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887 records · Page 18Linked to original sources
USGS2025

Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona

Managed aquifer recharge is a widespread practice for storing water in the subsurface as groundwater. At a managed aquifer recharge facility in southern Arizona, groundwater-level and repeat microgravity data were collected to monitor aquifer response. These data were used to inform parameter identification for an unsaturated-zone flow model used to simulate the recharge process. The facility, the Southeast Houghton Artificial Recharge Project (SHARP), consists of 3 surface basins (about 27,600 square meters [6.8 acres] total surface area) where recycled water is distributed in recharge cycles lasting several months, with dry periods in between. During the study period, December 2020–December 2022, Tucson Water (the City of Tucson’s water utility) reported 6.56×10 6 cubic meters of water (5,320 acre-feet) recharged. Monitoring included groundwater-level observations at 3 monitoring wells and repeat microgravity measurements at as many as 22 locations (some stations were destroyed between surveys). Six gravity surveys were carried out using absolute- and relative-gravity meters. Large gravity increases, more than 250 microgals, were observed during the first repeat survey, 3.5 months after the start of recharge, but only in the immediate vicinity of the recharge basins. Data show that water moved downward to the water table, and storage changes in the unsaturated zone away from the facility were likely minimal. Gravity decreased at stations more than 1 kilometer from the facility, consistent with regional groundwater-level changes. Groundwater-level increases in wells adjacent to the recharge basins began 2 months after the second repeat gravity survey, and 5.5 months after recharge began. Unsaturated-zone flow modeling was carried out using software that simulates water movement and parameter estimation. Model calibration was carried out by minimizing an objective function calculated from the differences between simulated and observed groundwater levels, and between simulated and observed repeat microgravity data. Including repeat microgravity data in the objective function reduced the uncertainty in estimated parameter values for saturated hydraulic conductivity and saturated water content. Modeling indicated that the unsaturated zone between the recharge basins and the water table does not become saturated even after 685 days of simulated infiltration. This gradual wetting may account for increasing infiltration rates over time, as hydraulic conductivity increases with increasing water content. Unsaturated-zone water content decreased rapidly between recharge cycles. Model-simulated groundwater mounding extended about 1 kilometer from the center of SHARP after the 685-day period following the onset of recharge.

Arizona↗
USGS2024

A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (𝑀 w ) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from 𝑀 w 3.5–4.5 earthquakes but includes three well-recorded 𝑀 w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (𝑉 S30 ) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The 𝑉 S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments.

California↗
USGS2024

Generalized potentiometric maps of the Fort Union, Hell Creek, and Fox Hills aquifers within the Standing Rock Reservation

Generalized potentiometric surfaces of the Fort Union, Hell Creek, and Fox Hills aquifers were constructed to assess the groundwater resources of the Standing Rock Reservation. Additionally, this information can provide water managers with tools and data to effectively manage water resources in the future. Previous studies that mapped the geology and hydrogeology of the area at differing scales were used to confirm in which aquifer the study wells were completed. Water-level data from wells are provided by the U.S. Geological Survey Groundwater System Inventory database, the South Dakota Department of Agriculture and Natural Resources, and the North Dakota Department of Water Resources. Hydrographs were constructed for five selected observation wells to evaluate historical water-level fluctuations and trends. Hydrographs for the Hell Creek aquifer showed a flat trend with a rise in 2020. Hydrographs for the deeper Fox Hills aquifer showed that water levels fluctuated in response to climatic conditions and demonstrated an increasing trend in water-level elevations starting in 2010. Hydrographs were not constructed for any wells completed in the Fort Union Formation because none of the wells had continuous long-term measurements. Generalized potentiometric surfaces, constructed from interpolating water-level elevations, gave insight into groundwater flow directions. Groundwater in the Fort Union aquifer likely flows radially outward from the northwest part of the study area to the northeast and south-southeast parts. Groundwater in the Hell Creek aquifer generally flows from higher elevations in the northwest towards lower areas, where surface-water tributaries have incised into the aquifer. Groundwater in the Fox Hills aquifer likely flows from higher elevations in the west, southwest, and central parts of the study area towards the valleys of the Grand River and Missouri River. Most wells used for constructing potentiometric maps had only one recorded water-level measurement from drillers at the time of well construction. These measurements are often subject to error because the well is still recovering and because of spatial limitations of data availability. Also, because single water-level measurements were recorded at different points in time, additional uncertainty is introduced by fluctuating climatic conditions effect on water levels. Potentiometric map interpretation limitations are a result of areas with sparse data. Limitations also arise from potentiometric surfaces generalizing a complex and dynamic hydrogeologic system; however, the generalized potentiometric surface maps can be used to assist water managers and can help prioritize locations for future monitoring in areas with high uncertainty from sparse existing data.

North Dakota, South Dakota↗
USGS2026

Spatio-temporal modeling for assessing geoenergy resources: A workflow applied to gas in place variation in coal beds

The ability to estimate spatio-temporal changes in hydrocarbon reservoir properties and energy resources within pore volumes is essential for optimizing production, reservoir management, geologic energy storage, and safety in underground mining operations. In coal seams, predicting remaining methane gas-in-place (GIP) is critical for quantifying producible gas and improving mine safety and productivity through effective ventilation planning. Although such changes are commonly evaluated using physics-based numerical simulation models, these approaches often require extensive data, calibration effort, and time. This study presents a spatio-temporal geostatistical modeling approach that bridges the gap between purely spatial models and full numerical simulations. The method is applied to a case study of coal seam degasification in the Mary Lee coal group, Black Warrior Basin, Alabama, USA, to estimate GIP evolution over time within a selected mining district. The analysis uses published data from prior natural gas production history-matching of degasification using vertical wells. Empirical spatial and temporal statistics were calculated for reservoir pressure and water saturation, and spatio-temporal variogram models were fitted to experimental variograms. These models provided the structural basis for spatio-temporal kriging, integrated with spatial estimates of time-invariant parameters (porosity, density, and thickness) to estimate GIP. This approach enabled estimation of GIP changes over time, including periods without data. Boxplots of GIP estimates indicated systematic depletion and decreasing spatial variability, reflecting the impacts of degasification. Comparison with cumulative gas production from empirical well records showed approximately 85% agreement based on a relative similarity metric. Spatio-temporal GIP estimates were also used to estimate methane emissions to longwall ventilation systems and compared with reported emissions from the U.S. EPA Greenhouse Gas Reporting Program, showing similar distributions (≈80%) given data limitations. Overall, this integrated modeling approach provides time-dependent GIP estimates with broader implications for resource assessment applications.

Alabama↗
USGS2025

Analyzing multi-year nitrate concentration evolution in Alabama aquatic systems using a machine learning model

Rising nitrate contamination in water systems poses significant risks to public health and ecosystem stability, necessitating advanced modeling to understand nitrate dynamics more accurately. This study applies the long short-term memory (LSTM) modeling to investigate the hydrologic and environmental factors influencing nitrate concentration dynamics in rivers and aquifers across the state of Alabama in the southeast of the United States. By integrating dynamic data such as streamflow and groundwater levels with static catchment attributes, the machine learning model identifies primary drivers of nitrate fluctuations, offering detailed insights into the complex interactions affecting multi-year nitrate concentrations in natural aquatic systems. In addition, a novel LSTM-based approach utilizes synthetic surface water nitrate data to predict groundwater nitrate levels, helping to address monitoring gaps in aquifers connected to these rivers. This method reveals potential correlations between surface water and groundwater nitrate dynamics, which is particularly meaningful given the lack of water quality observations in many aquifers. Field applications further show that, while the LSTM model effectively captures seasonal trends, limitations in representing extreme nitrate events suggest areas for further refinement. These findings contribute to data-driven water quality management, enhancing understanding of nitrate behavior in interconnected water systems.

Alabama↗
USGS2025

The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab

The southernmost portion of the Cascadia Subduction zone in Northern California produces high rates of moderate and large earthquakes owing to subduction of the Gorda slab and deformation associated with the Mendocino Triple Junction. Distributed Acoustic Sensing (DAS) is rapidly advancing as a method for detecting earthquakes and imaging crustal structure. We have begun a long-term DAS monitoring experiment on buried telecom fiber in Arcata, California, with the goal of increasing the available recordings of moderate to large earthquakes as well as imaging seismogenic structures. We have recorded over a year's worth of data, including most aftershocks of the 2022 M w 6.4 Ferndale earthquake, though not the mainshock itself. The dataset includes numerous magnitude 3.5 and larger earthquakes including the 2023/01/01 M w 5.4 Rio Dell earthquake. Here we present initial results comparing an earthquake detection algorithm, run in real-time on the processing unit of the interrogator system, with both the ShakeAlert earthquake early warning system as well as a post-processed earthquake catalog developed with deep-learning phase-picker algorithms. The rapid onboard processing of the detector demonstrates the potential utility of DAS-based edge computing for earthquake early warning. We also verify the quality of the strain waveforms both in terms of peak amplitudes and waveform similarity using about five months of nodal seismometer data. These instruments were deployed roughly every 300 m along the ~15km long cable and validate large variations in peak strain over short distances that are seen in the DAS data. All data from time windows surrounding both the local and teleseismic earthquakes are publicly available, which will improve our understanding of both the performance of DAS systems in moderate earthquakes and earthquake hazards associated with the Gorda subduction zone.

California↗
USGS2025

Hydrogeology and groundwater quality in the Snake River alluvial aquifer at Jackson Hole Airport, Wyoming, 2011–20

The Snake River alluvial aquifer underlying the Jackson Hole Airport (JHA) in northwest Wyoming is an important source of water used for domestic, commercial, and irrigation purposes by the airport and nearby residents. The U.S. Geological Survey, in response to previously identified water-quality concerns in the area, monitored and evaluated changes in hydrogeologic characteristics and groundwater-quality conditions of the alluvial aquifer during 2011–20. During that period, the Jackson Hole Airport made several changes that potentially improved water quality at and downgradient from the airport. Well, water level, and hydrogeologic data were collected from the alluvial aquifer to identify hydrogeologic characteristic and groundwater quality changes. Additionally, results of statistical tests were applied to water-quality results to evaluate trends in selected physical properties and constituent concentrations with time. The trends of those data show that water quality did improve overall during the study period compared to previously collected data. Presumably, these trends are in response to the changes in the aircraft deicing/anti-icing fluid (ADAF) formulation used by the JHA, the many JHA infrastructure improvements made during 2011–20, the degradation of existing ADAFs in subsurface soils and groundwater, or some combination of these possibilities.

Wyoming↗
USGS2024

2024 Crustal Deformation Modeling Workshop report

The 2024 Crustal Deformation Modeling Workshop was held June 10–14 at the Colorado School of Mines. The workshop included two days of tutorials on using PyLith for crustal deformation modeling, followed by three days of science talks and discussions. The workshop focused on four primary themes: ● Constraining long-term fault slip rates and their uncertainties using geodetic and geologic data; ● Earthquake cycle modeling with a focus on constraining models using seismic and geodetic data; ● Interaction of fluids and faulting; and ● Separating contributions of surface loading and tectonic loading in crustal deformation. The complete agenda is available on the CIG website.

Conference Paper↗
USGS2026

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation↗
USGS2024

The U.S. Geological Survey Ohio Water Microbiology Laboratory

The U.S. Geological Survey Ohio Water Microbiology Laboratory is a part of the Ohio-Kentucky-Indiana Water Science Center. The mission of the laboratory is to provide microbiological data of public health significance from surface waters, groundwaters, and sediments for a variety of study objectives. The laboratory conducts internal projects, works with external cooperators, and assists U.S. Geological Survey offices and National programs. The laboratory offers guidance, study design, and data interpretation expertise to collaborators, all following rigorous quality control and quality assurance procedures.

Fact Sheet↗
USGS2024

Shallow faulting and folding beneath south‐central Seattle, Washington State, from land‐based high‐resolution seismic‐reflection imaging

The geologic framework of the Seattle fault zone (SFZ) has been extensively studied, but the structure and fault strand locations in the central portion of the fault zone through the city of Seattle have remained controversial. Much of what is known about the SFZ has come from light detection and ranging (lidar)‐topographic surveys and paleoseismic investigations of fault scarps primarily west of Puget Sound, regional gravity and aeromagnetic modeling, and multiscale marine seismic imaging in waters both west and east of Seattle. We analyze ∼24 km of land‐based P ‐wave seismic‐reflection data that fill in a critical gap in our understanding of the SFZ beneath the urban areas of West Seattle, south‐central Seattle, and Mercer Island. These data image deformed strata in the upper 1 km, including upwarped Tertiary rock and younger sediments. Collectively, these data provide evidence for multiple Quaternary‐active thrust faults, back thrusts, and sub‐basins within the SFZ beneath the city of Seattle. The results indicate that multiple and potentially active back thrusts in the upper ∼500 m extend across the length of the SFZ and the entire urban corridor that may be analogous to those on Bainbridge Island west of Puget Sound.

Washington↗
USGS2026

Subsurface water ice mapping on Mars: A probabilistic approach

Subsurface water ice deposits on Mars are an important resource for potential future human exploration. They are also an indicator of the planet’s past climate. However, the distribution of subsurface water ice in Mars’s midlatitudes is uncertain because spacecraft imagery cannot directly observe subsurface ice in most cases. Various spacecraft remote sensing instruments are sensitive to subsurface water ice, including thermal imaging spectrometers, radar sounders, and neutron spectrometers. Geomorphic analyses of images can also implicate subsurface ice. Building upon the data products from the Mars Subsurface Water Ice Mapping project, we provide a probabilistic framework to jointly interpret existing data and estimate the likelihood of subsurface water ice in the Martian midlatitudes between 60 ∘ S and 60 ∘ N with uncertainty. Broadly, we find that near-surface ice is likely present poleward of ∼45 ∘ in both the northern and southern hemispheres. However, closer to the equator, existing remote sensing data cannot uniquely constrain the presence of subsurface water ice. Our probabilistic results provide a framework for quantifying the abundance of ice on Mars, and our uncertainty estimates allow future analysis and exploration to target regions of high uncertainty.

Planetary Science Journal↗
USGS2025

Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective

Aeromagnetic and magnetotelluric (MT) data are used to better understand the geology and mineral resources near the Stibnite-Yellow Pine mining district in central Idaho. The reduced-to-pole (RTP) transformation of regional-scale aeromagnetic data shows that allochthonous island-arc rocks west of the Salmon River suture are significantly more magnetic than the Laurentian continental rocks east of the suture and that the granitoids of the Idaho batholith have moderate to low magnetization in both early, metaluminous, and late, peraluminous phases. Application of tilt derivative to aeromagnetic data highlights major crustal-scale structures. The 5-km upward continued magnetic data indicate island-arc rocks have deep magnetic sources. The 110-km-long MT profile images resistivity structure to depths around 30 km. At shallow depths, resistivity corresponds to mapped geologic units, with moderate resistivities underlying volcanic and roof-pendant metasedimentary rocks and moderate to high resistivities occurring beneath the Idaho batholith. Crustal-scale moderate resistivities beneath the suture image the results of tectonomagmatic processes that accompanied suturing and translating allochthonous terranes. Low resistivity values beneath and fringing the batholith are derived from metasedimentary rocks that may have served as a melt source and reductant during melt generation and provided metals during later ore formation. In the Stibnite-Yellow Pine mining district, a high-resolution aeromagnetic compilation is shown to correlate with mapped lithologies and mineral deposit-related structures. The RTP transform distinguishes magnetic and nonmagnetic granitoid phases of the Idaho batholith. The tilt derivative highlights metasedimentary rocks, some of which are favorable ore hosts. The Meadow Creek fault hosts the Stibnite and Hangar Flats deposits and is imaged as a magnetic low due to hydrothermal alteration. Reconstructions of magnetic anomaly offsets and orebodies indicate around 3 km of post-95 Ma dextral separation, with some or all of the offset inferred to postdate the main Au mineralization episode (61–66 Ma).

Idaho↗
USGS2025

Estimating agricultural irrigation water consumption for the High Plains aquifer region with integrated energy- and water-balance evapotranspiration modeling approaches

Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. Conventionally, water use data are created based on reports and surveys from water users, whereas manual records may not be complete due to lacking flow meters, measurement gaps, inconsistent methods across regions, and time- and cost-consuming data processing. Alternatively, spatially explicit estimation of irrigation water use can be conducted efficiently using remote sensing evapotranspiration (ET) modeling approaches. In this study, we created a gridded blue water evapotranspiration (BWET) dataset to estimate historical irrigation water consumption (1986 – 2020) in the croplands across the United States High Plains aquifer region. The BWET data were generated by integrating an energy-balance ET model [Operational Simplified Surface Energy Balance model (SSEBop)] and a water-balance ET model [Vegetation ET model (VegET)]. BWET in croplands indicates crop consumptive use of irrigation water extracted from surface water and groundwater resources. The BWET estimates were compared with reported irrigation water use data for all counties within the aquifer region. The results revealed high agreement between growing season (May – September) BWET and annual water withdrawal at county level. Specifically, correlation coefficients of volumetric BWET and water withdrawal were 0.90 and 0.96, respectively, for the entire aquifer region and western Kansas. The timeseries of BWET and water withdrawal showed similar temporal trends and high covariations. The BWET estimates were systematically lower than the water withdrawal measurements, which was primarily attributed to blue water losses in the irrigation system. The irrigation efficiency, calculated as the ratio of BWET to water withdrawal depth, was 0.57 and 0.74 for the entire aquifer region and western Kansas, respectively. This study demonstrates the capability of using satellite-based ET models (e.g., SSEBop and VegET) to efficiently estimate crop water consumption and evaluate irrigation efficiency at landscape, county, and regional scales.

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗
USGS2026

Hydrogeologic conceptualization of the Arroyos subarea and Northeast Air Force Research Laboratory subarea of the Air Force Research Laboratory, Edwards Air Force Base, Antelope Valley, California, 2017–21

Research and testing within the Air Force Research Laboratory at Edwards Air Force Base in the southwestern Mojave Desert has been conducted since the 1950s. This testing requires large quantities of groundwater for cooling and operations involving hazardous constituents that have entered the groundwater. To better understand the potential movement of contaminants through the groundwater system, the U.S. Geological Survey entered into a cooperative agreement with the U.S. Air Force Civil Engineer Center with the purpose of (1) gaining a more detailed understanding of the hydraulic connection between the unconsolidated basin-fill sediment and the underlying weathered and crystalline bedrock and (2) investigating faults and their potential effect on groundwater flow. This study was specific to the Arroyos subarea and Northeast Air Force Research Laboratory subarea of the Air Force Research Laboratory. The refined hydrogeologic characterization was derived by evaluating surface geologic maps, a regional gravity model, new subsurface geophysical surveys, lithology data from boreholes, and groundwater-level data. Refinement of the hydrogeologic characterization of the study area involved developing a map of basin-fill sediment thickness, estimating the geometry and depth to bedrock, determining the presence of weathered bedrock material, and identifying the location of faults and subsurface structures. The thickness of basin-fill sediment was derived from a regional gravity model. Basin-fill sediment ranges from less than 20 feet (ft) thick to about 150 ft thick and increases substantially toward a deep structural basin in the northwestern part of the study area. The top of bedrock estimated from the new surface geophysical surveys is generally deeper than the top of bedrock from the regional gravity model. These differences in interpreted bedrock tops indicate that there may be a zone of weathered bedrock in the subsurface, overlying crystalline bedrock. Additional subsurface data evaluating the geometry and thickness of weathered bedrock are necessary for a comprehensive evaluation of weathered bedrock in the study area. Previously unmapped extensions of the Leuhman Fault, Spring Fault Zone, and Boron Gate Fault were identified in the new surface geophysical surveys. Evaluation of groundwater flow between bedrock and basin-fill sediment, and the effects of faults on groundwater flow, was done using groundwater-level data from 2020. The groundwater table was in crystalline bedrock throughout most of the Arroyos and Northeast Air Force Research Laboratory subareas, with a few exceptions where it was in basin-fill sediment and weathered bedrock. Basin-fill sediment, and likely weathered bedrock, was partially saturated in parts of the study area where basin-fill sediment was as thick as 150 ft. Weathered bedrock material may be present near the Spring Fault Zone, and if so, was likely saturated in 2020. The groundwater-level data near and within Spring Fault Zone indicate that the Spring Fault Zone acts as a vertical-along-strike conduit for, and as an across-strike impediment to, groundwater flow. In addition, steep groundwater-level gradients in the southeastern part of the study area indicate that a subsurface structure affecting groundwater flow could be related to the Leuhman Fault. Sufficient groundwater-level data were not available to conclusively determine if the Arroyos, Rich, and Boron Gate Faults, and their inferred extensions from the geophysical surveys, affect the movement or direction of groundwater flow.

California↗
USGS2025

ARCHI: A new R package for automated imputation of regionally correlated hydrologic records

Missing data in hydrological records can limit resource assessment, process understanding, and predictive modeling. Here, we present ARCHI (Automated Regional Correlation Analysis for Hydrologic Record Imputation), a new, open-source software package in R designed to aggregate, impute, cluster, and visualize regionally correlated hydrologic records. ARCHI imputes missing data in “target” records by linear regression using more complete “reference” records as predictors. Automated imputation is implemented using a novel, iterative algorithm that allows each site to be considered a target or reference for regression, growing the pool of complete references with each imputed record until viable gap-filling ceases. Users can limit artifacts from spurious correlations by specifying model-acceptance criteria and applying geospatial, correlation, and group-based filters to control reference selection. ARCHI provides additional functions for visualizing results, clustering records with similar correlation structures, evaluating holdout data, and interactive parameterization with an accessible and intuitive graphical user interface (GUI). This methods brief provides an overview of the ARCHI package, modeling guidelines, and benchmarking on two regional groundwater-level datasets from the Central Valley, CA and Long Island, NY. We evaluate ARCHI alongside widely used multivariate imputation software to highlight and contextualize its computational efficiency, imputation accuracy, and model transparency when applied to large, groundwater-level datasets.

California, New York↗
USGS2026

Tectonic controls on volcanism and associated hydrothermal activity in a sediment-dominated mid-ocean ridge; Escanaba Trough

Mid-ocean ridges, the Earth's most extensive volcanic system, exhibit unique characteristics in sediment-dominant environments. Thick sediment cover insulates the crust and channels fluid along pathways that can lead to the formation of distinct crustal alteration patterns, exceptionally large mineral deposits, and specialized chemosynthetic ecosystems. This study presents an interdisciplinary investigation into the tectonics of the Escanaba Trough, a heavily sedimented axial valley at the southern Gorda Ridge in the Northeast Pacific Ocean. A primary challenge in such environments is overcoming the masking effect of thick sediments on basement structures that control magmatic and hydrothermal activity. We address this by employing three-dimensional (3D) magnetic modeling of high-resolution near-seafloor magnetic data collected by an autonomous underwater vehicle (AUV). The 2022 surveys with AUV Sentry provided data for 3D magnetic susceptibility models, refining our understanding of the geometry of sub-sediment laccoliths/saucer-shaped sills and hydrothermal alteration. In conjunction with a new 1:100,000 scale lithostratigraphic map, we outline the tectonic controls on the emplacement of Escanaba Trough's three main volcanic centers, characterize the geometry of its spreading segments, and provide volumetric data on the distribution of sub-sediment volcanism in the southern Gorda Ridge.

Escanaba Trough, Pacific Ocean↗
USGS2026

Distributed faulting of the northern West Napa Fault Zone in Napa Valley, California

Mapped surface ruptures from the 24 August 2014 M w 6.0 South Napa earthquake in the Napa Valley, California, show a 2‐km‐wide zone of distributed faulting in the southern and central West Napa fault zone (WNFZ). In the northern WNFZ at Hendry Winery (HW), however, the mapped 2014 surface ruptures encompass an ∼100‐m‐wide zone, implying significant narrowing of the near‐surface fault zone to the north. We present a tomographic shear‐wave velocity ( ⁠⁠ V S ) model and guided‐wave data that indicate the northern WNFZ is at least 400‐m wide, with multiple near‐surface fault traces. Our V S model shows that the 2014 surface ruptures are underlain by discrete low‐velocity zones (LVZs), and coincident guided‐wave data show that the LVZs carry fault‐zone guided waves. If nearby (<500 m) mapped faults to the east of HW are part of the WNFZ, the entire WNFZ is more than 1 km wide in the northern Napa Valley. WNFZ guided waves travel up to 38% slower than S body waves, and low‐strain guided‐wave shaking is up to five times stronger than the associated body‐wave shaking. Our data suggest that guided waves, traveling along distributed faults, may result in an increased shaking hazard over a 1‐km‐wide area of the northern Napa Valley during future significant earthquakes. In places, the 2014 surface ruptures were difficult to find one year after the earthquake, and paleoseismic trenching showed only weak evidence for faulting, which may not have been identified in trenches if the locations of the 2014 surface ruptures had not been previously mapped ( Prentice et al. , 2015 ). Guided‐wave and V S tomography data, however, show strong evidence for faulting beneath the 2014 surface ruptures and at locations to the east. Although paleoseismic trenching is the gold standard for identifying near‐surface faulting, methods such as peak ground velocities of guided waves may better identify immature near‐surface fault traces.

California↗