Designing aquatic nest boxes is rarely afforded detailed scientific account. Here we provide some historical context for nest boxes used in production of large-bodied fishes of the Australian freshwater cod genus Maccullochella. Our experience with eastern freshwater cod is used as a case study to: (a) convey aspects of the complexity of the nest box design process and to (b) demonstrate the importance of visual literacy in project communication across the variety of contributors to the eco-design process. Specifically, we describe a new, two-variant, triangular nest box design for application in rivers and modifications to a standard stainless steel nest box for hatchery-pond-based spawning of eastern freshwater cod M. ikei. We designed the boxes to test adult preference for single versus double entrance/exits to cavities in hatchery and field environments. An important consideration specific to hatchery production is harvesting demersal, adhesive eggs prior to hatching to minimise fungal infection of eggs and physical loss of larvae, in addition to providing critical first feeding of larvae. In contrast, field nest box design incorporated multiple factors and associated trade-offs related to both internal and external design, ranging from manufacturer capability, material types, cost, transportability, hydrological performance, biodegradability, retrievability, as well as biological and ecological function. Only preliminary findings from field nest box deployments are provided here, and we focus primarily on elements of visual language in the form of conceptual drawings, sketches and final schematics which have been central to our process. We emphasise the benefit of harnessing input from multiple fields of expertise and documenting and testing designs of nest boxes for cavity nesting fishes, under both controlled hatchery and more complex field conditions.
","language":"English","publisher":"Wiley","doi":"10.1002/aff2.70095","usgsCitation":"Ebner, B.C., Morris, S.S., St Vincent Welch, J., Ryan, P.C., Turner, M., Cameron, L.M., Poitras, N., Coonrod, B., Welsh, S.A., McLellan, M., Jess, L., Vidler, S., Ingram, B.A., Thurstan, S., Rowland, S.J., Blake, S., and Butler, G.L., 2025, Blueprints for riverine cod nest boxes draw from multiple design considerations: Aquaculture, Fish and Fisheries, v. 5, no. 4, e70095, 13 p., https://doi.org/10.1002/aff2.70095.","productDescription":"e70095, 13 p.","ipdsId":"IP-166252","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aff2.70095","text":"Publisher Index 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However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address this issue, we propose a novel approach: the water balance equivalence (WABE) method, which generates spatially continuous WBET for correcting biases in RSET products. The WABE method computes synthetic WBET by integrating observed WBET and flux tower-derived FLUXCOM ET, which fills the spatial gaps of observed WBET and generates a spatially continuous WBET dataset. Synthetic WBET (2002–2015 annual average) of eight-digit hydrologic unit code (HUC8) basins across the conterminous United States (CONUS), constituting 44 % (887 out of 2035 basins) of CONUS basins, was determined within 2.0 % (RMSE = 12 %) of observed WBET at CONUS and between 1–12 % (RMSE = 3–33 %) across 18 regions in CONUS. With WABE-based bias corrections, the overall annual bias of RSET decreased from 10 % (RMSE = 34 %) to 6 % (RMSE = 26 %) across 37 flux tower sites. The WABE method offers a new approach for RSET accuracy improvement and shows great promise for large area implementations with a potential to yield substantial benefits for building accurate basin water budgets and water management decisions.
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An operational ETa using the Visible Infrared Imaging Radiometer Suite (VIIRS) and global weather datasets was developed through the Simplified Surface Energy Balance Model (SSEBop) model. An operational framework is established with the Famine Early Warning System Network (https://earlywarning.usgs.gov/fews) to generate and update global 1 km ETa at dekadal (∼10 day), monthly, and yearly time scales since February 2012. Modeled ETa at monthly and annual time scales was evaluated using 67 eddy covariance (EC) flux tower stations around the world and water balance-based ETa based on 810 United States eight-digit Hydrologic Unit Code (HUC8) and 18 Global Runoff Data Center (GRDC) basins. The correlation coefficient (r=0.68–0.94) shows relatively strong and consistent performance across the three datasets, capturing the spatiotemporal variability in HUC8 and GRDC basins and EC tower sites reliably. The bias (3%–15%) and root mean square error (RMSE: 13%–34%) showed relatively large errors and high variability among the three datasets. The evaluation results indicate the usefulness of the VIIRS ETa for drought monitoring and early warning applications without further adjustments, while bias-correction and calibration procedures may be required before using the VIIRS ETa data for localized water budget assessments. Availability of gridded actual ETa data from a combination of flux towers and basin-scale ETa is desired to establish bias-correction procedures to improve the absolute accuracy of remote-sensing ETa such as the SSEBop VIIRS operational products.
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Understanding how soil moisture is spatially distributed in desert shrublands provides valuable insights into how shrubs use and impact limiting water resources, and how shrublands may respond to future meteorological and climate change. Our goals were to determine how soil moisture is partitioned between soil volumes under canopies and in the bare soil interspaces across multiple desert shrublands, and to evaluate the roles of physical soil properties, shrub-type characteristics, meteorology, and measurement resolution in influencing and observing variation in soil moisture partitioning. Utilizing two long-term soil moisture datasets (monthly resolution, 30 years, whole soil profile measurements; and 30 min resolution, 10 years, 10–30 cm measurements), we compared soil moisture partitioning across nine northern Chihuahuan Desert shrubland sites (three sites dominated by creosotebush [Larrea tridentata], three by honey mesquite [Prosopis glandulosa], and three by tarbush [Flourensia cernua]) in the Jornada Basin, southern New Mexico, USA. Over 30 years, monthly, whole profile data showed that soil moisture in mesquite shrublands was consistently higher in bare soil interspaces compared to under canopies, whereas soil moisture under and between shrubs was more similar in creosotebush and tarbush shrublands. Physical soil properties were linked as explanatory variables of long-term soil moisture partitioning (monthly whole profile dataset), whereas 30-minute data showed that shorter-term periods of higher precipitation promoted greater near surface soil moisture (10–30 cm) in bare soil interspaces that was not captured at monthly time steps. Thus, although the long-term average partitioning of soil moisture in these shrublands is strongly controlled by soil physical properties, soil moisture partitioning varies at shorter timescales (daily to weekly) in response to precipitation events. Moreover, shrub-type characteristics influenced soil moisture partitioning, with dense and tall mesquite shrubs having lower under canopy soil moisture than tarbush, and root architecture potentially influencing partitioning across creosotebush sites. 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Agency","active":true,"usgs":false}],"preferred":false,"id":942337,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Jay R.","contributorId":238115,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","middleInitial":"R.","affiliations":[],"preferred":false,"id":942338,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keenan, William 0009-0007-4686-1796","orcid":"https://orcid.org/0009-0007-4686-1796","contributorId":357723,"corporation":false,"usgs":true,"family":"Keenan","given":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":942339,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dolan, Wayana 0000-0001-8405-4302","orcid":"https://orcid.org/0000-0001-8405-4302","contributorId":354442,"corporation":false,"usgs":true,"family":"Dolan","given":"Wayana","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":942340,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273905,"text":"70273905 - 2025 - Contaminated stormwater sediment source tracking for polychlorinated biphenyls in an urban watershed of the Chesapeake Bay, United States","interactions":[],"lastModifiedDate":"2026-02-13T15:35:19.238788","indexId":"70273905","displayToPublicDate":"2025-07-03T08:26:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Contaminated stormwater sediment source tracking for polychlorinated biphenyls in an urban watershed of the Chesapeake Bay, United States","docAbstract":"Fine-grained sediment in stormwater acts as a vector for persistent organic pollutants, like polychlorinated biphenyls (PCBs), through mobilization from sources within drainage areas of impacted urban watersheds. This study implemented a novel approach to identify the relative contributions of various landscape and stream sources of sediment from the Back River watershed in eastern Baltimore, Maryland, and investigated the applicability of using trace PCBs found in an urban environment as discriminants between each source type. Trace PCBs were found to be poor discriminants when identifying the relative sediment contributions of watershed-scale land use categories. When excluding PCBs in the development of a sediment fingerprinting model and instead utilizing trace elements and carbon only, sediment fingerprint modeling successfully differentiated green spaces and eroding streambanks as the most significant contributors to stormwaters sediment (37.1 % and 44.0 %, respectively) of the total sediment contributions of all considered source categories. In all samples collected from various landscape sources, storms, and cores detectable concentrations of PCBs were measured. The results of this study indicate that sediment fingerprinting may not be an effective method in predicting where PCBs may be found within an impacted watershed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2025.104657","usgsCitation":"Foss, E.P., Clifton, Z.J., Majcher, E.H., Needham, T.P., and Psoras, A.W., 2025, Contaminated stormwater sediment source tracking for polychlorinated biphenyls in an urban watershed of the Chesapeake Bay, United States: Journal of Contaminant Hydrology, v. 274, 104657, 16 p., https://doi.org/10.1016/j.jconhyd.2025.104657.","productDescription":"104657, 16 p.","ipdsId":"IP-177312","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":500086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","city":"Baltimore","otherGeospatial":"Back River watershed, Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.50954075138807,\n 39.32799166380633\n ],\n [\n -76.50954075138807,\n 39.256713104432606\n ],\n [\n -76.43110757990168,\n 39.256713104432606\n ],\n [\n -76.43110757990168,\n 39.32799166380633\n ],\n [\n -76.50954075138807,\n 39.32799166380633\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"274","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Foss, Ellie P. 0000-0001-9090-4617","orcid":"https://orcid.org/0000-0001-9090-4617","contributorId":290902,"corporation":false,"usgs":true,"family":"Foss","given":"Ellie","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clifton, Zachary J. 0000-0002-8148-5454","orcid":"https://orcid.org/0000-0002-8148-5454","contributorId":220551,"corporation":false,"usgs":true,"family":"Clifton","given":"Zachary","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Majcher, Emily H. 0000-0001-7144-6809","orcid":"https://orcid.org/0000-0001-7144-6809","contributorId":203335,"corporation":false,"usgs":true,"family":"Majcher","given":"Emily","middleInitial":"H.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Needham, Trevor P. 0000-0001-9356-4216","orcid":"https://orcid.org/0000-0001-9356-4216","contributorId":245024,"corporation":false,"usgs":true,"family":"Needham","given":"Trevor","email":"","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Psoras, Andrew W. 0000-0002-1779-5079","orcid":"https://orcid.org/0000-0002-1779-5079","contributorId":347166,"corporation":false,"usgs":true,"family":"Psoras","given":"Andrew","middleInitial":"W.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955725,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270676,"text":"70270676 - 2025 - Expansion of aquatic and marsh area into once forest and agricultural area reflects changing hydrological conditions along the Upper Mississippi and Illinois rivers (1989-2020)","interactions":[],"lastModifiedDate":"2025-08-22T14:58:35.451643","indexId":"70270676","displayToPublicDate":"2025-07-02T07:52:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Expansion of aquatic and marsh area into once forest and agricultural area reflects changing hydrological conditions along the Upper Mississippi and Illinois rivers (1989-2020)","docAbstract":"We examined 30-year trends in the abundance and distribution of aquatic and floodplain vegetation, as well as human land uses in five study reaches of the Upper Mississippi River and one reach of the Illinois River using aerial photography collected in years 1989, 2000, 2010, and 2020. Permanently inundated area increased in all study reaches over the 30-year period. Increases ranged from 0.8% of study reach area in Pool 8 (73 ha) to as much as 6.5% of study reach area in Pool 13 (1,562 ha). Agricultural land use declined in the three study reaches where it was common (>35% of reach area). Agricultural declines ranged from 5.8% of reach area in Pool 26 (2,096 ha) to as much as 15.4% of reach area in the Open River reach (7,121 ha) and corresponded with a similar magnitude increase in permanently inundated area and semi-permanently inundated marsh classes. Total forest area declined in the four northern study reaches of the Upper Mississippi River. Forest loss estimates were on the order of 3.7% of study reach area in Pool 13 (905 ha), 2.1% of Pool 8 (364 ha), and 2.3% of Pool 4 (563 ha). Such losses represent 16.2%, 13.2%, and 10.9% of the total forest area in 1989 in Pools 13, 8 and 4, respectively. Permanently inundated area, wet meadow, shallow marsh vegetation, and mud were the main cover types that replaced forest cover in these reaches. In contrast to the decline in forest cover in the northern reaches, forest cover remained unchanged in the La Grange reach of the Illinois River and increased by 3.5% of study reach area (1,607 ha) in the southern Open River reach of the Mississippi River, mainly in former marsh vegetation and agricultural areas that were acquired by Federal and State agencies. The predominant changes observed across the study system (replacement of agriculture and forest area by permanently inundated area and semi-permanently inundated marsh classes) indicates that hydrological changes have been the main driver of change since 1989 throughout most of the Upper Mississippi and Illinois Rivers. Our study provides an example of changes in a regulated river system driven by regional-scale hydrological changes and local scale restoration actions, changes that could be compared against changes occurring in other large, regulated rivers across the globe.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10661-025-14185-1","usgsCitation":"De Jager, N.R., and Rohweder, J.J., 2025, Expansion of aquatic and marsh area into once forest and agricultural area reflects changing hydrological conditions along the Upper Mississippi and Illinois rivers (1989-2020): Environmental Monitoring and Assessment, v. 197, 842, 20 p., https://doi.org/10.1007/s10661-025-14185-1.","productDescription":"842, 20 p.","ipdsId":"IP-170179","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":494518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisonsin","otherGeospatial":"Illinois River, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.47033368549535,\n 45.06494692895831\n ],\n [\n -91.03762213168787,\n 41.802781990612445\n ],\n [\n -91.78448001625273,\n 39.567901677188814\n ],\n [\n -91.08461221362812,\n 39.174838868970895\n ],\n [\n -90.67917447922278,\n 39.11778055382109\n ],\n [\n -89.16995599770802,\n 41.29643131364776\n ],\n [\n -89.6835242575309,\n 41.8482923449634\n ],\n [\n -91.43075209513108,\n 45.01362944893481\n ],\n [\n -93.47033368549535,\n 45.06494692895831\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"197","noUsgsAuthors":false,"publicationDate":"2025-07-02","publicationStatus":"PW","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":946810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":946811,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70268470,"text":"sir20255035 - 2025 - Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the California Sacramento–San Joaquin Delta at the landscape scale—Comparison of four (2018, 2020, 2021, 2022) spring high-resolution mapping surveys","interactions":[],"lastModifiedDate":"2025-08-05T15:54:19.474578","indexId":"sir20255035","displayToPublicDate":"2025-07-02T07:24:08","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":"2025-5035","displayTitle":"Assessing Spatial Variability of Nutrients, Phytoplankton, and Related Water-Quality Constituents in the California Sacramento–San Joaquin Delta at the Landscape Scale: Comparison of Four (2018, 2020, 2021, 2022) Spring High-Resolution Mapping Surveys","title":"Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the California Sacramento–San Joaquin Delta at the landscape scale—Comparison of four (2018, 2020, 2021, 2022) spring high-resolution mapping surveys","docAbstract":"This report summarizes results from boat-based, high-resolution water-quality mapping surveys completed before, during, and after upgrades to the EchoWater Resource Recovery Facility (EchoWater Facility), the regional wastewater facility for the City of Sacramento and surrounding areas, near Elk Grove, California. Surveys were completed in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) in spring (May or June) 2018, 2020, 2021, and 2022. In each survey, a suite of in situ sensors were used to continuously (one measurement per second) measure water-quality conditions, nutrients, phytoplankton abundance, and species composition. In addition to in situ data collection, discrete water samples were collected about every 2 miles while underway for determination of phosphate, ammonium, and nitrate concentration. The boat stopped at about 30 locations to collect discrete samples for a suite of additional analytes, including phytoplankton enumeration. The four surveys represent snapshots in time across different phases of the EchoWater Facility Biological Nutrient Reduction (BNR) upgrade. The May 2018 survey represents conditions before the upgrade. The second survey (June 2020) represents conditions after implementation of the Nitrifying Sidestream Treatment. The third survey (May 2021) was completed immediately after the completion of the BNR upgrade and represents a transitional period, and the final survey (May 2022) represents post-upgrade conditions.
Relevant hydrologic and climatic context such as water-year type, X2 position (the distance from the Golden Gate Bridge to the point upstream where bottom salinity is 2 parts per thousand; Jassby and others, 1995), water export to import ratio, and management actions like the Delta Cross Channel gate operations are presented for each survey so they may be considered in comparisons among surveys. Differences in water-quality parameters, like turbidity, temperature, salinity, pH, and dissolved oxygen (DO) improve understanding of nutrient cycling and phytoplankton dynamics. Because the Delta is a complex system, we divided the study area into hydrologic zones to better examine general trends and obtain a broadscale view of differences among the 4 study years. Results are presented for each survey and parameter using box plots to compare the different hydrologic zones. We also present each parameter using contour maps by survey to display gradients across the system.
The most evident change to water quality in the Delta across surveys is related to the EchoWater Facility BNR upgrade, which included nitrification and denitrification processes. Through this upgrade, effluent ammonium (NH4+) concentrations were reduced by more than 95 percent (from about 2,000 micromolars [μM] to below the reporting limit of 35 μM), and nitrate (NO3−) concentrations increased from near zero to about 500 μM; therefore, the concentration of dissolved inorganic nitrogen (DIN; the sum of NH4+ and NO3−) in the effluent was reduced by about 75 percent between May 2018 and May 2022. The BNR upgrade resulted in a reduction in NH4+ concentrations in aquatic habitats immediately below the facility, designated as the “north Delta tidal transition zone” (Bergamaschi and others, 2024), from about 30 μM pre-upgrade to near zero during the 2022 spring survey, whereas effluent NO3− increased from median concentrations of about 7 μM to about 15 μM. Because of the reduced effluent nitrogen loads and variability in Sacramento River nitrogen loads from upstream sources, DIN concentrations in the north Delta tidal transition zone decreased from a median of 53.3 μM in 2018 to 35.3 μM in 2020, 20.7 μM in 2021, and 11.3 μM in 2022 during the spring surveys.
The changes in DIN concentration and form observed in the north Delta tidal transition zone after the EchoWater Facility upgrade extended downstream but were rapidly altered by hydrologic mixing, biogeochemical processes, and other nutrient source inputs. Most of the Delta indicated near-zero concentrations of NH4+ 1 year after the completion of the EchoWater Facility upgrades represented by the 2022 survey. Exceptions to this finding were observed in the San Joaquin River near Stockton and in Suisun Bay, indicating there are NH4+ inputs to these locations from other sources (for example, Stockton Regional Wastewater Control Facility and Central Contra Costs Sanitary District wastewater treatment plants or agricultural and urban runoff).
Although there was an increase in NO3− concentrations in the north Delta tidal transition zone after the upgrade, increases in NO3− in other zones were not apparent, presumably because nitrification of effluent derived ammonium was no longer a source of NO3−. Concentrations of DIN in many Delta zones were lower in 2022 compared to 2018 and 2020, with concentrations near or below what is considered potentially nitrogen limiting conditions for phytoplankton growth in the North Delta tidal transition zone and the Cache Slough complex channel system. Unrelated to the EchoWater Facility upgrade, NO3− and therefore DIN concentrations increased in the San Joaquin River near Stockton and in adjacent water bodies by survey date (likely associated with increasing drought conditions). The Mokelumne River had low DIN concentrations, except in 2018 when the Delta Cross Channel was open, which allowed nutrient-rich Sacramento River water to flow into this section of the river. Data from these surveys also support the hypothesis that nutrient drawdown during phytoplankton blooms may create localized nitrogen limiting conditions.
The BNR upgrade resulted in lower effluent phosphate (PO43−) concentrations, which lowered PO43− concentrations in some zones of the Delta during the four spring surveys; however, PO43− concentrations throughout the Delta remained above 0.3 μM, indicating that primary productivity was not limited by phosphorous availability. DIN and PO43− decreased after the upgrade in many areas of the Delta, and the DIN to dissolved inorganic phosphorus (DIN:DIP) ratio remained similar to pre-upgrade conditions and was often below the Redfield Ratio of 16, indicating nitrogen is more likely to limit phytoplankton growth than phosphorous. Inputs of dissolved organic carbon (DOC) from the EchoWater Facility are a minor source of this constituent to the Delta, so the upgrade had little to no effect on DOC concentrations across the Delta.
Because phytoplankton abundance and species composition in the Delta are shaped by multiple factors other than nutrients (for example, light availability, temperature, salinity, and predation), it is important to consider these factors (as well as long-term monitoring) in addition to the EchoWater Facility upgrade. Although phytoplankton populations were low across much of the Delta during the spring surveys, several localized phytoplankton blooms (defined here as greater than 15 micrograms per liter [μg/L] of chlorophyll) provide insight into conditions that may favor the growth of beneficial and harmful species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255035","collaboration":"Prepared in cooperation with the Delta Regional Monitoring Program","programNote":"Water Resources Mission Area—Water Availability and Use Science Program","usgsCitation":"Richardson, E., Kraus, T., O’Donnell, K., Soto-Perez, J., Sturgeon, C., Stumpner, E., and Bergamaschi, B., 2025, Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the California\nSacramento–San Joaquin Delta at the landscape scale—Comparison of four (2018, 2020, 2021, 2022) spring high-resolution mapping surveys: U.S. Geological Survey Scientific Investigations Report 2025–5035, 78 p.,\nhttps://doi.org/10.3133/sir20255035.","productDescription":"Report: x, 78 p.; 3 Data Releases","onlineOnly":"Y","ipdsId":"IP-151343","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":491472,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5035/images"},{"id":491473,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5035/sir20255035.XML"},{"id":491469,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FQEUAL","text":"USGS data release","description":"USGS data release","linkHelpText":"Assessing spatial variability of nutrients and related water quality constituents in the California Sacramento–San Joaquin Delta at the landscape scale—2018 High resolution mapping surveys (ver. 2.0, October 2023)"},{"id":491468,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255035/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5035"},{"id":491467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5035/sir20255035.pdf","text":"Report","size":"41.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5035"},{"id":491466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5035/coverthb.jpg"},{"id":491471,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QULEAT","text":"USGS data release","description":"USGS data release","linkHelpText":"Assessing spatial variability of nutrients, phytoplankton, and related water quality constituents in the California Sacramento–San Joaquin Delta at the landscape scale—2022 High resolution mapping surveys"},{"id":491470,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90VYUBX","text":"USGS data release","description":"USGS data release","linkHelpText":"Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the California Sacramento–San Joaquin Delta at the landscape scale—2020–2021 high-resolution mapping surveys"}],"country":"United States","state":"Callifornia","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121,\n 38.5833\n ],\n [\n -122.1667,\n 38.5833\n ],\n [\n -122.1667,\n 37.5\n ],\n [\n -121,\n 37.5\n ],\n [\n -121,\n 38.5833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Context
Montane meadows play an important hydrologic role in headwater catchments, but past land use has largely degraded their condition. Low-tech restoration methods, such as beaver dam analogs (BDAs), are increasingly used to support recovery of incised streams by promoting key geomorphic processes. However, there remains a need for studies that leverage UAS for monitoring low-tech restoration treatments in incised meadow systems.
Objectives
This study maps and characterizes geomorphic changes in two incised meadow stream channels in Red Clover Valley, CA with installed beaver dam analog structures. We used UAS-based photogrammetric surveys to track changes over a three-year period (2021–2023).
Methods
Geomorphic change was assessed using DEM differencing with error thresholding, repeat geomorphic unit (GU) classification, and Shannon Diversity Index (SHDI) to measure spatial shifts in geomorphic complexity.
Results
Geomorphic responses varied by site and survey period. The subchannel B (SCB) site exhibited net deposition, while the lower Dixie Creek (LDC) site showed net erosion. BDAs appeared to enhance geomorphic activity, particularly in LDC, where near BDA areas showed greater sediment deposition and localized erosion compared to reference sites. SHDI values were positively correlated with erosion at both sites, suggesting that erosional processes may have promoted geomorphic diversity by creating or reorganizing GU in the incised channels.
Conclusions
UAS-SfM surveys captured erosion and deposition patterns and revealed the influence of BDAs and local channel characteristics on geomorphic change and unit diversity. These findings highlight the utility of UAS methods for monitoring restoration impacts in incised montane meadow streams.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10980-025-02134-9","usgsCitation":"LeBeau, R., Villarreal, M.L., and Davis, J., 2025, UAS-based geomorphic change detection of incised montane meadow stream channels with low-tech process-based restoration treatments: Landscape Ecology, no. 40, 135, 31 p., https://doi.org/10.1007/s10980-025-02134-9.","productDescription":"135, 31 p.","ipdsId":"IP-164377","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":492064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-025-02134-9","text":"Publisher Index Page"},{"id":491822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Red Clover Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.58675993175365,\n 40.31575686885685\n ],\n [\n -121.58675993175365,\n 39.3573574299993\n ],\n [\n -119.99751644063116,\n 39.3573574299993\n ],\n [\n -119.99751644063116,\n 40.31575686885685\n ],\n [\n -121.58675993175365,\n 40.31575686885685\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"40","noUsgsAuthors":false,"publicationDate":"2025-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"LeBeau, Raymond 0009-0005-1520-5249","orcid":"https://orcid.org/0009-0005-1520-5249","contributorId":350819,"corporation":false,"usgs":true,"family":"LeBeau","given":"Raymond","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":942238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"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":942239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Jerry D.","contributorId":357700,"corporation":false,"usgs":false,"family":"Davis","given":"Jerry D.","affiliations":[{"id":32962,"text":"SFSU","active":true,"usgs":false}],"preferred":false,"id":942240,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70268753,"text":"70268753 - 2025 - Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions","interactions":[],"lastModifiedDate":"2025-07-08T16:36:55.393587","indexId":"70268753","displayToPublicDate":"2025-07-01T09:29:50","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":"Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions","docAbstract":"Study region: Headwaters of the upper Colorado River basin (UCOL), USA
Study focus: Surface-water and groundwater numerical models incorporating water-use information were used to investigate changes in climate, water use, and simulated hydrologic responses of snow processes, evapotranspiration, groundwater, and streamflow during recent wet (1982–1999) and drought (2000–2022) periods in the headwater subregions of the upper Colorado River basin.
New hydrologic insights for the region: Decreases in average streamflow between wet and drought periods ranged from 20 % in the Colorado River headwaters subregion to 23 % in the Gunnison River headwaters subregion. Like streamflow, average surface runoff was statistically less during the drought than the wet period, with decreases from 24–31 % in the headwaters. On a volume basis, runoff decreases were greater than streamflow decreases in both the Colorado River and Gunnison River headwaters. Although the amount of water-year groundwater discharge to streams remained nearly the same between the wet and drought periods, groundwater as a percentage of streamflow increased between the wet and drought periods, highlighting the importance of groundwater in sustaining streamflow during drought conditions. Multiple linear regression analyses revealed that snowmelt-only models were better than the best precipitation and temperature models at explaining streamflow variability from all headwater subregions for both the wet and drought periods.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2025.102554","usgsCitation":"Tillman, F.D., Masbruch, M.D., Knight, J., Engott, J.A., Lopez, S.F., Jones, C.J., Dickinson, J.E., and Miller, M., 2025, Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions: Journal of Hydrology: Regional Studies, v. 60, 102554, 19 p., https://doi.org/10.1016/j.ejrh.2025.102554.","productDescription":"102554, 19 p.","ipdsId":"IP-176624","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":492063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2025.102554","text":"Publisher Index Page"},{"id":491819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"upper Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.83855791620346,\n 42.22226218528715\n ],\n [\n -110.83855791620346,\n 35.70206223466056\n ],\n [\n -106.7875698491801,\n 35.70206223466056\n ],\n [\n -106.7875698491801,\n 42.22226218528715\n ],\n [\n -110.83855791620346,\n 42.22226218528715\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Jacob E. 0000-0003-0271-9011","orcid":"https://orcid.org/0000-0003-0271-9011","contributorId":204140,"corporation":false,"usgs":true,"family":"Knight","given":"Jacob E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Samuel Francisco 0000-0002-3544-7465","orcid":"https://orcid.org/0000-0002-3544-7465","contributorId":344607,"corporation":false,"usgs":true,"family":"Lopez","given":"Samuel","email":"","middleInitial":"Francisco","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Casey J.R. 0000-0002-6991-8026","orcid":"https://orcid.org/0000-0002-6991-8026","contributorId":223364,"corporation":false,"usgs":true,"family":"Jones","given":"Casey","email":"","middleInitial":"J.R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":941866,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":941867,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70268726,"text":"70268726 - 2025 - Quantifying the success of stormwater control measure networks using effective imperviousness","interactions":[],"lastModifiedDate":"2025-07-08T18:02:59.896773","indexId":"70268726","displayToPublicDate":"2025-06-30T11:00:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11111,"text":"PLOS Water","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the success of stormwater control measure networks using effective imperviousness","docAbstract":"The deleterious effects of directly-connected impervious surfaces on urban streams have been widely recognized. To deal with these effects, the use of stormwater control measures that aim to disconnect impervious surfaces and prevent stormwater from reaching the stream has surged. However, we lack widespread use of consistent metrics that describe how effective these stormwater control measures are for mitigating the effects of untreated stormwater. Using total impervious area neglects the effect of stormwater control measures whereas directly-connected impervious area assumes that stormwater control measures perform perfectly. Comparing the success of stormwater control measures across many watersheds and cities will require use of consistent metrics of effective imperviousness, describing actual performance of stormwater control measures in reducing impervious areas hydraulically connected to the stream. This work applies two published approaches to quantify effective imperviousness, one that measures the frequency of downstream flow disturbances and another that computes parameters from a paired rainfall-runoff regression analysis. We apply these approaches in two settings: 1) two watersheds with new low impact development in Clarksburg, Maryland, USA and 2) five watersheds with stormwater retrofits in Melbourne, Australia. These methods gave largely similar results, with differences in effective imperviousness ranging from 1%-9%. Using these approaches in Clarksburg, the effective imperviousness for the treatment watersheds was 6–12%, whereas the total imperviousness was 33–44% and the directly-connected imperviousness was 0%. In Clarksburg, effective imperviousness better described stream hydrologic and biotic outcomes compared to either total imperviousness or directly-connected imperviousness. In Melbourne, effective imperviousness was a better metric for hydrologic and water quality changes that are likely to provide ecological benefits. In both cases, new development and retrofits, we demonstrate the utility of effective imperviousness metrics for predicting stream outcomes and how these metrics may be used to understand the success of stormwater control measure using a consistent metric.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pwat.0000335","usgsCitation":"Bhaskar, A.S., Stillwell, C.C., Burns, M.J., Hopkins, K.G., and Walsh, C.J., 2025, Quantifying the success of stormwater control measure networks using effective imperviousness: PLOS Water, v. 4, no. 6, e0000335, 18 p., https://doi.org/10.1371/journal.pwat.0000335.","productDescription":"e0000335, 18 p.","ipdsId":"IP-171981","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":492076,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000335","text":"Publisher Index Page"},{"id":491849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Bhaskar, Aditi S.","contributorId":199824,"corporation":false,"usgs":false,"family":"Bhaskar","given":"Aditi","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":941752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stillwell, Charles C. 0000-0002-4571-4897","orcid":"https://orcid.org/0000-0002-4571-4897","contributorId":270394,"corporation":false,"usgs":true,"family":"Stillwell","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Matthew J.","contributorId":146251,"corporation":false,"usgs":false,"family":"Burns","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":16645,"text":"Waterway Ecosystem Research Group, School of Ecosystem and Forest Sciences, The","active":true,"usgs":false}],"preferred":false,"id":941754,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":941755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Christopher J.","contributorId":171683,"corporation":false,"usgs":false,"family":"Walsh","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":941756,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268695,"text":"70268695 - 2025 - Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization","interactions":[],"lastModifiedDate":"2025-07-08T15:40:36.038242","indexId":"70268695","displayToPublicDate":"2025-06-27T10:36:46","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":"Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization","docAbstract":"Seawater intrusion (SWI) affects coastal landscapes worldwide. Here we describe the hydrologic pathways through which SWI occurs - over land via storm surge or tidal flooding, under land via groundwater transport, and through watersheds via natural and artificial surface water channels—and how human modifications to those pathways alter patterns of SWI. We present an approach to advance understanding of spatiotemporal patterns of salinization that integrates these hydrologic pathways, their interactions, and how humans modify them. We use examples across the East Coast of the United States that exemplify mechanisms of salinization that have been reported around the planet to illustrate how hydrologic connectivity and human modifications alter patterns of SWI. Finally, we suggest a path for advancing SWI science that includes (a) deploying standardized and well-distributed sensor networks at local to global scales that intentionally track SWI fronts, (b) employing remote sensing and geospatial imaging techniques targeted at integrating above and belowground patterns of SWI, and (c) continuing to develop data analysis and model-data fusion techniques to measure the extent, understand the effects, and predict the future of coastal salinization.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR038720","usgsCitation":"Helton, A., Dennedy-Frank, J., Emanuel, R., Neubauer, S.C., Adams, K., Ardon, M., Band, L., Befus, K.A., Borstlap, H., Duberstein, J., Gold, A., Kominoski John, Manda, A., Michael, H.A., Moysey, S., Myers-Pigg, A., Neville, J.A., Noe, G.E., Panthi, J., Pezeshki, E., Sirianni, M., and Ward.Nicolas, 2025, Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization: Water Resources Research, v. 61, no. 7, e2024WR038720, 8 p., https://doi.org/10.1029/2024WR038720.","productDescription":"e2024WR038720, 8 p.","ipdsId":"IP-167925","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":492056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr038720","text":"Publisher Index Page"},{"id":491805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Helton, Ashley","contributorId":219741,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":941662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennedy-Frank, James","contributorId":357528,"corporation":false,"usgs":false,"family":"Dennedy-Frank","given":"James","affiliations":[{"id":85449,"text":"Northeastern Universtiy","active":true,"usgs":false}],"preferred":false,"id":941663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Emanuel, Ryan","contributorId":333342,"corporation":false,"usgs":false,"family":"Emanuel","given":"Ryan","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":941664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neubauer, Scott C","contributorId":169723,"corporation":false,"usgs":false,"family":"Neubauer","given":"Scott","email":"","middleInitial":"C","affiliations":[{"id":25575,"text":"Dept. of Biology, Virginia Commonwealth University, Richmond, VA","active":true,"usgs":false}],"preferred":false,"id":941665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Kyra","contributorId":357529,"corporation":false,"usgs":false,"family":"Adams","given":"Kyra","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":941666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ardon, Marcelo","contributorId":298014,"corporation":false,"usgs":false,"family":"Ardon","given":"Marcelo","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":941667,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Band, Lawrence","contributorId":174085,"corporation":false,"usgs":false,"family":"Band","given":"Lawrence","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":941668,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Befus, Kevin A.","contributorId":299488,"corporation":false,"usgs":false,"family":"Befus","given":"Kevin","email":"","middleInitial":"A.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":941669,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Borstlap, Hanne","contributorId":357530,"corporation":false,"usgs":false,"family":"Borstlap","given":"Hanne","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":941670,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duberstein, Jamie 0000-0002-2787-5515","orcid":"https://orcid.org/0000-0002-2787-5515","contributorId":332972,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie","email":"","affiliations":[],"preferred":false,"id":941671,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gold, Adam","contributorId":357531,"corporation":false,"usgs":false,"family":"Gold","given":"Adam","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":941672,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kominoski John","contributorId":357532,"corporation":false,"usgs":false,"family":"Kominoski John","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":941673,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Manda, Alex","contributorId":333344,"corporation":false,"usgs":false,"family":"Manda","given":"Alex","email":"","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941674,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Michael, Holly A.","contributorId":190224,"corporation":false,"usgs":false,"family":"Michael","given":"Holly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":941675,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Moysey, Stephen","contributorId":357533,"corporation":false,"usgs":false,"family":"Moysey","given":"Stephen","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941676,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Myers-Pigg, Allison","contributorId":224762,"corporation":false,"usgs":false,"family":"Myers-Pigg","given":"Allison","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":941677,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Neville, Justine Annaliese 0000-0003-3160-5363","orcid":"https://orcid.org/0000-0003-3160-5363","contributorId":329739,"corporation":false,"usgs":true,"family":"Neville","given":"Justine","email":"","middleInitial":"Annaliese","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":941678,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":941679,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Panthi, Jeeban","contributorId":357534,"corporation":false,"usgs":false,"family":"Panthi","given":"Jeeban","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":941680,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Pezeshki, Elnaz","contributorId":357535,"corporation":false,"usgs":false,"family":"Pezeshki","given":"Elnaz","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941681,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Sirianni, Matthew","contributorId":357536,"corporation":false,"usgs":false,"family":"Sirianni","given":"Matthew","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941682,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ward.Nicolas","contributorId":357537,"corporation":false,"usgs":false,"family":"Ward.Nicolas","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":941683,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70268866,"text":"70268866 - 2025 - Isotopic niche plasticity of American alligators within the southern Everglades","interactions":[],"lastModifiedDate":"2025-07-09T15:07:58.020309","indexId":"70268866","displayToPublicDate":"2025-06-27T08:03:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Isotopic niche plasticity of American alligators within the southern Everglades","docAbstract":"Hydrologic alterations within the Everglades have degraded American alligator (Alligator mississippiensis) habitat, reduced prey base, and increased physiological stress. Alligator body condition declined across many management areas from 2000 through 2014, prompting us to investigate the relationship between their intraspecific isotopic niche dynamics and body condition. Alligators within the estuary had a larger niche driven by a wider range in stable carbon isotope ratios than those sampled in freshwater habitats. Spatially, model predictability was higher at the smaller scale, reflecting the variability in basal sources and biochemistry among capture sites. Male niches were often larger than those of females, driven by wider ranges of δ13C values, suggesting that they differ in their proportional use of habitats and or resources. However, the similar ranges of δ15N values indicated both sexes foraged within the same trophic level. Furthermore, while not significantly different, large alligators often had a larger niche with elevated δ15N values compared to medium-sized alligators. Although alligators utilize similar stable carbon and nitrogen isotope pools through time, there was considerable temporal variability. These temporal variations in alligators’ isotopic niche were likely influenced by seasonal hydrologic fluctuations within each site, with their niches often being larger in the spring captures than the fall captures. Alligators’ body condition estimates were correlated with intraspecific niche characteristics, including the mean centroid distance between sexes and the interaction between male and female niche size and overlap, within a site, capture period, and year. The variability in intraspecific niche dynamics, landscape heterogeneity, and dynamic hydrology are considerations for designing sustainable management strategies to conserve and enhance alligator populations within the Everglades landscape.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0326148","usgsCitation":"Denton, M., Cherkiss, M., Mazzotti, F.J., Brandt, L.A., Godfrey, S.T., Johnson, D., and Hart, K., 2025, Isotopic niche plasticity of American alligators within the southern Everglades: PLoS ONE, v. 20, no. 6, e0326148, 29 p., https://doi.org/10.1371/journal.pone.0326148.","productDescription":"e0326148, 29 p.","ipdsId":"IP-152063","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":492082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0326148","text":"Publisher Index Page"},{"id":491899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"southern Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.15227880692397,\n 26.64313806276658\n ],\n [\n -82.15227880692397,\n 25.088643124435762\n ],\n [\n -79.51780855484174,\n 25.088643124435762\n ],\n [\n -79.51780855484174,\n 26.64313806276658\n ],\n [\n -82.15227880692397,\n 26.64313806276658\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Denton, Mathew 0000-0002-1024-3722","orcid":"https://orcid.org/0000-0002-1024-3722","contributorId":210504,"corporation":false,"usgs":true,"family":"Denton","given":"Mathew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":942428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":222180,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":942429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazzotti, Frank J.","contributorId":146647,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank","email":"","middleInitial":"J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":942430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Laura A.","contributorId":146646,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":942431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Godfrey, Sidney T.","contributorId":302877,"corporation":false,"usgs":false,"family":"Godfrey","given":"Sidney","email":"","middleInitial":"T.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":942432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Darren 0000-0002-0502-6045","orcid":"https://orcid.org/0000-0002-0502-6045","contributorId":203921,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":942433,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":222407,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":942434,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268445,"text":"sir20245134 - 2025 - Assessment and validation of depressions in digital elevation models from multiple elevation data sources and delineation of depressions, sinking streams, and their watersheds in Tennessee and parts of Kentucky, Virginia, North Carolina, Georgia, Alabama, and Mississippi","interactions":[],"lastModifiedDate":"2025-08-14T19:40:56.797048","indexId":"sir20245134","displayToPublicDate":"2025-06-26T13:45:32","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":"2024-5134","displayTitle":"Assessment and Validation of Depressions in Digital Elevation Models From Multiple Elevation Data Sources and Delineation of Depressions, Sinking Streams, and Their Watersheds in Tennessee and Parts of Kentucky, Virginia, North Carolina, Georgia, Alabama, and Mississippi","title":"Assessment and validation of depressions in digital elevation models from multiple elevation data sources and delineation of depressions, sinking streams, and their watersheds in Tennessee and parts of Kentucky, Virginia, North Carolina, Georgia, Alabama, and Mississippi","docAbstract":"Closed depressions and sinking streams in karst landscapes pose difficulties for water-resources management, in the construction of roads and other public works, and in hydrologic and hydrogeomorphic analyses. Digital elevation models (DEMs) can be used to identify the location and determine the size and shape of closed depressions, but separating artificial depressions due to error from real depressions in DEMs can be difficult. Artificial depressions in the DEMs can result from errors that were inherited from limitations in the source data, the interpolation of the elevation data into a grid of values, or horizontal and vertical accuracy of the elevation data. Because the source dataset used to derive DEMs is only a model of the true landscape, field verification is necessary to separate artificial depressions from real ones in DEMs. DEM analysis alone can only be used to determine whether a depression is likely or unlikely to exist in the landscape.
The U.S. Geological Survey has applied methods to delineate depressions, sinking streams, and their watersheds by using DEMs derived from two sources of elevation data within karst areas of Tennessee and parts of surrounding States. Preliminary depressions, which include all depressions before separating the likely depressions from the unlikely depressions, were delineated from the DEMs with 30- by 30-foot cells derived from each elevation data source. The characteristics of these preliminary depressions were compared to occurrence probabilities for depressions derived from numerical error propagation tests in 10 test areas across the study area and to topographic-contour source data within a 17,739-square-mile test area in middle Tennessee and northern Alabama. The comparison was conducted to determine depression characteristics that, when combined with depression-proximity filters, could be used to separate unlikely from likely depressions. Preliminary depressions were examined in the field at 91 sites in Tennessee, and field observations were compared to digital determinations of unlikely and likely depressions.
The density and size of depressions derived from each elevation dataset were compared within eight karst regions in the study area. Depressions and their watersheds were compiled from each elevation dataset. Sinking streams derived from the National Hydrography Dataset and their watersheds also were compiled for the study area.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"Increasing fragmentation from constructed barriers, increased water use, and climate change limits the resiliency of stream fish metapopulations by reducing colonization. Management actions such as stocking or translocating fish may help contribute to the resilience of isolated habitats and increase redundancy of populations in intermittent stream networks. Our objective was to determine whether translocating fish into prairie headwater refuges could reestablish or supplement isolated populations.
We examined apparent survival and probability of detection of four native, small-bodied fishes that were translocated in 2022 and 2023 to prairie headwater refuges that were affected by a severe drought and experienced slow recovery of their fish assemblages. All the fish were marked with passive integrated transponder tags, allowing us to use a mark–recapture framework to track the fate of these fish.
Apparent survival was predicted by an interaction between time and translocation site, indicating an important consideration of environmental factors. Approximately one-quarter of the fish remained at site A through the summer of both years, whereas estimates were near zero at site B in both years and mixed across years at site C. The decreases in apparent survival probabilities following flow events suggest that fish may be emigrating during these periods of reconnection. During the lower flow year, more fish remained at the headwater sites and young-of-year fish were captured during long-term sampling, suggesting that the translocated fish reproduced.
The success of translocation projects will depend on a variety of factors, including management goals, habitat, and hydrology, but the initially high survival reported in this study is encouraging. Difficulties with examining the movement of small fish during hydrologic events limited our conclusions about the relative contributions of mortality and emigration to apparent survival estimates. Despite low yearly apparent survival, we found evidence of reproduction from translocated fish, suggesting that the reestablishment of a viable population is possible.
The 1973 Oklahoma Groundwater Law (Oklahoma Statute §82–1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s aquifers to determine the maximum annual yield for each groundwater basin. The U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, conducted an updated hydrologic investigation of the Salt Fork Arkansas River and Chikaskia River alluvial aquifers in northern Oklahoma for the study period spanning 1980–2020 and evaluated the simulated effects of potential groundwater withdrawals on groundwater flow and availability in the Salt Fork Arkansas River alluvial aquifer. A hydrogeologic framework and conceptual model were developed to guide the development of a numerical model.
Three groundwater-availability scenarios were evaluated by using the calibrated numerical model, which was focused on the Salt Fork Arkansas River alluvial aquifer. These scenarios were used to (1) estimate equal-proportionate-share groundwater withdrawal rates, (2) quantify the potential effects of projected well withdrawals on groundwater storage over a 50-year period, and (3) simulate the potential effects of a hypothetical 10-year drought. The 20-, 40-, and 50-year equal-proportionate-share groundwater withdrawal rates for the Salt Fork Arkansas River alluvial aquifer under normal recharge conditions were about 0.63, 0.58, and 0.57 acre-foot per acre per year, respectively. Projected 50-year groundwater withdrawal scenarios were used to simulate the effects of modified well withdrawal rates. Because well withdrawals were less than 2 percent of the calibrated numerical-model water budget, changes to the well groundwater withdrawal rates had little effect on simulated Salt Fork Arkansas River base flows and groundwater storage in the Salt Fork Arkansas River alluvial aquifer. A hypothetical 10-year drought scenario was used to simulate the potential effects of a prolonged period of reduced recharge on groundwater storage. Groundwater storage at the end of the hypothetical drought period was 14.5 percent less than the groundwater storage of the calibrated numerical model without the simulated drought.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
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","tableOfContents":"Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.
","language":"English","publisher":"Elsevier B.V.","doi":"10.1016/j.agrformet.2025.110686","usgsCitation":"Reed, D., Chu, H., Peter, B.G., Chen, J., Abraha, M., Amiro, B., Anderson, R.G., Arain, M., Arruda, P., Barron-Gafford, G.A., Bernacchi, C., Beverly, D., Biraud, S., Black, T.A., Blanken, P.D., Bohrer, G., Bowler, R., Bowling, D., Bret-Harte, M., Bretfeld, M., Brunsell, N., Bullock, S., Celis, G., Chen, X., Classen, A., Cook, D., Cueva, A., Dalmagro, H.J., Davis, K.J., Desai, A., Duff, A., Dunn, A., Durden, D., Edgar, C.W., Euskirchen, E., Bracho, R., Ewers, B.E., Flanagan, L.B., Florian, C.R., Foord, V., Forbrich, I., Forsythe, B., Frank, J., Garatuza-Payan, J., Goslee, S., Gough, C.M., Green, M.B., Griffis, T., Helbig, M., Hill, A., Hinkle, R., Horne, J., Humphreys, E., Ikawa, H., Iwahana, G., Jassal, R., Johnson, B.K., Johnson, M.S., Kannenberg, S., Kelsey, E., King, J., Knowles, J.F., Knox, S., Kobayashi, H., Kolb, T., Kolka, R., Krauss, K., Kutzbach, L., Lamb, B.T., Law, B.E., Lee, S., Lee, X., Liu, H., Loescher, H.W., Malone, S.L., Matamala, R., Mauritz, M., Metzger, S., Meyer, G., Mitra, B., Munger, J., Nesic, Z., Noormets, A., O'Halloran, T., O'Keeffe, P., Oberbauer, S.F., Oechel, W., Oikawa, P., Olivas, P., Ouimette, A., Pastorello, G., Perez-Quezada, J., Phillips, C., Posse, G., Qu, B., Quinton, W.L., Reba, M.L., Richardson, A.D., Picasso, V., Rocha, A., Rodriguez, J., Ruzol, R., Saleska, S., Scott, R.L., Schreiner-McGraw, A.P., Schuur, E., Silveira, M., Sonnentag, O., Spittlehouse, D., Staebler, R., Starr, G., Staudhammer, C., Still, C., Sturtevant, C., Sullivan, R., Suyker, A., Trejo, D., Ueyama, M., Vargas, R., Viner, B., Vivoni, E.R., Wang, D., Ward, E.J., Wiesner, S., Windham-Myers, L., Yannick, D., Yepez, E., Zenone, T., Zhao, J., and Zona, D., 2025, Network of networks: Time series clustering of AmeriFlux sites: Agricultural and Forest Meteorology, v. 372, 110686, 18 p., https://doi.org/10.1016/j.agrformet.2025.110686.","productDescription":"110686, 18 p.","ipdsId":"IP-167572","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":492047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2025.110686","text":"Publisher Index Page"},{"id":491777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"372","noUsgsAuthors":false,"publicationDate":"2025-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, David E.","contributorId":349160,"corporation":false,"usgs":false,"family":"Reed","given":"David E.","affiliations":[{"id":83451,"text":"School of the Environment, Yale University, New Haven","active":true,"usgs":false}],"preferred":false,"id":942108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chu, Housen","contributorId":330059,"corporation":false,"usgs":false,"family":"Chu","given":"Housen","affiliations":[{"id":78784,"text":"Lawrence Berkeley National Lab, Berkeley, CA 94702, USA","active":true,"usgs":false}],"preferred":false,"id":942109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peter, Brad G.","contributorId":192813,"corporation":false,"usgs":false,"family":"Peter","given":"Brad","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":942110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Jiquan","contributorId":330058,"corporation":false,"usgs":false,"family":"Chen","given":"Jiquan","affiliations":[{"id":78783,"text":"Michigan State University, East Lansing, MI 48823, USA","active":true,"usgs":false}],"preferred":false,"id":942111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abraha, Michael","contributorId":357644,"corporation":false,"usgs":false,"family":"Abraha","given":"Michael","affiliations":[{"id":85486,"text":"Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI, 48823, USA","active":true,"usgs":false}],"preferred":false,"id":942112,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amiro, Brian","contributorId":357645,"corporation":false,"usgs":false,"family":"Amiro","given":"Brian","affiliations":[{"id":85487,"text":"Department of Soil Science, University of Manitoba, Winnipeg, MB, R3T2N2, Canada","active":true,"usgs":false}],"preferred":false,"id":942113,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, Ray G.","contributorId":269952,"corporation":false,"usgs":false,"family":"Anderson","given":"Ray","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":942114,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arain, M. 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Yet their physical position, complex shape, and large watersheds make reservoirs especially susceptible to eutrophication and harmful algal bloom (HAB) production. Boysen Reservoir, WY, is a high priority for proactive nutrient management because it is an important source for drinking water and recreation, and has a history of toxic cyanobacterial blooms. We combined four years of comprehensive monitoring efforts by state and federal agencies to characterize the spatiotemporal patterns of nutrient inflow, internal water quality dynamics, and phytoplankton community shifts in Boysen Reservoir. We found nutrient inflow was hydrologically driven, with snowmelt runoff transporting high nutrient loads. Our findings suggest physicochemical and nutrient conditions of the reservoir were strongly different between the furthest reaches of the reservoir, but less variable among the intermediate sites. Space did not play a role in phytoplankton community dynamics, but time was an important factor. Cyanobacteria dominated phytoplankton communities by mid-summer across the reservoir and were driven mainly by temporal physicochemical conditions, like stratification and water temperature. The two most dominant phytoplankton taxa across the four years of sampling were N-fixing, toxin producing cyanobacteria. Extensive monitoring efforts and data analyses can illuminate strategies to safeguard water resources via understanding the drivers of water quality changes and HAB production.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10661-025-14258-1","usgsCitation":"Rock, L., Fetzer, W., Patterson, L., Sillen, S., Steg, R., Walters, A.W., and Collins, S.M., 2025, Spatiotemporal drivers of water quality and phytoplankton communities in a cyanobacteria-dominated reservoir provide management insights: Environmental Monitoring and Assessment, v. 197, 795, 18 p., https://doi.org/10.1007/s10661-025-14258-1.","productDescription":"795, 18 p.","ipdsId":"IP-173265","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":492477,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-025-14258-1","text":"Publisher Index Page"},{"id":492137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Boysen Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.28940875950443,\n 43.45008748233806\n ],\n [\n -108.28940875950443,\n 43.149830823543425\n ],\n [\n -108.11100943189061,\n 43.149830823543425\n ],\n [\n -108.11100943189061,\n 43.45008748233806\n ],\n [\n -108.28940875950443,\n 43.45008748233806\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"197","noUsgsAuthors":false,"publicationDate":"2025-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Rock, Linnea A.","contributorId":357815,"corporation":false,"usgs":false,"family":"Rock","given":"Linnea A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":942651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fetzer, William W.","contributorId":357816,"corporation":false,"usgs":false,"family":"Fetzer","given":"William W.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":942652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Lindsay","contributorId":356033,"corporation":false,"usgs":false,"family":"Patterson","given":"Lindsay","affiliations":[{"id":84900,"text":"Wyoming Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":942653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sillen, Samuel J.","contributorId":357817,"corporation":false,"usgs":false,"family":"Sillen","given":"Samuel J.","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":942654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steg, Ron","contributorId":357818,"corporation":false,"usgs":false,"family":"Steg","given":"Ron","affiliations":[{"id":84900,"text":"Wyoming Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":942655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":942656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collins, Sarah M.","contributorId":204070,"corporation":false,"usgs":false,"family":"Collins","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":36821,"text":"Center for Limnology, University of Wisconsin Madison, Madison","active":true,"usgs":false}],"preferred":false,"id":942657,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268358,"text":"ofr20251033 - 2025 - Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models","interactions":[],"lastModifiedDate":"2025-06-24T13:43:22.987262","indexId":"ofr20251033","displayToPublicDate":"2025-06-23T14:10:00","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":"2025-1033","displayTitle":"Select Elements of Concern in Surface Water of Three Hydrologic Basins (Delaware River, Illinois River, and Upper Colorado River)—Data Screening for the Development of Spatial and Temporal Models","title":"Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models","docAbstract":"The report focuses on the screening of previously published concentration data associated with 12 elements of concern (aluminum, arsenic, cadmium, chromium, copper, iron, mercury, manganese, lead, selenium, uranium, and zinc) measured in stream surface waters of three hydrologic basins (Delaware River Basin, Illinois River Basin, and the Upper Colorado River Basin). The purpose of this analysis is to determine what subsets of the original dataset (containing more than 1,500,000 observations) may be most suitable for each of two types of modeling efforts. The first type of modeling envisions a machine learning approach to determine which geospatial attributes are most significant in describing the spatial distribution of elemental concentrations within a basin. The second type of modeling envisions a stepwise regression approach to develop multivariable models that can be used to determine high resolution time-series estimates of elemental concentrations or loads at discrete U.S. Geological Survey real-time stream surface water sites. These site-specific temporal models are based on continuous measurements of available discharge and (or) in situ sensor data (temperature, pH, turbidity, dissolved oxygen, specific conductance, and (or) fluorescent dissolved organic matter) as the explanatory variables. The data screening for both model types considered historical trends in analytical methods and detection quantitation limits, the extent of censored data, data density, and environmental relevance with respect to three U.S. Environmental Protection Agency water quality thresholds (drinking water guidelines, human health criteria, and aquatic life criteria). The result of this analysis was the production of a final list of potential models deemed suitable for further development based upon the data exclusion (or inclusion) scheme developed herein for each model type. In both cases, the final models included mostly the three crustal elements (iron, manganese, and aluminum) that are found at comparatively high concentrations in surface water, whereas most of the more pernicious elements were excluded from the final model lists owing to various data limitations. The one exception to this was arsenic, for which the existing data were sufficient at three U.S. Geological Survey real-time sites for potential further development of time-series models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251033","programNote":"Water Quality Program","usgsCitation":"Marvin-DiPasquale, M.C., McCleskey, R.B., Sullivan, S.L., Root, J.C., Seawolf, S.M., Ransom, K.M., Wherry, S.A., Kakouros, E., and Baesman, S., 2025, Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models: U.S. Geological Survey Open-File Report 2025–1033, 25 p., https://doi.org/10.3133/ofr20251033.","productDescription":"Report: v, 25 p.; 2 Data Releases","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-151463","costCenters":[{"id":37277,"text":"WMA - Earth System Processes 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Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Ave, Suite 1950
Portland, OR 97204
Northern deltas receive chromophoric dissolved organic matter (CDOM) from their watersheds, which can be oxidized to carbon dioxide upon absorption of sunlight (i.e., photomineralized). These deltas also receive total suspended solids (TSS), which may shade sunlight absorption by CDOM, thus limiting photomineralization. To quantify this interaction for the first time, we measured photomineralization rates at 11sites in the Peace‐Athabasca Delta (PAD), Canada. We sampled waters during a July 2022 field campaign for TSS concentration, CDOM concentration (αCDOM,λ), total downwelling sunlight attenuation coefficients (Kd,tot,λ), and light attenuation coefficients due to CDOM (Kd,CDOM,λ). TSS ranged from <1 to 112 mg/L with an average of 19 ± 34 mg/L (mean ± one standard deviation), an order of magnitude lower than TSS reported in rivers entering the PAD earlier in the open water season. αCDOM,λ at 305 nm (αCDOM,305) ranged from 23.3 to 65.2 m-1, Kd,CDOM,305 ranged from 26.3 to 74.1 m−1, and Kd,tot,305 ranged from 19.0 to 63.7 m−1. The ratio of sunlight absorbed by CDOM relative to total sunlight attenuation Kd,CDOM,λ/Kd,tot,λ was inversely correlated with TSS concentration across all wavelengths measured (305–412 nm). TSS thus limited photomineralization rates by shading CDOM from ultraviolet A and visible wavelengths of sunlight, reducing photomineralization rates by up to 56% compared to rates in the absence of TSS or other non-CDOM particles that attenuate sunlight. Results suggest that shifts in delta hydrology that affect TSS concentration likely influence photomineralization rates within TSS-rich northern deltas.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JG008620","usgsCitation":"Dolan, W., Pavelsky, T.M., Davis, J., LaFramboise, N., Polik, C., and Cory, R., 2025, Effects of total suspended solids on photomineralization of dissolved organic matter in the Peace-Athabasca Delta, Canada: JGR Biogeosciences, v. 130, no. 6, e2024JG008620, 23 p., https://doi.org/10.1029/2024JG008620.","productDescription":"e2024JG008620, 23 p.","ipdsId":"IP-172665","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":491877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Peace‐Athabasca Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.23884840686532,\n 59.99203702983766\n ],\n [\n -113.23884840686532,\n 58.3291665449174\n ],\n [\n -110.01835852259443,\n 58.3291665449174\n ],\n [\n -110.01835852259443,\n 59.99203702983766\n ],\n [\n -113.23884840686532,\n 59.99203702983766\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Dolan, Wayana 0000-0001-8405-4302","orcid":"https://orcid.org/0000-0001-8405-4302","contributorId":354442,"corporation":false,"usgs":true,"family":"Dolan","given":"Wayana","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":941615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pavelsky, Tamlin M.","contributorId":258838,"corporation":false,"usgs":false,"family":"Pavelsky","given":"Tamlin","email":"","middleInitial":"M.","affiliations":[{"id":52312,"text":"Department of Geological Sciences, University of North Carolina, Chapel Hill, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":941616,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Julianne","contributorId":357497,"corporation":false,"usgs":false,"family":"Davis","given":"Julianne","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":941617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaFramboise, Nathan","contributorId":357499,"corporation":false,"usgs":false,"family":"LaFramboise","given":"Nathan","affiliations":[{"id":85432,"text":"University of Michigan at Ann Arbor","active":true,"usgs":false}],"preferred":false,"id":941618,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Polik, Catherine","contributorId":357500,"corporation":false,"usgs":false,"family":"Polik","given":"Catherine","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":941619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cory, Rose","contributorId":357501,"corporation":false,"usgs":false,"family":"Cory","given":"Rose","affiliations":[{"id":85432,"text":"University of Michigan at Ann Arbor","active":true,"usgs":false}],"preferred":false,"id":941620,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274598,"text":"70274598 - 2025 - Near-surface geophysics: Environmental applications","interactions":[],"lastModifiedDate":"2026-04-01T13:53:22.33473","indexId":"70274598","displayToPublicDate":"2025-06-20T08:47:58","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Near-surface geophysics: Environmental applications","docAbstract":"The field of geophysics encompasses a broad and diverse compilation of methodologies that employs principles of physics to characterize properties of earth materials within the subsurface. While geophysical methods have a long history in resource exploration and studies of Earth’s interior, the subdiscipline of “near-surface geophysics” has evolved in recent decades for examination of the shallow, near-surface environment for a range of purposes ranging from archaeological or forensic investigations to assessment of geologic, hydrologic, biologic, and geochemical properties and processes. “Environmental geophysics” are near-surface geophysical studies and methods that focus on understanding natural systems (e.g., watershed hydrology, groundwater–surface water connections, biophysical processes) as well as research pertaining to anthropogenic impacts and land management, (e.g., contamination and remediation, saltwater intrusion, agricultural practices). This field can be further subdivided into subdisciplines focused on specific topics and applications, such as water resources and hydrology (hydrogeophysics) or biologic and microbial processes (biogeophysics). Studies in environmental geophysics span a range of scales, from pore-scale laboratory tests to watershed-scale or regional field experiments. Methods vary by the nature of physics employed, the specific measurement acquired, and how that data is ultimately processed and analyzed to produce interpretable results. There exists further diversity in the acquisition logistics, geometry, and timing of data collection. Geophysical data can be collected in boreholes (one-dimensional, 1-D, vertical profiles), along survey lines (two-dimensional, 2-D, cross-sections), or in dense sensor arrays or gridded profiles (three-dimensional, 3-D, models). Regarding the temporal aspect, studies can conduct one-time geophysical surveys to obtain detailed imaging of subsurface structure or use timelapse and continuous monitoring to investigate variations in subsurface properties over time. The cumulation of all possible permutations of these factors (method, acquisition geometry, survey design, and target application) results in an immense diversity among environmental geophysical studies. Nevertheless, this field remains unified in the pursuit of understanding natural and human-impacted near-surface environments through geophysical investigations. Here we highlight some key references within environmental geophysics. Resources on geophysical theory, acquisition logistics, processing and inversion workflows, and example case studies are categorized into the most common geophysical classes within Geophysical Methods. Lastly, example references for the dominant types of applications in environmental geophysical studies are catalogued in Environmental Applications.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Oxford Bibliographies","largerWorkSubtype":{"id":11,"text":"Bibliography"},"language":"English","publisher":"Oxford University Press","doi":"10.1093/obo/9780199363445-0146","usgsCitation":"James, S.R., Glaser, D.R., and Garcia, A., 2025, Near-surface geophysics: Environmental applications, chap. of Oxford Bibliographies, HTML Document, https://doi.org/10.1093/obo/9780199363445-0146.","productDescription":"HTML Document","ipdsId":"IP-172909","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":501916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"James, Stephanie R. 0000-0001-5715-253X","orcid":"https://orcid.org/0000-0001-5715-253X","contributorId":260620,"corporation":false,"usgs":true,"family":"James","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":958466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glaser, Dan R.","contributorId":292710,"corporation":false,"usgs":false,"family":"Glaser","given":"Dan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":958467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garcia, Alejandro","contributorId":369112,"corporation":false,"usgs":false,"family":"Garcia","given":"Alejandro","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":958468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273971,"text":"70273971 - 2025 - Streamflow regime characterization in the changing boreal ecosystem: Wildfire impacts from stream-to-regional scales","interactions":[],"lastModifiedDate":"2026-02-20T17:06:56.875893","indexId":"70273971","displayToPublicDate":"2025-06-19T09:57:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow regime characterization in the changing boreal ecosystem: Wildfire impacts from stream-to-regional scales","docAbstract":"The boreal ecosystem has experienced significant changes over recent decades as wildfires become more frequent, intense, and severe. As streams are highly prevalent and ecologically relevant, understanding interactions among wildfire and hydrologic patterns is important for effective aquatic ecosystem management. This study used a Bayesian mixture model to classify streamflow regimes from modeled streamflow data for 32,730 stream reaches (totaling 295,880 km) across the Yukon and Kuskokwim basins and the Northwestern Boreal Ecosystem in Alaska, USA, and Yukon Territory, Canada. We assessed time since burn and calculated the total length of stream (km) within burn perimeters for each streamflow class from 1985 to 2015. Additionally, we used field observations (2018–2022) to compare streamflow regimes in four burned and four unburned headwater streams (drainage basins ≤150 km2) in interior Alaska. Modeled stream reaches were grouped into twenty-two classes and reduced to eleven metaclasses based on similarities in streamflow statistics. These metaclasses formed two broad groups: 1) large rivers with lower variability and strong seasonal signals, and 2) mid- to small-sized tributaries with high variability, frequent high flow events, and weaker seasonal signals. The stream length burned analysis indicated an average increase of 47 km per year with first- and second-order streams experiencing more frequent fire. Empirical streamflow metrics from headwater stream gages revealed additional differences in streamflow patterns between burned and unburned streams. This streamflow classification establishes a baseline for understanding boreal stream responses to wildfire, detecting climate-induced regime shifts, and facilitating management and conservation of important boreal aquatic species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.179770","usgsCitation":"Strohm, D.D., Sergeant, C.J., Paul, J.D., Falke, J.A., 2025, Streamflow regime characterization in the changing boreal ecosystem: Wildfire impacts from stream-to-regional scales: Science of the Total Environment, v. 991, 179770, 14 p., https://doi.org/10.1016/j.scitotenv.2025.179770.","productDescription":"179770, 14 p.","ipdsId":"IP-173153","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Boreal Yukon-Kuskokwim study area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -151.25073280649116,\n 65.22533418311923\n ],\n [\n -151.08883708497373,\n 64.1874521027234\n ],\n [\n -147.81756784832672,\n 64.90432777046252\n ],\n [\n -144.75370718998238,\n 64.258653756473\n ],\n [\n -144.56100126166737,\n 65.39083680482943\n ],\n [\n -148.2119885011982,\n 65.53590677988976\n ],\n [\n -151.25073280649116,\n 65.22533418311923\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"991","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Strohm, Deanna D.","contributorId":366469,"corporation":false,"usgs":false,"family":"Strohm","given":"Deanna","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":955951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sergeant, Christopher J.","contributorId":140496,"corporation":false,"usgs":false,"family":"Sergeant","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":955953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paul, Josh D.","contributorId":366470,"corporation":false,"usgs":false,"family":"Paul","given":"Josh","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":955954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":955952,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70268377,"text":"70268377 - 2025 - Borehole geophysical time-series logging to monitor passive ISCO treatment of residual chlorinated-ethenes in a confining bed, NAS Pensacola, Florida","interactions":[],"lastModifiedDate":"2025-06-24T14:49:19.213209","indexId":"70268377","displayToPublicDate":"2025-06-18T07:43:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21827,"text":"Hydrology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Borehole geophysical time-series logging to monitor passive ISCO treatment of residual chlorinated-ethenes in a confining bed, NAS Pensacola, Florida","docAbstract":"In-situ chemical oxidation (ISCO) is a common method to remediate chlorinated ethene contaminants in groundwater. Monitoring the effectiveness of ISCO can be hindered because of insufficient observations to assess oxidant delivery. Advantageously, potassium permanganate, one type of oxidant, provides the opportunity to use its strong electrical signal as a surrogate to track oxidant delivery using time-series borehole geophysical methods, like electromagnetic (EM) induction logging. Here we report a passive ISCO (P-ISCO) experiment, using potassium permanganate cylinders emplaced in boreholes, at a chlorinated ethene contamination site, Naval Air Station Pensacola, Florida. The contaminants are found primarily at the base of a shallow sandy aquifer in contact with an underlying silty-clay confining bed. We used results of the time-series borehole logging collected between 2017 and 2022 in 4 monitoring wells to track oxidant delivery. The EM-induction logs from the monitoring wells showed an increase in EM response primarily along the contact, likely from pooling of the oxidant, during P-ISCO treatment in 2021. Interestingly, concurrent natural gamma-ray (NGR) logging showed a decrease in NGR response at 3 of the 4 wells possibly from the formation of manganese precipitates coating sediments. The coupling of time-series logging and well-chemistry data allowed for an improved assessment of passive ISCO treatment effectiveness.
","language":"English","publisher":"MDPI","doi":"10.3390/hydrology12060155","usgsCitation":"Harte, P., Singletary, M., and Landmeyer, J., 2025, Borehole geophysical time-series logging to monitor passive ISCO treatment of residual chlorinated-ethenes in a confining bed, NAS Pensacola, Florida: Hydrology Journal, v. 12, no. 6, 155, 21 p., https://doi.org/10.3390/hydrology12060155.","productDescription":"155, 21 p.","ipdsId":"IP-172305","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":491498,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology12060155","text":"Publisher Index Page"},{"id":491184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","city":"Pensacola","otherGeospatial":"NAS Pensacola","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.35238712915951,\n 30.378828812173666\n ],\n [\n -87.35238712915951,\n 30.32983549008638\n ],\n [\n -87.23991634365869,\n 30.32983549008638\n ],\n [\n -87.23991634365869,\n 30.378828812173666\n ],\n [\n -87.35238712915951,\n 30.378828812173666\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Harte, Philip 0000-0002-7718-1204","orcid":"https://orcid.org/0000-0002-7718-1204","contributorId":217273,"corporation":false,"usgs":true,"family":"Harte","given":"Philip","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singletary, Michael A.","contributorId":357307,"corporation":false,"usgs":false,"family":"Singletary","given":"Michael A.","affiliations":[{"id":85401,"text":"U.S. Navy Facilities Command, Southeast","active":true,"usgs":false}],"preferred":false,"id":941146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landmeyer, James E. 0000-0002-5640-3816","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":346430,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941147,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70268362,"text":"70268362 - 2025 - Characterizing water-quality response after the 2020 Cameron Peak Fire using a novel application of the Weighted Regressions on Time, Discharge, and Season method","interactions":[],"lastModifiedDate":"2025-06-24T14:08:12.18671","indexId":"70268362","displayToPublicDate":"2025-06-16T09:02:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing water-quality response after the 2020 Cameron Peak Fire using a novel application of the Weighted Regressions on Time, Discharge, and Season method","docAbstract":"The frequency and severity of wildfire activity in the western United States emphasises the utility of hydrologic models to predict water-quality response. This study presents a novel application of the Weighted Regressions on Time, Discharge and Season (WRTDS) method to assess potential changes in water quality in two watersheds draining the North Fork Big Thompson River and Buckhorn Creek in Larimer County, Colorado that were affected by the 2020 Cameron Peak Fire. WRTDS models were developed using 12 years of pre-fire data and used to estimate the expected constituent concentrations for each sample collected in the post-fire record. The predicted constituent concentrations modelled in this manner are representative of conditions in the absence of fire and allow pre-fire and post-fire stream chemistry to be quantitatively compared. Nitrate and total phosphorus concentrations showed the greatest differences between the observed and predicted concentrations, which were up to 153% greater than expected. We linked changes in source inputs and elevation as likely controls on the difference in magnitude and timing of response between the two watersheds. Post-fire arsenic and manganese concentrations were greater than the predicted concentrations in both watersheds, with arsenic up to 42% greater and manganese up to 85% greater than the model predictions. Post-fire calcium, magnesium, chloride and sulphate concentrations were greater than model predictions at the North Fork and less than the predictions at Buckhorn. We argue that greater burn severity at Buckhorn likely reduced soil–water infiltration and led to bypassed subsurface flow paths through a major lithologic source of these constituents. Post-fire changes in total organic carbon and dissolved iron concentrations were weakly supported by the model results, as observed concentrations were largely within the bounds of expected values calculated from the pre-fire model. The novel approach to WRTDS presented in this study could be a useful tool for water-quality assessments after land disturbances in the western United States.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70178","usgsCitation":"Ruckhaus, M.H., Clow, D.W., Hirsch, R.M., and Chapin, T.W., 2025, Characterizing water-quality response after the 2020 Cameron Peak Fire using a novel application of the Weighted Regressions on Time, Discharge, and Season method: Hydrological Processes, v. 39, no. 6, e70178, 21 p., https://doi.org/10.1002/hyp.70178.","productDescription":"e70178, 21 p.","ipdsId":"IP-171701","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":491489,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70178","text":"Publisher Index Page"},{"id":491178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Larimer County","otherGeospatial":"Buckhorn Creek watershed, North Fork Big Thompson River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.1667,\n 40.75\n ],\n [\n -106,\n 40.75\n ],\n [\n -106,\n 40.333\n ],\n [\n -105.1667,\n 40.333\n ],\n [\n -105.1667,\n 40.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruckhaus, Manya Helene 0009-0006-3111-1127","orcid":"https://orcid.org/0009-0006-3111-1127","contributorId":344234,"corporation":false,"usgs":true,"family":"Ruckhaus","given":"Manya","email":"","middleInitial":"Helene","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":941105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapin, Tanner William 0000-0003-3905-3241","orcid":"https://orcid.org/0000-0003-3905-3241","contributorId":297923,"corporation":false,"usgs":true,"family":"Chapin","given":"Tanner","email":"","middleInitial":"William","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}