependent on groundwater are potentially adversely affected by groundwater drought. We computed yearly groundwater-drought metrics and mean groundwater levels at well locations across the conterminous United States (CONUS), using data from wells and remotely sensed and modeled Gravity Recovery and Climate Experiment Drought Monitor Data Assimilation (GRACE-DADM). We also modeled the probability of low or high human impact at each well location. The spatial distribution of groundwater-drought duration and severity from 2001 to 2020 for 1,510 wells shows longer maximum duration and higher maximum severity events in drier regions like the Southwest than in wetter regions like the Northeast. Based on 613 wells in CONUS from 1981 to 2020, there are many significant decreases in drought duration and severity in the Northeast and many significant increases in annual-mean groundwater levels. In contrast, there are many significant increases in drought metrics and decreases in mean water levels in parts of the Southeast. There are major differences in trends from 2001 to 2020 between well-based and GRACE-DADM-based groundwater metrics in some CONUS regions and a very low correlation between trends at individual locations across CONUS. A potential reason for this disparity is the low GRACE-DADM resolution (∼12 km) and the potential for a large amount of groundwater variation at the local scale. Also, GRACE-DADM represents shallow, unconfined aquifers which may not match the screened interval of the monitoring wells we evaluated. Large spatial gaps in long-term, high frequency, and quality-assured groundwater-well monitoring data present a challenge for understanding groundwater-drought variability across CONUS. Remote sensing tools such as GRACE can help but cannot fully replace well monitoring, as highlighted by our study results. Substantially more long-term monitoring wells would more accurately represent groundwater-drought trends and spatial variability across CONUS, particularly in western regions.
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0000-0003-3263-6452","orcid":"https://orcid.org/0000-0003-3263-6452","contributorId":221008,"corporation":false,"usgs":true,"family":"Simeone","given":"Caelan","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957074,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldwell, Todd 0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957078,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274211,"text":"70274211 - 2026 - Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin","interactions":[],"lastModifiedDate":"2026-03-13T14:29:50.599041","indexId":"70274211","displayToPublicDate":"2026-03-11T09:20:41","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin","docAbstract":"Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence Micropterus dolomieu (Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2026.181562","usgsCitation":"Sorensen, S.F., Fox, J.T., and Magoulick, D.D., 2026, Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution: Science of the Total Environment, v. 1025, 181562, 9 p., https://doi.org/10.1016/j.scitotenv.2026.181562.","productDescription":"181562, 9 p.","ipdsId":"IP-176491","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":502098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2026.181562","text":"Publisher Index Page"},{"id":502032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark-Ouachita Interior Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.06835076729865,\n 37.54392591075137\n ],\n [\n -95.58753725694291,\n 35.616131979244244\n ],\n [\n -96.86430792379102,\n 34.30485408838467\n ],\n [\n -95.13839254168458,\n 34.13182914589751\n ],\n [\n -93.02844126052034,\n 33.84485206480821\n ],\n [\n -91.20526644252189,\n 35.93662462412837\n ],\n [\n -90.46426221649432,\n 38.03635872039271\n ],\n [\n -95.06835076729865,\n 37.54392591075137\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1025","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sorensen, Sarah F.","contributorId":369126,"corporation":false,"usgs":false,"family":"Sorensen","given":"Sarah","middleInitial":"F.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, J. Tyler","contributorId":369127,"corporation":false,"usgs":false,"family":"Fox","given":"J.","middleInitial":"Tyler","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958497,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274636,"text":"70274636 - 2026 - Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages","interactions":[],"lastModifiedDate":"2026-04-02T17:32:18.629216","indexId":"70274636","displayToPublicDate":"2026-03-08T10:25:49","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16456,"text":"Frontiers in Enviornmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages","docAbstract":"Introduction:
Hydrologic variability is a key driver of ecological structure in lotic systems, shaping habitat conditions, taxonomic diversity, and the functional traits that mediate species’ persistence and performance (e.g., reproductive success). While many studies examine taxonomic responses to variation in flows, few evaluate how spatiotemporal hydrologic variation influences the functional organization within stream fish communities.
Methods:
We quantified seasonal habitat structure and functional trait diversity of fish assemblages across six Ozark Plateau headwater streams representing two contrasting flow regimes: Groundwater Flashy and Runoff/Intermittent Flashy. Fish and habitat data were collected seasonally during a dry year (2002) and a wet year (2003). Functional space was constructed using PCoA of morphological, ecological, and life-history traits, and functional diversity was measured using community weighted means (CWMs), functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv).
Results:
We found that habitat structure differed strongly by flow regime and season, with Runoff/Intermittent streams exhibiting pronounced reductions in depth, area, and velocity, while groundwater streams remained structurally stable. Functional identity of assemblages was similar across flow regimes, dominated by benthic, hydrodynamic taxa with opportunistic and periodic life-history strategies. However, functional structure differed significantly: FEve and FDiv were consistently lower in Runoff/Intermittent Flashy streams in both years, indicating assemblage dominance of species with similar trait combinations and reduced trait partitioning under variable flow. FRic and taxonomic richness remained stable across seasons and flow regimes, suggesting high functional redundancy despite species turnover.
Discussion:
Together, results show that flow regime mediates both habitat structural stability and functional organization. As climatic warming and extreme drought increase hydrologic instability in headwaters, functional trait approaches provide a sensitive tool for detecting losses of functional roles that may not be evident by using taxonomic metrics alone.
Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2026.114741","usgsCitation":"Norman, L., Petrakis, R.E., Wilson, N.R., Middleton, B.R., Villarreal, M.L., Pollock, M., Minckley, T.A., and Hendrickson, D., 2026, Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach: Ecological Indicators, v. 184, 114741, 16 p., https://doi.org/10.1016/j.ecolind.2026.114741.","productDescription":"114741, 16 p.","ipdsId":"IP-179305","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":501684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2026.114741","text":"Publisher Index Page"},{"id":501477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, New Mexico","otherGeospatial":"Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.05152972005978,\n 33.0768867725987\n ],\n [\n -112.05152972005978,\n 29.88732922369421\n ],\n [\n -108.36301240182003,\n 29.88732922369421\n ],\n [\n -108.36301240182003,\n 33.0768867725987\n ],\n [\n -112.05152972005978,\n 33.0768867725987\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Natalie R. 0000-0001-5145-1221 nrwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":214982,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie","email":"nrwilson@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, Barry R.","contributorId":367728,"corporation":false,"usgs":false,"family":"Middleton","given":"Barry","middleInitial":"R.","affiliations":[{"id":36921,"text":"Ret. USGS","active":true,"usgs":false}],"preferred":false,"id":957550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":214980,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pollock, Michael","contributorId":367729,"corporation":false,"usgs":false,"family":"Pollock","given":"Michael","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":957552,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Minckley, Thomas A.","contributorId":367730,"corporation":false,"usgs":false,"family":"Minckley","given":"Thomas","middleInitial":"A.","affiliations":[{"id":87617,"text":"University of Wyoming, Department of Geology and Geophysics, Laramie, WY 82071-2000","active":true,"usgs":false}],"preferred":false,"id":957553,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hendrickson, Dean","contributorId":367731,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Dean","affiliations":[{"id":87618,"text":"University of Texas at Austin, College of Natural Sciences, Austin, TX 78712","active":true,"usgs":false}],"preferred":false,"id":957554,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70274192,"text":"ofr20261066 - 2026 - Floods of June 2024 in northwestern Iowa","interactions":[],"lastModifiedDate":"2026-03-13T17:07:59.33217","indexId":"ofr20261066","displayToPublicDate":"2026-03-05T11:00:46","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1066","displayTitle":"Floods of June 2024 in Northwestern Iowa","title":"Floods of June 2024 in northwestern Iowa","docAbstract":"Following a heavy, multiday rainfall event that took place between June 20 and June 22, 2024, widespread flooding occurred in parts of northwestern Iowa. Ten U.S. Geological Survey (USGS) streamgages with periods of record ranging from 56 to 99 years in length experienced new peaks of record, three of which were more than double the previous peak-of-record: 06483500 (Rock River near Rock Valley, Iowa), 06605850 (Little Sioux River at Linn Grove, Iowa), and 06606600 (Little Sioux River at Correctionville, Iowa). A Presidential declaration of a major disaster for the State of Iowa was approved on June 24, 2024, and the cost of the flooding is estimated at over $310 million. The severity of this flooding prompted the USGS, in cooperation with the Iowa Department of Transportation, to summarize the meteorological and hydrological conditions preceding the flooding, compile estimates of the magnitude of peak flows resulting from the flooding, and update estimates of peak-flow frequency for selected USGS streamgages. Of the 33 streamgages analyzed, a peak streamflow occurred that corresponded to an annual exceedance probability of less than 4 percent at 13 streamgages, an annual exceedance probability of less than 1 percent at 6 streamgages, and an annual exceedance probability of less than 0.2 percent at 1 streamgage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261066","collaboration":"Prepared in cooperation with the Iowa Department of Transportation","usgsCitation":"Marti, M.K., and O’Shea, P.S., 2026, Floods of June 2024 in northwestern Iowa: U.S. Geological Survey Open-File Report 2026–1066, 16 p., https://doi.org/10.3133/ofr20261066.","productDescription":"Report: vi, 16 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-175807","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500762,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261066/full"},{"id":500761,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1066/images/"},{"id":500760,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1066/ofr20261066.XML"},{"id":500759,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1066/ofr20261066.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1066"},{"id":500758,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1066/coverthb.jpg"},{"id":501165,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119301.htm","linkFileType":{"id":5,"text":"html"}},{"id":500763,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1JFCNSZ","text":"USGS data release","linkHelpText":"Peak-flow frequency analysis for U.S. Geological Survey streamgages in northwestern Iowa, based on data through water year 2024"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.667,\n 43.6\n ],\n [\n -96.667,\n 41.667\n ],\n [\n -93,\n 41.667\n ],\n [\n -93,\n 43.6\n ],\n [\n -96.667,\n 43.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
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In arid and semi-arid regions, groundwater sustains vegetation through subsurface water access, yet the responses of groundwater-dependent ecosystems (GDEs) to changing hydroclimate and groundwater availability are relatively understudied. This study investigates seasonal and spatial patterns in vegetation greenness using Landsat Enhanced Vegetation Index (EVI) values across riparian and upland zones in the semi-arid Upper San Pedro (USP) watershed, southern Arizona, which experiences a bimodal precipitation regime. We paired 25 years (2000–2024) of EVI and depth to groundwater (DTG) data from 89 wells and climate metrics (precipitation and vapour pressure deficit) to quantify the sensitivity of vegetation to subsurface moisture as well as atmospheric moisture supply and demand. Vegetation at wells near the USP riparian area showed strong associations between EVI and DTG anomalies during the monsoon season, indicating sustained groundwater use even during this wet period when summer precipitation is abundant. In contrast, upland vegetation that lacked access to groundwater showed minimal sensitivity in EVI to DTG and was generally less responsive to vapour pressure deficit. Interestingly, the riparian GDEs were not decoupled from precipitation and climate variability. These results underscore the importance of groundwater for maintaining riparian productivity and highlight the utility of remote sensing in identifying vegetation-climate-groundwater linkages across heterogeneous dryland landscapes.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70405","usgsCitation":"Bromley, F., Borxton, P., Zhang, J., van Leeuwen, W.J., Nagler, P., and Hu, J., 2026, Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States: Hydrological Processes, v. 40, no. 3, e70405, 18 p., https://doi.org/10.1002/hyp.70405.","productDescription":"e70405, 18 p.","ipdsId":"IP-180542","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70405","text":"Publisher Index Page"},{"id":501145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Upper San Pedro watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.31987279028372,\n 31.82228360728554\n ],\n [\n -110.31987279028372,\n 31.379497469636988\n ],\n [\n -109.98150823782808,\n 31.379497469636988\n ],\n [\n -109.98150823782808,\n 31.82228360728554\n ],\n [\n -110.31987279028372,\n 31.82228360728554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Bromley, Fern 0000-0003-0596-1487","orcid":"https://orcid.org/0000-0003-0596-1487","contributorId":367222,"corporation":false,"usgs":false,"family":"Bromley","given":"Fern","affiliations":[{"id":36671,"text":"School of Natural Resources and the Environment, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":957082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borxton, Patrick 0000-0002-2665-6820","orcid":"https://orcid.org/0000-0002-2665-6820","contributorId":248510,"corporation":false,"usgs":false,"family":"Borxton","given":"Patrick","email":"","affiliations":[{"id":49935,"text":"2University of Arizona, School of Natural Resources and the Environment","active":true,"usgs":false}],"preferred":false,"id":957083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Jiaqi","contributorId":202467,"corporation":false,"usgs":false,"family":"Zhang","given":"Jiaqi","email":"","affiliations":[{"id":36453,"text":"University of Texas, Arlington, TX, USA","active":true,"usgs":false}],"preferred":false,"id":957084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Leeuwen, Willem J.D. 0000-0002-3188-7172","orcid":"https://orcid.org/0000-0002-3188-7172","contributorId":191856,"corporation":false,"usgs":false,"family":"van Leeuwen","given":"Willem","middleInitial":"J.D.","affiliations":[],"preferred":false,"id":957085,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagler, Pamela L. 0000-0003-0674-103X","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":363777,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","middleInitial":"L.","affiliations":[],"preferred":true,"id":957086,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hu, Jia","contributorId":367226,"corporation":false,"usgs":false,"family":"Hu","given":"Jia","affiliations":[],"preferred":false,"id":957087,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274150,"text":"70274150 - 2026 - Urbanization alters riverine fluorescent dissolved organic matter characteristics in a forested city – metropolitan Atlanta, Georgia (USA)","interactions":[],"lastModifiedDate":"2026-03-02T14:49:19.406602","indexId":"70274150","displayToPublicDate":"2026-02-27T08:39:47","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1561,"text":"Environmental Research","active":true,"publicationSubtype":{"id":10}},"title":"Urbanization alters riverine fluorescent dissolved organic matter characteristics in a forested city – metropolitan Atlanta, Georgia (USA)","docAbstract":"Streams and rivers in urban watersheds are predicted to export more bioreactive, autochthonous dissolved organic matter (DOM) relative to forested watersheds. However, the spatial and temporal variations of DOM quality in forested urban watersheds remain uncertain, and their relationships with socioeconomic conditions, biological characteristics, and the built environment are understudied. We measured optical properties of fluorescent DOM (FDOM) in 93 streams spanning a gradient of land-use and land cover during four seasons in metropolitan Atlanta, Georgia, USA. Streamwater FDOM was dominated by humic substances from anthropogenic (41%) and terrestrial origin (41.5%). Impervious surface cover was the strongest predictor, which was positively correlated with anthropogenically- and autochthonously-derived FDOM. Overwater canopy cover was positively associated with autochthonous FDOM, and housing age increased diagenetic FDOM. FDOM was more proteinaceous during low-flow conditions (fall, winter), and more allochthonous humic-like FDOM was detected during periods of higher flows (spring, summer). Interestingly, wastewater-related FDOM proxies were highest during low flows, suggesting that sewer exfiltration is a pervasive source and is diluted by other inputs during high flows. Overall, seasonal patterns in FDOM quality were associated with changes in hydrology, and FDOM was primarily humic throughout the year, a pattern likely driven by ubiquitous forest canopy cover. Our results highlight the importance of urban forests in mediating aquatic carbon cycling and provide a template for future studies that integrate sociodemographic and infrastructure information into studies of watershed biogeochemistry, especially in regions undergoing rapid, intense, and localized urban development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2026.124085","usgsCitation":"Chen, S., Hale, R., Hopkins, K.G., Ortiz Muñoz, L., Kominoski, J., Ledford, S., and Capps, K., 2026, Urbanization alters riverine fluorescent dissolved organic matter characteristics in a forested city – metropolitan Atlanta, Georgia (USA): Environmental Research, v. 297, 124085, 15 p., https://doi.org/10.1016/j.envres.2026.124085.","productDescription":"124085, 15 p.","ipdsId":"IP-183715","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":500667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","city":"Atlanta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.1667,\n 34\n ],\n [\n -84.7,\n 34\n ],\n [\n -84.7,\n 33.5\n ],\n [\n -84.1667,\n 33.5\n ],\n [\n -84.1667,\n 34\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"297","noUsgsAuthors":false,"publicationDate":"2026-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Shuo","contributorId":343806,"corporation":false,"usgs":false,"family":"Chen","given":"Shuo","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":956692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hale, Rebecca","contributorId":348368,"corporation":false,"usgs":false,"family":"Hale","given":"Rebecca","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":956693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ortiz Muñoz, Liz","contributorId":343807,"corporation":false,"usgs":false,"family":"Ortiz Muñoz","given":"Liz","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":956695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kominoski, John","contributorId":298258,"corporation":false,"usgs":false,"family":"Kominoski","given":"John","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":956696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ledford, Sarah","contributorId":300624,"corporation":false,"usgs":false,"family":"Ledford","given":"Sarah","email":"","affiliations":[{"id":52554,"text":"Georgia State University","active":true,"usgs":false}],"preferred":false,"id":956697,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Capps, Krista A.","contributorId":270490,"corporation":false,"usgs":false,"family":"Capps","given":"Krista A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":956698,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274110,"text":"tm18B1 - 2026 - RoadxStr user’s guide—For collection of road-stream crossing assessment field observations","interactions":[],"lastModifiedDate":"2026-02-27T14:27:56.90049","indexId":"tm18B1","displayToPublicDate":"2026-02-26T14:28:28","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"18-B1","displayTitle":"RoadxStr User’s Guide—For Collection of Road-Stream Crossing Assessment Field Observations","title":"RoadxStr user’s guide—For collection of road-stream crossing assessment field observations","docAbstract":"Intersections of drainage networks and road networks represent a critical nexus between natural waterways and human infrastructure. Managing these systems involves decisions related to management of infrastructure, hydrologic and geomorphic processes, and ecological connectivity. Interactions among these systems influence multiple values, including the intactness of transportation networks, public safety, water quality, and ecosystem function that collectively amount to billions of dollars. Despite the importance of road- stream crossings, there are countless gaps in knowing where and what they are. These gaps limit the degree to which managers can inventory and assess stream and road networks to inform decisions. To address this first- level need, we developed RoadxStr (road- stream crossings): a survey tool that effectively characterizes road- stream crossings across the full stream and drainage network. This document describes the RoadxStr Field Form, available within a mobile application, which is designed for rapid and standardized data collection involving assessment of a road- stream crossing, including the road, crossing structure(s), and the nearby hydrologic channel. This document provides instructions on how to (1) access and download the RoadxStr Field Form within the mobile application service and (2) use and complete a RoadxStr Field Form survey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm18B1","collaboration":"Prepared in cooperation with the Bureau of Land Management and U.S. Forest Service","usgsCitation":"Heaston, E., Winter, S., Bauer, S., Ronningen, T., and Dunham, J., 2026, RoadxStr user’s guide—For collection of road-stream crossing assessment field observations: U.S. Geological Survey Techniques and Methods, book 18, chap. B1, 32 p., https://doi.org/10.3133/tm18B1.","productDescription":"vii, 32 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-176750","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":500549,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm18B1/full"},{"id":500548,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/18/b1/images/"},{"id":500547,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/18/b1/tm18B1.XML"},{"id":500546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/18/b1/tm18B1.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 18-B1"},{"id":500545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/18/b1/coverthb.jpg"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center Corvallis Research Group
3200 SW Jefferson Way
Corvallis, OR 97331
fresc_outreach@usgs.gov
Acadia National Park has had increases in the frequency and magnitude of precipitation in recent years, leading to increased flood flows, stream erosion, and costly infrastructure damage. To improve infrastructure management in a changing climate, the U.S. Geological Survey, in cooperation with the National Park Service, has developed multiple datasets that can help natural resource managers identify stream reaches and stream crossings that have the highest potential for erosion and flood damage within Acadia National Park. To develop these datasets, we first created a lidar- derived hydrography based on a 1- meter digital elevation model and then estimated peak flows at stream crossings and along the stream network using regional regression equations for Maine. We assessed the erosion potential of stream reaches by computing channel morphologic and hydrologic metrics associated with erosive power, such as stream steepness, topographic openness, and percent storage in the contributing watershed. Stream crossing flood vulnerability was assessed by comparing estimated peak flows to stream crossing conveyance capacities. Our results indicate that stream reaches in the headwaters of the Acadia National Park highlands such as Sargent, Penobscot, and Cadillac Mountain, have the highest erosion potential and generally coincide with reaches that have had erosion and infrastructure damage in the past. Stream crossings with the highest flood vulnerability are distributed throughout Mount Desert Island and Acadia National Park, especially south of Jordan Pond, north of Sargent Mountain, and surrounding Eagle Lake. Over a quarter of the total stream crossings have insufficient information to compute flood vulnerability and are often on the parts of the stream with the highest potential for erosion. The datasets allow users to identify stream reaches with the highest erosion potential, stream crossings that are most vulnerable to flood damage, and to highlight areas where supplemental field assessments could most effectively be completed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265116","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Armstrong, I.P., McCallister, M.A., Hyslop, K.M., and Benthem, A.J., 2026, Erosion potential and flood vulnerability of streams and stream crossings at Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2026–5116, 21 p., https://doi.org/10.3133/sir20265116.","productDescription":"Report: vii, 21 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-178032","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":500752,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13Y2RY2","text":"USGS data release","linkHelpText":"Data for an Erosion and Flood Vulnerability Assessment of Streams and Stream Crossings at Acadia National Park, Maine"},{"id":500656,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119275.htm","linkFileType":{"id":5,"text":"html"}},{"id":500517,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://geonarrative.usgs.gov/acadiaerosionfloodvulnerability/","text":"Interactive dashboard","linkHelpText":"- Erosion Potential and Flood Vulnerability of Streams and Stream Crossings at Acadia National Park"},{"id":499819,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265116/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5116 HTML"},{"id":499818,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5116/sir20265116.pdf","size":"7.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5116 PDF"},{"id":499817,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5116/coverthb.jpg"},{"id":499820,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5116/sir20265116.xml","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5116 XML"},{"id":499821,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5116/images/"},{"id":499822,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1EHZNHN","text":"USGS data release","linkHelpText":"Data for an erosion potential and flood vulnerability assessment of streams and stream crossings at Acadia National Park, Maine"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.45003175798666,\n 44.44178922865794\n ],\n [\n -68.45003175798666,\n 44.21621316604151\n ],\n [\n -68.13514216440173,\n 44.21621316604151\n ],\n [\n -68.13514216440173,\n 44.44178922865794\n ],\n [\n -68.45003175798666,\n 44.44178922865794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
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The U.S. Geological Survey, in cooperation with the National Park Service, has developed multiple datasets that can help natural resource managers identify stream reaches with the highest potential for erosion and stream crossings most vulnerable to flood damage within Acadia National Park. These datasets allow users to identify areas where supplemental field assessments could be most effectively completed.
","publicationDate":"2026-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Armstrong, Ian P. 0000-0002-8239-8029","orcid":"https://orcid.org/0000-0002-8239-8029","contributorId":344363,"corporation":false,"usgs":true,"family":"Armstrong","given":"Ian","email":"","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCallister, Meghan A. 0000-0001-8814-7725","orcid":"https://orcid.org/0000-0001-8814-7725","contributorId":358213,"corporation":false,"usgs":true,"family":"McCallister","given":"Meghan","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hyslop, Kristina M. 0009-0001-2525-5574","orcid":"https://orcid.org/0009-0001-2525-5574","contributorId":334465,"corporation":false,"usgs":true,"family":"Hyslop","given":"Kristina","middleInitial":"M.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benthem, Adam J. 0000-0003-2372-0281","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":220000,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955713,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274091,"text":"70274091 - 2026 - A tool to monitor hydrologic conditions on tree islands in the Everglades","interactions":[],"lastModifiedDate":"2026-02-26T16:50:16.661474","indexId":"70274091","displayToPublicDate":"2026-02-24T08:13:22","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"A tool to monitor hydrologic conditions on tree islands in the Everglades","docAbstract":"Tree islands are patchy upland forested habitats in Florida's Everglades that face degradation and disappearance due to altered hydrologic patterns. The U.S. Geological Survey coordinated with the Miccosukee Tribe of Indians of Florida and the Seminole Tribe of Florida to co-develop a decision-support tool based on tree-island hydrologic conditions. Everglades managers can use this tool to help with restoration planning and water operations decisions that affect tree-island conditions. After a series of organized workshops and meetings, a list of hydrologic metrics was selected as indicators of tree-island health, including hydroperiod, number of days since last dry, and maximum water depth at the head of the island. As a result, a web application tool, called ETree, has been developed and is publicly available online. This web application provides data on daily metrics for the current Everglades water year and annual summaries for past years, beginning in 2000.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2026.114640","usgsCitation":"Haider, S.M., van der Heiden, C., Bozas, M., and Romañach, S.S., 2026, A tool to monitor hydrologic conditions on tree islands in the Everglades: Ecological Indicators, v. 183, 114640, 7 p., https://doi.org/10.1016/j.ecolind.2026.114640.","productDescription":"114640, 7 p.","ipdsId":"IP-175495","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":500612,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2026.114640","text":"Publisher Index Page"},{"id":500509,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.08373270516965,\n 26.65815841176284\n ],\n [\n -82.08373270516965,\n 25.02905745196128\n ],\n [\n -80.69833784238166,\n 25.02905745196128\n ],\n [\n -80.69833784238166,\n 26.65815841176284\n ],\n [\n -82.08373270516965,\n 26.65815841176284\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"183","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haider, Saira M. 0000-0001-9306-3454","orcid":"https://orcid.org/0000-0001-9306-3454","contributorId":206253,"corporation":false,"usgs":true,"family":"Haider","given":"Saira","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":956505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van der Heiden, Craig","contributorId":366978,"corporation":false,"usgs":false,"family":"van der Heiden","given":"Craig","affiliations":[{"id":87517,"text":"Seminole Tribe of Florida","active":true,"usgs":false}],"preferred":false,"id":956506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bozas, Marcel","contributorId":366979,"corporation":false,"usgs":false,"family":"Bozas","given":"Marcel","affiliations":[{"id":87518,"text":"Miccosukee Tribe of Indians of Florida","active":true,"usgs":false}],"preferred":false,"id":956507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romañach, Stephanie S. 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":213745,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":956508,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273927,"text":"sir20265114 - 2026 - Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study","interactions":[],"lastModifiedDate":"2026-03-18T21:13:34.944932","indexId":"sir20265114","displayToPublicDate":"2026-02-18T12:45:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5114","displayTitle":"Assessing Natural Recharge in Indian Wells Valley, California: A Basin Characterization Model Case Study","title":"Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study","docAbstract":"The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm3) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot- wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265114","collaboration":"Prepared in cooperation with Kern County, California","programNote":"Water Availability and Use Science Program","usgsCitation":"Saleh, D., Flint, L., and Stern, M., 2026, Assessing natural recharge in Indian Wells Valley, California—A Basin Characterization Model case study (ver. 1.1, March 2026): U.S. Geological Survey Scientific Investigations Report 2026–5114, 34 p., https://doi.org/10.3133/sir20265114.","productDescription":"vi, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-104255","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501283,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119214.htm","linkFileType":{"id":5,"text":"html"}},{"id":501282,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2026/5114/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2026-5114 Version History"},{"id":501281,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5114/images"},{"id":501278,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5114/sir20265114.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5114 PDF"},{"id":501279,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265114/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5114 HTML"},{"id":501280,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5114/sir20265114.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5114 XML"},{"id":500366,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5114/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Indian Wells Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.5,\n 36.5\n ],\n [\n -118.5,\n 35\n ],\n [\n -117,\n 35\n ],\n [\n -117,\n 36.5\n ],\n [\n -118.5,\n 36.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: February 18, 2026; Version 1.1: March 18, 2026","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Chlorinated solvents, including trichloroethene (TCE) and other chlorinated volatile organic compounds (cVOCs), are widespread contaminants that can be treated by bioremediation approaches that enhance anaerobic reductive dechlorination. Reductive dechlorination can be enhanced either through the addition of an electron donor (biostimulation) or the addition of a known dechlorinating culture (bioaugmentation) along with an electron donor. Although bioremediation has been applied at many TCE- contaminated groundwater sites, application in source zones at sites where residual dense nonaqueous phase liquid (DNAPL) is present is more limited. In this study, laboratory and field treatability tests were completed to evaluate the potential application of anaerobic bioremediation for a shallow groundwater plume containing TCE in a perched alluvial aquifer at Site K, former Twin Cities Army Ammunition Plant, Arden Hills, Minnesota, which was on the National Priorities List as the New Brighton/Arden Hills Superfund site until 2019. In addition to the presence of residual DNAPL at the site, temporal variability in groundwater flow directions and input of oxygenated recharge were possible complicating factors for the application of enhanced anaerobic biodegradation in the shallow plume. The Site K plume extends beneath the footprint of Building 103, which was demolished in 2006, and soil excavations to a maximum depth of 6 feet (ft) below ground surface in 2014 were known to leave some deeper contaminated soil in place in the TCE source area. Groundwater treatment at the site, formalized as part of the 1997 Record of Decision, has been in operation since 1986 and consists of an extraction trench at the downgradient edge of the plume to collect groundwater, which is then pumped to an on- site air stripper. Groundwater concentrations in the plume have been relatively stable since treatment began, indicating a continued source of TCE in the aquifer. The desire for a destructive remedy that would enhance the removal of cVOCs in the aquifer at Site K and shorten the remediation timeframe led the U.S. Army to request that the U.S. Geological Survey conduct a groundwater treatability study to assess bioremediation. This report describes the U.S. Geological Survey bioremediation treatability study conducted during 2020–22, including pre- design site characterization to assist in formulating the bioremediation approach, laboratory experiments to support the design of the field pilot test, and implementation and 1-year performance monitoring results for the pilot test.
Pre- design site characterization included the collection of soil cores for cVOC analysis and lithologic descriptions and the re- installment of three wells to obtain hydrologic measurements and initial groundwater chemistry. Relatively flat head gradients were measured at the site, and substantial decreases in water- level elevations occurred from spring to summer (May–July 2021). Continuous water- level monitoring indicated a rapid response to precipitation. Groundwater flow velocities were consistently less than 0.5 foot per day, and the pilot bioremediation test was therefore designed with short lateral distances (about 5 ft) between injection and individual monitoring points. Soil analyses confirmed that high volatile organic compound contamination was left in place in the source area. The highest concentrations were near or in clay at the base of the perched aquifer. Concentrations of cVOCs measured in the replaced wells were consistent with historical data and had a maximum TCE concentration of 57,700 micrograms per liter (μg/L), indicative of nearby residual DNAPL based on the general rule of observed concentrations exceeding 1 percent of solubility. The primary TCE daughter product detected was 1,2- cis- dichloroethene (cisDCE), which indicated limited reductive dechlorination in the plume. Groundwater in both the source and downgradient areas was relatively reducing during the pre- design characterization, particularly in the source area where methane concentrations greater than 400 μg/L were measured.
Initial laboratory tests conducted using native aquifer microorganisms from the three replacement wells showed that anaerobic TCE biodegradation rates were low when biostimulated with the addition of sodium lactate as an electron donor, also known as a carbon donor, and resulted in the production of only cisDCE. Addition of a known dechlorinating culture, WBC- 2, however, resulted in rapid biodegradation and production of ethene, verifying complete reductive dechlorination of TCE. Microcosms constructed with aquifer soil collected from the site were used to evaluate other electron donors besides lactate to support reductive dechlorination by WBC- 2, including corn syrup as an alternative fast- release compound and whey, soy- based vegetable oil, and 3- D Microemulsion (Regenesis, San Clemente, California) as slow-release compounds. First- order rate constants for total organic chlorine removal in these WBC- 2 amended microcosms were greatest with either lactate or vegetable oil as the donor, ranging between 0.061 and 0.047 per day or corresponding half- lives of 11–15 days. Testing of commercial products in other WBC- 2- bioaugmented microcosms led to selection for the field pilot test of an emulsified vegetable oil product that also contained some sodium lactate as a fast- release donor. Delaying the addition of WBC- 2 relative to the donor in the microcosms resulted in the most rapid overall biodegradation rates.
The selected design for the pilot test utilized three separate test plots, each about 30-ft wide and 60-ft long: plots GS1 and GS2 in the source area of the plume and plot GS3 in the downgradient area of the plume near the excavation trench. Each test plot had one injection well, one monitoring well upgradient from the injection point, and 12 surrounding monitoring wells in a grid to capture variable groundwater flow directions. Donor injections, which included a bromide tracer, were completed in October 2021, immediately following baseline sampling, and the WBC- 2 culture was injected about 40 days later, between November 30 and December 2, 2021. Performance monitoring conducted until December 2022 included hydrologic measurements and analyses of cVOCs, redox- sensitive constituents, dissolved organic carbon, bromide, volatile fatty acids, compound- specific carbon isotopes, and microbial communities.
The biogeochemical data collected during the pilot tests in the three treatment plots showed that enhanced, complete reductive dechlorination of cVOCs in the groundwater was achieved in the GS1 and GS3 plots. In contrast, evidence of distribution of the injected amendments and subsequent biodegradation was limited in GS2, which was in an area of more heterogeneous soil lithology and low water table elevations. The molar composition of volatile organic compounds in the GS1 and GS3 plots was dominated by ethene in wells that were reached by the injected amendments by the end of the monitoring period. In the GS1 and GS3 plots, similar patterns were observed of cVOC concentrations decreasing to near detection levels, or below, at some wells sampled in July and October 2022, whereas ethene became dominant and indicated sustained complete reductive dechlorination. Baseline cVOC concentrations were more than a factor of 10 higher in the groundwater in the GS1 plot than in GS3, but no apparent inhibition of complete dechlorination occurred. As expected from the initial pre- design site data and the laboratory experiments, enhanced dissolution of residual DNAPL coupled to biodegradation was evident in the GS1 plot, where a marked increase in dichloroethene (DCE) above the initial baseline and upgradient TCE and DCE concentrations occurred. DCE concentrations subsequently declined where DNAPL dissolution was evident, concurrent with production of vinyl chloride and then predominantly ethene. Thus, overall biodegradation rates outpaced the DNAPL dissolution and desorption and DCE production in the source area. This success in complete degradation to predominantly ethene was achieved even in areas where the DCE concentrations reached a maximum of about 30,000 μg/L. Compound specific isotope analysis of carbon in TCE, cisDCE, trans- 1,2- dichloroethene, and vinyl chloride was conducted to provide another line of evidence of the occurrence and extent of anaerobic biodegradation. Along a flow path in each plot that was affected by the injected amendments, carbon isotopes in the TCE and daughter cVOCs in the groundwater became isotopically heavier, indicating biodegradation.
Enhanced biodegradation rates calculated from the field tests in GS1 and GS3 showed half- lives of 36.9–75.3 days for DCE degradation and 9.48–38.5 days for ethene production. Notably, these ethene production rates calculated from the field tests are consistent with the results of WBC- 2- bioaugmented microcosms amended with either lactate or vegetable oil, which had half- lives for total organic chlorine removal that ranged from 11 to 15 days. These rates indicated rapid enhanced biodegradation, which is promising for application of a full- scale bioremediation remedy. Ultimately, however, the mass of residual or sorbed TCE in the aquifer that remains accessible for dissolution and biodegradation would likely control the time required for a full- scale bioremediation effort to achieve performance goals for TCE and cisDCE specified in the Record of Decision for Site K.
The field pilot tests showed that the relatively low hydraulic head gradients and temporal changes in groundwater flow directions in the shallow aquifer would add complexity to a full- scale bioremediation effort. The radius of influence (ROI) at GS1 and GS3 (16.3 ft and 12.7 ft, respectively) were close to the design ROI of 15 ft. The estimated ROI at GS2 was about four times the design ROI, but may be less reliable at this location owing to groundwater flow direction. In addition, the low temperatures following WBC- 2 injection in late November to early December 2021, in combination with the low hydraulic head gradients, were probably major factors in the delay observed before the onset of enhanced biodegradation following injection of the culture. Additional test injections could be beneficial to optimize the timing of donor and culture injections with the variable temperatures and hydraulic head in the shallow aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255113","collaboration":"Prepared in cooperation with U.S. Army Environmental Command","usgsCitation":"Lorah, M.M., Majcher, E.H., Mumford, A.C., Foss, E.P., Needham, T.P., Psoras, A.W., Livdahl, C.T., Trost, J.J., Berg, A.M., Polite, B.F., Akob, D.M., and Cozzarelli, I.M., 2026, Treatability study to evaluate bioremediation of trichloroethene at Site K, former Twin Cities Army Ammunition Plant, Arden Hills, Minnesota, 2020–22: U.S. Geological Survey Scientific Investigations Report 2025–5113, 88 p., https://doi.org/10.3133/sir20255113.","productDescription":"Report: xii, 88 p.; Data Release","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-175852","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":500361,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119213.htm","linkFileType":{"id":5,"text":"html"}},{"id":500106,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13QTBR7","text":"USGS data release","linkHelpText":"Former Twin Cities Army Ammunition Site K treatability test data including various field measurements, laboratory tests and degradation constituents in the bioremediation of trichloroethylene and dichloroethylene, Arden Hills, Minnesota 2020–2022"},{"id":500104,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5113/sir20255113.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5113 XML"},{"id":500103,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255113/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5113 HTML"},{"id":500102,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5113/sir20255113.pdf","size":"6.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5113 PDF"},{"id":500101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5113/coverthb.jpg"},{"id":500105,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5113/images/"}],"country":"United States","state":"Minnesota","county":"Ramsey County","city":"Arden Hills","otherGeospatial":"Site K, former Twin Cities Army Ammunition Plant","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.17794646411902,\n 45.1090420800339\n ],\n [\n -93.17794646411902,\n 45.08000250215488\n ],\n [\n -93.14480906199879,\n 45.08000250215488\n ],\n [\n -93.14480906199879,\n 45.1090420800339\n ],\n [\n -93.17794646411902,\n 45.1090420800339\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
The Puyallup River drains a 990 square mile watershed in western Washington, with headwaters on the glacier-covered flanks of Mount Rainier. Major tributaries include the White, Carbon, and Mowich Rivers. In the levee-confined reaches of the lower watershed, loss of flood conveyance due to sand and gravel deposition has been a chronic issue. Over much of the 20th century, flood conveyance was maintained through sediment removal, but this practice ended in the late 1990s. Flood hazard management activities since the 1990s have primarily involved levee removal or setback projects. Assessments of 1984-2009 repeat cross sections suggested that sediment deposition rates were particularly high in reaches with recent levee setbacks. However, there have been no assessments of recent deposition rates since the 2009 surveys. There are also concerns that intensifying flood hydrology or increased sediment delivery from Mount Rainier may exacerbate deposition. However, assessment of those risks has been hindered by limited understanding of watershed-scale sediment delivery and routing, particularly for coarse sand and gravel.
The U.S. Geological Survey, in cooperation with Pierce County, initiated this study to improve understanding of sediment deposition in the lower Puyallup River watershed. This work is primarily based on differencing of multiple aerial lidar datasets collected during 2002–2022, supplemented by early 1990 photogrammetric elevation datasets, geomorphic assessments of streamgage data, historical topographic surveys from 1907, and previously collected sediment transport measurements. Analyses cover the Puyallup, Carbon, and Mowich Rivers, but do not include the White River.
During 2004–2020, repeat aerial lidar indicates that 1.3 ± 0.3 million yd3 of sediment accumulated in the lower 20 valley miles (VMs) of the Puyallup River, averaging 80,000 ± 20,000 cubic yards per year (yd3/yr). Deposition was observed during both 2004–11 and 2011–20 lidar differencing intervals. This continued a long-term depositional trend that extends back to at least 1977. From 2004 to 2011, deposition rates along the Soldiers Home levee setback reach, the only setback project downstream of VM 20 completed prior to 2011, were approximately four times higher than in adjacent unmodified reaches. From 2011 to 2020, two additional setback projects were completed; volumetric deposition rates over all three setback reaches were similar to adjacent unmodified reaches, suggesting elevated setback deposition in the 2004–11 interval may have been influenced by an extreme flood in November 2006. These levee setback projects increased the local cross-sectional area of the floodway, used as a rough proxy for relative flood conveyance, by 50 to 200 percent above 2004 conditions. If deposition continued at recent rates, cross-sectional area over the levee setback reaches would be reduced back to 2004 values by 2050-90.
Deposition also occurred over the lower six VMs of the Carbon River during 2004–20, though volumes (0.15 ± 0.09 million yd3) were an order of magnitude lower than along the Puyallup River. Relatively lower deposition rates in the Carbon River are most likely the combined result of modestly lower incoming sediment loads, modestly steeper channel slope, and the additional sediment transport capacity provided by two large non-glacial tributaries that enter the Carbon River near VM 5.
Upstream of the depositional reaches described above, 2002–22 sediment storage trends along the Puyallup, Carbon, and Mowich Rivers were predominately negative (net erosion) up to the Mount Rainier National Park boundary. Net erosion was the result of bank and bluff erosion exceeding deposition across wetted channel and bare gravel areas, as opposed to uniform vertical downcutting. Net erosion along these river valleys delivered 3.4 ± 0.6 million yd3 to the river system, equivalent to 190,000 ± 35,000 yd3/yr. Most of that volume was supplied by erosion of relatively low (4–10 ft) surfaces along the Puyallup and Mowich Rivers and tall (300 ft) glacial bluffs along the lower Carbon River. Substantial aggradation from 1984 to 2009 reported by Czuba and others (2010) along reaches of the Puyallup River (VM 19–22) where levee confinement has recently been removed was most likely an artifact of methodologic bias.
The Puyallup, Mowich, and Carbon Rivers drain five distinct glaciated watersheds on the flanks of Mount Rainier, four of which were assessed in this study. All four watersheds were impacted by an extreme November 2006 rainstorm. Between 2002 and 2008, debris flows occurred in all four headwater areas, collectively eroding at least 2.1 million yd3 of sediment. These debris flows formed distinct deposits one to two miles downstream of source areas, depositing 30-50 percent of the material eroded upstream. From 2008 to 2022, no headwater debris flows were observed and overall rates of geomorphic change in the headwaters were low. Rivers eroded into debris flow deposits emplaced over the 2002–08 interval, but re-deposited equivalent volumes of material within a half mile downstream.
Stage-discharge relations at five streamgages on upland rivers draining Mount Rainier show either net channel incision or dynamic variability with no long-term trend over the past 60–100 years. Observations of pervasive river valley erosion and stable or incising trends at long-term streamgages in the upper watershed do not support prior claims of widespread and accelerating aggradation of upland rivers draining Mount Rainier.
Erosion and deposition volumes estimated in this report were combined with sediment transport estimates from limited suspended sediment and bedload measurements, estimates of sub-glacial erosion rates, and sediment delivery from non-glacial tributaries to construct watershed-scale sediment budgets for the Puyallup River watershed. During 2004–20, the estimated sediment load entering the depositional lowlands was well balanced by estimated inputs from, in order of relative magnitude, subglacial erosion (33–60 percent of total sediment load), erosion along the major river valleys (25–45 percent), erosion in recently deglaciated headwater areas (7–17 percent) and non-glacial tributaries (3–9 percent). These results are specific to the study period and represent total sediment loads, most of which is fine material carried in suspension. The relative sourcing of sand and gravel may be different than implied by this sediment budget.
Downstream of VM 12, comparison of 1907 and 2009 channel surveys show net lowering of the channel thalweg of 4–12 ft. A long-term gage near VM 22 shows lowering of 4–5 ft through the 1960s. Lowering at both locations was inferred to be a channel response to the substantial straightening, and so steepening, of the river during major phases of levee construction through the early and mid-20th century.
Application of a simple empirical bedload-discharge power-law relation to an ensemble of model-estimated daily mean discharge records in the lower Puyallup River between 1977 and 2100 projects that annual bedload transport capacity in the lower Puyallup River will increase by 20–60 percent by the middle of the 21st century. Actual changes in bedload transport and deposition rates will depend on concurrent changes in sediment supply and local hydraulics governing deposition.
This report presents several key conclusions. First, the persistence and spatial patterns of sand and gravel deposition along the lower Puyallup River support prior claims that deposition is fundamentally caused by decreases in channel slope moving downstream. Given this underlying cause and the abundance of sand and gravel available to be transported downstream, deposition is likely to continue for the foreseeable future. Second, despite continued sediment deposition, recent levee setback projects in the lower Puyallup River will likely provide several decades of flood conveyance benefits relative to a no-action alternative. Third, while the rivers linking Mount Rainier to the Puget Sound lowlands have often been discussed as conduits that either pass or accumulate sediment from Mount Rainier, observations from 2002–22 show these river valleys acting as substantial sediment sources, delivering three times more sediment than recently deglaciated headwater areas on Mount Rainier. While the persistence and underlying cause of recent river valley erosion remain unknown, sediment storage dynamics along these river valleys are likely to be a major control on sand and gravel delivery to the lower watershed.
The duration, magnitude, and frequency of heatwaves are predicted to increase in the coming decades, a combination that can reduce the survival of many fish species. Across the world, there is broad interest in identifying thermal refuge for heat-intolerant fish species and exploring opportunities to enhance or protect these areas. Because deeper groundwater maintains a relatively constant temperature, groundwater-influenced areas along streams can provide cool-water refuge for fish during periods of extreme heat. A targeted approach was developed for identifying existing cold-water zones and areas of substantial groundwater discharge in four high priority Lake Ontario tributaries. Our approach included: (1) predicting where groundwater discharge is most likely with a simple geospatial model and (2) using model predictions to select field sites for intensive high-resolution study, including ground-based mapping of groundwater features (springs, seeps, tributaries) as well as drone-based optical and thermal infrared surveys. Results from field sites were used to both verify model performance and map different types and aerial extents of thermal anomalies. Geospatial modelling successfully predicted regions of widespread groundwater upwelling, later verified and mapped by field and drone surveys. Comparison of model and field survey results further highlighted specific geospatial layers, such as soil/bedrock types and topographic wetness index, as being particularly useful for predicting groundwater influence on streams in the study area. In addition, a comparison of geospatial model results with a model of fish abundances along the studied streams showed significant positive correlations for many heat-intolerant fish species over a wide geographic area. The approach developed in this study can be applied to other watersheds to highlight areas of probable groundwater discharge and could be used by fishery and water resource managers to support cold-water fish habitat management decision-making and resource conservation.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70459","usgsCitation":"Woda, J., Terry, N., Kelley, D.J., Finkelstein, J., Gazoorian, C.L., and McKenna, J., 2026, A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries: Hydrologic Processes, v. 40, e70459, 16 p., https://doi.org/10.1002/hyp.70459.","productDescription":"e70459, 16 p.","ipdsId":"IP-176833","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":501102,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70459","text":"Publisher Index Page"},{"id":500774,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"New York","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.34397142741707,\n 44.03795020350384\n ],\n [\n -80.34397142741707,\n 42.83906785974037\n ],\n [\n -75.35823758327766,\n 42.83906785974037\n ],\n [\n -75.35823758327766,\n 44.03795020350384\n ],\n [\n -80.34397142741707,\n 44.03795020350384\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2026-03-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Woda, Joshua 0000-0002-2932-8013","orcid":"https://orcid.org/0000-0002-2932-8013","contributorId":290172,"corporation":false,"usgs":true,"family":"Woda","given":"Joshua","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":956840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, David J 0000-0002-0143-0956","orcid":"https://orcid.org/0000-0002-0143-0956","contributorId":367137,"corporation":false,"usgs":true,"family":"Kelley","given":"David","middleInitial":"J","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956843,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":190798,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":956844,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273939,"text":"70273939 - 2026 - Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics","interactions":[],"lastModifiedDate":"2026-02-18T15:12:53.887851","indexId":"70273939","displayToPublicDate":"2026-02-17T07:57:49","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics","docAbstract":"Due to a lack of management operations data, hydrological models may represent reservoirs as natural lakes, leading to poor discharge predictions in regulated basins. To parse seasonal operational signatures, we compare the dynamics of natural lake and reservoir systems across North America using Surface Water and Ocean Topography (SWOT) satellite observations and derived discharge estimates. Overall, reservoirs and their adjacent river reaches exhibit significantly greater variability (in standard deviation) than their natural counterparts across almost all SWOT observed (e.g. water surface elevation) and inferred (e.g. discharge) variables. Natural lakes show strong same-day correlations between inflow and outflow discharge (median Spearman R = 0.8), whereas 76% of reservoirs exhibit maximum correlation when outflow is lagged, suggesting operations buffer seasonal flow variability. Our findings indicate operations not only affect reservoir dynamics themselves but also have upstream and downstream consequences, which, when integrated into models, will offer more realistic hydrologic conditions.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ae436e","usgsCitation":"Riggs, R.M., Dickinson, J.E., Brinkerhoff, C.B., Sikder, M.S., Wang, J., Gao, H., and Allen, G.H., 2026, Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics: Environmental Research Letters, v. 21, 044008, 11 p., https://doi.org/10.1088/1748-9326/ae436e.","productDescription":"044008, 11 p.","ipdsId":"IP-177052","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":500251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ae436e","text":"Publisher Index Page"},{"id":500137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -165.20917200792005,\n 72.32481180155446\n ],\n [\n -116.99838105786625,\n 14.863773568551608\n ],\n [\n -87.70978967120412,\n 18.449041713609518\n ],\n [\n 1.251170353917047,\n 74.7933097957411\n ],\n [\n -165.20917200792005,\n 72.32481180155446\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","noUsgsAuthors":false,"publicationDate":"2026-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Riggs, Ryan Matthew 0000-0001-6834-9469","orcid":"https://orcid.org/0000-0001-6834-9469","contributorId":359717,"corporation":false,"usgs":true,"family":"Riggs","given":"Ryan","middleInitial":"Matthew","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":955826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinkerhoff, Craig B. 0000-0001-6701-4835","orcid":"https://orcid.org/0000-0001-6701-4835","contributorId":345546,"corporation":false,"usgs":false,"family":"Brinkerhoff","given":"Craig","middleInitial":"B.","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":955828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sikder, Md. Safat 0000-0002-1910-1800","orcid":"https://orcid.org/0000-0002-1910-1800","contributorId":359718,"corporation":false,"usgs":false,"family":"Sikder","given":"Md.","middleInitial":"Safat","affiliations":[{"id":85904,"text":"Department of Geography and Geographic Information Science, University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":955829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Jida","contributorId":333531,"corporation":false,"usgs":false,"family":"Wang","given":"Jida","email":"","affiliations":[{"id":79917,"text":"Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS, USA.","active":true,"usgs":false}],"preferred":false,"id":955830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gao, Huilin 0000-0001-7009-8005","orcid":"https://orcid.org/0000-0001-7009-8005","contributorId":359721,"corporation":false,"usgs":false,"family":"Gao","given":"Huilin","affiliations":[{"id":51860,"text":"Department of Civil Engineering, Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":955831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Allen, George H. 0000-0001-8301-5301","orcid":"https://orcid.org/0000-0001-8301-5301","contributorId":225161,"corporation":false,"usgs":false,"family":"Allen","given":"George","middleInitial":"H.","affiliations":[{"id":41057,"text":"Department of Geography, Texas A&M University, College Station, TX, 77843","active":true,"usgs":false}],"preferred":false,"id":955832,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274640,"text":"70274640 - 2026 - Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes","interactions":[],"lastModifiedDate":"2026-04-02T18:30:01.828215","indexId":"70274640","displayToPublicDate":"2026-02-16T11:24:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes","docAbstract":"Freshwater fishes are among the most threatened taxa, yet conservation assessments remain incomplete for many species. Freshwater fishes provide essential ecosystem services such as food security, recreational opportunities, and cultural significance. Despite heavy alterations to freshwater ecosystems, the reasons for species’ sensitivity and resistance to imperilment are unclear. To address this need, we develop a machine learning framework to predict global imperilment status for 10,631 freshwater fish species using a comprehensive set of environmental, socioeconomic, and intrinsic species-level predictors. Using updated IUCN Red List data, we train and validate Random Forest classifiers to distinguish imperiled (Vulnerable, Endangered, Critically Endangered) from non-imperiled species. We examine the relative influence of 52 variables derived from 12 global sources describing extrinsic environmental and socioeconomic factors and intrinsic species-specific characteristics. Our models achieve higher accuracy for non-imperiled species (90.1%) compared to imperiled species (81.8%), reflecting the greater heterogeneity of threats and conditions driving imperilment. Across models, key predictors include habitat variables, taxonomic order, hydrological characteristics, and disturbance indicators, underscoring the interplay between ecology, geography, and human pressures. This integrative, reproducible approach demonstrates the utility of machine learning for guiding proactive conservation and provides a scalable framework for global biodiversity risk assessment.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-025-68154-w","usgsCitation":"Murphy, C.A., Olivos, J.A., Arismendi, I., García-Berthou, E., Johnson, S.L., and Dunham, J., 2026, Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes: Nature Communications, v. 17, 1661, 11 p., https://doi.org/10.1038/s41467-025-68154-w.","productDescription":"1661, 11 p.","ipdsId":"IP-170109","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-025-68154-w","text":"Publisher Index Page"},{"id":502030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationDate":"2026-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olivos, J. Andres","contributorId":369132,"corporation":false,"usgs":false,"family":"Olivos","given":"J.","middleInitial":"Andres","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arismendi, Ivan","contributorId":341108,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"García-Berthou, Emili","contributorId":6293,"corporation":false,"usgs":false,"family":"García-Berthou","given":"Emili","affiliations":[],"preferred":false,"id":958525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Sherri L.","contributorId":369137,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":958526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":958527,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273930,"text":"70273930 - 2026 - Effects of groundwater withdrawals for water bottling and municipal use, Wards Brook Valley, Maine and New Hampshire","interactions":[],"lastModifiedDate":"2026-02-18T15:14:50.497171","indexId":"70273930","displayToPublicDate":"2026-02-13T09:08:06","publicationYear":"2026","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Effects of groundwater withdrawals for water bottling and municipal use, Wards Brook Valley, Maine and New Hampshire","docAbstract":"Hydrologic models for the Wards Brook valley near Fryeburg, Maine were developed for historical (2016 – 2021) and hypothetical future conditions (2046 – 2065 and 2080 – 2099) to understand the effects of groundwater withdrawals for bottled water and municipal use on hydrologic conditions (stream base flows and groundwater levels). Analyses showed that the simulated base flows in Wards Brook were reduced because of pumping for both municipal water supplies and for water bottling, and about half of the total pumping impact on the base flows in Wards Brook was from the bottled water extraction. Simulated flows were greater than the minimum recommended streamflow of 2,180 cubic meters per day (400 gallons per minute) throughout the historical period. Simulated groundwater levels at two of three nearby ponds (Round Pond and Davis Pond) were minimally affected by pumping conditions, and effects were primarily from the municipal well closest to the ponds.
Several estimates of future projected recharge were used to understand the potential effects of groundwater withdrawals on hydrologic conditions under multiple hypothetical climate conditions. Annual projected recharge rates in the mid- and late-21st century from two climate scenarios (stabilized greenhouse-gas emissions and high greenhouse-gas emissions) were similar to rates for 2016 – 2021. However, monthly recharge patterns for the future periods shifted toward more recharge in the winter months (December, January, and February) and less recharge in April, May, and October relative to 2016 – 2021.
The lowest mean monthly base flows from the future emission scenarios all remain larger than the minimum recommended streamflow and indicate no long-term declines in flow relative to historical conditions. However, simulated base flows during hypothetical 3-year drought scenarios declined below minimum recommended streamflow during the summer months in the stabilized- and high-emission scenarios in the mid-21st century. Although water is generally plentiful in the Wards Brook valley, reduced pumping may be needed to maintain streamflows in Wards Brook under future climate conditions similar to modeled drought scenarios.
Groundwater quality in and around oil fields in the Southern San Joaquin Valley is of interest to many California residents that rely heavily on groundwater for domestic, commercial, and agricultural use. To help assess the effects of historical oil-field activities and natural geologic sources on groundwater near the southwest margins of the Kern County Groundwater Subbasin, a multiple-well monitoring site was installed near the administrative boundary between the Midway-Sunset and Buena Vista Oil Fields in Kern County, California. The installation of the Midway-Sunset Buena Vista multiple-well monitoring site (MSBV) supports regional analysis of the relations of oil and gas sources to groundwater quality by providing information about the geology, hydrology, geophysical properties, and water quality of the alluvial and upper Tulare aquifers in areas where groundwater data were limited. Data collected from the site included drill cuttings, whole core samples, sidewall core samples, mud-gas analysis, borehole geophysical logs, depth to water measurements, and water quality samples. Whole cores were scanned using dual energy computed tomography. Subsamples of selected cores were analyzed for density, porosity, specific retention, and bulk minerology. Thin sections of the subsamples were prepared, photographed, and examined. Two samples were analyzed using scanning electron microscope technology to examine the microporosity of diatomite laden sediment. Instrumentation installed in the wells collect hourly depth to water measurements.
Analysis of the data show there is 355 feet of alluvium overlying the Tulare Formation at the well site. The contact between the two formations is an aquitard resulting in a perched aquifer in the alluvium and unconfined aquifer in the Tulare Formation. The alluvium is more heterogenous and finer grained than the Tulare Formation resulting in markedly higher porosity in the alluvium compared to the Tulare Formation. Higher specific retention observed in the alluvium is attributed to the finer grained sediment and greater abundance of reworked diatomite (as represented by opal-CT [cristobalite-tridymite]) compared to the Tulare Formation. Total dissolved solids (TDS) approached or exceeded 10,000 milligrams per liter (mg/L) in the alluvium from approximately 176 to 242 feet below land surface and at the top of the Amnicola clay at approximately 670 feet below land surface within the Tulare Formation. Elevated TDS, chloride, and boron concentrations in the alluvium and on top of the Amnicola clay likely reflect groundwater that is mixed with oil-field water. Water chemistry and modern-aged groundwater in the alluvial monitoring well (MSBV #3) are consistent with the oil-field water in the alluvium being derived from documented historical surface disposal of oil-field water upslope (northwest) of the site. Water chemistry and pre-modern groundwater age in the deeper Tulare monitoring well (MSBV #1) on top of the Amnicola clay are consistent with oil-field fluids derived from upslope natural geologic sources or old oil wells that leak in the subsurface. Shallow groundwater in the Tulare (MSBV #2) is not affected by mixing with oil-field sources.
In situ surface-water monitoring strategies are biased towards larger perennial streams and lakes and are generally not designed to track mechanisms of baseflow supply contributed by the dynamic storage of aquifers. Additionally, small (< 1 km2) groundwater-influenced lakes and wetlands globally have little in situ monitoring infrastructure. We explored the utility of remotely sensed Surface Water Ocean Topography Satellite (SWOT) data, collected from 2023 onward, to characterise the seasonal and multi-year water-level trends of groundwater flow-through kettle lakes distributed across the permeable sediments of eastern Massachusetts, USA. This analysis indicated that water levels for kettle lakes with areas down to approximately 0.05 km2 are resolvable in the study area. Our examination of 17 kettle lakes found that SWOT water-surface elevation data closely tracked groundwater levels in adjacent monitoring wells where available, including the timing of seasonal patterns (highest levels generally in late spring), although there was some variation between years and there was a substantial lag in the timing of high water levels for a lake located downgradient from a 30-m-thick vadose zone. Furthermore, SWOT-observed water-level increases in kettle lakes tracked with baseflow increases in two adjacent groundwater-dominated streams, as would be expected from increased hydraulic gradients. Unlike spectral remote sensing, SWOT data are generally not affected by cloud cover, resulting in a potential for groundwater-dominated lakes to be sentinels of dynamic storage patterns, including identification of baseflow drought lags, which are currently ill-defined hydrological processes. SWOT monitoring of groundwater-influenced surface waters shows potential for augmenting existing monitoring wells and streamgages as continuous monitors of groundwater levels and baseflow supply in permeable terrain.
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The western PNW faces similar challenges to other regions with shifting wildfire regimes and large population centers reliant on surface water from forested catchments. However, the uniquely wet and highly seasonal climate of the western PNW suggests that findings from other, more frequently burned regions may not be directly applicable. To identify science, monitoring, and management gaps and opportunities in the western PNW, this review was collaboratively undertaken by academics, non-government and industry representatives, and local, state, and federal government entities who have been working together since the 2020 Labor Day fires in Oregon. Focusing on Oregon and Washington, we found that monitoring networks for continuous water quantity and quality cover much of the state with greater representation in western U.S. ecoregions, but few studies have analyzed and published these data to capture and communicate the post-wildfire response. Approximately half of the streamgages in Oregon and Washington record major water quality parameters, and hundreds of sites in the area have discrete sampling for a wide range of water quality constituents. Still, numerous gaps exist in understanding the short- and long-term impacts of wildfire on hydrology, water chemistry, including pH and dissolved oxygen, mobilization of metals, aquatic ecosystems, and downstream drinking water treatment. Collective action to further collect, analyze, interpret, and publish the key data could help improve our understanding of post-wildfire water quality impacts in this and other increasingly wildfire-affected regions.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/3033-4942/ae36cb","usgsCitation":"Wall, S., Compton, J.E., Coble, A.A., Haley, B.M., Lin, J., Myers-Pigg, A., Reale, J.K., Wampler, K., Swartz, A., Moffett, K., Bladon, K.D., Carpenter, K., Chang, H., Chen, J., Donahue, D., Eckley, C.S., Hohner, A.K., Kiffney, P.M., Miralha, L., Regier, P., Seeds, J., and River, M., 2026, Post-wildfire water quality and aquatic ecosystem response in the U.S. Pacific Northwest: science and monitoring gaps: Environmental Research: Water, no. 2, 015004, 31 P., https://doi.org/10.1088/3033-4942/ae36cb.","productDescription":"015004, 31 P.","ipdsId":"IP-181756","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":500249,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/3033-4942/ae36cb","text":"Publisher Index 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