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326 records · Page 16Linked to original sources
USGS2025

Assessing flood water infiltration and storage in a restored floodplain

In urban areas, floodplain restoration is gaining prominence as a strategy for restoring the natural functions of floodplain ecosystems and reducing flood risk. This has spurred research into potential interactions between floodwaters, the hyporheic zone, and the floodplain aquifer. An urban restored stream in Wisconsin, USA, was used as a case study to examine four methods to estimate floodplain infiltration and storage during overbank floods. We characterised flood-related infiltration over a 4-year period from 2018 through 2021 by simultaneously and continuously measuring groundwater levels and vertical temperature profiles with stream water levels linked to high-resolution flood inundation maps. High-resolution topographic data helped to quantify surface floodplain storage and the unsaturated soil volume relative to flood stage. Infiltration estimates from the simple methods align well with those from the more complex methods; however, the complex methods provide additional insights about the factors influencing infiltration. Results from all methods indicate that the volume of water that vertically infiltrates during floods is likely small relative to the total volume of the flood, with 0.08%–0.52% of flood water infiltrating into the floodplain, on average. Spatially variable vertical hydraulic gradients, driven by flood depth, groundwater level, and permeability, imply heterogeneous patterns of infiltration across the floodplain. Gradients favourable for infiltration typically occurred during the onset of flooding but, over the study period, were mostly (98% of the time) favourable for groundwater discharge to the channel (non-flood periods). These findings highlight the importance of considering surface-groundwater dynamics, floodplain soils, and unsaturated floodplain volume in defining the benefits of floodplain infiltration for flood attenuation.

Wisconsin↗
USGS2024

Anaerobic biodegradation of perfluorooctane sulfonate (PFOS) and microbial community composition in soil amended with a dechlorinating culture and chlorinated solvents

Perfluorooctane sulfonate (PFOS), one of the most frequently detected per - and polyfluoroalkyl substances (PFAS) occurring in soil, surface water, and groundwater near sites contaminated with aqueous film-forming foam (AFFF), has proven to be recalcitrant to many destructive remedies, including chemical oxidation. We investigated the potential to utilize microbially mediated reduction (bioreduction) to degrade PFOS and other PFAS through addition of a known dehalogenating culture, WBC-2, to soil obtained from an AFFF-contaminated site. A substantial decrease in total mass of PFOS (soil and water) was observed in microcosms amended with WBC-2 and chlorinated volatile organic compound (cVOC) co-contaminants — 46.4 ± 11.0 % removal of PFOS over the 45-day experiment. In contrast, perfluorooctanoate (PFOA) and 6:2 fluorotelomer sulfonate (6:2 FTS) concentrations did not decrease in the same microcosms. The low or non-detectable concentrations of potential metabolites in full PFAS analyses, including after application of the total oxidizable precursor assay, indicated that defluorination occurred to non-fluorinated compounds or ultrashort-chain PFAS. Nevertheless, additional research on the metabolites and degradation pathways is needed. Population abundances of known dehalorespirers did not change with PFOS removal during the experiment, making their association with PFOS removal unclear. An increased abundance of sulfate reducers in the genus Desulfosporosinus (Firmicutes) and Sulfurospirillum (Campilobacterota) was observed with PFOS removal, most likely linked to initiation of biodegradation by desulfonation. These results have important implications for development of in situ bioremediation methods for PFAS and advancing knowledge of natural attenuation processes.

Science of the Total Environment↗
USGS2024

Enhanced microplastic fragmentation along human built structures in an urban waterway

Plastic pollution and microplastic (MP, 1 µm to 5 mm) generation are growing problems affecting the global community and a wide range of natural and disturbed environments. Urban and suburban waterways are directly impacted by plastic pollution due to their proximity to population centers and many different types single use plastic waste sources. In this study, plastic waste accumulation and fragmentation was investigated along the Cooper River in Camden County, NJ. Polymer composition was identified for individual plastic waste particles collected along the Cooper River using Fourier transform infrared (FTIR) spectrometry. Multiple human-built structures (Wallworth Lake, Evans Pond and Hopkins Pond dams) along the Cooper River were found to accumulate different types of plastic waste. The accumulation of plastic waste along these structures resulted in the initial stages of plastic fragmentation and the identification of large MP particles (1 to 5 mm). Quantitative analysis revealed that fragmented polystyrene (PS) particles constituted 82.8% of the total plastic fragments identified, most of which were identified at the Wallworth Lake dam. Many other types of fragmented plastic litter, including polyethylene and polypropylene, were identified at the Wallworth Lake dam, as well. This research demonstrates that engineered structures within urban and suburban aquatic ecosystems serve as significant aggregators of plastic debris, thereby catalyzing its breakdown into microplastics. Considering the escalating ecological and human health ramifications of microplastic proliferation, the fragmentation of plastic waste in an urban and suburban waterway observed in this study can also result in potentially toxic smaller MP particles, and increased exposure to aquatic organisms and humans.

New Jersey↗
USGS2025

Effect of land cover type on 3D deformation recovery from synthetically deformed high-resolution satellite optical imagery

The limits of detection for earthquake surface deformation in the spatial domain have improved with advances in remote sensing imagery data availability, resolution, and analysis. Sub-pixel correlation and digital elevation model (DEM) differencing from sub-meter, earthquake-spanning satellite optical imagery has enhanced surface rupture mapping and deformation measurements. However, knowledge of measurement accuracy and uncertainty is limited. To address this, we construct orthophotos and digital elevation models (DEMs) from repeat high resolution (∼0.5 m) satellite optical imagery along two sections of the Garlock fault, California with clear fault geomorphology and differing land cover. We deform later sets of DEMs and images with synthetic earthquakes containing both diffuse and discrete horizontal and vertical displacements. Sub-pixel image correlation and DEM differencing demonstrate how vegetation degrades recovered displacement accuracy. In barren land cover, horizontal displacements are detectable to an expected ∼1/10th-pixel size. With shrubs, trees, and grass, detectable displacements increase to >1/2-pixel size, and filtering results by correlation score and using elevation values as input rather than image values improves accuracy. Vertical displacement detection thresholds remain lower in vegetation, at >1-pixel size. Higher slope angles degrade displacement recovery, worsened by vegetation. Diminishing seasonal separation improves accuracy over vegetated regions, though not to the level achieved in barren environments. These results will inform research and operational efforts on the utility of high resolution satellite optical imagery for detecting deformation in varied land cover. Furthermore, they reveal where alternative measurements, such as from LiDAR or radar interferometry, are required to mitigate the effects of vegetation and capture fine-scale crustal deformation.

California↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2024

U.S. Geological Survey Karst Interest Group proceedings, Nashville, Tennessee, October 22-24, 2024

Karst hydrogeologic systems represent challenging and unique conditions to scientists studying groundwater flow and contaminant transport. Karst terrains are characterized by distinct and beautiful landscapes, caverns, and springs, and many of the exceptional karst areas are designated as national or state parks. The range and complexity of landforms and groundwater flow systems associated with karst terrains are enormous, perhaps more than any other aquifer type. The U.S. Geological Survey (USGS) Karst Interest Group (KIG), formed in 2000, is a loosely knit, grassroots organization of USGS and non-USGS scientists and researchers devoted to fostering better communication among scientists working on, or interested in, karst aquifers. The primary mission of the KIG is to encourage and support interdisciplinary collaboration and technology transfer among scientists working in karst areas. To accomplish its mission, the KIG has organized a series of workshops. To date (2024), nine KIG workshops, including the workshop documented in this report, have been held. The abstracts and extended abstracts provide a snapshot in time of past and current karst related studies. The USGS Water Availability and Use Science Program funded the workshop and proceedings. The planning committee for the ninth workshop includes Thomas D. Byl (USGS and Tennessee State University), Allan K. Clark (USGS), Laura M. DeMott (USGS), Eve L. Kuniansky (USGS, Emeritus), Benjamin V. Miller (USGS), and Lawrence E. Spangler (USGS, Emeritus). The workshop proceedings are edited by Eve L. Kuniansky and Lawrence E. Spangler. The field trip guide was produced by Benjamin V. Miller and Brian Ham (Tennessee Department of Environment and Conservation) and included in the proceedings from the KIG’s 2021 virtual workshop to be used on the optional field trip held on Thursday, October 24, 2024.

Open-File Report↗
USGS2024

Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand

On 14 February 2016, a magnitude (M)5.7 earthquake struck in Christchurch New Zealand (Aotearoa in the Maori language). The shaking caused damage to historic facades, power outages, cliff collapses, rock falls, and liquefaction but no reported injuries or fatalities. This Valentine’s Day earthquake was an aftershock in the Canterbury earthquake sequence (CES), which began on 4 September 2010 with the M7.1 Darfield Earthquake and included the destructive and fatal M6.2 Christchurch aftershock on 22 February 2011. This study, eight months after the Valentine’s Day earthquake and six years after the initiation of the CES, is the first to explore long-term aftershock forecast information and communication needs. The exploratory study also aimed to gather feedback on aftershock scenarios, an alternative form for communicating the forecast. The qualitative study involved workshops with emergency managers, public health officials, and members of the public in Christchurch. Key findings for long-term communication throughout an earthquake sequence include: 1. divergent earthquake experiences affect aftershock communication response and information needs; 2. understanding aftershock sequence behavior is foundational to sense-making when large aftershocks occur; 3. strategic earthquake sequence updates from the trusted science agency and local agencies could serve as important reminders for earthquake preparedness; 4. communication of aftershock forecast uncertainty could aid with both the credibility of the information and living with uncertainty, and 5. inclusion of impact information and preparedness advice into aftershock forecast scenarios could provide links to actionable information. The paper derives implications for research and practice of long-term communications during an aftershock sequence.

Christchurch↗
USGS2024

Developing international standards and guidelines for disseminating and validating simulated ground motions

We are leading an effort to develop international standards and guidelines for curating, disseminating, and validating simulated ground-motion data. This effort is organized as a working group within the Consortium of Organizations for Strong Motion Observation Systems (COSMOS). In 2022 we held online workshops on 7 and 8 June and 20 October. The first workshop focused on curating and disseminating simulated ground-motion data. The second workshop focused on validating simulated ground-motions for engineering applications. About 100 people participated in each of the workshops with strong representation from North America, Europe, and western Asia. In the coming year, we intend to form a technical committee to draft the international guidelines and standards while continuing to engage stakeholders from across the globe through online and in-person meetings. The key points from the workshops include: (1) Numerous groups are generating simulated earthquake ground motions and making them openly available; however there is very little coordination among groups to provide consistent interfaces for searching and retrieving data; (2) Standardizing interfaces for metadata and data access should consider agile approaches that can adapt to changing capabilities and user needs while building upon existing efforts; (3) A distributed architecture is preferred by most participants to allow institutions to host and manage their own data while broadcasting their holdings to a combined catalog; (4) Validation of ground-motion simulations applies to the entire workflow for simulating earthquake ground-motions, including the rupture model, seismic velocity model, and seismic wave propagation software; (5) Metrics to evaluate the validation are application dependent; more research is needed to tie structural response characteristics to ground-motion characteristics; and (6) Validation results should provide a clear, transparent, and quantitative assessment of the simulated ground motions.

Conference Paper↗
USGS2026

Evaluating harvest liberalization strategies on population dynamics of southern latitude temperate-breeding Canada geese

The recovery of the Canada goose ( Branta canadensis ) is one of North America's greatest conservation success stories. Today, continental abundance of temperate-breeding Canada geese (those breeding in southern Canada and lower 48 states in the United States) greatly exceeds historical levels. As a result of increased abundance, human–goose conflicts have also increased, ranging from private and agricultural property damage to human health concerns. Managers have primarily attempted to lower Canada goose populations using hunter harvest via liberalized hunting regulations (increased bag limits and total hunting days). To evaluate the effectiveness of harvest strategies for temperate-breeding Canada geese, managers need a better understanding of how liberalized hunting regulations affect population dynamics. We estimated survival and harvest probabilities, abundance, and recovery distribution of temperate-breeding Canada geese banded in Arkansas, USA, during 2005–2020. We found that adult harvest probabilities declined overall during the study and adult survival probabilities increased. Annual abundances of juvenile geese (≤1 year old) declined during the study, whereas there was no detectable trend in abundance of the adult population over time. Most Canada geese breeding in Arkansas were shot in Arkansas, indicating potential for population dynamics to be influenced largely by state-specific harvest regulations. However, our results suggest that harvest liberalization as a management tool may have limited capacity to further influence population dynamics of Canada geese. Declines in productivity and recruitment likely had a greater influence on the similar observed declines in juvenile and adult abundances, respectively, during our study. More research is needed to better understand the ecological mechanism affecting the population dynamics of Canada geese in both urban and rural environments.

Arkansas↗
USGS2025

Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques

Satellite-derived shorelines (SDS) have the potential to help researchers answer critical coastal science questions and support work to predict coastal change by filling in the spatial and temporal gaps present in current field-based and remote-sensing data collection methods. The U.S. Geological Survey conducted comparison analyses of traditionally sourced shorelines and SDS in diverse coastal landscapes to determine how SDS could be used in ongoing and future work across varied coastal environments and provided some initial findings that could be used for implementation. Using CoastSeg, a browser-based program for SDS detection and mapping, SDS for the period 1984–2023 for multiple locations across the United States were compared to shoreline positions from traditionally sourced shoreline data. In this report, the authors present these comparisons alongside lessons learned and challenges encountered when building SDS workflows in different coastal locations. Results show that individual SDS have larger uncertainty and yet produced similar linear trends to sparser, traditionally sourced shoreline data; because SDS methods provide orders of magnitude more data than traditional shoreline-detection methods, they can be used to evaluate shoreline behaviors. Refining average scalar slopes used in tidal corrections did not result in substantial decreases in uncertainty. Using lessons from this work to outline needs for regional implementation, initial setup time would be considerable, being on the order of weeks. However, once complete, shoreline detections and analyses are fast (on the order of minutes to hours) and achievable using a desktop computer.

Alaska, Florida, Massachusetts, Washington↗
USGS2024

Colored shaded relief bathymetry and acoustic backscatter of Ozette Lake, Washington

Offshore of the Pacific Northwest of the United States is the Cascadia Subduction Zone, a 1,000-kilometer-long tectonic boundary defined by a large fault, called a megathrust, that extends from the Mendocino Junction off northern California to the Nootka Fracture Zone off Vancouver Island, Canada (U.S. Geological Survey, 2023). The Juan de Fuca and Gorda oceanic plates to the west of this boundary subduct under the North America continental plate to the east. Several other smaller faults that cut through the North America plate crust also affect the region. Although their effects upon Ozette Lake are uncertain, geological evidence for past earthquakes, such as underwater landslides, may be found in Pacific Northwest lakes. Underwater landslides caused by past earthquakes should be well preserved in these relatively undisturbed lake environments. The floor of Ozette Lake, Washington, located along the Pacific coast of the United States, west of the Puget Sound region and about 140 kilometers east of the megathrust was mapped by the U.S. Geological Survey in July of 2019 to search for evidence of past earthquakes. Mapping was completed using a SWATHplus-M 234-kHz interferometric side scan sonar system pole-mounted on the U.S. Geological Survey research vessel San Lorenzo. The system collected full-coverage bathymetric and acoustic backscatter data that were processed to 2-meter spatial resolution (Dartnell and others, 2024). This two-map series displays the results of this mapping. A colored shaded relief bathymetry map (sheet 1) and an acoustic backscatter map (sheet 2) show the lake floor morphology and backscatter intensities, respectively, that can be analyzed for evidence of past earthquakes.

Washington↗
USGS2025

A generalized deep learning model to detect and classify volcano seismicity

Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] ( 10.1029/2024JB029194 ) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network ( VOISS-Net ) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.

Volcanica↗
USGS2021

Critical review of mercury methylation and methylmercury demethylation rate constants in aquatic sediments for biogeochemical modeling

Mercury is a toxin that causes neurological impairments in adults, is particularly harmful for fetuses and children, and is deadly in severe cases, making it a worldwide health concern. Methylmercury (MeHg) is the environmentally relevant form of mercury (Hg) because it biomagnifies along the food chain. Methylmercury is mainly produced in aquatic sediments via methylation of inorganic Hg (Hg(II)) and transformed back via demethylation. Because transformation rates determine MeHg concentrations, quantification of methylation and demethylation rates is needed to inform management of MeHg. Published rate constants for Hg(II) methylation ( 𝑘 𝑚 ) and MeHg demethylation ( 𝑘 𝑑 ) vary greatly, stemming partly from differences in experimental methods. We conducted a comprehensive review of rate laws, evaluated published rate constants, and performed biogeochemical simulations to assess variability in reported 𝑘 𝑚 and 𝑘 𝑑 . Based on selected studies employing the same pseudo-first-order rate law and similar experimental methods, we found that 𝑘 𝑚 = 0.04 ± 0.03 d −1 is a reasonable range for wetland sediments. Over a number of environments, maximum 𝑘 𝑑 was smaller at sites without Hg source ( 𝑘 𝑑 = 0.5 d −1 ) than at sites with identified Hg source ( 𝑘 𝑑 = 1.8 d −1 ). Larger variability and higher uncertainty in 𝑘 𝑑 compared to 𝑘 𝑚 highlight the need for more research on MeHg demethylation rates. This critical review: (a) aids the design of future experimental studies of 𝑘 𝑚 and 𝑘 𝑑 ; (b) provides guidance for comparing rate constants from different studies; (c) presents a biogeochemical reaction model to assess rate constants; and (d) informs selection of 𝑘 𝑚 and 𝑘 𝑑 values from the literature for use in model simulations.

Critical Reviews in Environmental Science and Tech↗
USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗
USGS2026

Postglacial ecosystem development of a hydrothermal landscape in Yellowstone National Park

The Yellowstone geo-ecosystem has been the subject of much research, but the ecological history of the Yellowstone Plateau volcanic field and its iconic geyser basins is less known. In this investigation, paleoenvironmental analyses of sediment cores from lakes in Lower Geyser Basin were compared with regional records and paleoclimate model simulations to reconstruct the vegetation, wildfire, limnology, hydrothermal dynamics, and climate drivers since deglaciation, 15,000 to 14,000 years ago. Pollen data from Lower Geyser Basin lakes reveal the strong influence of infertile rhyolitic soils on vegetation history: an initial late-glacial steppe was replaced by lodgepole pine forest from 12.8 to 11.0 ka, with little change in forest composition or cover thereafter despite changing climate. This stability contrasts with the more dynamic vegetation response on nonrhyolite substrates in the Yellowstone region where nutrient and moisture availability is greater. Highest wildfire activity and low lake nutrient levels in Lower Geyser Basin occurred from 12 to 4 ka, when summers were substantially warmer and drier and fire-inducing vapor pressure deficits were 29 to 56% higher. The hydrothermal history, inferred from sedimentary arsenic and cesium abundances, was spatially and temporally variable but lake-forming hydrothermal events align with periods of abundant moisture. Thus, long-term changes in wildfire, limnology, and, to some extent, hydrothermal activity were governed by insolation-driven climate variations, whereas the vegetation response was muted and constrained by geologic processes. These findings suggest that warmer, drier conditions in the future could result in less hydrothermal activity yet little change in forest cover across the Yellowstone Plateau volcanic field despite more wildfires.

Idaho, Montana, Wyoming↗
USGS2025

A scientific vision and roadmap for earthquake rupture forecast developments, a USGS perspective

We articulate a scientific vision and roadmap for the development of improved Earthquake Rupture Forecast models, which are one of the two main modeling components used in modern seismic hazard and risk analysis. One primary future objective is to provide fully time-dependent models that include both elastic rebound and spatiotemporal clustering nationwide, which is particularly important for shorter-term hazard and risk considerations (e.g., earthquake insurance products). We also discuss the importance and perennial challenges associated with quantifying epistemic uncertainties, including those associated with deformation-model slip rates, un-quantified sampling errors with respect to off-fault seismicity, and any spatial covariances. The need for more physics-based approaches is also emphasized, as is the benefit of adding model valuation (quantifying usefulness) to our verification and validation protocols. Given the multidisciplinary and system-level nature of this activity, modular design is critical. Future updates will also draw from best-available science by both the United States Geological Survey and the external community. The primary goal of this paper is to highlight plans that guide research and facilitate community engagement with model development, especially with respect to lowering the entry barrier for early career scientists and engineers. The paper is written so readers can focus on the sections that interest them most (see table of contents), with the Introduction and Discussion providing a stand-alone overview and summary.

Bulletin of the Seismological Society of America↗
USGS2026

Assessing environmental drivers of denitrification in restored riverine floodplains

Restoration of impaired floodplains is an increasingly prevalent strategy for alleviating water quality concerns and reducing downstream flooding at watershed scales. Floodplains temporarily store water and slow flow velocity to promote sedimentation during overbank flooding and remove inorganic nitrogen from floodwater and groundwater via denitrification. Evaluating the impacts of different restoration strategies on denitrification can inform more strategic investments into floodplain modifications that improve water quality outcomes. Our research investigates how denitrification rates in floodplains respond to environmental factors that are actionable from an engineering perspective through design and water resources management. We seasonally measured soil denitrification enzyme activity and various environmental characteristics in 4 floodplains with different restoration design and management approaches at the confluence of the Wabash and Tippecanoe Rivers in Indiana, United States. Our results showed that denitrification rates in an agricultural floodplain were significantly lower than in restored floodplains with native vegetation. Certain soil conditions characteristic of floodplain wetlands were associated with higher denitrification, particularly elevated total nitrogen, moisture, silt, and organic matter contents. Vegetation species composition was correlated with denitrification rates. This link may reflect the direct effects of vegetation on soil conditions, such as supplying labile organic carbon, or indirect effects, such as vegetation acting as an indicator of hydrologic regime and land use. Denitrification seasonally varied, peaking in winter when nitrate supply from rivers draining agricultural watersheds in the region is also high. Substrate limitation of soil denitrification enzyme activity was most significant during the summer when overbank flooding, which replenishes soil nitrogen stocks, rarely occurs. Our findings indicate that denitrification capacity will likely be maximized in riverine floodplains that are restored as wetlands with diverse native vegetation and enhanced hydrologic connectivity. Such restoration activities promote higher denitrification rates via elevated moisture, fine sediment deposition, and soil organic matter.

Tippecanoe River, Wabash River↗
USGS2026

Long-term intermittent connection between the western Snake River Plain and Columbia basin: A two-phased incision history of Hells Canyon

For more than a century, researchers have debated the route of the Snake River across the northern Cordillera and U.S. Pacific Northwest, including the associated incision history of Hells Canyon. Here, we use detrital zircon U-Pb provenance analysis of Miocene strata upstream and downstream of Hells Canyon to constrain the evolution in fluvial pathways over time. Downstream of Hells Canyon, we show that the ca. 10−6 Ma Clarkston Heights gravel was dominantly sourced from the nearby Salmon and Clearwater rivers but also with substantial input from drainages that now flow into the western Snake River Plain. These same western Snake River Plain drainages were contributing to time-equivalent Lake Idaho strata, upstream of Hells Canyon, indicating a Hells Canyon fluvial connection between the western Snake River Plain and Columbia basin before 6 Ma. Results from Lake Idaho strata suggest a two-phased lacustrine history in the western Snake River Plain: Before ca. 6.0 Ma, lake strata were derived from local tributaries, suggesting that the western Snake River Plain was isolated from the modern upper Snake River system. Between ca. 4.3 Ma and 2.2 Ma, the source area expanded to include eastern tributaries in conjunction with migration of high-standing topography of the Yellowstone hotspot. Our results challenge the long-held hypothesis of “capture” of the Snake River through Hells Canyon. Instead, we infer that Hells Canyon was a long-established route for outflow of lakes occupying the western Snake River Plain, possibly intermittently, during a ca. 10−2 Ma phase of slow regional incision, followed by rapid incision in Hells Canyon starting ca. 2 Ma in conjunction with erosion of the topographic barrier impounding Lake Idaho.

Idaho, Oregon↗