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Article: explore 974 source-linked works published from 1974 to 2026, with original documents and citations.

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Sources: usgs. Collection updated 2026-09-14. Counts describe this index, not the complete source archives.

USGS2025

SURF: An automated method for building nonplanar 3D fault models from earthquake hypocenters

Accurately characterizing 3D fault geometry is vital for improving our understanding of earthquake behavior and informing the development of seismic hazard models. Despite their importance, subsurface fault structures tend to be poorly constrained because of limitations in observational data. Improvements to the seismic networks and earthquake detection algorithms have increased the precision and volume of earthquake catalogs, which help illuminate detailed subsurface fault structure and provide the most direct information available about fault geometries at depth. We present a Python package to automate generating 3D fault geometries directly from hypocentral seismicity patterns. This method begins with clustering events based on their spatial density, identifying coherent patterns. Nearby clusters are then merged based on the similarity of their orientations. We fit nonplanar surfaces using support vector regression to balance surface accuracy with minimal deviations from planarity. The fault models are output as quadrilateral meshes at user‐defined resolution. In the process of generating the 3D fault surfaces, we compute the spatial density of seismicity around the surface and the planarity as quantitative metrics of the model outputs. As a proof of concept, we apply this approach to the San Andreas–Calaveras fault junction region and the 2019 Ridgecrest earthquake sequence, both in California, which contain complex subparallel faults well defined at the Earth’s surface and abundant microseismicity. These case studies demonstrate the method’s ability to model complex fault structures, including long continuous fault surfaces, crossing faults, variably dipping segments, and subparallel faults. We test the method on both standard network catalogs and double‐difference relocated catalogs. We find that our seismicity‐based fault model results align with published 3D models that incorporate additional constraints and interpretations ( Plesch et al. , 2020 ; Aagaard and Hirakawa, 2021 ). This workflow provides a low‐user‐input solution for estimating fault geometries at depth from earthquake catalogs.

California↗

USGS2025

Dating a medieval tsunami with uranium-series techniques on Caribbean corals

Uranium-series dates from coral boulders constrain the timing of a medieval tsunami from the Puerto Rico Trench. Previously reported evidence for this tsunami includes hundreds of coral boulders that came to rest hundreds of meters inland on Anegada, British Virgin Islands. New U-series dates on these coral boulders provide limiting dates for the tsunami. The narrowest limits were by dating interior bands of a coral that retains the hemispherical form of a living coral colony, and which include adjustments for the number of annual density band couplets between the dated samples and the boulder exteriors. By those limits, the tsunami dates between 1381 and 1391 CE, and likely occurred during summer or fall. The tsunami is important as the only reported sign that the eastern Puerto Rico Trench has produced a great earthquake. The dating may aid in defining the earthquake source and in communicating tsunami hazards.

British Virgin Islands, Puerto Rico↗

USGS2025

Submarine groundwater discharge creates cold‐water refugia that can mitigate exposure of heat stress in nearshore corals

Coral reef mortality around the world is accelerating due to human activities and rising sea temperatures that cause bleaching, which is expected to become more frequent. Our ability to predict which corals will be most resilient, however, remains limited due to insufficient information characterizing nearshore temperature and habitat conditions. In this study, we examine how submarine groundwater discharge (SGD) reduces nearshore water temperatures and exposure of corals to heat stress, complementing the understanding that SGD can adversely affect coral when it contains elevated nutrient concentrations. Data from fixed nearshore sensors and vertical depth profiles along ~100 km of the western shoreline of the Island of Hawai’i from 2003 to 2014 demonstrate that submarine groundwater discharge (SGD) can reduce nearshore water temperatures by 1 °C–5°C and create estuarine-like conditions with salinities as low as 20 PSU, where the prevalent coral species, Pocillopora meandrina, Porites lobata , and Montipora capitata , thrive. Time-series temperature records reveal that exposure to high ambient ocean temperatures, which are known to initiate bleaching events, are reduced up to 5%–46% of the time. Coral health surveys indicated coral bleaching in response to moderately high annual temperatures in 2010 and 2011, with more colonies affected farther from cold, SGD-fed waters. Synthesis of these results, along with coral response data following the more extreme marine heat wave of 2014–2015, demonstrates lower coral loss and greater coral recovery near groundwater seeps, particularly those with higher flux and influence on reducing nearshore water temperatures. Our results demonstrate that SGD may therefore provide a beneficial ecosystem service and enhance coral reef resilience, particularly where human-related nutrient additions to groundwater can be mitigated. The implications of our findings are relevant across tropical coasts where groundwater inputs can be substantial, such as the Caribbean and Indo-Pacific, and contribute to improving our understanding of coral sensitivity to gradients in temperature and nutrient stress. Improved management of groundwater resources could thus be vital to local–regional strategies for mitigating future heat stress.

Hawaii↗

USGS2025

Mapping a Carrington storm

A map is presented of median 1-min-resolution peak geoelectric-field strength across the United States as would be induced by magnetic storms as intense as the 2 September 1859 Carrington storm. The map is constructed from two data sets: Magnetometer time series from 22 ground-based observatories recording 40 magnetic storms, and surface impedance tensors derived from magnetotelluric measurements acquired at 1616 survey sites across the contiguous United States. Carrington-class storm geoelectric fields are likely to be very strong in the United States East and Midwest; > 5.00 V/km at many places. In Virginia, strengths would likely range from 30.30 V/km, with a 68% confidence interval of [19.44,47.20] V/km, to as low as 0.05 [0.03,0.07] V/km. Comparison of model geopotentials with those measured on 30 long lines, indicates errors of about 18%. A Carrington-class storm would likely induce geoelectric fields with strengths 55% greater than for the 13–14 March 1989 storm.

contiguous United States↗

USGS2025

RioM-1: A new calcite reference material for U-Pb LA-ICP-MS geochronology

Determining absolute ages of carbonate diagenesis, faulting, fossil formation, speleothem growth, carbonate-hosted hydrocarbon deposits, vein mineralisation and hydrothermal alteration has become increasingly accessible through LA-ICP-MS U-Pb dating of calcite, complementing traditional isotope dilution methods still applicable to certain materials (e.g., speleothems via micro-drilling). However, well-calibrated reference materials for LA-ICP-MS calcite geochronology remain scarce. Here, we characterise the Rio Maior calcite, designated ‘RioM-1’, as a potential reference material for U-Pb dating by LA-ICP-MS. Fragments (0.1 to 1 cm 3 ) from a single scalenohedral crystal were analysed by ID-TIMS (U-Pb), LA-ICP-MS (U-Pb and 87 Sr/ 86 Sr), and SIMS (O isotopes). RioM-1 displays high U mass fraction and low, though variable, proportions of common Pb. Combined ID-TIMS analyses from two independent laboratories yielded a Tera-Wasserburg lower intercept date of 63.93 ± 0.11 Ma (2 s , MSWD = 1.3, n = 16). LA-ICP-MS U-Pb data from three independent laboratories are concordant with the TIMS age, producing a pooled date of 64.10 ± 0.12/1.2 Ma (2 s , MSWD = 7.7, n = 708) and an initial 207 Pb/ 206 Pb ratio of 0.85 ± 0.01. Other calcite reference materials, when normalised to RioM-1, yielded dates within uncertainty of their published values. SIMS measurements returned a mean 18 O/ 16 O of 0.002044450 ± 181 (1 s ) and δ 18 O SMOW of 19.57 ± 0.92‰ (1 s ), while LA-ICP-MS strontium isotope measurement yielded a mean 87 Sr/ 86 Sr of 0.708177 ± 9 (2 s ).

Geostandards and Geoanalytical Research↗

USGS2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

Comptes Rendus. Géoscience↗

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↗

USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗

USGS2025

Widespread anhydrite saturation in Laramide-age arc magmas of southwestern USA

Anhydrite is considered a rare mineral phase in magmas, with only ∼33 documented occurrences worldwide. However, anhydrite readily decomposes in the near-surface environment, making it difficult to recognize its former presence in rocks collected at or near Earth’s surface. In such samples, only small anhydrite inclusions fully shielded within other minerals can have survived. During a recent field trip to the southwestern USA, we sampled 17 Laramide-age (ca. 40−80 Ma) magma systems, most of which are associated with porphyry copper deposits. A systematic search for anhydrite inclusions preserved within apatite, amphibole, plagioclase, and quartz phenocrysts in ∼100 rock samples by optical microscopy and Raman spectroscopy revealed that each of these 17 magma systems was at least temporarily anhydrite-saturated. Also, most previously identified magmatic anhydrite-bearing intrusions are associated with porphyry copper deposits, and both intrusive and volcanic rocks containing magmatic anhydrite show high Sr/Y ratios. These observations suggest that anhydrite saturation and porphyry copper formation are linked via magma fractionation at high pressure. Compared to average arc magmas, anhydrite-bearing magmas are unusually oxidized and sulfur-rich and seem to also be unusually water-rich. Hence, our preferred interpretation is that magma generation and/or fractionation at high pressure promotes the formation of superhydrous and oxidized magmas, which in turn promotes high sulfur contents and ultimately the precipitation of anhydrite. The high mineralization potential of these magmas does not need to result from their high sulfur content but could be caused by other properties of high-pressure magmas.

Arizona, New Mexico↗

USGS2025

Late Pleistocene kinematics of the Great Southern Puerto Rico Fault Zone, Puerto Rico

Several onshore faults in southern Puerto Rico have recently been recognized as Quaternary active. However, the kinematics of these faults, particularly any lateral component, remain largely unconstrained. It is difficult to characterize low strain‐rate faults, partially due to extensive erosional and anthropogenic landscape modification, steep relief, and frequent landsliding, limiting the preservation of geomorphic features that could serve as recorders of fault motion. Here, we constrain the kinematics along sections of the Great Southern Puerto Rico Fault Zone (GSPRFZ) on the southern coastal plain of Puerto Rico. We integrate ∼1‐m‐resolution light detection and ranging (lidar)‐derived topography, historical air photos, and field mapping to identify a series of ∼50–1200‐m‐long fault scarps and lineaments that trend northwest–southeast and extend for ≥25 km across the southern coastal plain. Fault scarps are primarily south facing, cut across topography, and displace Quaternary deposits and landforms. We document multiple offset geomorphic markers, including channel thalwegs and interfluves formed in deposits previously mapped as Quaternary piedmont alluvial plain. We observe both vertical (south‐side‐down) and right‐lateral meter‐scale displacements, which indicate that the GSPRFZ accommodates right‐lateral oblique motion in the late Pleistocene, consistent with northeast motion of the Puerto Rico and the Virgin Islands microplate away from the Hispaniola block.

Puerto Rico↗

USGS2025

Earthquake magnitude and source parameter estimation with a distributed acoustic sensing dataset in the Gorda subduction zone

Distributed acoustic sensing (DAS) systems offer a cost‐effective way to create large‐scale strainmeter arrays for seismological applications using fiber‐optic cables. DAS‐based strain measurements are known to be influenced by various factors, bringing into question their general reliability for accurate earthquake characterization. A 15‐km‐long DAS deployment in northern California was operational within 3 days of the 2022 M w 6.4 Ferndale earthquake and ran continuously throughout the aftershock sequence. We utilize these aftershock data to validate DAS‐based strain measurements in two ways. We first test the accuracy of DAS‐based magnitude estimates from peak dynamic strains by comparing them with magnitude and attenuation scaling relations derived independently from traditional borehole strainmeter (BSM) data. We demonstrate that DAS‐based magnitudes are comparable to BSM‐based magnitudes when corrections for variations in site response along the fiber‐optic cable are properly made. Magnitude errors are spatially correlated, potentially because of factors such as finite‐fault effects (e.g., stress drop) or more complex, unmodeled path attenuation or because of wave propagation effects in heterogeneous media. We then apply more advanced source characterization methodology to the DAS data using a time‐domain empirical Green’s function (EGF) deconvolution approach to measure details of the moment rate history. The EGF approach using DAS data depends on careful treatment of distorting factors such as anthropogenic sources of noise and optical phase wrapping but successfully isolates source spectra for moderate‐magnitude earthquakes: source spectral ratios obtained from DAS data, broadband seismometer data, and BSM data in the same region show consistent results, revealing differences in directivity and spectral shape among earthquakes. Although further research is needed to refine source‐time‐function estimation techniques for DAS data, particularly for larger magnitude events, these case studies demonstrate the clear potential of DAS for earthquake source characterization.

California↗

USGS2025

Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks

The estimated ultimate recovery (EUR) is an important parameter for forecasting oil and gas production and informing decisions regarding field development strategies. In this study, we combined site-specific geologic, completion, and operational parameters with the predictive capabilities of machine learning (ML) models to predict EURs of the wells for the Eagle Ford Marl Continuous Oil Assessment Unit. We developed an extensive dataset of wells that have produced from the lower and upper Eagle Ford Shale intervals and reduced the model complexity using principal component analysis. We tested the ML models and estimated the sensitivities of ML-predicted EURs to changes in the values of different input variables. The results of applying the optimized ML model to the Eagle Ford suggest that the approach developed in this study could be promising. The ML estimates of the EURs fit the DCA-based values with an R 2 ~ 0.9 and a mean absolute error of ~36 × 10 3 bbl. In the lower Eagle Ford Shale, the EUR estimates were found to be most sensitive to changes in porosity, net thickness of the interval, clay volume, and the API gravity of the oil; and that in the upper Eagle Ford Shale they were most sensitive to changes in the total organic carbon and water saturation, which suggests that it could be important to consider these parameters in assessing these intervals or close analogs.

Louisiana, Mississippi, Texas↗

USGS2025

Preface to the focus section on earthquake-induced ground deformation

Ground failure due to earthquake-induced liquefaction, surface fault rupture, and landsliding has caused substantial damage in the past and continues to pose risks to critical infrastructure in the future. The consideration of ground failure is central to engineering analysis and design, ranging from site-specific engineering assessments of ground failure potential to broader regional-scale ground failure assessments of near-real-time earthquake impacts or longer-term portfolio risk. Uncertainties in all aspects of the problem complicate the prediction of earthquake-induced ground failure, including the identification of hazard-susceptible geomaterials, characterizing their spatial extent and physical properties, spatio-temporal variability in groundwater conditions, characterization of earthquake ground motions, assessing ground failure severity, and linking ground failure severity to infrastructure damage and loss.

Seismological Research Letters↗

USGS2025

A global database of soil microbial phospholipid fatty acids and enzyme activities

Soil microbes drive ecosystem function and play a critical role in how ecosystems respond to global change. Research surrounding soil microbial communities has rapidly increased in recent decades, and substantial data relating to phospholipid fatty acids (PLFAs) and potential enzyme activity have been collected and analysed. However, studies have mostly been restricted to local and regional scales, and their accuracy and usefulness are limited by the extent of accessible data. Here we aim to improve data availability by collating a global database of soil PLFA and potential enzyme activity measurements from 12,258 georeferenced samples located across all continents, 5.1% of which have not previously been published. The database contains data relating to 113 PLFAs and 26 enzyme activities, and includes metadata such as sampling date, sample depth, and soil pH, total carbon, and total nitrogen. This database will help researchers in conducting both global- and local-scale studies to better understand soil microbial biomass and function.

Scientific Data↗

USGS2025

Unveiling coseismic deformation from differenced legacy aerial photography and modern lidar topography: The 1983 M6.9 Borah Peak earthquake, Idaho, USA

The 1983 M6.9 Borah Peak, Idaho, earthquake is one of the largest historical normal fault earthquakes in the western United States. We quantified meter-scale vertical change along the 35 km-long rupture using topographic differencing of 1966 aerial imagery and 2019 lidar-derived data. The initial differencing results are largely obscured by horizontal and vertical georeferencing errors and flight-line stripes. Our error corrections are designed to be insensitive to the coseismic deformation and reduced error by 50%. We calculated vertical separation and resolved a maximum of 2.02 ± 0.46 m at Doublespring Pass. Our vertical separation measurements are generally consistent with those from prior studies using field data and post-earthquake topographic data. However, the differencing measurements are a few decimeters lower than these prior measurements, indicating that differencing can isolate historical from prehistoric earthquake deformation. Our study demonstrates that revisiting historical earthquakes can provide new insights into the magnitude and patterns of coseismic deformation.

Idaho↗

USGS2025

Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration

Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model-data integration workflow to address uncertainty in groundwater response to beaver-induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning-based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down-valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down-valley underflow, from 2% during dry pond periods to 20% during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down-valley underflow, minimizes the effect of beaver-induced inundation on water quality. We emphasize the need for field-scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response.

Colorado↗

USGS2025

Examining the compositional selectivity of hydrocarbon oxidation products using liquid–liquid extraction and solid-phase extraction techniques

The effect of extraction methods on detecting hydrocarbon oxidation products (HOPs) in groundwater remains unclear. HOPs are polar, water-soluble byproducts of petroleum biodegradation. Our previous work showed that liquid–liquid extraction (LLE), a method commonly used in regulatory monitoring, has a significantly lower extraction efficiency for HOPs compared to solid-phase extraction (SPE). In this study, we evaluate the analytical limitations and compositional selectivity of LLE and SPE using groundwater samples from the Bemidji, MN, crude oil spill site. Optical properties were characterized using excitation–emission matrix spectroscopy (EEMs), and a three-component PARAFAC model was validated, showing consistent trends across both extracts and whole water samples. Ultrahigh-resolution mass spectrometry (UHR-MS) revealed that LLE selectively recovered aliphatic-like compounds but underrepresented more polar oxygenated HOPs. In contrast, SPE methods were more effective at isolating highly oxidized compound classes. These differences were consistent across a gradient of contamination. Overall, the LLE was less precise and less representative of polar HOPs, introducing bias in the characterization of HOPs. This study is the first to quantitatively demonstrate the compositional selectivity and analytical bias of LLE versus SPE for HOPs using combined EEM-PARAFAC and UHR-MS techniques, with implications for long-term monitoring and site assessment protocols.

Environmental Science and Technology↗

USGS2025

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California↗

Compare source metadata on this page

Work	Published	Source identifier	Source
SURF: An automated method for building nonplanar 3D fault models from earthquake hypocenters	2025-10-08	70272805	usgs
Dating a medieval tsunami with uranium-series techniques on Caribbean corals	2025-10-08	70276827	usgs
Submarine groundwater discharge creates cold‐water refugia that can mitigate exposure of heat stress in nearshore corals	2025-10-07	70272206	usgs
Mapping a Carrington storm	2025-10-07	70274119	usgs
RioM-1: A new calcite reference material for U-Pb LA-ICP-MS geochronology	2025-10-06	70272056	usgs
Ambient field seismology in critical zone hydrological sciences	2025-10-06	70274600	usgs
Assessing flood water infiltration and storage in a restored floodplain	2025-10-05	70273139	usgs
Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks	2025-10-05	70273513	usgs
Widespread anhydrite saturation in Laramide-age arc magmas of southwestern USA	2025-10-03	70272057	usgs
Late Pleistocene kinematics of the Great Southern Puerto Rico Fault Zone, Puerto Rico	2025-10-02	70272094	usgs
Earthquake magnitude and source parameter estimation with a distributed acoustic sensing dataset in the Gorda subduction zone	2025-10-01	70272184	usgs
Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks	2025-09-30	70272027	usgs
Preface to the focus section on earthquake-induced ground deformation	2025-09-30	70278103	usgs
A global database of soil microbial phospholipid fatty acids and enzyme activities	2025-09-26	70278939	usgs
Unveiling coseismic deformation from differenced legacy aerial photography and modern lidar topography: The 1983 M6.9 Borah Peak earthquake, Idaho, USA	2025-09-25	70272023	usgs
Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration	2025-09-25	70272041	usgs
Examining the compositional selectivity of hydrocarbon oxidation products using liquid–liquid extraction and solid-phase extraction techniques	2025-09-25	70273314	usgs
Irrigated agriculture influences selenium levels in an endangered marsh bird	2025-09-24	70273990	usgs

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.