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Abstract: Magmatic systems below volcanoes are often dominated by partially crystalline magma over the long term. Rejuvenation of these systems during eruptive events can impact lava composition and eruption style—sometimes resulting in more violent or explosive activity than would be expected, as was the case at Fissure 17 during Kīlauea’s 2018 eruption. Here, we explore how the crystallinity of unerupted intrusion magmas affect hybrid magma compositions and petrological signatures by constructing phase-equilibria models to evaluate mineral and melt compositions of low-MgO lavas erupted along the East Rift Zone of Kīlauea volcano on 30 to 31 January 1997 (Episode 54, Fissures A-F). We then compare calculated mixing proportions and petrologically derived magma volumes to GPS-based geodetic inversions of ground deformation and intrusion growth in an attempt to reconcile geodetic and petrologically estimated magma volumes. Open-system phase-equilibria thermodynamic models were used to constrain the composition, degree of differentiation, and thermodynamic state of a rift-stored, two pyroxene + plagioclase saturated low-MgO magma body immediately preceding its mixing with high-MgO recharge and degassed drainback (lava lake) magma from Pu‘u‘ō‘ō‘, shortly before fissure activity within Nāpau Crater began on 29 January 1997. Mixing models constructed using the Magma Chamber Simulator reproduce the mineralogy and compositions of Episode 54 lavas within uncertainties and suggest that the identity of the low-MgO magma body may be either variably differentiated remnants of un-erupted magmas intruded into Nāpau Crater in October 1968, or another spatially and compositionally similar magma body. We find that magmas derived from a single, compositionally stratified magma emplaced beneath Nāpau Crater in 1968 can mix with mafic Kīlauea magmas to reproduce average Episode 54 bulk lava, mineralogy and mineral compositions without necessitating the interaction of multiple, low-MgO rift-stored magma bodies to produce Episode 54 lava compositions. Further, by constructing phase equilibria-based mixing models of Episode 54, we can better define the pre-eruptive state of the magmatic system. The resultant mineral assemblages and compositions are consistent with the possibility that the now-fractionated, rift-stored magma body was compositionally stratified and ~ 40% to 50% crystalline at the time of mixing. Finally, we estimate the volume of the low-MgO magma body to be ~7.51 Mm3. Phase-equilibria model results corroborate field and geochemical relationships demonstrating how shallow intrusions at intraplate shield volcanoes can crystallize, evolve, and then be remobilized by new, later batches of mafic magma. Most notably, our MCS models demonstrate that the pre-eruptive conditions of an intrusive body may be recovered by examining mineral compositions within mixed lavas. Discrepancies between the geodetic constraints on volumes of stored rift versus newly intruded (recharge) magma and our best-fit results produced by MCS mixing models (which respectively are mmafic:mlow-MgO ≈ 2 vs. mmafic:mlow-MgO ≈ 0.75) are interpreted to highlight the complex nature of incomplete mixing on more localized scales as reflected in erupted lavas, compared to geodetically constrained volumes that likely reflect large spatial scale contributions to a magmatic system. These dissimilar volume relationships may also help to constrain eruptive versus unerupted volumes in magmatic systems undergoing mixing. By demonstrating the usefulness of MCS in modeling past eruptions, we highlight the potential to use it as a tool to aid in petrologic monitoring of ongoing activity.

Continuous microseismic monitoring using three-component (3C) accelerometers deployed in multiple boreholes allows for tracking the detailed evaluation of mesoscale (∼10 m scale) fracture growth during the fracture stimulation experiments at the first Enhanced Geothermal Systems (EGS) Collab testbed. Building on a well-constrained microseismic event catalog, we invert for moment tensor of the events to better understand the fracture geometry and stress orientations. However, it is challenging because of the unknown orientation of 3C accelerometers and low signal-to-noise-ratio nature of high-frequency (several kHz) monitoring. To address these challenges, we first perform the hodogram analysis on the continuous active-source seismic monitoring (CASSM) data to determine the orientations of the 18 3C accelerometers. We then apply the principal component analysis (PCA) to the observed microseismic waveforms to improve the signal-to-noise ratios. We perform a grid search for the full moment tensor by fitting the PCA-denoised waveforms at a frequency range of 5 to 8 kHz. The moment tensor results show both the creation of hydraulic fractures and the reactivation of natural fractures during the hydraulic stimulations. Our stress inversion based on the inverted moment tensors reveals the alteration of stress regime caused by hydraulic fracture stimulations.

Methane (CH4) is a potent greenhouse gas emitted by archaea in anaerobic environments such as wetland soils. Tidal freshwater wetlands are predicted to become increasingly saline as sea levels rise due to climate change. Previous work has shown that increases in salinity generally decrease CH4 emissions, but with considerable variation, including instances where salinization increased CH4 flux. We measured microbial community composition, biogeochemistry, and CH4 flux from field samples and lab experiments from four different sites across a wide geographic range. We sought to assess how site differences and microbial ecology affect how CH4 emissions are influenced by salinization. CH4 flux was generally, but not always, positively correlated with CO2 flux, soil carbon, ammonium, phosphate, and pH. Methanogen guilds were positively correlated with CH4 flux across all sites, while methanotroph guilds were both positively and negatively correlated with CH4 depending on site. There was mixed support for negative relationships between CH4 fluxes and concentrations of alternative electron acceptors and abundances of taxa that reduce them. CH4/salinity relationships ranged from negative, to neutral, to positive and appeared to be influenced by site characteristics such as pH and plant composition, which also likely contributed to site differences in microbial communities. The activity of site-specific microbes that may respond differently to low-level salinity increases is likely an important driver of CH4/salinity relationships. Our results suggest several factors that make it difficult to generalize CH4/salinity relationships and highlight the need for paired microbial and flux measurements across a broader range of sites.

To improve the predictive capability of ecosystem biogeochemical models (EBMs), we discuss the feasibility of formulating biogeochemical processes using physical rules that have underpinned the many successes in computational physics and chemistry. We argue that the currently popular empirically based approaches, such as multiplicative empirical response functions and the law of the minimum, will not lead to EBM formulations that can be continuously refined to incorporate improved mechanistic understanding and empirical observations of biogeochemical processes. Instead, we propose that EBM parameterizations, as a lossy data compression problem, can be better formulated using established physical rules widely used in computational physics and chemistry, and different biogeochemical processes can be more robustly integrated within a reactive-transport framework. Through several examples, we demonstrate how mathematical representations derived from physical rules can improve understanding of relevant biogeochemical processes and enable more effective communication between modelers, observationalists, and experimentalists regarding essential questions, such as what measurements are needed to meaningfully inform models and how can models generate new process-level hypotheses to test in empirical studies. Finally, while empirical models with more parameters are often less robust, physical rules-based models can be more robust and show lower predictive equifinality, stemming from their enhanced consistency in representations of processes, interactions and spatial scaling.

According to classic stomatal optimization theory, plant stomata are regulated to maximize carbon assimilation for a given water loss. A key component of stomatal optimization models is marginal water-use efficiency (mWUE), the ratio of the change of transpiration to the change in carbon assimilation. Although the mWUE is often assumed to be constant, variability of mWUE under changing hydrologic conditions has been reported. However, there has yet to be a consensus on the patterns of mWUE variabilities and their relations with atmospheric aridity. We investigate the dynamics of mWUE in response to vapor pressure deficit (VPD) and aridity index using carbon and water fluxes from 115 eddy covariance towers available from the global database FLUXNET. We demonstrate a non-linear mWUE-VPD relationship at a sub-daily scale in general; mWUE varies substantially at both low and high VPD levels. However, mWUE remains relatively constant within the mid-range of VPD. Despite the highly non-linear relationship between mWUE and VPD, the relationship can be informed by the strong linear relationship between ecosystem-level inherent water-use efficiency (IWUE) and mWUE using the slope, m*. We further identify site-specific m* and its variability with changing site-level aridity across six vegetation types. We suggest accurately representing the relationship between IWUE and VPD using Michaelis–Menten or quadratic functions to ensure precise estimation of mWUE variability for individual sites.

Earthquake nowcasting has been proposed as a means of tracking the change in large earthquake potential in a seismically active area. The method was developed using observable seismic data, in which probabilities of future large earthquakes can be computed using Receiver Operating Characteristic methods. Furthermore, analysis of the Shannon information content of the earthquake catalogs has been used to show that there is information contained in the catalogs, and that it can vary in time. So an important question remains, where does the information originate? In this paper, we examine this question using stochastic simulations of earthquake catalogs. Our catalog simulations are computed using an Earthquake Rescaled Aftershock Seismicity (“ERAS”) stochastic model. This model is similar in many ways to other stochastic seismicity simulations, but has the advantage that the model has only 2 free parameters to be set, one for the aftershock (Omori-Utsu) time decay, and one for the aftershock spatial migration away from the epicenter. Generating a simulation catalog and fitting the two parameters to the observed catalog such as California takes only a few minutes of wall clock time. While clustering can arise from random, Poisson statistics, we show that significant information in the simulation catalogs arises from the “non-Poisson” power-law aftershock clustering, implying that the practice of de-clustering observed catalogs may remove information that would otherwise be useful in forecasting and nowcasting. We also show that the nowcasting method provides similar results with the ERAS model as it does with observed seismicity.

Abstract: Glacial fjord circulation determines the import of oceanic heat to the Greenland Ice Sheet and the export of ice sheet meltwater to the ocean. However, limited observations and the presence of both glacial and coastal forcing—such as coastal‐trapped waves—make uncovering the physical mechanisms controlling fjord‐shelf exchange difficult. Here we use multi‐year, high‐resolution, realistically forced numerical simulations of Sermilik Fjord in southeast Greenland to evaluate the exchange flow. We compare models, with and without a plume, to differentiate between the exchange flow driven by shelf variability and that driven by subglacial discharge. We use the Total Exchange Flow framework to quantify the exchange volume transports. We find that a decline in offshore wind stress from January through July drives a seasonal reversal in the exchange flow increasing the presence of warm Atlantic Water at depth. We also find that including glacial plumes doubles the exchange flow in the summer. Our results show that the plume‐driven circulation is more effective at renewal with a flushing time 1/3 that of the shelf‐driven circulation near the fjord head.

Magma ascent and eruption are driven by a set of internally and externally generated stresses that act upon the magma. We present microstructural maps around melt inclusions in quartz crystals from six large rhyolitic eruptions using synchrotron Laue X-ray microdiffraction to quantify elastic residual strain and stress. We measure plastic strain using average diffraction peak width and lattice misorientation, highlighting dislocations and subgrain boundaries. Quartz crystals across studied magma systems preserve similar and relatively small magnitudes of elastic residual stress (mean 53–135 MPa, median 46–116 MPa) in comparison to the strength of quartz (~ 10 GPa). However, the distribution of strain in the lattice around inclusions varies between samples. We hypothesize that dislocation and twin systems may be established during compaction of crystal-rich magma, which affects the magnitude and distribution of preserved elastic strains. Given the lack of stress-free haloes around faceted inclusions, we conclude that most residual strain and stress was imparted after inclusion faceting. Fragmentation may be one of the final strain events that superimposes stresses of ~ 100 MPa across all studied crystals. Overall, volcanic quartz crystals preserve complex, overprinted deformation textures indicating that quartz crystals have prolonged deformation histories throughout storage, fragmentation, and eruption.

The chemical and isotopic characteristics of a solidified pluton represent the integration of magmatic and sub-solidus processes operating across a range of spatial and temporal scales during pluton construction, crystallization, and cooling. Disentangling these processes and understanding where chemical and isotopic signatures were acquired requires the combination of multiple tools tracing processes at different time and length scales. We combine whole-rock oxygen and Sr-Nd isotopes, zircon oxygen isotopes and trace elements, and mineral compositions with published high-precision U-Pb zircon geochronology to evaluate differentiation within the bimodal Guadalupe Igneous Complex, Sierra Nevada, California (USA). The complex was constructed in ~300 k.y. between 149 and 150 Ma. Felsic magmas crystallized as centimeter- to meter-sized segregations in gabbros in the lower part of the complex and as granites and granophyres structurally above the gabbros. A central mingling zone separates the mafic and felsic units. Pluton-wide δ18O(whole-rock), δ18O(zircon), and Sr-Nd isotopic ranges are too large to be explained by in situ, closed-system differentiation, instead requiring open-system behavior at all scales. Low δ18O(whole-rock) and δ18O(zircon) values indicate assimilation of hydrothermally altered marine host rocks during ascent and/or emplacement. In situ differentiation processes operated on a smaller scale (meters to tens of meters) for at least ~200 k.y. via (1) percolation and segregation of chemically and isotopically diverse silicic interstitial melt from a heterogeneous gabbro mush; (2) crystal accumulation; and (3) sub-solidus, high-temperature, hydrothermal alteration at the shallow roof of the complex to modify the chemical and isotopic characteristics. Whole-rock and mineral chemistry in combination with geochronology allows deciphering open-system differentiation processes at the outcrop to pluton scale from magmatic to sub-solidus temperatures over time scales of hundreds of thousands to millions of years.

Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case-specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial-ENzyme Decomposition model, this study aimed to test whether a common set of microbially-relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two-year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial-relevant parameters for large-scale soil model projections.

We present a synthetic multi-scale, multi-physics dataset constructed from the Kimberlina 1.2 CO2 reservoir model based on a potential CO2 storage site in the Southern San Joaquin Basin of California. Among 300 models, one selected reservoir-simulation scenario produces hydrologic-state models at the onset and after 20 years of CO2 injection. Subsequently, these models were transformed into geophysical properties, including P- and S-wave seismic velocities, saturated density where the saturating fluid can be a combination of brine and supercritical CO2, and electrical resistivity using established empirical petrophysical relationships. From these 3D distributions of geophysical properties, we have generated synthetic time-lapse seismic, gravity and electromagnetic responses with acquisition geometries that mimic realistic monitoring surveys and are achievable in actual field situations. We have also created a series of synthetic well logs of CO2 saturation, acoustic velocity, density and induction resistivity in the injection well and three monitoring wells. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected at the potential storage site. In addition, to better calibrate our datasets, measurements of permeability and pore connectivity have been made on cores of Vedder Sandstone, which forms the primary reservoir unit. These measurements provide the range of scales in the otherwise synthetic dataset to be as close to a real-world situation as possible. This dataset consisting of the reservoir models, geophysical models, simulated time-lapse geophysical responses and well logs forms a multi-scale, multi-physics testbed for designing and testing geophysical CO2 monitoring systems as well as for imaging and characterization algorithms. The suite of numerical models and data have been made publicly available for downloading on the National Energy Technology Laboratory's (NETL) Energy Data Exchange (EDX) website.

We conducted two-dimensional numerical simulations to investigate the mechanisms underlying the strong spatiotemporal correlation observed between submarine landslides and gas hydrate dissociation due to glacial sea-level drops. Our results suggest that potential plastic deformation or slip could occur at localized and small scales in the shallow-water portion of the gas hydrate stability zone (GHSZ). This shallow-water portion of the GHSZ typically lies within the area enclosed by three points: the BGHSZ–seafloor intersection, the seafloor at ∼600 m below sea level (mbsl), and the base of the GHSZ (BGHSZ) at ∼1,050 mbsl in low-latitude regions. The deep BGHSZ (>1,050 mbsl) could not slip; therefore, the entire BGHSZ was not a complete slip surface. Glacial hydrate dissociation alone is unlikely to cause large-scale submarine landslides. Observed deep-water (much greater than 600 mbsl) turbidites containing geochemical evidence of glacial hydrate dissociation potentially formed from erosion or detachment in the GHSZ pinch-out zone.

Enhanced geothermal systems (EGS) require cost-effective monitoring of fracture networks. We validate the capability of using borehole distributed acoustic sensing (DAS) ambient noise for fracture monitoring using core photos and core logs. The EGS Collab project has conducted 10 m scale field experiments of hydraulic fracture stimulation using 50-60 m deep experimental wells at the Sanford Underground Research Facility (SURF) in Lead, South Dakota. The first EGS Collab testbed is located at 1616.67 m (4850 ft) depth at SURF and consists of one injection well, one production well, and six monitoring wells. All wells are drilled subhorizontally from an access tunnel called a drift. The project uses a single continuous fiber-optic cable installed sequentially in the six monitoring wells to record DAS data for monitoring hydraulic fracturing during stimulation. We analyze 60 s time records of the borehole DAS ambient noise data and compute the noise root-mean-square (rms) amplitude on each channel (points along the fiber cable) to obtain DAS ambient noise rms amplitude depth profiles along the monitoring wellbore. Our noise rms amplitude profiles indicate amplitude peaks at distinct depths. We compare the DAS noise rms amplitude profiles with borehole core photos and core logs and find that the DAS noise rms amplitude peaks correspond to the locations of fractures or lithologic changes indicated in the core photos or core logs. We then compute the hourly DAS noise rms amplitude profiles in two monitoring wells during three stimulation cycles in 72 h and find that the DAS noise rms amplitude profiles vary with time, indicating the fracture opening/growth or closing during the hydraulic stimulation. Our results demonstrate that borehole DAS passive ambient noise can be used to detect fractures and monitor fracturing processes in EGS reservoirs.

Mountainous watersheds are characterized by variability in functional traits, including vegetation, topography, geology, and geomorphology, which determine nitrogen (N) retention, and release. Coal Creek and East River are two contrasting catchments within the Upper Colorado River Basin that differ markedly in total nitrate (NO3−) export. The East River has a diverse vegetation cover, and sinuous floodplains, and is underlain by N-rich marine shale. At 0.21 ± 0.14 kg ha−1 yr−1, the East River exports ∼3.5 times more NO3− relative to the conifer-dominated Coal Creek (0.06 ± 0.02 kg ha−1 yr−1). While this can partly be explained by the larger size of the East River, the distinct watershed traits of these two catchments imply different mechanisms controlling the aggregate N-export signal. A causality analysis shows physical and biogenic processes were critical in determining NO3− export from the East River catchment. Stable isotope ratios of NO3− (δ15NNO3 and δ18ONO3) show the East River catchment is a strong hotspot for biogeochemical processing of NO3− at the hillslope soil-saprolite. By contrast, the conifer-dominated Coal Creek retained nearly all atmospherically deposited NO3−, and its export was controlled by catchment hydrological traits (i.e., snowmelt periods and water table depth). The conservative N-cycle within Coal Creek is likely due to the abundance of conifer trees, and smaller riparian regions, retaining more NO3− overall and reduced processing prior to export. This study highlights the value of integrating isotope systematics to link watershed functional traits to mechanisms of watershed element retention and release.

The past decades have witnessed the increased applications of induced polarization (IP) method in the critical zone studies with ubiquitous clay minerals. Although IP outperforms traditional electrical and electromagnetic methods through its unique ability to measure quadrature conductivity, the nonlinearity that quadrature conductivity behaves with salinities and frequencies greatly tortures IP practitioners, as (a) salinity-dependency makes the quadrature conductivity a varyingly unstable parameter to quantitatively estimate hydraulic properties and clay content; (b) frequency-dependent Cole-Cole and Debye/Warburg decomposition models, although mathematically sound, physically mingle the properties of pore water and clay minerals and are empirical in nature. From basic principles, we demonstrate that quadrature conductivity remains a hybrid property involving both clay and water, and develop relevant models to distinguish them. Our models are validated by theories, experiments, simulations, and comparisons, all of which proclaim considerable advantages over previous models and offer the prospect of quantitative applications.

Sedimentary basins provide a deep time archive of tectonic and Earth-surface processes that can be leveraged by detrital mineral U-Pb dating and geochemistry to track paleogeography, magmatism, and crustal evolution. Zircon preserves the long-term (billions of years) record of supercontinent cycles; however, it is biased toward preserving felsic crustal records. Detrital rutile complements the detrital zircon record by providing constraints on the time and temperature of rifting and mafic magmatism, metamorphism, exhumation of the middle and lower crust, subduction, and amagmatic orogenesis. We use detrital zircon U-Pb and detrital rutile U-Pb geochronology and trace element analysis of Permian to Eocene siliciclastic rocks in the southern Pyrenees to capture supercontinent cycles of ocean basins opening and closing. Detrital rutile age spectra show peaks at ca. 100 Ma associated with rifting and hyperextension in the Pyrenean realm, 200 Ma associated with the Central Atlantic Magmatic Province, and 330 Ma, 375 Ma, and 400 Ma associated with subduction and Rheic Ocean crust formation. Zr-in-rutile thermometry and rutile Cr-Nb systematics provide further insight into metamorphic facies (peak metamorphic temperatures) and source rock lithology (mafic versus felsic affinity). Detrital zircon age spectra have peaks at ca. 300 Ma, 450 Ma, and 600 Ma associated with major orogenic events and felsic magmatism, and Th/U ratios provide information on relative zircon formation temperatures. Comparison of these independent records shows that detrital rutile reflects rifting, magma-poor orogenesis, and oceanic lithospheric processes, while detrital zircon detects continental lithospheric processes. Integrated detrital zircon and rutile data sets archive past geological events across multiple Wilson cycles.

SUMMARY: As the high-frequency analogue to field-scale earthquakes, acoustic emissions (AEs) provide a valuable complement to study rock deformation mechanisms. During the load-stepping creep experiments with CO2-saturated water injection into a basaltic sample from Carbfix site in Iceland, 8791 AE events are detected by at least one of the seven piezoelectric sensors. Here, we apply a cross-correlation-based source imaging method, called geometric-mean reverse-time migration (GmRTM) to locate those AE events. Besides the attractive picking-free feature shared with other waveform-based methods (e.g. time-reversal imaging), GmRTM is advantageous in generating high-resolution source images with reduced imaging artefacts, especially for experiments with relatively sparse receivers. In general, the imaged AE locations are found to be scattered across the sample, suggesting a complicated fracture network rather than a well-defined major shear fracture plane, in agreement with X-ray computed tomography imaging results after retrieval of samples from the deformation apparatus. Clustering the events in space and time using the nearest-neighbour approach revealed a group of ‘repeaters’, which are spatially co-located over an elongated period of time and likely indicate crack, or shear band growth. Furthermore, we select 2196 AE events with high signal-to-noise-ratio (SNR) and conduct moment tensor estimation using the adjoint (backpropagated) strain tensor fields at the locations of AE sources. The resulting AE locations and focal mechanisms support our previously assertion that creep of basalt at the experimental conditions is accommodated dominantly by distributed microcracking.

Abstract: Hyperspectral remote sensing has the potential to map numerous attributes of the Earth’s surface, including spatial patterns of biological diversity. Grasslands are one of the largest biomes on Earth. Accurate mapping of grassland biodiversity relies on spectral discrimination of endmembers of species or plant functional types. We focused on spectral separation of grass lineages that dominate global grassy biomes: Andropogoneae (C4), Chloridoideae (C4), and Pooideae (C3). We examined leaf reflectance spectra (350–2,500 nm) from 43 grass species representing these grass lineages from four representative grassland sites in the Great Plains region of North America. We assessed the utility of leaf reflectance data for classification of grass species into three major lineages and by collection site. Classifications had very high accuracy (94%) that were robust to site differences in species and environment. We also show an information loss using multispectral sensors, that is, classification accuracy of grass lineages using spectral bands provided by current multispectral satellites is much lower (accuracy of 85.2% and 61.3% using Sentinel 2 and Landsat 8 bands, respectively). Our results suggest that hyperspectral data have an exciting potential for mapping grass functional types as informed by phylogeny. Leaf‐level hyperspectral separability of grass lineages is consistent with the potential increase in biodiversity and functional information content from the next generation of satellite‐based spectrometers.

The paleogeography of Laurentia throughout the Neoproterozoic is critical for reconstructing global paleogeography due to its central position in the supercontinent Rodinia. We develop a new paleomagnetic pole from red siltstones and fine-grained sandstones of the early Neoproterozoic Jacobsville Formation which is now constrained to be ca. 990 Ma in age. High-resolution thermal demagnetization experiments resolve detrital remanent magnetizations held by hematite. These directions were reoriented within siltstone intraclasts and pass intraformational conglomerate tests—giving confidence that the magnetization is detrital and primary. An inclination-corrected mean paleomagnetic pole position for the Jacobsville Formation indicates that Laurentia's motion slowed down significantly following the onset of the Grenvillian orogeny. Prior rapid plate motion associated with closure of the Unimos Ocean between 1,110 and 1,090 Ma transitioned to slow drift of Laurentia across the equator in the late Mesoproterozoic to early Neoproterozoic. We interpret the distinct position of this well-dated pole from those in the Grenville orogen that have been assigned a similar age to indicate that the ages of the poles associated with the Grenville Loop likely need to be revised to be younger due to prolonged exhumation.

Miocene strata of the Claremont, Orinda, and Moraga formations of the Berkeley Hills (California Coast Ranges, USA) record sedimentation and volcanism during the passage of the Mendocino triple junction and early evolution of the San Andreas fault system. Detrital zircon laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) age spectra indicate a change in sedimentary prove nance between the marine Claremont formation (Monterey Group) and the terrestrial Orinda and Moraga Formations associated with uplift of Franciscan Complex lithologies. A sandstone from the Claremont formation produced a detrital zircon chemical abrasion–isotope dilution–thermal ionization mass spec trometry (CA-ID-TIMS) maximum depositional age of 13.298 ± 0.046 Ma, indicating younger Claremont deposition than previously interpreted. A trachydacite tuff clast within the uppermost Orinda Formation yielded a CA-ID-TIMS U-Pb zircon date of 10.094 ± 0.018 Ma, and a dacitic tuff within the Moraga Formation produced a CA-ID-TIMS U-Pb zircon date of 9.974 ± 0.014 Ma. These results indicate rapid progression from subsidence in which deep-water siliceous sediments of the Claremont formation were deposited to uplift that was followed by subsidence during deposition of terrestrial sediments of the Orinda Forma tion and subsequent eruption of the Moraga Formation volcanics. We associate the Orinda tuff clast and Moraga volcanics with slab-gap volcanism that followed the passage of the Mendocino triple junction. Given the necessary time lag between triple junction passage and the removal of the slab that led to this volcanism, subsidence associated with ca. 13 Ma Claremont sedimentation and subsequent Orinda to Moraga deposition can be attributed to basin formation along the newly arrived transform boundary.

The Snake River Plain (SRP) volcanic province overlies the track of the Yellowstone hotspot, a thermal anomaly that extends deep into the mantle. Most of the area is underlain by a basaltic volcanic province that overlies a mid-crustal intrusive complex, which in turn provides the long-term heat flux needed to sustain geothermal systems. Previous studies have identified several known geothermal resource areas within the SRP. For the geothermal study presented herein, our goals were to: (1) adapt the methodology of Play Fairway Analysis (PFA) for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal PFA model for the SRP and identify the most promising plays, using GIS-based software tools that are standard in the petroleum industry. The study focused on identifying three critical resource parameters for exploitable hydrothermal systems in the SRP: heat source, reservoir and recharge permeability, and cap or seal. Data included in the compilation for heat source were heat flow, distribution and ages of volcanic vents, groundwater temperatures, thermal springs and wells, helium isotope anomalies, and reservoir temperatures estimated using geothermometry. Reservoir and recharge permeability was inferred from the analysis of stress orientations and magnitudes, post-Miocene faults, and subsurface structural lineaments based on magnetics and gravity data. Data for cap or seal included the distribution of impermeable lake sediments and clay-seal associated with hydrothermal alteration below the regional aquifer. These data were used to compile Common Risk Segment maps for heat, permeability, and seal, which were combined to create a Composite Common Risk Segment map for all southern Idaho that reflects the risk associated with geothermal resource exploration and identifies favorable resource tracks. Our regional assessment indicated that undiscovered geothermal resources may be located in several areas of the SRP. Two of these areas, the western SRP and Camas Prairie, were selected for more detailed assessment, during which heat, permeability, and seal were evaluated using newly collected field data and smaller grid parameters to refine the location of potential resources. These higher resolution assessments illustrate the flexibility of our approach over a range of scales.

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

Geologic carbon storage (GCS) is ramping up worldwide as a viable component of carbon capture, utilization, and storage (CCUS) projects aimed at reducing greenhouse pollution to limit climate change. GCS may be a growth opportunity for the application of geophysics in reservoir characterization and monitoring. Federal and state government financial incentives are the economic motivators of the CCUS business in the United States, and recent increases in these incentives have triggered a large number of U.S. Environmental Protection Agency Class VI permit applications to inject CO2 for GCS. The applications indicate that almost all such projects propose using geophysical technology for monitoring. We assessed the GCS geophysical market in the United States based on an intensive analysis of recently filed Class VI permit applications. The analysis shows that reprocessing of existing seismic data will be the primary geophysical activity for reservoir characterization prior to CO2 injection. For monitoring, verification, and recording of CO2 injection, time-lapse vertical seismic profiling and 3D seismic imaging will be the dominant technologies followed by 2D time-lapse seismic imaging and some nonseismic methods. Passive seismic monitoring is planned for the majority of CCUS projects to reduce the risk of induced seismicity. If assumptions related to the United States meeting its current climate goals by 2050 are met, then geophysical activity will increase over the next 30 years. An estimate of the seismic crew count needed to support the projects suggests that the scale of GCS-related seismic acquisition by 2050 may reach the current level of onshore oil and gas geophysics crews in the United States. While the economic incentives of a regulation-driven market will press for the minimization of geophysical sensing in GCS, there is also the potential for growth in geophysical activity with the development of advanced processing and analysis tools, multiphysics data interpretation, and cost-effective continuous monitoring.

Abstract: West Antarctic Ice Sheet mass loss is a major source of uncertainty in sea level projections. The primary driver of this melting is oceanic heat from Circumpolar Deep Water originating offshore in the Antarctic Circumpolar Current. Yet, in assessing melt variability, open ocean processes have received considerably less attention than those governing cross-shelf exchange. Here, we use Lagrangian particle release experiments in an ocean model to investigate the pathways by which Circumpolar Deep Water moves toward the continental shelf across the Pacific sector of the Southern Ocean. We show that Ross Gyre expansion, linked to wind and sea ice variability, increases poleward heat transport along the gyre’s eastern limb and the relative fraction of transport toward the Amundsen Sea. Ross Gyre variability, therefore, influences oceanic heat supply toward the West Antarctic continental slope. Understanding remote controls on basal melt is necessary to predict the ice sheet response to anthropogenic forcing.

Abstract: Foraminifera are unicellular organisms that inhabit the oceans. They play an important role in the global carbon cycle and record valuable paleoclimate information through the uptake of trace elements such as strontium into their calcitic shells. Understanding how foraminifera control their internal fluid composition to make calcite is important for predicting their response to ocean acidification and for reliably interpreting the chemical and isotopic compositions of their shells. Here, we model foraminiferal calcification and strontium partitioning in the benthic foraminifera Cibicides wuellerstorfi and Cibicidoides mundulus based on insights from inorganic calcite experiments. The numerical model reconciles inter-ocean and taxonomic differences in benthic foraminifer strontium partitioning relationships and enables us to reconstruct the composition of the calcifying fluid. We find that strontium partitioning and mineral growth rates of foraminiferal calcite are not strongly affected by changes in external seawater pH (within 7.8–8.1) and dissolved inorganic carbon (DIC, within 2100–2300 μmol/kg) due to a regulated calcite saturation state at the site of shell formation.

The Nonesuch Formation microbiota provide a window into ca. 1075 Ma life within the interior of ancient North America. The Nonesuch water body formed following the cessation of widespread volcanism within the Midcontinent Rift as the basin continued to subside. In northern Michigan and Wisconsin, USA, the Copper Harbor Conglomerate records terrestrial alluvial fan and fluvial plain environments that transitioned into subaqueous lacustrine deposition of the Nonesuch Formation. These units thin toward a paleotopographic high associated with the Brownstone Falls angular unconformity. Due to these “Brownstone Highlands,” we were able to explore the paleoenvironment laterally at different depths in contemporaneous deposits. Rock magnetic data constrain that when the lake was shallow, it was oxygenated as evidenced by an oxidized mineral assemblage. Oxygen levels were lower at greater depth—in the deepest portions of the water body, anoxic conditions are recorded. An intermediate facies in depth and redox between these endmembers preserves detrital magnetite and hematite, which can be present in high abundance due to the proximal volcanic highlands. This magnetic facies enabled the development of a paleomagnetic pole based on both detrital magnetite and hematite that constrains the paleolatitude of the lake to 7.1 ± 2.8°N. Sediments of the intermediate facies preserve exquisite organic-walled microfossils, with microfossils being less diverse to absent in the anoxic facies where amorphous organic matter is more likely to be preserved. The assemblage of cyanobacteria and eukaryotes (both photoautotrophs and heterotrophs) lived within the oxygenated waters of this tropical Mesoproterozoic water body.

Abstract: The westernmost Nankai Trough, southwest Japan, exhibits a rapid along-strike reduction in plate coupling in the proximity to the subducting Kyushu-Palau ridge. Yet how and to what extent the ridge subduction impacts physical properties at the megathrust have not been investigated. Here we present high-resolution seismic P-wave velocity models along the forearc wedge in the western Nankai Trough derived from full-waveform inversion analyses of seismic refraction data. The velocity models show that where the plate coupling is weak and the plate boundary presumably hosts slow earthquakes, the upper plate exhibits lower seismic velocities indicating higher degree of fracturing over a ~ 100 km length along trough. Intriguingly, the extent of the upper-plate low-velocity features is significantly larger than the surficial width of the Kyushu-Palau ridge, and this low-velocity zone is underthrust by the slab with increased crustal thickness by 2–4 km. Seismic reflection images consistently reveal that the thicker slab crust has appreciable basement roughness extending ~ 60 km from the eastern margin of the Kyushu-Palau ridge beneath the western Shikoku basin. We suggest that such a thicker and rugged slab crust, together with the main body of the Kyushu-Palau ridge, can cause significant fracture zones in the overriding plate, decrease the interplate coupling and produce preferable conditions for shallow slow earthquakes to occur when subducted. The results may also provide structural constraints on the western limit of future megathrust earthquakes in the Nankai Trough. Graphical Abstract

Monitoring, verification, and accounting (MVA) are crucial to ensure safe and long-term geologic carbon storage. Seismic monitoring is a key MVA technique that utilizes seismic data to infer elastic properties of CO2-saturated rocks. Reliable accounting of CO2 in subsurface storage reservoirs and potential leakage zones requires an accurate rock physics model. However, the widely used CO2 rock physics model based on the conventional Biot-Gassmann equation can substantially underestimate the influence of CO2 saturation on seismic waves, leading to inaccurate accounting. We develop an accurate CO2 rock physics model by accounting for both effects of the stress dependence of seismic velocities in porous rocks and CO2 weakening on the rock framework. We validate our CO2 rock physics model using the Kimberlina-1.2 model (a previously proposed geologic carbon storage site in California) and create time-lapse elastic property models with our new rock physics method. We compare the results with those obtained using the conventional Biot-Gassmann equation. Our innovative approach produces larger changes in elastic properties than the Biot-Gassmann results. Using our CO2 rock physics model can replicate shear-wave speed reductions observed in the laboratory. Our rock physics model enhances the accuracy of time-lapse elastic-wave modeling and enables reliable CO2 accounting using seismic monitoring.

Right-lateral transform motion associated with the Pacific-North American plate boundary in the modern-day San Francisco Bay Area occurs across a series of sub-parallel fault zones. Much of this motion is accommodated east of the San Andreas Fault by the faults of the East Bay fault system. A major tool for reconstructing the spatial and temporal history of fault motion is the correlation of offset Neogene volcanic rocks. These Neogene volcanics within the California Coast Ranges formed in association with the slab gap that grew as the Mendocino Triple Junction migrated northward. Some of the volcanic centres have been variably offset by subsequent strike-slip faulting. A felsic volcanic unit exposed in Berkeley, CA, known as the Northbrae rhyolite has variably been interpreted to be one of these Neogene volcanic units or to be a Mesozoic volcanic unit associated with the Coast Range ophiolite. A new U-Pb zircon date of 11.10 (Formula presented.) 0.09 Ma confirms the Neogene volcanic interpretation. This date is indistinguishable from previously published Ar/Ar dates from the Burdell Mountain volcanics of the North Bay region as well as a new U-Pb zircon date of 11.07 (Formula presented.) 0.10 Ma. In addition to the indistinguishable ages, similarities in bulk lithology, zircon crystallization/dissolution textures, and zircon trace element geochemistry are consistent with these rhyolites being associated with the same volcanic centre. This correlation implies that 40 (Formula presented.) 5 km of right-lateral offset occurred to the west of the modern-day position of the Hayward-Rodgers Creek fault zone. This offset represents (Formula presented.) 20% of the total offset along the East Bay fault system. A proto-Hayward Fault with a different geometry than that of the present-day played a significant role in the evolution of the fault system. This result highlights the dynamic spatiotemporal variability of strike-slip faults along transform margins.

The intensity and frequency of wildfires in California (CA) have increased in recent years, causing significant damage to human health and property. In October 2007, a number of small fire events, collectively referred to as the Witch Creek Fire or Witch Fire started in Southern CA and intensified under strong Santa Ana winds. As a test of current mesoscale modeling capabilities, we use the Weather Research and Forecasting (WRF) model to simulate the 2007 wildfire event in terms of meteorological conditions. The main objectives of the present study are to investigate the impact of horizontal grid resolution and planetary boundary layer (PBL) scheme on the model simulation of meteorological conditions associated with a Mega fire. We evaluate the predictive capability of the WRF model to simulate key meteorological and fire-weather forecast parameters such as wind, moisture, and temperature. Results of this study suggest that more accurate predictions of temperature and wind speed relevant for better prediction of wildfire spread can be achieved by downscaling regional numerical weather prediction products to 1 km resolution. Furthermore, accurate prediction of near-surface conditions depends on the choice of the planetary boundary layer parameterization. The MYNN parameterization yields more accurate prediction as compared to the YSU parameterization. WRF simulations at 1 km resolution result in better predictions of temperature and wind speed than relative humidity during the 2007 Witch Fire. In summary, the MYNN PBL parameterization scheme with finer grid resolution simulations improves the prediction of near-surface meteorological conditions during a wildfire event.

Deep-learning inversion has recently drawn attention in geological carbon storage research due to its potential of imaging and monitoring carbon storage in real time, significantly improving efficiency and safety of carbon storage operations. We present a deep-learning full waveform inversion method that after the neural network has been trained can image CO2 saturation and its uncertainty in real time. Our deep-learning inversion method is based on the U-Net architecture with the neural network trained on pairs of synthetic seismic data and CO2 saturation models. Accordingly, our training establishes a mapping relationship between seismic data and CO2 saturation models and once fully trained directly estimates CO2 saturation as a function of subsurface location. We further quantify uncertainties of CO2 saturation estimates using the Monte Carlo dropout method and a bootstrap aggregating method. For this proof-of-concept study, the CO2 training models and data are derived from the Kimberlina 1.2 model, a hypothetical 3D geological carbon storage model that is constructed based on various geological and hydrological data from the Southern San Joaquin Basin, California. We perform deep-learning inversion experiments using noise-free and noisy training and test data sets and compare the results. Our modelling experiments show that (1) the deep-learning inversion can estimate 2D distributions of CO2 fairly well even in the presence of Gaussian random noise and (2) both CO2 saturation imaging and uncertainty quantification can be done in real time. Our results suggest that the deep-learning inversion method can serve as a robust real-time monitoring tool for geological carbon storage and/or other time-varying reservoir/aquifer properties that result from injection, extraction, and/or other subsurface transport phenomena.

Multiphysics inversion exploits different types of geophysical data that often complement each other and aims to improve overall imaging resolution and reduce uncertainties in geophysical interpretation. Despite the advantages, traditional multiphysics inversion is challenging because it requires a large amount of computational time and intensive human interactions for preprocessing data and finding trade-off parameters. These issues make it nearly impossible for traditional multiphysics inversion to be applied as a real-time monitoring tool for geological carbon storage. In this paper, we present a deep learning (DL) multiphysics network for imaging CO2 saturation in real time. The multiphysics network consists of three encoders for analysing seismic, electromagnetic and gravity data and shares one decoder for combining imaging capabilities of the different geophysical data for better predicting CO2 saturation. The network is trained on pairs of CO2 label models and multiphysics data so that it can directly image CO2 saturation. We use the bootstrap aggregating method to enhance the imaging accuracy and estimate uncertainties associated with CO2 saturation images. Using realistic CO2 label models and multiphysics data derived from the Kimberlina CO2 storage model, we evaluate the performance of the deep learning multiphysics network and compare its imaging results to those from the deep learning single-physics networks. Our modelling experiments show that the deep learning multiphysics network for seismic, electromagnetic, and gravity data not only improves the imaging accuracy but also reduces uncertainties associated with CO2 saturation images. Our results also suggest that the deep learning multiphysics network for the non-seismic data (i.e., electromagnetic and gravity) can be used as an effective low-cost monitoring tool in between regular seismic monitoring.

Knowing the structure of the crust is critical to understanding a planet's geologic evolution. Crustal thickness inversions rely on bulk density estimates, which are primarily affected by porosity. Due to the absence of high‐resolution gravity data, Mercury's crustal porosity has remained unknown. Here, we use a model that was calibrated to the Moon to relate Mercury's impact crater population and long‐wavelength crustal porosity in the cratered terrains. Therein, porosity is created by large impacts and then decreased as the surface ages due to pore compaction by smaller impacts and overburden pressure. Our models fit independent gravity‐derived porosity estimates in the northern regions, where data is well resolved. Porosity in the cratered terrains is found to be 9%–18% with an average and standard deviation of 13% ± $\pm $ 2%, indicating lunar‐like crustal bulk densities of 2,565 ± $\pm $ 70 kg m−3 ${\mathrm{m}}^{-3}$ from which updated crustal thickness maps are constructed. Plain Language Summary: The crust of a planet is a thermal barrier, which controls how fast heat escapes to space. Depending on its thickness, the crust can strongly insulate the planet's interior preventing efficient cooling. Therefore, knowing the structure of the crust is critical to unraveling the geologic history of planetary bodies. Crustal thickness is typically inverted from gravity and topography data. One critical parameter for these inversions is the bulk density of the crust, which is primarily driven by porosity variations. While high‐resolution gravity field mapping allowed constraining the bulk density and porosity of the lunar crust, crustal porosity on other planetary bodies has remained unknown. In this work, we use a model that was calibrated to the Moon to relate Mercury's impact crater population and long‐wavelength crustal porosity in the cratered terrains. We show that crustal porosity in the cratered terrains ranges from 9% to 18% with an average and standard deviation of 13% ± $\pm $ 2%, indicating lunar‐like low bulk densities of 2,565 ± $\pm $ 70 kg m−3 ${\mathrm{m}}^{-3}$. Key Points: Mercury's crustal porosity estimated from the crater population, assuming porosity formed by large impacts and decreased with surface agingCrustal porosity in the cratered terrains ranges from 9% to 18% with an average and standard deviation of 13% ± 2%The low bulk density of Mercury's crust in the cratered terrain, 2,565 ± 70 kg m−3, is similar to that of the lunar highlands [ABSTRACT FROM AUTHOR]

Identification of preferential flow‐paths, such as fractures, is required for various issues in geosciences. When chemicals are injected into the subsurface, monitoring the resulting structural and chemical changes remains a challenge. The ability of geophysical tomography to tackle this problem is not fully explored due to the lack of numerical methods suitable for modeling narrow structures. We explore how discrete representation of preferential flow‐paths provides innovative ways to invert electrical resistivity data collected during reagent injection at a contaminated site. The data set is inverted with a scheme where a new fracture is added at every iteration. This allows identifying newly created narrow conductive structures from the field data collected before and after injection. Fracture location remains overall consistent despite using different starting points for the fracture search. A prior constraint on fracture length improves convergence. These results show the potential of discrete inversion for identifying narrow structures from electrical resistivity monitoring. Plain Language Summary: In some geoscience activities, such as water extraction, geological storage, and contaminant fate, chemical solutions are injected into wells, which potentially leads to modify the system properties. Identifying preferential flow‐paths is therefore necessary even though monitoring structural and chemical changes in the subsurface remains a challenge. Electrical geophysical imaging techniques may be adapted to provide information for this purpose. However, their potential is not fully explored due to the limitations of numerical models to represent small‐scale structures. In this work, we explore the representation of preferential flow‐paths by discrete elements for the inversion of electrical resistivity data collected during a reagent injection at a contaminated site. The inversion scheme based on discrete forward simulations successively identifies small‐scale structures and focuses on evaluating their localization and length. The results show the need for further efforts to use discrete electrical resistivity inversion in the presence of narrow structures. Key Points: Standard modeling strategies are not well suited to identify narrow geological structures from cross‐borehole electrical data inversionInversion scheme based on discrete‐dual‐porosity forward simulations enable to image narrow preferential flow‐paths from electrical dataPrior assumptions are needed to invert the position and length of narrow preferential flow‐paths [ABSTRACT FROM AUTHOR]

Accurate and stable measurement of inertial quantities is essential in geophysics, geodesy, fundamental physics, and inertial navigation. Here, we present an architecture for a compact cold-atom accelerometer-gyroscope based on a magnetically launched atom interferometer. Characterizing the launching technique, we demonstrate 700-parts per million gyroscope scale factor stability over 1 day, while acceleration and rotation rate bias stabilities of 7 × 10-7 meters per second squared and 4 × 10-7 radians per second are reached after 2 days of integration of the cold-atom sensor. Hybridizing it with a classical accelerometer and gyroscope, we correct their drift and bias to achieve respective 100-fold and 3-fold increase on the stability of the hybridized sensor compared to the classical ones. Compared to a state-of-the-art atomic gyroscope, the simplicity and scalability of our launching technique make this architecture easily extendable to a compact full six-axis inertial measurement unit, providing a pathway toward autonomous positioning and orientation using cold-atom sensors. [ABSTRACT FROM AUTHOR]

Regional and nationwide geophysical merges consisting of magnetic and radiometric datasets have become standard practice within Australia and some parts of the world. The best practice for geophysical merges is to ensure the highest quality survey data is incorporated in all given areas. However, the traditional means of accomplishing this determination is quite qualitative without a well-defined methodology. Here, a quantitative algorithmic approach is provided, reducing user "guesswork" regarding which survey supersedes others when occupying the same space within geophysical merges. This is accomplished by assessing a wide range of survey specifications and applying weighted scores to their relative importance. This algorithm is applied to 889 datasets flown in New South Wales between 1957 and 2023 and provides a clear efficacy in determination of data quality based on survey design. Results from this algorithm have demonstrated proficiency in ranking surveys from highest to lowest quality and have formed the basis of all statewide geophysical merges in NSW since 2020. [ABSTRACT FROM AUTHOR]

The complete catalogue of moment tensor (MT) solutions is essential for a wide range of research in solid earth science. However, the number of reliable MT solutions for small to moderate earthquakes (3.0 ≤ M  ≤ 5.5) is limited due to uncertainties arising from data and theoretical errors. In this study, we develop a new procedure to enhance the resolvability of MT solutions and provide more reliable uncertainty estimates for these smaller to moderate earthquakes. This procedure is fully automatic and efficiently accounts for both data and theoretical errors through two sets of hybrid linear–non-linear Bayesian inversions. In the inversion process, the covariance matrix is estimated using an empirical approach: the data covariance matrix is derived from the pre-event noise and the theoretical covariance matrix is derived from the residuals of the initial solution. We conducted tests using synthetic data generated from the 3-D velocity model and interference from background seismic noise. The tests found that using a combination of the non-Toeplitz data covariance matrix and the Toeplitz theoretical covariance matrix improves the solution and its uncertainties. Test results also suggest that including a theoretical covariance matrix when analysing MT in complex tectonic regions is essential, even if we have the best 1D velocity model. The application to earthquakes in the northern region of the Banda Arc resulted in the first published Regional Moment Tensor (RMT) catalogue, containing more than three times the number of trusted solutions compared to the Global Centroid Moment Tensor (GCMT) and the Indonesian Agency for Meteorology Climatology and Geophysics Moment Tensor (BMKG-MT) catalogue. The comparison shows that the trusted solutions align well with the focal mechanism of the GCMT and BMKG-MT, as well as with the maximum horizontal stress of the World Stress Map, and tectonic conditions in the study area. The newly obtained focal mechanisms provide several key findings: (i) they confirm that the deformation in the northern and eastern parts of Seram Island is influenced by oblique intraplate convergence rather than by the subduction process; (ii) they validate the newly identified Amahai Fault with a greater number of focal mechanisms and (iii) they reveal an earthquake M w 4.7 with the same location and source mechanism 6 yr before the 2019 Ambon-Kairatu earthquake (M w 6.5) which occurred on a previously unidentified fault. [ABSTRACT FROM AUTHOR]

Recent research in the later Bronze Age of the southern Carpathian Basin has revealed an extensive network of large, often-enclosed settlements. Within this network, a particularly dense group of sites has recently been characterized: the Tisza Site Group (TSG). Building on advances in inter-site relations in recent research, we explore social organization within settlements using five case studies from different parts of this network. Using a multi-proxy approach of satellite imagery, systematic surface survey, and geophysical prospection, we studied the distribution of archaeological features and surface traces of activity within the enclosed space. Results indicate that sites in the TSG shared a common ethos regarding the use of space and the role of the built environment that was specific to LBA occupation of this landscape. Activity areas with domestic assemblages distributed in low-density relative to the enclosed space indicates settlement and specialist subsistence activities took place in parallel. [ABSTRACT FROM AUTHOR]

Field evidence indicates c. 40 Ma (Early-Middle Eocene) contractional deformation in the S Amanos Mountains. Following latest Cretaceous southward ophiolite emplacement, an intra-platform basin infilled with shallow to deeper marine, dominantly carbonate sediments. Localized thrusting, reverse faulting, and folding were followed by subaerial erosion and non-marine clastic deposition, sealed by an Early Miocene marine transgression. Eocene emergence elsewhere in SE Türkiye probably also resulted from regional crustal shortening. Alternative hypotheses for collision in SE Türkiye propose latest Cretaceous, Mid-Late Eocene, Early Miocene, or Late Miocene suturing of S Neotethys. Much geological evidence in SE Türkiye and NW Iran supports Mid-Late Eocene initial continent-continent collision. Plate reconstructions suggest S Neotethys survived in this region until the Mid-Late Eocene. Biogeographical evidence points to minor Eocene mammal migration across S Neotethys, followed by Early Miocene large-scale terrestrial migrations. Seawater isotopic data suggest a major decrease in inter-Indian Ocean-Mediterranean Sea current flow during the Early Miocene. Instrumental geophysics and both numerical and analogue modelling suggest that the northern Arabian platform underthrust Eurasia (>200 km in S central Iran). In SE Türkiye, Eocene initial ‘soft’ collision was followed by Early Miocene ‘hard collision’, with crustal thickening and exhumation continuing until the Late Miocene, followed by westward ‘tectonic escape’. [ABSTRACT FROM AUTHOR]

A key challenge in helium (He) exploration is determining the efficacy of surficial soil gas surveys. While soil gas surveys can detect helium, the mechanisms leading to these signals are often poorly understood, hindering reliable interpretation for exploration purposes. Here we present the results of seven new He soil gas surveys (n = 1974) at the Akah Nez Field, Beautiful Mountain Field, Porcupine Dome area, Rattlesnake Field, Tom area, Tohache Wash area, and White Rock area, on the Colorado Plateau, Four Corners area, United States. Utilizing 2D seismic, well logs, and geophysical potential field data, structural maps were constructed of potential He reservoirs at depth and relationships were examined. Given geospatial relationships are being examined using the soil gas survey data, it is important to understand the mechanism that allows subsurface He to migrate upwards into the soil. In several fields interpreted basement faults act as migration conduits from the basement to the surface (i.e., leaky reservoir seals), and in other cases there is evidence for reservoir flank/crest fracturing likely due to differential compaction. Based on the regional geologic history, advective systems are likely responsible for the observed He soil gas signatures. Additionally, based on the Tohache Wash data (most prospective He area) an effective and risk-reducing novel technique is presented that constructs a predictive He exploration model utilizing soil gas geochemistry, high-resolution geophysical data, well data and seismic data using Bayesian ANOVA techniques, which may be translated to areas outside of the Four Corners area, United States. [ABSTRACT FROM AUTHOR]

Vegetation indices have become an indispensable tool in remote sensing‐based agricultural research. A recent area of advancement in agricultural remote sensing research is in high‐throughput phenotyping, often conducted on a plot by plot basis. FIELDimageR is a tool used extensively in high‐throughput phenotyping that estimates zonal statistics of vegetation indices per plot. However, being written in R language, FIELDimageR requires high computing time. As a high‐resolution image over a large area means a large number of pixels, FIELDimageR is incapable of using high‐resolution orthomosaicked images without reducing image resolution by aggregating digital numbers of several pixels and treating them as one pixel. This research tool implements FIELDimageR in the Python language as FIELDimagePy. FIELDimagePy follows similar workflows as FIELDimageR and generates equivalent results for zonal statistics of vegetation indices per plot. FIELDimagePy is significantly and substantially faster than FIELDimageR. Computing time by FIELDimagePy are three to four times lower than computing times by FIELDimageR, even when using raw images with 16 times denser pixels. Moreover, FIELDimagePy is useful beyond plot by plot research in agriculture and capable of estimating zonal statistics of any raster bounded by any polygons. With slight modifications, FIELDimagePy can be useful for other disciplines of science, such as geophysics, geography, economics, medical sciences, among others. FIELDimagePy can be accessed from the GitHub repository: https://github.com/SumantraChatterjee/FIELDimagePy. [ABSTRACT FROM AUTHOR]

Lithology classification is a fundamental aspect of reservoir classification. Due to the limited availability of core samples, computational modelling methods for lithology classification based on indirect measurements are required. The main challenge for standard clustering methods is the complex vertical dependency of sedimentological sequences as well as the spatial coupling of well logs. Machine learning methods, such as recurrent neural networks, long short‐term memory and bidirectional long short‐term memory, can account for the spatial correlation of the measured data and the predicted model. Based on these developments, we propose a novel approach using two distinct models: a self‐attention‐assisted bidirectional long short‐term memory model and a multi‐head attention‐based bidirectional long short‐term memory model. These models consider spatial continuity and adaptively adjust the weight in each step to improve the classification using the attention mechanism. The proposed method is tested on a set of real well logs with limited training data obtained from core samples. The prediction results from the proposed models and the benchmark one are compared in terms of the accuracy of lithology classification. Additionally, the weight matrices from both attention mechanisms are visualized to elucidate the correlations between depth steps and to help analyse how these mechanisms contribute to improved prediction accuracy. The study shows that the proposed multi‐head attention‐based bidirectional long short‐term memory model improves classification, especially for thin layers. [ABSTRACT FROM AUTHOR]

Ongoing investments in irrigation technologies highlight the need to accurately estimate the longevity and magnitude of water savings at the watershed level to avoid the paradox of irrigation efficiency. This paradox arises when irrigation pumping exceeds crop water demand, leading to excess water that is not recovered by the watershed. Comprehensive water accounting from farm to watershed scales is challenging due to spatial variability and inadequate socio-hydrological data. We hypothesize that water savings are short term, as prior studies show rapid recharge responses to surface changes. Precise estimation of these time scales and water savings can aid water managers making decisions. In this study, we examined water savings at three 65-hectare sites in Nebraska with diverse soil textures, management practices, and groundwater depths. Surface geophysics effectively identified in-field variability in soil water content and water flux. A one-dimensional model showed an average 80% agreement with chloride mass balance estimates of deep drainage. Our findings indicate that groundwater response times are short and water savings are modest (1–3 years; 50–900 mm over 10 years) following a 120 mm/year reduction in pumping. However, sandy soils with shallow groundwater show minimal potential for water savings, suggesting limited effectiveness of irrigation efficiency programs in such regions. [ABSTRACT FROM AUTHOR]

In the twentieth century, exploration geophysics and digital vocal processing each underwent key technical transformations based on formally similar signal processing techniques derived from prior work in statistics and information theory. Engineers at Texas Instruments (TI) and the Massachusetts Institute of Technology (MIT) developed deconvolution filtering as a way to model geological strata from seismograph recordings in order to facilitate oil exploration. Meanwhile, engineers at Bell Laboratories and Nippon Telegraph and Telephone (NTT) used similar techniques to digitally encode and transmit speech signals more efficiently – a method known as linear predictive coding (LPC). These cognate approaches to modeling geophysical and vocal signals provided a practical basis for subsequent forays by oil industry figures into the world of digital audio. Tracing the histories of four technologies – LPC secure voice transmission terminals, the TI Speak & Spell educational toy, automatic speech recognition, and the vocal pitch correction software Auto-Tune – I analyze the role of security interests in facilitating spillovers between technologies of oil and the voice. I argue that, by approaching both geophysical and vocal signals as matters of national security, the United States’ defense and intelligence services furnished the bulk of socio-economic connective tissue between petroleum geophysics and vocal processing research. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) imaging aims to produce large-scale, high-resolution soil conductivity maps that provide essential information for Earth subsurface exploration. To rigorously generate EM subsurface models, one must address both the forward problem and the inverse problem. From these subsurface resistivity maps, also referred to as volumes of resistivity distribution, it is possible to extract useful information (lithology, temperature, porosity, permeability, among others) to improve our knowledge about geo-resources on which modern society depends (e.g., energy, groundwater, and raw materials, among others). However, this ability to detect electrical resistivity contrasts also makes EM imaging techniques sensitive to metallic structures whose EM footprint often exceeds their diminutive stature compared to surrounding materials. Depending on target applications, this behavior can be advantageous or disadvantageous. In this work, we review EM modeling and inverse solutions in the presence of metallic structures, emphasizing how these structures affect EM data acquisition and interpretation. By addressing the challenges posed by metallic structures, our aim is to enhance the accuracy and reliability of subsurface EM characterization, ultimately leading to improved management of geo-resources and environmental monitoring. Here, we consider the latter through the lens of a triple helix approach: physics behind metallic structures in EM modeling and imaging, development of computational tools (conventional strategies and artificial intelligence schemes), and configurations and applications. The literature review shows that, despite recent scientific advancements, EM imaging techniques are still being developed, as are software-based data processing and interpretation tools. Such progress must address geological complexities and metallic casing measurements integrity in increasing detail setups. We hope this review will provide inspiration for researchers to study the fascinating EM problem, as well as establishing a robust technological ecosystem to those interested in studying EM fields affected by metallic artifacts. [ABSTRACT FROM AUTHOR]

High-energy-density laser facilities and advances in dynamic compression techniques have expanded access to material states in the Terapascal regime relevant to inertial confinement fusion, planetary science, and geophysics. However, experimentally determining the material temperature in these extreme conditions has remained a difficult challenge. Extended X-ray Absorption Fine Structure (EXAFS), referring to the modulations in x-ray absorption above an absorption edge from photoelectrons' interactions with neighboring atoms, has proven to be a versatile and robust technique for probing material temperature and density for mid-to-high Z elements under dynamic compression. The current platform at the National Ignition Facility has developed six configurations for EXAFS measurements between 7 and 18 keV for different absorption edges (Fe K, Co K, Cu K, Ta L3, Pb L3, and Zr K) using a curved-crystal spectrometer and a bright, continuum foil x-ray source. In this work, we describe the platform geometry, x-ray source performance, spectrometer resolution and throughput, design considerations, and data in ambient and dynamic-compression conditions. [ABSTRACT FROM AUTHOR]

Basin aquifers are important groundwater sources in the Western United States that are increasingly stressed due to growing populations, increased resource use, and the impacts of climate change. These aquifers are mainly recharged through melting snowpack in the surrounding mountains that infiltrates to the water table and flows directly into the basin (Mountain Front Recharge), or through deeper groundwater pathways that flow from the mountains directly into the basin aquifer (Mountain Block Recharge). However, the dominant system of recharge remains uncharacterized in many mountain basin aquifers. To address this challenge, near‐surface geophysical methods are being implemented to efficiently measure properties that govern groundwater storage and movement. This study infers groundwater storage and recharge to the Casper Aquifer around Laramie, WY, building off past studies that relied solely on sparse monitoring well data and observation of rainfall events. In this study, we use a clustering analysis on airborne electromagnetic data to define hydrogeophysical layers within the Casper Aquifer. These layers, which represent significant changes in bulk subsurface electrical resistivity, are integrated with existing hydrologic, lithologic, and smaller scale geophysical datasets to build a more representative hydrogeophysical model. Through this analysis, we define two sub‐aquifers within the larger Casper Aquifer system that are connected through structurally induced fractures and faults. This research highlights the importance of integrating geophysical data at multiple scales for defining hydrogeophysical layers that provide both a more complete understanding of basin aquifer recharge dynamics and constrain more detailed hydrologic models. Plain Language Summary: Growing populations, increased resource use, and climate change all lead to rising stress on groundwater resources in the Western United States. Groundwater in the western mountain region is generally stored in sedimentary basin aquifers that are understood to be recharged through precipitation that either: (1) infiltrates the water table and then flows directly into the basin, or (2) through deeper groundwater paths that flow from the crystalline cores of the mountains into the basin aquifers. However, relevant recharge systems are uncharacterized in many mountainous aquifers of the Western US. To address this challenge, near‐surface geophysical methods are being used to efficiently measure properties that govern groundwater storage and movement into these basin aquifers. This study uses hydrologic and multiple scale near surface geophysical data (airborne, surface and borehole) as inputs to constrain the storage and recharge dynamics on the Casper Aquifer near Laramie, WY. Integrating lithologic, hydrologic, and geophysical data at fine to large scale, highlights that the Casper Aquifer recharges primarily through snowmelt infiltration atop the nearby Laramie Range, where it flows downslope into the basin until it intersects fracture zone permeability pathways that facilitate movement of groundwater to shallower levels from a deeper primary subsurface aquifer layer. Key Points: Hydrogeophysical layers, distinct by their geophysical properties, are defined through the integration of multi‐scale geophysical dataNew mountain basin, front slope flow recharge regime defined for basin aquifers that outcrop from valley basin to summit of front slopeIntegrating multiscale geophysical data generates more complete understanding of groundwater storage and movement than traditional hydrologic studies [ABSTRACT FROM AUTHOR]