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267 records · Page 6Linked to original sources
USGS2026

The petrogenesis of Þingmúli volcano, East Fjords, Iceland

In this work we revisit Þingmúli volcano (Þ = Th), a classic locality known as an example of a complete tholeiitic differentiation. Þingmúli is a ~ 9.5 Ma extinct central volcano located in the East Fjords of Iceland, in which the whole compositional spectrum from basalt to rhyolites have erupted. These volcanic products have been previously considered as petrogenetically related by an ideal fractionation trend, regardless any temporal relationship or volumetric considerations. Here we report new whole-rock geochemistry, mineral chemistry, isotope analyses, estimation of residence times of the different eruptive deposits, and an update of the original petrogenetic model. Our results highlight that an enriched source, likely spinel lherzolites, generated transitional-alkaline basaltic melts after 15–20% of partial melting at depths of 40–45 km. Many of these basaltic melts erupted at various stages of the volcano's history, while others remained longer in the volcanic plumbing system. These evolved by fractional crystallisation into basaltic andesite magmas with a residence time of ~5 years based on the crystal size distribution of the plagioclase population. Isotopic differences between the basalts/basaltic andesites ( 87 Sr/ 86 Sr ~ 0.7034; 143 Nd/ 144 Nd ~ 0.51315) and the erupted rhyolites ( 87 Sr/ 86 Sr ~ 0.7037; 143 Nd/ 144 Nd ~ 0.51304) indicate that the latter are not petrogenetically related to the former. Therefore, instead of a fractional crystallisation mechanism to generate the rhyolites, we propose the partial melting of ignimbrite layers located beneath the volcano. The broad range of trace element concentrations in andesites and dacites and their different isotopic values compared to the basalts strongly suggest that these magmas have been generated by magma mixing between basaltic and rhyolitic melts, similar to modern day Icelandic volcanoes such as Hekla. These results highlight the need to revisit previously studied Icelandic classic localities and reassess their traditionally proposed petrogenetic models.

Þingmúli volcano, East Fjords↗
USGS2024

Predicting hydrothermal reservoir depth from chemical geothermometers using a three-dimensional temperature model in the Great Basin, USA

Recent work in the Great Basin region of the western United States has made it possible to predict the depth of hydrothermal reservoirs (i.e., the depth at which heat is accumulated prior to ascent via hydrothermal upflow) identified through geochemistry and to contextualize the spatial patterns of these reservoir depths. Chemical geothermometers use the chemical and mineral constituents of hydrothermal fluids to predict the temperature at which fluids equilibrated with the host rocks at depth. Assuming that most of the Great Basin is dominated by conductive conditions until a vertically connected hydrothermal flow path is created (e.g., by faulting), geothermometers reflect the chemical and thermal conditions at the depth interval that the fluid has conductively equilibrated over a long period before a vertical conduit allows convective upflow. By pairing geothermometer temperature estimates with our recent three-dimensional temperature model of conductive heat flow in the Great Basin, we estimate the corresponding reservoir depths and construct a map of circulation depths. The predicted depths from geothermometers have spatial patterns across the Great Basin that relate to patterns seen in other geologic and geophysical data. Deeper springs generally occur disproportionately in areas with higher strain rates and in basins. We posit that current elevated strain rates reflect patterns of historic deformation where ongoing tectonic activity maintains permeable pathways to deeper reservoirs, some of which are estimated to exceed 6 km depth. Basins, as expected, contain a disproportionate number of these deep systems, because the underlying aquifers are closer to the surface in basins, thus requiring less water pressure to reach the surface than in mountain ranges. Most springs estimated to have their source in a deep reservoir occur at places known to host a hydrothermal system; these refined depth estimates of the source reservoir can help to better constrain the source depth for many known hydrothermal systems across the Great Basin.

Arizona, California, Idaho, Nevada, Oregon, Utah↗
USGS2026

Transit time modeling framework for predicting freshwater salinization in urban catchments

The salinity of inland freshwaters is rising globally, particularly in urban watersheds where winter road deicers are widely applied. Attributing stream salinity dynamics to specific sources and transport pathways remains challenging due to episodic salt inputs, engineered drainage, and strong coupling between hydrology and subsurface storage. We present a modeling framework that couples climate-driven deicer build-up and wash-off with transient transit time distribution theory to simulate salt transport through drainage, interflow, and groundwater pathways. Applied to an urban watershed in Northern Virginia (USA), the model reproduces ten years of high-frequency stream salinity measurements across daily-to-decadal timescales. The calibrated model implies an average deicer application of 206 tonnes Cl −1 yr −1 , or roughly one 20 kg bag of rock salt person −1 yr −1 when normalized by the 20,000 people living in the watershed. In winter months, higher infiltration routes a large fraction of snowmelt and deicers into shallow subsurface pathways, enhancing vadose-zone and interflow contributions to stream salinity. Limited subsurface storage capacity and seasonal hydrologic turnover flush excess chloride from the vadose zone and groundwater during subsequent summer storms. By linking climate-driven deicer inputs, hydrologic connectivity, and stream water age, the framework provides a transferable basis for diagnosing and managing freshwater salinization in urban watersheds.

Virginia↗
USGS2024

Managing basin-scale carbon sequestration: A tragedy of the commons approach

The Tragedy of the Commons is a well studied problem in the literature of ecology, economics, and environmental policy which illustrates the deleterious consequences of managing common pool resources when individual and social incentives are misaligned. In this work, we apply a simple model of carbon sequestration in a deep saline aquifer by two neighboring geologic CO 2 storage (GCS) operators to begin investigating if a Tragedy of the Commons framework applies to GCS. Specifically, we consider the pressure space as a “commons” because the injection by each firm at its own well increases the downhole injection pressure at both wells. We assume that a firm will decrease its injection rate if the downhole pressure at its well exceeds a predefined maximum (i.e., exceeds the “pressure limit”). With this assumption in place, we find that the same injection flowrates are optimal for both wells, regardless of whether they are owned by the same firm or competing firms. This suggests that GCS may not be best represented by a pure Tragedy of the Commons framework under our initial assumptions. However, there could be economic incentives or contractual obligations that may result in either or both GCS operators being unwilling to reduce their injection rates. Thus, we conclude the conference paper with a discussion of future extensions of our approach that may demonstrate closer alignment with the Tragedy of the Commons, including explicit definitions of pore-space rights, firm uncertainty regarding the parameters of the Theis equation, and the potential role of unitization.

Conference Paper↗
USGS2026

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters↗
USGS2025

A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities

As wildfires increasingly affect water-supply watersheds, the demand for models to predict water-quality responses is increasing. This work reviews and synthesizes existing post-wildfire applications of water-quality models in the context of geographic and ecohydrological distribution, hydrologic and water-quality response process representation, model parameterization, model and input data scales, model calibration data availability, as well as calibration and performance evaluation approaches. Emphasis is placed on models that simulate water-quality output, rather than sediment and erosional response as the primary focus. Here, identified gaps and opportunities to advance the post-wildfire application of water-quality models include: 1. applying models in under-represented geographic and ecohydrologic regions, 2. simulating multiple streamflow generation mechanisms, including groundwater, with an emphasis on shifting dominant flow pathways as the landscape recovers following wildfire, 3. adding studies that include the simulation of metals, 4. incorporating more biogeochemical and in-stream processes to model applications, 5. applying finer spatial and temporal resolution of precipitation data input as well as finer spatial resolution hydrologic response units, 6. implementing fully distributed grid or element models or finer resolution response units to capture burn severity heterogeneity, 7. collecting enhanced water-quality data for model calibration and validation, 8. conducting model-intercomparison studies, and 9. developing model parameter value guidance in post-wildfire applications. These identified gaps and opportunities may assist users in deciding on key processes and approaches to consider in modeling post-wildfire water-quality conditions.

Science of the Total Environment↗
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

False positives in the identification of dynamic earthquake triggering

Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with global M ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial-temporal windows in Southern California tested in DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 , thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023, https://doi.org/10.1029/2023jb026487 ), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor-Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance.

JGR Solid Earth↗
USGS2024

The 2023 U.S. 50-state National Seismic Hazard Model: Changes in 2023 compared to 2018 ground motions

We present the 2023 U.S. National Seismic Hazard Model (NSHM) for all 50 states that applies new smoothed seismicity, fault rupture, and ground motion models. New data and methods are introduced in the 2023 earthquake rupture forecast that include: new earthquake catalogs - excluding induced earthquakes, alternative declustering methods, spatially smoothed seismicity distributions, full-catalog scaled rates to account for aftershocks, updated CEUS-WUS attenuation boundary, new magnitude-scaling equations, new geodetic and geologic deformation models, and alternative fault system solutions accounting for a more complete representation of epistemic uncertainty potential for earthquake generation in Alaska, Hawaii, and the conterminous U.S. Improved ground motion models consider new Next Generation Attenuation NGASubduction, modified NGA-East, and adjustments to account for regional biases in ground shaking observations. Semi-empirical and 3D simulations of ground motion are applied to account for shaking at 21 oscillator periods, 2 peak motions, and 8 site conditions. Site effects models are constructed for western U.S. basins (Seattle, Portland/Tualatin, San Francisco, Central Valley of California, Los Angeles, and Salt Lake City) and for sites with deep sedimentary wedges found across the central and eastern U.S. Gulf Coast and Atlantic coastal plain regions. These models result in substantial changes compared to the older NSHMs and are differentiated for the earthquake rupture forecast and ground motion model changes to display sensitivities and impacts.

Conference Paper↗
USGS2025

Generalized Bancroft algorithm for locating earthquakes with P- and S-wave arrival times

Because of similarities between locating an earthquake with seismic stations and locating a Global Positioning System (GPS) receiver from satellites, the Bancroft algorithm developed for GPS processing can be used to locate earthquakes. Such an approach to earthquake location differs from the conventional method of choosing an initial or trial solution and then iteratively improving the solution until convergence. The Bancroft algorithm has the advantage of being a direct, noniterative solution but with the disadvantage of only being able to accommodate a homogeneous velocity model. An additional limitation of the standard Bancroft algorithm is that it considers arrival times in a medium with a single propagation velocity. This poses no problem for GPS processing because electromagnetic waves travel at the speed of light; however, for seismic waves it means the algorithm can be applied to collections of either P ‐ or S ‐wave arrival times. Here, I show how the Bancroft algorithm can be generalized to handle both P ‐ and S ‐wave arrival‐time measurements simultaneously. I also show how to accommodate depth‐varying P ‐ and S ‐wave velocity models. I apply the generalized Bancroft algorithm to microearthquakes beneath Tanaga Volcano in Alaska and compare standard locations from the widely used HYPOINVERSE location code to Bancroft locations and to the output of HYPOINVERSE when setting the trial location to the Bancroft location. I find the Bancroft locations outperform the results from the other methods for shallow earthquakes near sea level, where a quantity known as the geometric dilution of precision is large and linearized approaches such as HYPOINVERSE are expected to struggle.

Alaska↗
USGS1998

Continuous hydrologic simulation of runoff for the Middle Fork and South Fork of the Beargrass Creek basin in Jefferson County, Kentucky

The Hydrological Simulation Pro-gram-FORTRAN (HSPF) was applied to an urban drainage basin in Jefferson County, Ky to integrate the large amounts of information being collected on water quantity and quality into an analytical framework that could be used as a management and planning tool. Hydrologic response units were developed using geographic data and a K-means analysis to characterize important hydrologic and physical factors in the basin. The Hydrological Simulation Program FORTRAN Expert System (HSPEXP) was used to calibrate the model parameters for the Middle Fork Beargrass Creek Basin for 3 years (June 1, 1991, to May 31, 1994) of 5-minute streamflow and precipitation time series, and 3 years of hourly pan-evaporation time series. The calibrated model parameters were applied to the South Fork Beargrass Creek Basin for confirmation. The model confirmation results indicated that the model simulated the system within acceptable tolerances. The coefficient of determination and coefficient of model-fit efficiency between simulated and observed daily flows were 0.91 and 0.82, respectively, for model calibration and 0.88 and 0.77, respectively, for model confirmation. The model is most sensitive to estimates of the area of effective impervious land in the basin; the spatial distribution of rain-fall; and the lower-zone evapotranspiration, lower-zone nominal storage, and infiltration-capacity parameters during recession and low-flow periods. The error contribution from these sources varies with season and antecedent conditions.

Kentucky↗
USGS2025

Pre-Acadian tectonics of the eastern Orange-Milford Belt, south-central Connecticut

This excursion presents a reinterpretation of mapping and new analytical data from the eastern Orange-Milford belt (OMB) in south-central Connecticut. The OMB is a fault-bound terrane of argillites and mafic rocks of anomalously low metamorphic grade—and of poorly constrained ages and tectonic affinity—wedged between kyanite/sillimanite-grade peri- Laurentian rocks to the west and anatectic peri-Gondwanan rocks to the east (Fig. 1A). Our data demonstrate that Ordovician(?) igneous and sedimentary rocks of the OMB were variably metamorphosed in the Ordovician and Silurian but escaped regionally pervasive, high-grade Devonian and later metamorphism. Previous interpretations (Fritts 1963a, 1965a, 1965b; Burger, 1967; Burger and others, 1968; Rodgers, 1985) described these rocks as a conformable sequence of low-grade, Ordovician to Devonian metasediments and metavolcanics. Our results reveal that the “metavolcanics” are not extrusive rocks but rather slivers of lower oceanic crust with complicated high- and low-grade metamorphic fabrics, intruded by a swarm of Silurian sheeted basalt dikes, and in fault contact with the surrounding metasediments. The purpose of this trip is to show evidence of early Paleozoic (Taconic) deformation and metamorphism preserved in rocks of the eastern OMB. These rocks remained shallow, cool, and sufficiently dry during the regionally dominant Acadian and Alleghanian orogenies to have avoided significant overprinting. As such, these rocks serve as windows into a geologic history otherwise unavailable between anatectic rocks of the peri-Gondwanan Bronson Hill, Avalon, and Gander terranes east of the Hartford basin and sillimanite-grade rocks of the peri-Laurentian Hartland and gneiss dome belts west of the OMB. We present major and trace element geochemistry including rare-earth element patterns for all mafic units in the eastern OMB as well as 40 Ar/ 39 Ar age spectra of amphibole, muscovite, and K-feldspar from rocks of the Maltby Lakes complex (of Deasy and others, 2017), Savin Schist, and Wepawaug Schist. Our evidence demonstrates that the units of the OMB have been assembled by faulting or intrusion, and that no stratigraphic relationships exist between the argillaceous schists and the metaigneous rocks.

Connecticut↗
USGS2025

Characterizing sedimentary organic carbon in a hydrothermal spreading center, the Escanaba Trough

Sediments in critical marine mineral environments are of wide importance due to their preservation of both marine minerals and organic carbon (OC) stocks. However, OC storage and cycling is often overlooked in mineral system studies. This work characterizes sedimentary OC within the Escanaba Trough, a hydrothermal sulfide system off the coast of northern California. By utilizing ROV-based push coring, we collected sediments near and far from high temperature, low temperature, and inactive vents. We applied a multipronged organic geochemical approach, measuring bulk sediment, OC fractions of varying labilities, and biomarkers to tease apart the storage, source, and cycling of OC within this complex system. In contrast to past work indicating a primarily terrestrial source to deeper, Pleistocene sediments, our results suggest a primarily marine source in surface sediments at least 50 m away from active venting. Near active venting, we see evidence of locally produced chemosynthetic OC in addition to the background marine source. This chemosynthetic OC appears to be rapidly remineralized and supports more complex deep-sea food webs compared to hemipelagic sites. Still, the greatest contribution of labile OC was observed at inactive vent sites, which we suggest is due to hydrothermal fluid alteration of more labile OC at actively venting sites. Depending on fluid temperature, hydrothermally altered OC is either preserved in the sediments as petroleum or migrated with fluid flow. Considering inactive sites are those most likely to be targeted by potential mining, we suggest additional studies could verify if these results apply at other sedimented seafloor massive sulfide systems.

California↗
USGS2025

Smectite-rich horizons in Inceptisols trigger shallow landslides in tropical granitic terranes

Puerto Rico was affected by >70,000 landslides in the wake of 2017 Hurricane Maria, and landslide prevalence was especially high in the Utuado region in the Cordillera Central. Landslide density was highest where soil parent material is granodiorite; landslide slip surfaces tended to be shallow (<60 cm), and often were mobilized rapidly and with long runout distances. This study combines field observations with soil mineralogy (bulk and clay fractions), soil geochemistry (bulk fraction), and soil strength as determined by field cone penetrometer testing (CPT) to test the hypothesis that clay-rich subsoil horizons function as slip planes when water-logged. Soil pits were excavated to depths of ∼200 cm in Ultisols on an undulating plateau and to ∼100 cm in Inceptisols on steep slopes (36-43 o ) that flank the plateau and cone penetrometer tests (CPT) were done within 2 m of the soil pit. Six pits were located adjacent to scarps from previous landslides, enabling analysis of soil profiles downward through extrapolated slip surfaces. Results from X-ray diffraction (XRD), X-ray fluorescence (XRF) and thermogravimetric analysis (TGA) indicate that soils are heterogeneous, often with subsoil horizons enriched in clay minerals and immobile elements (Al, Fe, Ti). Inceptisols on steep slopes often contain smectite-rich horizons at 30–60 cm depth that appear to function as slip surfaces; in other Inceptisols, such horizons are not present and landslide susceptibility is potentially lower. In Ultisols, soil mineralogy is dominated by kaolinite with minor halloysite, and increased kaolinite content at soil depths ≥80 cm at some sites suggests potential slip surfaces enhancing probability of landslides. The origin of clay-rich horizons appears to be (1) fractures in granodiorite that facilitate water flow and leaching, accelerating mineral dissolution during early weathering stages, and (2) smectite-rich buried soils under permeable colluvium likely deposited by a prior mass wasting event. Where clay-rich layers occur beneath more-permeable horizons, rapid infiltration then absorption of water in clay-rich subsoil horizons causes decreased shear strength and increased landslide susceptibility.

Puerto Rico↗
USGS2026

Groundwater budget for the Mountain Home area, southern Idaho, 2022–23

The U.S. Geological Survey, with funding from the Idaho Department of Water Resources, developed a groundwater budget for the Mountain Home area in southern Idaho for irrigation year 2023 (November 1, 2022–October 31, 2023). This study focused on the water balance across the Cinder Cone Butte Critical Groundwater Area (CGWA), Mountain Home Groundwater Management Area (GWMA), and the rest of the study area (RoSA), compiling data from various sources, including precipitation records, groundwater level measurements, metered groundwater pumpage data, surface water diversions and evapotranspiration (ET) estimates derived from remote sensing satellite imagery, and ground-based reference data. Key inflow components included recharge from applied surface water irrigation (which incorporates incidental recharge from irrigation practices and conveyance losses), estimated tributary streamflow, and estimated mountain block recharge. The key outflow components were groundwater pumpage for irrigation, municipal, industrial, and domestic uses, and ET. Recharge from applied irrigation and mountain block recharge were the largest inflows, and groundwater pumpage for irrigation was the largest outflow. The CGWA had a positive groundwater budget residual of 2,170 acre-feet (acre-ft), which contrasts with observed long-term groundwater level declines and historical trends of storage depletion. This positive residual is likely associated with unquantified outflows, including lateral groundwater flow out of the subregion, or other complexities, such as overestimated tributary contributions relative to the actual recharge for the 2023 water budget. The GWMA exhibited a positive residual of 56,563 acre-ft, primarily owing to recharge from applied surface water irrigation and areal recharge during a wetter-than-average year, which allowed irrigation entities to deliver more water from in-basin and out-of-basin reservoirs. The RoSA showed a large positive residual of 124,933 acre-ft. The interpretation of these positive residuals must account for significant uncertainties, including estimations of areal recharge, tributary streamflow (particularly losses and diversions), ET, the volume of surface water loss to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and the unquantified groundwater discharge to the Snake River. These uncertainties, in combination with the complex hydrogeologic controls on water movement and limitations of remotely sensed data, directly affect the accuracy of water availability assessments. Future data collection efforts would help reduce these uncertainties and support water resource management decisions in the Mountain Home area. Key efforts could include installing additional streamflow gaging stations (particularly to quantify tributary losses and gains and surface water losses to the Snake River), improving groundwater pumpage metering, and validating remotely sensed ET data with ground-based measurements. Furthermore, to better quantify unrepresented or highly uncertain fluxes, focused investigations on groundwater discharge to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and a more robust determination of the actual influence and volume of mountain block recharge would help refine future water availability assessments for the Mountain Home area.

Idaho↗
USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗
USGS2025

Exploration for blind geothermal systems in the eastern Great Basin of Utah: An update on the “Lund North” INGENIOUS detailed study site

Existing geothermal production in Utah is commonly collocated with surficial expressions of geothermal heat including active hot springs and hot spring deposits. However, geothermal potential across the Great Basin region is thought to be much higher for hidden or blind geothermal systems. Accordingly, exploration techniques that can locate geothermal resources that lack surface thermal features could support future development of these systems. The goal of the INGENIOUS project is to reduce exploration risk and discover new, economically viable hidden geothermal systems in the Great Basin region. This paper summarizes the efforts and preliminary results of blind geothermal resource prospecting in Utah as part of the larger INGENIOUS project. The Lund North site in the Basin and Range province of southwest Utah was designated as the fourth detailed study site for the project. The site was initially identified from the preliminary Play Fairway Analysis (PFA) geothermal favorability map, which is based on various data elements, and the identification of favorable structural settings across Utah. This site contains existing legacy data including a thermal gradient borehole with a heat-flow value exceeding 220 mW/m 2 . New data collected at this site include terrestrial gravity, magnetotellurics, transient electromagnetics, fluid geochemistry, geologic mapping, UAV-based lidar, paleomagnetism, aeromagnetic surveys, and a shallow temperature survey. Preliminary data and model interpretations corroborate the presence of a large, east-dipping, northeast-southwest-trending normal fault on the edge of a typical Basin and Range graben. Quaternary fault mapping refined by high-resolution lidar surveys suggests a complex step over fault geometry. Utilizing multi-disciplinary datasets for further site assessment at Lund North will facilitate the development of a local-scale PFA and geothermal conceptual model. This new data will be used to site successive thermal gradient drilling to verify heat flow with temperatures at depth at the Lund North site and further investigate the existence of a local geothermal system.

Utah↗
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↗