The Zuni Salt Lake is located in a maar in west-central New Mexico and contains hypersaline water that has long been used by Native Americans for religious purposes and the collection of salt. There have been several investigations suggesting different sources for the water and salt to the lake. Springs, seeps, and ephemeral streamflow have all been observed to contribute freshwater to the lake, and brackish to hypersaline seeps have been documented along the banks of the lake. This report summarizes the findings of a study that characterizes the lake’s hydrology, its water and salinity sources, and the hydrogeologic conceptual model. Regional groundwater levels indicate that each of the aquifers in the area have the potential to discharge groundwater to the lake. There is also evidence of vertical groundwater flow pathways at the maar that were likely created by the igneous intrusion that fractured the intersecting aquifers. A detailed water budget was constructed from continuous lake stage, precipitation, and evaporation data to estimate the groundwater inflow to the Zuni Salt Lake. It was determined that groundwater inflow to the lake is 441 ±94 acre-feet per year, which composes as much as 77 percent of the total inflows. The high sodium and chloride concentrations measured in two hypersaline samples collected near the lake indicate that the majority of the dissolved solids entering the lake are from a hypersaline groundwater source. The geochemical and isotopic compositions measured in the lake and surrounding features support the interpretation that hypersaline groundwater is the primary source of salts to the lake, which is likely sourced from the older (and deeper) Permian units. The hypersaline groundwater samples collected during this investigation have a unique aqueous chemistry relative to each of the mapped aquifers, and variability in groundwater compositions is interpreted to result from differences in minerology and residence time.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Contact Us- USGS Publications Warehouse
","tableOfContents":"Hydrologic connectivity (HC), particularly in floodplain systems, is pivotal in regulating ecosystem services by facilitating the movement of nutrients, sediments, chemicals, and biota. However, human interventions such as dam construction, levee installation, water management practices, and alterations in vegetation have significantly disrupted natural HC patterns globally. To provide a structured entry into the growing body of HC research, we conducted a systematic literature review of 1920 studies, analysing diverse definitions, influencing factors, quantification approaches, spatial and temporal scales, and management strategies. In addition to traditional review methods, our approach integrates keyword and cluster analysis to elucidate dominant research themes and trends across the literature. Our review reveals that the literature is heavily skewed towards research in North America and Europe (accounting for 72% of studies) and predominantly utilises field investigations, simulation modelling, and remote sensing integrated with geographic information systems. Although these methodologies have advanced our understanding, most studies focus on restricted spatial scales such as individual hillslopes, catchments, or stream networks and short temporal intervals, including single precipitation events or seasonal cycles. A narrow focus becomes a limitation when such studies do not contribute to broader efforts aimed at scaling insights across larger domains. These limitations highlight the potential benefits of innovative conceptual frameworks and quantification methods to better capture HC across broader environments and extended temporal scales. We conclude by discussing challenges in defining and quantifying floodplain HC and outlining potential future research directions to advance connectivity science and management, particularly in floodplain systems characterised by frequent hydrologic fluctuations, such as seasonal inundation and changing flow paths.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70260","usgsCitation":"Hafez Ahmad, Miranda, L.E., Dunn, C.G., Melanie R. Boudreau, and Colvin, M.E., 2025, Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management: Hydrological Processes, v. 39, no. 9, e70260, 23 p., https://doi.org/10.1002/hyp.70260.","productDescription":"e70260, 23 p.","ipdsId":"IP-177204","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hafez Ahmad","contributorId":362594,"corporation":false,"usgs":false,"family":"Hafez Ahmad","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":950631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melanie R. Boudreau","contributorId":362597,"corporation":false,"usgs":false,"family":"Melanie R. Boudreau","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":950634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950735,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272995,"text":"70272995 - 2025 - Model‐based decomposition of spatially varying temporal shifts in seasonal streamflow across north temperate US rivers.","interactions":[],"lastModifiedDate":"2025-12-15T14:20:44.203219","indexId":"70272995","displayToPublicDate":"2025-09-16T07:54:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Model‐based decomposition of spatially varying temporal shifts in seasonal streamflow across north temperate US rivers.","docAbstract":"Anthropogenically forced climate shifts disrupt the seasonal behavior of climatic and hydrologic processes. The seasonality of streamflow has significant implications for the ecology of riverine ecosystems and for meeting societal demands for water resources. We develop a hierarchical Bayesian model of daily streamflow to quantify how the shape of annual hydrographs are changing and to evaluate temporal trends in model-based hydrologic indices related to flow timing and magnitude shifts. We apply this model to 1,112 gages across the Northern US over the years 1965–2022. We identify large-scale patterns in temporal changes to streamflow profiles that are consistent with regional changes in hydroclimate, including decreasing seasonal flow variability in the Pacific Northwest and increasing winter flows in the northeastern United States. Within these regions we also observe fine-scale heterogeneity in streamflow timing and magnitude shifts, both of which have potentially significant implications for riverine ecosystem function and the ecosystem services they provide.
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Georgia","active":true,"usgs":false}],"preferred":false,"id":948611,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"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":948612,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Folk, Gwendolynn","contributorId":361320,"corporation":false,"usgs":false,"family":"Folk","given":"Gwendolynn","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":948613,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70272284,"text":"70272284 - 2025 - Seasonal synchronicity and multi-decadal stability of headwater biogeochemistry in the northern temperate zone","interactions":[],"lastModifiedDate":"2025-11-20T16:23:06.555018","indexId":"70272284","displayToPublicDate":"2025-09-08T09:17:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal synchronicity and multi-decadal stability of headwater biogeochemistry in the northern temperate zone","docAbstract":"Temporal patterns in chemistry of headwater streams reflect responses of water and elemental cycles to perturbations occurring at local to global scales. We evaluated multi-scale temporal patterns in up to 32 y of monthly observations of stream chemistry (ammonium, calcium, dissolved organic carbon, nitrate, total dissolved phosphorus, and sulfate) in 22 reference catchments within the northern temperate zone of North America. Multivariate autoregressive state-space (MARSS) models were applied to quantify patterns at multi-decadal, seasonal, and shorter intervals during a period that encompassed warming climate, seasonal changes in precipitation, and regional declines in atmospheric deposition. Significant long-term trends in solute concentrations within a subset of the catchments were consistent with recovery from atmospheric deposition (e.g., calcium, nitrate, sulfate) and increased precipitation (e.g., dissolved organic carbon). Lack of evidence for multi-decadal trends in most catchments suggests resilience of northern temperate ecosystems or that subtle net effects of simultaneous changes in climate and disturbance regimes do not result in directional trends. Synchronous seasonal oscillations of solute concentrations occurred across many catchments, reflecting shared climate and biotic drivers of seasonality within the northern temperate zone. Despite shared patterns among catchments at a seasonal scale, multi-scale temporal patterns were statistically distinct among even adjacent headwater catchments, implying that local attributes of headwater catchments modify the signals imparted by atmospheric phenomena and regional disturbances. To effectively characterize hydrologic and biogeochemical responses to changing climate and disturbance regimes, catchment monitoring programs could include multiple streams with contributing areas that encompass regional heterogeneity in vegetation, topography, and elevation. Overall, detection of long-term patterns and trends requires monitoring multiple catchments at a frequency that captures periodic variation (e.g., seasonality) and a duration encompassing the perturbations of interest.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10533-025-01263-2","usgsCitation":"Harms, T.K., Hood, J., Scheuerell, M.D., Creed, I., Campbell, J.L., Fernandez, I.J., Higgins, S.N., Johnson, S.L., Shanley, J.B., Sebestyen, S., Webster, K.L., and Yoa, H., 2025, Seasonal synchronicity and multi-decadal stability of headwater biogeochemistry in the northern temperate zone: Biogeochemistry, v. 168, 72, 19 p., https://doi.org/10.1007/s10533-025-01263-2.","productDescription":"72, 19 p.","ipdsId":"IP-167949","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-025-01263-2","text":"Publisher Index Page"},{"id":496696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -136.78854045934415,\n 57.31227395978971\n ],\n [\n -126.56774947282855,\n 36.21030831674423\n ],\n [\n -69.53376916748583,\n 35.89418743935734\n ],\n [\n -49.19753148607294,\n 46.04477310474076\n ],\n [\n -55.28204218823373,\n 56.67586141571607\n ],\n [\n -136.78854045934415,\n 57.31227395978971\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"168","noUsgsAuthors":false,"publicationDate":"2025-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Harms, Tamara K.","contributorId":362630,"corporation":false,"usgs":false,"family":"Harms","given":"Tamara","middleInitial":"K.","affiliations":[{"id":13325,"text":"University of California Riverside","active":true,"usgs":false}],"preferred":false,"id":950672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hood, Jim","contributorId":362633,"corporation":false,"usgs":false,"family":"Hood","given":"Jim","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":950673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":950674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Creed, Irena F.","contributorId":204051,"corporation":false,"usgs":false,"family":"Creed","given":"Irena F.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":950675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, John L.","contributorId":362636,"corporation":false,"usgs":false,"family":"Campbell","given":"John","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":950676,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fernandez, I. J. 0000-0002-7220-2205","orcid":"https://orcid.org/0000-0002-7220-2205","contributorId":239648,"corporation":false,"usgs":false,"family":"Fernandez","given":"I.","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":950677,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Higgins, S. N.","contributorId":362639,"corporation":false,"usgs":false,"family":"Higgins","given":"S.","middleInitial":"N.","affiliations":[{"id":86541,"text":"Experimental Lakes Area","active":true,"usgs":false}],"preferred":false,"id":950678,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Sherri L.","contributorId":362640,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":950679,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950680,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sebestyen, Stephen","contributorId":298358,"corporation":false,"usgs":false,"family":"Sebestyen","given":"Stephen","affiliations":[{"id":64539,"text":"U.S. Forest Service Northern Research Station","active":true,"usgs":false}],"preferred":false,"id":950681,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Webster, K. L.","contributorId":362641,"corporation":false,"usgs":false,"family":"Webster","given":"K.","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":950682,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yoa, H.","contributorId":362642,"corporation":false,"usgs":false,"family":"Yoa","given":"H.","affiliations":[{"id":86544,"text":"Ontario Ministry of Environment","active":true,"usgs":false}],"preferred":false,"id":950683,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70271463,"text":"70271463 - 2025 - Speleothem evidence for Late Miocene extreme Arctic amplification – An analogue for near-future anthropogenic climate change?","interactions":[],"lastModifiedDate":"2025-09-17T14:00:53.292778","indexId":"70271463","displayToPublicDate":"2025-09-08T07:56:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Speleothem evidence for Late Miocene extreme Arctic amplification – An analogue for near-future anthropogenic climate change?","docAbstract":"The Miocene provides an excellent climatic analogue for near-future runaway anthropogenic warming, with atmospheric CO2 concentrations and global average temperatures similar to those projected for the coming century under extreme-emissions scenarios. However, the magnitude of Miocene Arctic warming remains unclear due to the scarcity of reliable proxy data. Here we use stable oxygen isotope and trace element analyses, alongside clumped isotope and fluid inclusion palaeothermometry of speleothems to reconstruct palaeo-environmental conditions near the Siberian Arctic coast during the Tortonian (8.68 ± 0.09 Ma). Stable oxygen isotope records suggest warmer-than-present temperatures. This is supported by temperature estimates based on clumped isotopes and fluid inclusions giving mean annual air temperatures between +6.6 and +11.1 °C, compared with −12.3 °C today. Trace elements records reveal a highly seasonal hydrological environment.
Our estimate of > 18 °C of Arctic warming supports the wider consensus of a warmer-than-present Miocene and provides a rare palaeo-analogue for future Arctic amplification under high-emissions scenarios. The reconstructed increase in mean surface temperature far exceeds temperatures projected in fully coupled global climate models, even under extreme-emissions scenarios. Given that climate models have consistently underestimated the extent of recent Arctic amplification, our proxy data suggest Arctic warming may exceed current projections.
The potential for environmental DNA (eDNA) to disperse widely from source organisms enables high detection efficiency but raises questions about eDNA's ability to differentiate fine-scale spatial patterns relative to conventional fish capture data.
We evaluate these questions in the St. Louis River estuary—a hydrologically and spatially complex coastal system within Lake Superior that supports a diverse assemblage of resident and migratory fish species—via comparison of eDNA metabarcoding (12S and 16S loci) to multigear capture survey data from 2 years and two seasons.
The eDNA and capture surveys collectively yielded 68 fish species: 2 species detected only by capture, 27 detected only by eDNA, and 39 shared across both survey types but having generally higher occurrence frequencies with eDNA than capture. Six species detected only by eDNA were unexpected, having no prior records in the Lake Superior basin. Data from paired eDNA and capture stations showed little relationship between the two survey types, with capture yielding species at stations that eDNA did not, eDNA detecting species in different habitats and distant locations from any captures, and assemblage patterns homogenized in eDNA surveys relative to capture surveys.
Our study finds that eDNA is a sensitive tool for assessing species presence at the system scale but that capture surveys may better yield the fine-scale spatial distribution information of interest to fisheries and habitat managers, especially in spatially and hydrologically complex systems.
Food chain length (FCL) is a primary determinant of food web structure and is hypothesized to be influenced by habitat size, productivity, and disturbance. Understanding the environmental characteristics that determine food chain length can assist in understanding how food webs may be impacted due to changes in habitats and environmental characteristics. This study examines the impact of hydrologic disturbance on stream food webs when the top predator is constant. We analyzed FCL in less disturbed groundwater flashy streams and more disturbed runoff flashy streams using stable isotopes. Despite no difference in species richness or fish density, food chains in more disturbed streams had a lower FCL compared to food chains in more stable streams. Assemblage analysis showed that flow regime and drainage area significantly impacted individual species abundances. The more disturbed runoff flashy streams had higher proportions of primary consumer fish, such as the algivorous Campostoma sp. (Stonerollers), which likely drives the reduced FCL. Drainage area and land cover had non-significant relationships with FCL. Shifting community structure due to hydrologic variability likely leads to differences in diet of Micropterus dolomieu (Smallmouth Bass), and thus a difference in FCL.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2025.2552789","usgsCitation":"Sorensen, S.F., and Magoulick, D.D., 2025, Disturbance is the primary determinant of food chain length when the top predator is constant: Journal of Freshwater Ecology, v. 40, no. 1, 2552789, 13 p., https://doi.org/10.1080/02705060.2025.2552789.","productDescription":"2552789, 13 p.","ipdsId":"IP-158669","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496764,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2025.2552789","text":"Publisher Index Page"},{"id":496698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","otherGeospatial":"Boston Mountains, Ozark Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.36140202738136,\n 36.86778775165942\n ],\n [\n -95.16750642659139,\n 35.284730700987836\n ],\n [\n -90.54968868524054,\n 35.4188870788884\n ],\n [\n -89.35998010774131,\n 36.86867805963976\n ],\n [\n -92.3624285247389,\n 37.51630205547987\n ],\n [\n -93.33606079252797,\n 37.097059236951665\n ],\n [\n -94.36140202738136,\n 36.86778775165942\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sorensen, Sarah F.","contributorId":362643,"corporation":false,"usgs":false,"family":"Sorensen","given":"Sarah","middleInitial":"F.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":950684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":950685,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70272596,"text":"70272596 - 2025 - Long‐term regime shifts in xeric ecoregion freshwater fish assemblages due to Anthropogenic and climate stressors","interactions":[],"lastModifiedDate":"2025-11-24T15:08:54.65527","indexId":"70272596","displayToPublicDate":"2025-09-01T08:04:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Long‐term regime shifts in xeric ecoregion freshwater fish assemblages due to Anthropogenic and climate stressors","docAbstract":"Shifting climate regimes are projected to increase the area of xeric regions and result in more pronounced intermittency across river networks. Given these projected changes, we aim to understand the factors contributing to species persistence under increasing aridity. To investigate how changing flow regimes are related to changes in fish richness and assemblage composition, we compiled data from 1473 xeric stream sites in the United States and Australia. The temporal coverage of this dataset is more than 40 years, from 1980 to 2021. Our focus was on fishes occurring in xeric streams and included 191 species. We compiled climate, hydrologic, and fish species trait data to identify relationships between environmental drivers of species persistence and corresponding characteristics common to species in these systems and traits eliciting the strongest responses to environmental change. Our data show declines in overall precipitation in concert with increasing temperatures over the last several decades. Climatic shifts were accompanied by declines in discharge, increased zero-flow days, and longer durations of no-flow periods. In these same systems, an overall linear decline in fish species richness was observed, but it was not directly correlated with any hydrologic predictors. However, xeric species of conservation concern were small-bodied and occupied lower trophic levels than those not of concern. Listed species were primarily affected by multiple stressors, including habitat degradation and invasive species, compounded by a small geographic range. We thus propose a multiple stressors argument for the declines in xeric fish assemblages, something that may be exacerbated by climate alterations in the future. This work highlights a critical conservation need for xeric fishes and identifies taxa that are especially vulnerable to a combination of anthropogenic stressors and changing climates.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72067","usgsCitation":"Krabbenhoft, C.A., Rogosch, J.S., and Rowland, F.E., 2025, Long‐term regime shifts in xeric ecoregion freshwater fish assemblages due to Anthropogenic and climate stressors: Ecology and Evolution, v. 15, no. 9, e72067, 15 p., https://doi.org/10.1002/ece3.72067.","productDescription":"e72067, 15 p.","ipdsId":"IP-167908","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496929,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72067","text":"Publisher Index Page"},{"id":496822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -126.68838705734726,\n 42.46729142856819\n ],\n [\n -126.68838705734726,\n 31.274100073517374\n ],\n [\n -101.81329639705922,\n 31.274100073517374\n ],\n [\n -101.81329639705922,\n 42.46729142856819\n ],\n [\n -126.68838705734726,\n 42.46729142856819\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 112.14586345695147,\n -18.081847635268318\n ],\n [\n 112.14586345695147,\n -33.43692331548075\n ],\n [\n 144.94300096233883,\n -33.43692331548075\n ],\n [\n 144.94300096233883,\n -18.081847635268318\n ],\n [\n 112.14586345695147,\n -18.081847635268318\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Krabbenhoft, Corey A. 0000-0002-1041-5301","orcid":"https://orcid.org/0000-0002-1041-5301","contributorId":362965,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Corey","middleInitial":"A.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogosch, Jane S. 0000-0002-1748-4991","orcid":"https://orcid.org/0000-0002-1748-4991","contributorId":317717,"corporation":false,"usgs":true,"family":"Rogosch","given":"Jane","middleInitial":"S.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rowland, Freya Elizabeth 0000-0002-1041-5301","orcid":"https://orcid.org/0000-0002-1041-5301","contributorId":302395,"corporation":false,"usgs":true,"family":"Rowland","given":"Freya","email":"","middleInitial":"Elizabeth","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950885,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271905,"text":"70271905 - 2025 - A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","interactions":[],"lastModifiedDate":"2025-09-24T15:03:35.249606","indexId":"70271905","displayToPublicDate":"2025-09-01T07:53:41","publicationYear":"2025","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":"A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","docAbstract":"Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO3−), magnesium (Mg2+) and calcium (Ca2+). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO3−, 0.65 for Ca2+, and 0.79 for Mg2+. Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.180286","usgsCitation":"Green, C., Hirsch, R.M., Essaid, H., and Sanford, W.E., 2025, Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin: Science of the Total Environment, v. 999, 180286, 14 p., https://doi.org/10.1016/j.scitotenv.2025.180286.","productDescription":"180286, 14 p.","ipdsId":"IP-159069","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":496136,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.180286","text":"Publisher Index Page"},{"id":495782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.79788517502844,\n 39.713218235332164\n ],\n [\n -75.44918608740714,\n 38.663983307614814\n ],\n [\n -74.82016028228699,\n 38.99952921670035\n ],\n [\n -74.61504317192174,\n 39.81307746348011\n ],\n [\n -74.15695069541222,\n 41.998596289750736\n ],\n [\n -74.9227212407762,\n 42.30779251171998\n ],\n [\n -75.65430560107949,\n 41.9782683665571\n ],\n [\n -76.07821429583441,\n 41.159834427011475\n ],\n [\n -76.03035363674925,\n 40.632678412780365\n ],\n [\n -75.79788517502844,\n 39.713218235332164\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"999","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":949040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":949041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essaid, Hedeff 0000-0003-0154-8628","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":361587,"corporation":false,"usgs":false,"family":"Essaid","given":"Hedeff","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":949042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":337084,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":949043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271435,"text":"70271435 - 2025 - Wetland ecohydrology","interactions":[],"lastModifiedDate":"2025-09-15T13:53:29.901159","indexId":"70271435","displayToPublicDate":"2025-08-28T08:49:26","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Wetland ecohydrology","docAbstract":"Ecohydrology emphasizes the interactions between ecological and hydrological patterns and processes in wetlands. Given that wetlands are fundamentally defined by prolonged saturation or flooding of land, an ecohydrological perspective is implicit in wetland ecology. In this review, we provide examples of how variation in hydrologic processes in space and time influences wetland ecosystems in temperate riparian zones, inland temperate wetlands, and subtropical monsoonal wetlands. Because wetland ecosystems are highly impacted by anthropogenic change, an understanding of ecohydrological processes in wetlands will be critical for future conservation and restoration of wetlands in a changing world.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Routledge handbook of wetlands","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Routledge","doi":"10.4324/9781003219644-6","usgsCitation":"Dixon, M.D., Johnson, W.C., and Middleton, B., 2025, Wetland ecohydrology, chap. of Routledge handbook of wetlands, p. 38-53, https://doi.org/10.4324/9781003219644-6.","productDescription":"16 p.","startPage":"38","endPage":"53","ipdsId":"IP-149990","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":495485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Dixon, Alan","contributorId":361412,"corporation":false,"usgs":false,"family":"Dixon","given":"Alan","affiliations":[],"preferred":false,"id":948788,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Maddock, Ian","contributorId":361413,"corporation":false,"usgs":false,"family":"Maddock","given":"Ian","affiliations":[],"preferred":false,"id":948789,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Dixon, Mark D.","contributorId":361403,"corporation":false,"usgs":false,"family":"Dixon","given":"Mark","middleInitial":"D.","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":948753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, W. Carter","contributorId":361404,"corporation":false,"usgs":false,"family":"Johnson","given":"W.","middleInitial":"Carter","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":948754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":216869,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":948755,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270435,"text":"ofr20251041 - 2025 - Collaborative drought science planning in the Colorado River Basin","interactions":[],"lastModifiedDate":"2026-02-03T15:11:15.87049","indexId":"ofr20251041","displayToPublicDate":"2025-08-20T14:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1041","displayTitle":"Collaborative Drought Science Planning in the Colorado River Basin","title":"Collaborative drought science planning in the Colorado River Basin","docAbstract":"The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20251041","usgsCitation":"Anderson, P.J., Godaire, J.E., Jones, D.K., Andrews, W.J., Torregrosa, A.A., Bell, M.T., Holloway, J.M., Blakowski, M.A., Hevesi, J.A., and Qi, S.L., 2025, Collaborative drought science planning in the Colorado River Basin: U.S. Geological Survey Open-File Report 2025–1041, 32 p., https://doi.org/10.3133/ofr20251041.","productDescription":"vi, 32 p.","onlineOnly":"Y","ipdsId":"IP-165607","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":494357,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1041/ofr20251041.xml"},{"id":494378,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251041/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1041"},{"id":494325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1041/ofr20251041.pdf","text":"Report","size":"9.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1041"},{"id":494356,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1041/images"},{"id":494324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1041/coverthb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.23441985470737,\n 42.42360949558767\n ],\n [\n -110.0074572875208,\n 42.9273485741041\n ],\n [\n -110.88201818257588,\n 40.83215412591818\n ],\n [\n -112.09041488325958,\n 37.81270064609009\n ],\n [\n -113.86864235906498,\n 37.77076755792572\n ],\n [\n -113.94586057217214,\n 38.21912009189296\n ],\n [\n -115.10119317735365,\n 39.08121928179544\n ],\n [\n -115.47544949784407,\n 35.429353160164375\n ],\n [\n -115.29249888241867,\n 31.986896837542588\n ],\n [\n -110.42076682180414,\n 30.172954165166573\n ],\n [\n -108.95437388160886,\n 30.991312421045535\n ],\n [\n -108.56364522256465,\n 31.857948821439074\n ],\n [\n -107.84802514114666,\n 32.26017852956302\n ],\n [\n -107.22575341999277,\n 34.155285973008596\n ],\n [\n -107.68523996280838,\n 35.482296714195456\n ],\n [\n -106.46728549757393,\n 37.071939542790304\n ],\n [\n -105.6885671199549,\n 39.88037502712785\n ],\n [\n -106.23441985470737,\n 42.42360949558767\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The Ili River Basin is characterized by complex topography and diverse climatic zones with limited in situ observations. This study evaluates the performance of six widely used precipitation datasets, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), ERA5_Land (European Centre for Medium-Range Weather Forecasts—ECMWF Reanalysis 5_Land), GPCC (Global Precipitation Climatology Centre), IMERG (Integrated Multi-satellite Retrievals for GPM), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and TerraClimate, against ground-based data from 2001 to 2023. The evaluation is conducted across multiple spatial scales and temporal resolutions. At the basin scale, most datasets exhibit strong correlations with in situ observations across all temporal scales (r > 0.7), except for PERSIANN, which demonstrates a relatively weaker performance during summer and winter (r < 0.6). All datasets except ERA5_ Land show low annual and monthly bias (<5%), although larger errors are observed during summer, particularly for IMERG and PERSIANN. Dataset performance generally declines with increasing elevation. Basin-wide gridded evaluations reveal distinct spatial variations across all elevation zones, with CHIRPS showing the strongest ability to capture orographic precipitation gradients throughout the basin. All datasets correctly identified 2008 as a drought year and 2016 as a wet year, even though the magnitude and spatial resolution of the anomalies varied among them. These findings highlight the importance of selecting precipitation datasets that are suited to the complex topographic and climatic characteristics of transboundary basins. Our study provides valuable insights for improving hydrological modeling and can be used for water sustainability and flood–drought mitigation support activities in the Ili River Basin.
","language":"English","publisher":"MDPI","doi":"10.3390/su17167418","usgsCitation":"Duisebek, B., Senay, G., Ojima, D.S., Zhang, T., Sagin, J., and Wang, X., 2025, Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan: Sustainability, v. 17, no. 16, 7418, 26 p., https://doi.org/10.3390/su17167418.","productDescription":"7418, 26 p.","ipdsId":"IP-181853","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":495056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su17167418","text":"Publisher Index Page"},{"id":494743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Kazakhstan","otherGeospatial":"Ili River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 46.71910209135149,\n 50.09770097338648\n ],\n [\n 46.71910209135149,\n 44.15010644271524\n ],\n [\n 84.48446379774907,\n 44.15010644271524\n ],\n [\n 84.48446379774907,\n 50.09770097338648\n ],\n [\n 46.71910209135149,\n 50.09770097338648\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"16","noUsgsAuthors":false,"publicationDate":"2025-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Duisebek, Baktybek","contributorId":360498,"corporation":false,"usgs":false,"family":"Duisebek","given":"Baktybek","affiliations":[{"id":86016,"text":"Kazakh British Technical University","active":true,"usgs":false}],"preferred":false,"id":947122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":947123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ojima, Dennis S.","contributorId":208511,"corporation":false,"usgs":false,"family":"Ojima","given":"Dennis","email":"","middleInitial":"S.","affiliations":[{"id":37812,"text":"Colorado State University; North Central Climate Science Center","active":true,"usgs":false}],"preferred":false,"id":947124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Tibin","contributorId":360499,"corporation":false,"usgs":false,"family":"Zhang","given":"Tibin","affiliations":[{"id":86019,"text":"State Key Laboratory of Soil and Water Conservation Science and Engineering, Northwest A&F University","active":true,"usgs":false}],"preferred":false,"id":947125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sagin, Janay","contributorId":360500,"corporation":false,"usgs":false,"family":"Sagin","given":"Janay","affiliations":[{"id":86016,"text":"Kazakh British Technical University","active":true,"usgs":false}],"preferred":false,"id":947126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xuejiao","contributorId":271179,"corporation":false,"usgs":false,"family":"Wang","given":"Xuejiao","email":"","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":947127,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271317,"text":"70271317 - 2025 - Evapotranspiration terminology and definitions","interactions":[],"lastModifiedDate":"2026-02-10T13:40:04.779874","indexId":"70271317","displayToPublicDate":"2025-08-15T08:12:55","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22342,"text":"Irrigation and Drainage Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Evapotranspiration terminology and definitions","docAbstract":"Evapotranspiration (ET), the combined process of evaporation from soil and plant surfaces and transpiration from plant tissue, plays a pivotal role in the global water and energy balance. Accurately quantifying ET at various spatial scales is important for diverse applications, including irrigation and natural resource management. While efforts to standardize ET methodology have progressed over the last few decades, some confusion and disagreements in terminology persist among communities of researchers and practitioners involved in the measurement, estimation, and simulation of ET. This technical note addresses the historical evolution and standardization of ET terminology, aiming to reduce and mitigate disparities in definitions and usage by advocating for standardized definitions and emphasizing the adoption of reference ET (ETref) terminology to promote consistency and accuracy and to avoid ambiguity. This document provides comprehensive definitions of key terms, including crop (i.e., vegetation cover) coefficients, consumptive use (CU), actual crop evapotranspiration (ETa), and ETref variants for short (grass, ETo) and tall (alfalfa, ETr) reference crops. Practical discussion on several relevant topics is given: (1) single and dual crop coefficient approaches, (2) applications to nonagricultural vegetation, (3) recommended subscripts for terms, (4) practical guidelines and considerations for ETref calculation, (5) encouragement to replace “potential ET” terminology with better terms, (6) clarification on maximum ET (ETmax) and maximum crop coefficient (Kc max) terms, (7) ET products derived from remote sensing, (8) a brief description of the role of ET in water rights, and (9) a figure illustrating the use of the terms defined herein. The conclusion emphasizes the importance of consistent terminology for effective communication among researchers and end-users, which will facilitate the adoption of standardized ET methods and technologies. This technical note was created by the American Society of Civil Engineers, Environmental and Water Resources Institute (ASCE-EWRI), Evapotranspiration in Irrigation and Hydrology Committee, with input and endorsement from other relevant organizations in the United States and internationally. This note serves as a comprehensive reference guide for ET practitioners and researchers.
","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/JIDEDH.IRENG-10491","usgsCitation":"DeJonge, K.C., Allen, R., Kilic, A., Thorp, K.R., Kukal, M., Marek, G., Altenhofen, J., Amatya, D., Blankenau, P., Datta, S., Grabow, G., Hashem, A., Kisekka, I., Kjaersgaard, J., Marek, T., Peters, T., Porter, D., Reba, M., Rudnick, D., Senay, G., Sharma, V., Sridhar, V., Sun, G., Taghvaeian, S., Trezza, R., and Trout, T., 2025, Evapotranspiration terminology and definitions: Irrigation and Drainage Engineering, v. 15, no. 5, 06025003, 13 p., https://doi.org/10.1061/JIDEDH.IRENG-10491.","productDescription":"06025003, 13 p.","ipdsId":"IP-174613","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":498229,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/jidedh.ireng-10491","text":"Publisher Index 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Saleh","contributorId":360953,"corporation":false,"usgs":false,"family":"Taghvaeian","given":"Saleh","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":947994,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Trezza, Ricardo","contributorId":360954,"corporation":false,"usgs":false,"family":"Trezza","given":"Ricardo","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":947995,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Trout, Thomas","contributorId":360955,"corporation":false,"usgs":false,"family":"Trout","given":"Thomas","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":947996,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70271133,"text":"70271133 - 2025 - Effects of climate on temporal variability in streamflow and salinity in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2025-08-28T15:27:40.790329","indexId":"70271133","displayToPublicDate":"2025-08-12T10:22:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate on temporal variability in streamflow and salinity in the Upper Colorado River Basin","docAbstract":"In 2021, the U.S. Geological Survey (USGS) published Circular 1490 titled, “Integrated Science for the Study of Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) in the Environment: A Strategic Science Vision for the U.S. Geological Survey” (Tokranov and others, 2021). Circular 1490 was created to be a resource for USGS scientists prioritizing and planning research related to per- and polyfluoroalkyl substances (PFAS) and to be a guide for developing partnerships with other scientists, State and Federal agencies, and stakeholders engaged in PFAS research and management and mitigation of the environmental and human-health effects of PFAS. This USGS PFAS Strategic Science Vision document was intended to be the foundation for a “living strategic vision,” periodically providing updates on the state of USGS PFAS research, emerging PFAS data gaps and needs, and progress on interagency and stakeholder PFAS partnerships and priorities. To meet this objective, the USGS planned to host an Interagency and Stakeholder PFAS Workshop every 2–3 years.
During September 10–12, 2024, the USGS hosted the first Interagency and Stakeholder PFAS Workshop in Reston, Virginia. The Workshop brought together experts from other Federal agencies (U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, Food and Drug Administration, Department of Defense [Air Force, Army]), State agencies (Washington Fish and Wildlife, Virginia Department of Transportation), and academia (Harvard University, University of Maryland) to address key challenges relating to the measurement and modeling of PFAS and the implications for environmental health. Participants engaged in in-depth discussions centered around six pivotal topics related to PFAS: (1) sampling protocols, methods and interpretation; (2) environmental sources, source apportionment, and occurrence; (3) environmental fate and transport; (4) human and wildlife exposure routes and risk; (5) bioconcentration, bioaccumulation, and biomagnification; and (6) ecotoxicology and effects. Each topic had three breakout sessions.
A recurrent theme of workshop discussions was how data on a nationwide scale for PFAS occurrence in various environmental matrices, including air, water, food crops, biota, soil, and streambed sediment could help to advance scientific understanding. Participants noted significant geospatial data gaps, particularly in the midwestern and southern United States and the Pacific Northwest. PFAS data collection tends to be more robust along the eastern seaboard and in California.
Participants stressed how enhancing the integration of large and small datasets across various agencies could help to support national scale understanding of PFAS. To address these gaps, attendees suggested leveraging datasets from Federal entities like the USGS and the U.S. Department of Defense, State agencies, and municipal utility services to develop predictive contaminant detection and transport models. Improved coordination between water quality programs and USGS research could help to facilitate access to valuable data, leading to comprehensive databases that inform PFAS point (wastewater treatment plants and landfills) and nonpoint (runoff from land, atmospheric deposition, food packaging) sources, environmental transport mechanisms, environmental detection and concentrations, potential exposure routes, and health effects on different biota, including humans. A specific request was made to develop a map demarking the depth of modern (1953 or later) groundwater, which is susceptible to surface-derived anthropogenic (that is, human-made) contamination, based on tritium-age dating. Emphasis was placed on incorporation of hydrology, groundwater flow paths, groundwater–surface water interactions, and landscape factors in predictive statistical models as a step to improve contaminant source identification and tracking.
Molecular fingerprinting approaches garnered attention as techniques to link specific PFAS mixtures detected in a sample to environmental sources and levels in biota (Dávila-Santiago and others, 2022). Integrating data from abiotic (that is, water, soil, and air) and biotic (that is, living organisms) systems identified as a research opportunity. For example, understanding the composition of soils and sediments, which include a mixture of mineral, plant, and animal components, could advance understanding of exposure pathways.
The discussions highlighted opportunities to explore and understand the potential redistribution and biotic exposures of PFAS from biosolid and wastewater treatment plant effluent land application practices, in addition to atmospheric releases and discharges from landfill and wastewater treatment plants. Participants identified research gaps surrounding how these sources may contribute to contamination and may affect surrounding ecosystems, including a better definition of anthropogenic background concentrations.
Moving forward, the collection of co-occurrence data was noted as a means to improve understanding of complex mixtures and to leverage companion modeling efforts focused on areas with high and low contamination levels to identify areas of concern and unaffected resources. Participants emphasized how centralized USGS databases and the establishment of sample-metadata archives can help to ensure that samples are preserved and accessible for future research.
In conclusion, the workshop participants identified opportunities to bridge data gaps and improve measurement techniques, modeling frameworks, databases, and communication, to enhance the understanding of PFAS and their effects on environmental and human health. Upon completion of the workshop, participants indicated an interest in developing strategic data collection, modeling, and analytical approaches to address these challenges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251044","programNote":"Environmental Health Program","usgsCitation":"Iwanowicz, D.D., Beisner, K.R., Bradley, P.M., Bright, P.R., Brown, J.B., Churchill, C.J., Gordon, S.E., Karouna, N.K., Kolpin, D.W., Lambert, R.B., Pulster, E.L., Shively, R.S., Smalling, K., Steevens, J.A., and Tokranov, A.K., 2025, Insights and strategic opportunities from the USGS 2024 Per- and Polyfluoroalkyl Substances (PFAS) Interagency Workshop—Addendum I of Circular 1490: U.S. Geological Survey Open-File Report 2025–1044, 10 p., https://doi.org/10.3133/ofr20251044.","productDescription":"iii, 10 p.","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-177608","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":493438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1044/coverthb.jpg"},{"id":493439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1044/ofr20251044.pdf","text":"Report","size":"2.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1044 PDF"},{"id":493440,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251044/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1044 HTML"},{"id":493442,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1044/images/"},{"id":493441,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1044/ofr20251044.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1044 XML"}],"contact":"Director, Ecosystems Mission Area
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Five years after the deadly and destructive 9 January 2018 Montecito debris flows (Santa Barbara County, California, USA), an atmospheric river storm on 9 January 2023 triggered widespread landsliding that affected many of the same drainages in the Santa Ynez Mountains. Using high-resolution aerial imagery, we identified >10,000 landslides over an ∼160 km2 area. Most of the landslides were shallow (<1 m in depth) translational debris slides that initiated on steep (∼40°), south-facing hillslopes, with the highest incidence of landsliding in a sandstone-dominated bedrock unit. The landslides mobilized into debris flows and delivered substantial quantities of sediment downstream, which contributed to costly infrastructure impairments. We detected order-of-magnitude differences in landslide density across the study area that could not be attributed to variations in geomorphology (topographic aspect and slope), geology (bedrock type), or hydrology (seasonal antecedent rainfall, peak hourly storm rainfall intensity, total storm rainfall), which are usually considered relevant factors for shallow landsliding. Rather, we found that vegetation regrowth following wildfire was likely a relevant factor associated with the highly variable landslide densities. Hillslopes with less and different types of vegetation regrowth after fire appear to have been more susceptible to shallow landslides. We identify a possible vegetation control on postfire landsliding, which highlights an opportunity for hypothesis testing using more advanced techniques to track the evolution of vegetation cover and vegetation type in steep shrubland environments following wildfire.
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Urban infrastructure and water management alter natural hydrological pathways in developed watersheds, which can violate assumptions of a watershed approach to ecosystem science. We focus on two aspects of urban landscapes that often create challenges to model watershed processes within and among urban areas: (1) accurate delineation of urban flow paths and (2) consistent characterisation of the urban landscape within and among cities. Here, we describe these challenges and identify how certain components of these challenges can be addressed, highlighting examples and lessons learned in a project that is assessing scales and drivers of variability in dissolved organic carbon across five urban centres in the United States. Our goal is to facilitate a dialogue that will advance the applications of watershed approaches in urban ecosystem science by recognising and addressing these challenges. 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B.","contributorId":272085,"corporation":false,"usgs":false,"family":"Fisher","given":"J.","email":"","middleInitial":"B.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":945670,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ruhoff, Anderson","contributorId":269919,"corporation":false,"usgs":false,"family":"Ruhoff","given":"Anderson","email":"","affiliations":[{"id":56044,"text":"Universidade Federal do Rio Grande do Sul","active":true,"usgs":false}],"preferred":false,"id":945671,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Purdy, A.J.","contributorId":333376,"corporation":false,"usgs":false,"family":"Purdy","given":"A.J.","email":"","affiliations":[{"id":79854,"text":"NASA Ames Research Center Cooperative for Research in Earth Science and Technology, California State University Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":945672,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Huntington, J.","contributorId":192453,"corporation":false,"usgs":false,"family":"Huntington","given":"J.","email":"","affiliations":[],"preferred":false,"id":945673,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70272679,"text":"70272679 - 2025 - Quantitative subsurface characterization illuminates the origin of the Quaternary Mississippi River Valley alluvial aquifer","interactions":[],"lastModifiedDate":"2025-12-04T15:56:36.025068","indexId":"70272679","displayToPublicDate":"2025-08-08T09:48:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17089,"text":"Communications Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative subsurface characterization illuminates the origin of the Quaternary Mississippi River Valley alluvial aquifer","docAbstract":"The Mississippi River Valley alluvial aquifer (MRVA) is vital to U.S. food security and global agricultural supply. However, quantitative understanding of its Quaternary origin, architecture, and hydrologic function remains incomplete. Here we develop a three-dimensional hydrostratigraphic model to characterize the deposition of clay and silt, fine-medium sands, and graveliferous sands using lithologic data from 75,000 boreholes compiled across the Lower Mississippi Valley and a geostatistical method—interval kriging. We find that cyclic glacial entrenchments, evidenced by remnants of pre-Wisconsinan postglacial sediments, alongside geodynamic activities shaped the MRVA basal configuration. Stratal weakening from faulting and salt diapirism enhanced glacial incision and thereby produced abrupt aquifer thickening. We demarcate the top of graveliferous sands as the regional marker of the Pleistocene-Holocene transition. The MRVA hydrostratigraphy reveals hydrologic function and geologic controls on groundwater storage and quality, advancing the assessment of aquifer sustainability under a changing climate, with implications for alluvial aquifers globally.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-025-02545-1","usgsCitation":"Song, Y., Tsai, F.T., Minsley, B.J., Wu, C., and Heggy, E., 2025, Quantitative subsurface characterization illuminates the origin of the Quaternary Mississippi River Valley alluvial aquifer: Communications Earth and Environment, v. 6, 646, 16 p., https://doi.org/10.1038/s43247-025-02545-1.","productDescription":"646, 16 p.","ipdsId":"IP-172339","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497110,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-025-02545-1","text":"Publisher Index Page"},{"id":497056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi River Valley alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94,\n 38\n ],\n [\n -94,\n 28.5\n ],\n [\n -88,\n 28.5\n ],\n [\n -88,\n 38\n ],\n [\n -94,\n 38\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2025-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Song, Yuqi","contributorId":363220,"corporation":false,"usgs":false,"family":"Song","given":"Yuqi","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":951315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tsai, Frank T.-C.","contributorId":305938,"corporation":false,"usgs":false,"family":"Tsai","given":"Frank","email":"","middleInitial":"T.-C.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":951316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Chenliang","contributorId":363221,"corporation":false,"usgs":false,"family":"Wu","given":"Chenliang","affiliations":[{"id":13500,"text":"Tulane University","active":true,"usgs":false}],"preferred":false,"id":951318,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heggy, Essem","contributorId":363223,"corporation":false,"usgs":false,"family":"Heggy","given":"Essem","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":951319,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269892,"text":"sir20255066 - 2025 - Simulated hydrologic responses to proposed wastewater-returnflow scenarios in Falmouth, Massachusetts","interactions":[],"lastModifiedDate":"2026-04-01T14:28:13.392829","indexId":"sir20255066","displayToPublicDate":"2025-08-08T08:55:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5066","displayTitle":"Simulated Hydrologic Responses to Proposed Wastewater-Return-Flow Scenarios in Falmouth, Massachusetts","title":"Simulated hydrologic responses to proposed wastewater-returnflow scenarios in Falmouth, Massachusetts","docAbstract":"The Cape Cod aquifer is the sole source of drinking water for communities on Cape Cod, Massachusetts, including the Town of Falmouth, where the aquifer is currently threatened by contamination from septic-system-derived nitrogen. To address this problem, the Town is proposing to sewer areas of Falmouth, treat the wastewater at the Town’s Main Wastewater Treatment Facility (a nitrogen removing/tertiary treatment facility), and discharge the treated wastewater to an ocean outfall pipe in Nantucket Sound.
The U.S. Geological Survey, in cooperation with the Town of Falmouth, updated a three-dimensional steady-state groundwater flow model to represent current (defined as 2019–23) average hydrologic conditions and to simulate the long-term average freshwater hydrologic response to two wastewater-return-flow scenarios. Scenario 1 involves the sewering of all properties south of Route 28 in Falmouth, which approximates the Town’s possible sewer expansion over the next 20–30 years. Scenario 2 involves sewering of all properties in Falmouth to demonstrate the maximum potential effect of sewering on the aquifer.
Overall, the simulated hydrologic response of water-table altitudes and streamflow in both scenarios was relatively small compared to fluctuations from natural recharge. In scenario 1, the water-table altitude decreased by about 0.1 feet south of Route 28, where the conversion to municipal sewers removed wastewater-return flow from onsite septic systems. The water-table altitude decreased by about 0.1–0.2 feet over a larger area in Falmouth under town-wide sewering in scenario 2. The greatest decrease in water-table altitude in both scenarios occurred near the Main Wastewater Treatment Facility, with a decrease of about 1.1 feet in scenario 1 and about 1.3 feet in scenario 2.
Simulated decreases in streamflow also were estimated for six selected streams in Falmouth and Mashpee. In both scenarios, the largest simulated decreases in streamflow were at the Coonamessett River, which is the closest stream to the Main Wastewater Treatment Facility. In scenario 1, the average annual decrease in flow at the Coonamessett River was 0.1 cubic feet per second, a 1.1 percent decrease from current (2019–23) conditions. In scenario 2, streamflow at the Coonamessett River decreased by 0.6 cubic feet per second, a 5.4 percent decrease from current (2019–23) conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255066","collaboration":"Prepared in cooperation with the Town of Falmouth","usgsCitation":"Goldstein, K.M.F., and McCobb, T.D., 2025, Simulated hydrologic responses to proposed wastewater-returnflow scenarios in Falmouth, Massachusetts (ver. 1.1, 2026): U.S. Geological Survey Scientific Investigations Report 2025–5066, 19 p., https://doi.org/10.3133/sir20255066.","productDescription":"Report: vii, 19 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-172502","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501695,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5066/versionHist.txt","size":"694 B","linkFileType":{"id":2,"text":"txt"}},{"id":493661,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1O3SSE5","text":"USGS data release","linkHelpText":"MODFLOW-2005 groundwater flow model used to simulate wastewater-return-flow scenarios in Falmouth, Massachusetts"},{"id":493660,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5066/images/"},{"id":493659,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5066/sir20255066.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5066 XML"},{"id":493658,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5066 HTML"},{"id":493657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5066/sir20255066.pdf","text":"Report","size":"4.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5066 PDF"},{"id":493656,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5066/coverthb2.jpg"}],"country":"United States","state":"Massachusetts","city":"Falmouth","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.69386874698256,\n 41.790542081897485\n ],\n [\n -70.69386874698256,\n 41.50620936893142\n ],\n [\n -70.2313991423423,\n 41.50620936893142\n ],\n [\n -70.2313991423423,\n 41.790542081897485\n ],\n [\n -70.69386874698256,\n 41.790542081897485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: August 8, 2025; Version 1.1: April 1, 2026","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Water level drawdowns are common in reservoirs and can affect dissolved oxygen (DO) dynamics via several pathways. In large storage reservoirs, inflow deltas are often important sites for sediment deposition, with some sediment laden rivers forming highly dynamic delta regions as they enter the reservoir. As water levels change, deposited sediment may be remobilized and affect pelagic DO dynamics. Here, we analyze a long-term set of DO profiles to ask how water levels have interacted with both reservoir age and spring inflow volumes to affect metalimnion low DO events in Lake Powell, desert Southwest, USA. The most supported model suggests that declining water levels interact with reservoir age, such that an older and lower elevation reservoir leads to more metalimnion DO consumption, with larger spring snowmelt inflows furthering DO declines. We also conducted incubations to understand how sediment source, monsoon inputs, and water temperature affect DO demand and nutrient cycling. Incubation oxygen demand varied significantly by sediment source, exhibiting modest temperature dependence at the nonmonsoonal sites. We observed the highest oxygen demand from monsoonal inputs and substantial phosphorus release from 2 of 3 sediment types. Our findings emphasize how reservoir aging and hydrological dynamics can combine to reduce DO availability.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20442041.2025.2476309","usgsCitation":"Deemer, B., Andrews, C.M., Reibold, R.H., Mihalevich, B.A., Sabol, T.A., Drewel, J., and Yackulic, C., 2025, Low water levels interact with reservoir aging to increase the severity of summertime metalimnion dissolved oxygen minima in Lake Powell, desert Southwest, USA: Inland Waters, v. 15, no. 1, 2476309, 16 p., https://doi.org/10.1080/20442041.2025.2476309.","productDescription":"2476309, 16 p.","ipdsId":"IP-169658","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Lake Powell","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.11073805318645,\n 37.26333469404298\n ],\n [\n -111.74162726575902,\n 36.997266633380335\n ],\n [\n -111.35931664510963,\n 36.87613235542568\n ],\n [\n -110.32254234263192,\n 37.24143878879368\n ],\n [\n -110.31017219601101,\n 37.95477774275503\n ],\n [\n -111.11073805318645,\n 37.26333469404298\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, Caitlin M.","contributorId":361011,"corporation":false,"usgs":false,"family":"Andrews","given":"Caitlin","middleInitial":"M.","affiliations":[{"id":86147,"text":"National Park Service, Southern Florida and Caribbean Network, Flagstaff AZ","active":true,"usgs":false}],"preferred":false,"id":948108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reibold, Robin H. 0000-0002-3323-487X","orcid":"https://orcid.org/0000-0002-3323-487X","contributorId":207499,"corporation":false,"usgs":true,"family":"Reibold","given":"Robin","email":"","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mihalevich, Bryce A.","contributorId":361012,"corporation":false,"usgs":false,"family":"Mihalevich","given":"Bryce","middleInitial":"A.","affiliations":[{"id":86149,"text":"Bureau of Reclamation, Upper Colorado Basin, Salt Lake City UT","active":true,"usgs":false}],"preferred":false,"id":948110,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sabol, Thomas A. 0000-0002-4299-2285 tsabol@usgs.gov","orcid":"https://orcid.org/0000-0002-4299-2285","contributorId":3403,"corporation":false,"usgs":true,"family":"Sabol","given":"Thomas","email":"tsabol@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drewel, Jeremiah","contributorId":361013,"corporation":false,"usgs":false,"family":"Drewel","given":"Jeremiah","affiliations":[{"id":86150,"text":"Oregon Water Science Center, U.S. Geological Survey, Klamath Falls OR","active":true,"usgs":false}],"preferred":false,"id":948112,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948113,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}