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USGS2024

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

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

Science of the Total Environment↗
USGS2024

Triggering the 2022 eruption of Mauna Loa

Distinguishing periods of intermittent unrest from the run-up to eruption is a major challenge at volcanoes around the globe. Comparing multidisciplinary monitoring data with mineral chemistry that records the physical and spatio-temporal evolution of magmas fundamentally advances our ability to forecast eruptions. The recent eruption of Mauna Loa, Earth’s largest active volcano, provides a unique opportunity to differentiate unrest from run-up and improve forecasting of future eruptions. After decades of intermittent seismic and geodetic activity over 38 years of repose, Mauna Loa began erupting on 27 November 2022. Here we present a multidisciplinary synthesis that tracks the spatio-temporal evolution of precursory activity by integrating mineral and melt chemistry, fluid inclusion barometry, numerical modeling of mineral zoning, syn-eruptive gas plume measurements, the distribution and frequency of earthquake hypocenters, seismic velocity changes, and ground deformation. These diverse data indicate that the eruption occurred following a 2-month period of sustained magma intrusion from depths of 3–5 km up to 1–2 km beneath the summit caldera, providing a new model of the plumbing system at this very high threat volcano. Careful correlation of both the geochemistry and instrumental monitoring data improves our ability to distinguish unrest from the run-up to eruption by providing deeper understanding of the both the monitoring data and the magmatic system—an approach that could be applied at other volcanic systems worldwide.

Hawaii↗
USGS2025

Dendroseismological investigation of redwood trees along the North Coast section of the San Andreas Fault

Sequoia sempervirens (coast redwood) tree rings have the potential to annually resolve late-Holocene earthquakes on the northern San Andreas Fault based on direct (e.g., physical damage) and indirect (e.g., co-seismic environmental change) impacts, but scarcity of suitable samples and challenges crossdating this long-lived species have limited progress. More precise dating of the pre-1906 (penultimate) earthquake can improve hazard assessment and understanding of rupture segmentation. We target old trees (maximum >815 yr) along the North Coast section of the fault (increment cores via rope-climbing, 11 living trees; plunge cuts, 23 stumps) and employ complementary disturbance detection methods including radial-growth averaging (tree- and series-level), cataloging anatomical indicators (e.g., traumatic resin ducts, TRD), and dating structural components (e.g., reiterated trunks, leans). Multi-centennial ring-width chronologies at Fort Ross (1569−2023) and Gualala (1397−2023) promote continued study with incomplete crossdating limiting utilization of some series. Growth pulses (reductions, releases) and TRD dispersed across the record reflect dynamic environments that obfuscate detection of earthquake signals. The 1906 earthquake did not leave strong signatures on most trees, and when it did, within-tree response varied from normal presentation to discoloration, TRD, and missing rings. Synchrony of indicators at both locations identified 1678−1680 (6 of 15 trees) and 1698−1700 (8 of 16 trees) as the strongest disturbances among dated rings in the time range of the penultimate earthquake, peaking at 1698 (15.7 % of possible growth and anatomical indicators), but the triggering mechanisms for these events are unknown.

California↗
USGS2025

A 10-year continuous daily simulation of chloride flux from a suburban watershed in Fairfax County, Virginia, USA

Increasing levels of chloride in surface water are associated with detrimental effects on water quality, aquatic ecosystems, infrastructure, and human health. Numerous mass-balance studies have inferred watershed transport processes by interpreting chloride inputs and outputs, but few represent internal dynamics explicitly. We constructed a coupled water/chloride mass balance model to gain insights into storage, residence time, and transport processes in a 10-km 2 urban watershed. The model, which operates over a 10-year period at a daily time scale, represents storage in a dynamic soil-moisture reservoir, quick-flow runoff from storm events, and slow-flow runoff that sustains streamflow in dry weather. The calibrated model accurately represented (a)the observed transition from a streamflow enrichment regime in cold months to a dilution regime in warmer months, (b) the observed tendency for late-summer concentrations to be higher after winters with heavy snowfall, and (c) a period-of-record downward trend in chloride concentration likely associated with a downward trend in annual snowfall. Estimated chloride inputs averaged 195 metric tons per year, while the average output was 270 metric tons per year. In contrast, estimated storage was only 107 metric tons. The estimated mean residence time in groundwater was 1.27 years. This short residence time indicates that efforts to reduce inputs will manifest as decreased concentrations in streamflow on a management-relevant time scale of several years. The coupled mass balance model yielded insights into internal watershed dynamics that would not be possible from simple input/output analysis; such models can be useful tools for gaining insight into small watershed hydrology and pollutant transport.

Virginia↗
USGS2026

Magnitude conversion relations create substantial differences in seismic hazard models

Earthquake catalogs are essential data inputs for seismic hazard modeling. Because earthquake magnitudes are reported in a variety of types (e.g., local magnitudes and moment magnitudes), magnitude conversion relationships must be used to convert the different magnitude types present in a catalog to a uniform magnitude type to avoid biases in the hazard computation. However, these conversion relationships are often uncertain and have been shown to sometimes perform poorly. Here, we investigate the sensitivity of the gridded seismicity component of the National Seismic Hazard Model (NSHM) to the catalog conversion equations in the Eastern United States. In the 2023 NSHM, magnitudes of various types were converted to moment magnitudes using equations developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn), based on least‐squares (LS) regressions made using data from a catalog containing events up through 2008. We recompute these equations using events in the Advanced National Seismic System Comprehensive Earthquake Catalog with multiple magnitudes from 2000 to 2023. Although we prefer the use of orthogonal regressions for our datasets, LS regressions produce broadly similar results, with both approaches exhibiting large deviations from the CEUS‐SSCn conversions, especially at smaller magnitudes. We compare the spatial distribution of annual rates using three different models: (1) the 2023 NSHM conversions, (2) our updated conversions, and (3) no conversions. We find that the choice of conversions leads to substantial differences in the rate forecasts, which can greatly impact the seismic hazard model, particularly in regions with low‐seismicity rates such as the Eastern United States, where the hazard is dominated by gridded seismicity rather than a fault model.

Seismological Research Letters↗
USGS2026

Earthquake-hazard exposure of residents with potential access and functional needs in the United States

Earthquake response plans and earthquake early warning (EEW) systems designed for general populations may not consider potential access and functional needs (AFN) of individuals with physical, sensory, cognitive, or social limitations. Previous efforts to map the distribution of these populations have focused on social-vulnerability indices that ignore or oversimply these limitations. The descriptive and exploratory analysis summarized in this United States (U.S.) case study addresses this gap by identifying and integrating spatially explicit data for AFN-related residential populations, earthquake hazards, and county and county equivalents for the conterminous U.S., Alaska, Puerto Rico, and Hawaii. We focus on 13 AFN-related attributes that relate to an individual's ability to access information contained in an EEW alert, to understand and process earthquake information or observed ground shaking, and to take self-protective actions based on this information and physical cues of an earthquake. Depending on the demographic attribute, there are millions to tens of millions of U.S. residents with AFN-related attributes in areas considered to have varying likelihoods (2%, 10%, and 50%) of exceedance of a damaging earthquake in the next 50 years. Although these amounts represent low percentages at the national level, the percentage of individuals with AFN-related attributes in many counties and county equivalents substantially exceeds national percentages. No one county, county equivalent, U.S. state, or U.S. territory has the highest percentage of individuals in all AFN-related attributes; therefore, future efforts to increase individual resilience to earthquakes may benefit from understanding the local context of individuals with potential access and functional needs.

International Journal of Disaster Risk Reduction↗
USGS2026

Geochemical disequilibrium at the brittle-ductile transition

We investigate the microtextural, microchemical, and isotopic effects of late-stage ductile deformation in quartzite mylonites and kyanite–muscovite–quartz veins from the Raft River shear zone (Utah). Quartz microstructures record pervasive disequilibrium, expressed by unannealed features including undulatory extinction, deformation lamellae, and poorly defined fabrics, typical of waning deformation in shear zones. Microchemical disequilibrium is best preserved in kyanite quartzites, where CL-zoned kyanite records repeated fractures, overgrowth, and mineral precipitation, and in muscovite from muscovite-poor quartzite mylonites that shows minor-element zoning consistent with syn-deformational overgrowth on detrital cores. In contrast, muscovite from muscovite-rich kyanite quartzites exhibits minimal chemical zoning. These microchemical variations correlate with 40 Ar/ 39 Ar age systematics. Chemically zoned muscovite preserves variable single-step ages, including ∼150 Ma ages, reflecting retention of detrital cores. In contrast, syndeformational muscovite consistently yields Miocene ages, indicating recrystallization and new growth below argon closure temperatures that reset inherited isotopic signatures. Similar trends are observed in quartzite mylonites, where increasing quartz recrystallization and stronger crystallographic preferred orientations occur toward deeper structural levels. Together, these observations indicate increasing retrograde deformation and recrystallization with depth in the Raft River shear zone and demonstrate that strain-driven recrystallization exerts a first-order control on muscovite ages. We suggest that apparent thermochronologic gradients in retrograde shear zones may reflect recrystallization gradients rather than temperature gradients. Where cooling limits the thermal driving force for recrystallization, isotopic relics are preserved, and local deformation and fluid availability control re-equilibration. Consequently, isotopic disequilibrium—particularly in the 40 Ar/ 39 Ar system—may be the rule rather than the exception of retrograde tectonic environments.

Idaho, Utah↗
USGS2025

“Leaky weirs” capture alluvial deposition and enhance seasonal mountain-front recharge in dryland streams

“Leaky weirs” are rock structures installed in dryland streams, which are anchored into exposed bedrock, loosely cemented, and designed to allow water to slowly pass through. They are being tested at a ranch in southeastern Arizona, USA, to restore and conserve the historic range and desert wetlands. Data are collected to assess how leaky weirs impact surface water, subsurface water, and groundwater recharge—including stream discharge, timing, and depth of infiltration, and groundwater elevations. Three adjacent watersheds, two with outlets just below leaky weirs and one with leaky weirs farther upstream, were instrumented with water-level loggers, wildlife cameras, and crest stage instruments with temperature sensors in the soil. As most groundwater recharge is assumed to be focused along the mountain fronts in this region, mountain-block recharge is also evaluated to differentiate between the two using isotope analyses. Finally, a single, late-season flood event is scrutinized to consider the leaky weir effect on all monitored components in the water budget. Results indicated groundwater flow is primarily from the mountains to the east via older, regional mountain-block recharge. However, the development of shallow alluvial aquifers is supported by the leaky weirs, that slow flows, capture permeable sediments, and allow infiltration, thus enhancing mountain-front recharge. In turn, these new pockets of water help support the restoration of historic wetlands. Sediment accumulates where leaky weirs are installed, reducing flashy peak flows, and resulting in a series of infiltration ponds along the channel that support vegetation during growing seasons and recharge the shallow aquifer during non-growing seasons.

Arizona↗
USGS2025

Using subducting plate motion to constrain Cascadia slab geometry and interface strength

Subduction zones are home to multiple geohazards driven by the evolution of the regional tectonics, including earthquakes, volcanic eruptions and landslides. Past evolution builds the present-day structure of the margin, while the present-day configuration of the system determines the state-of-stress in which individual hazardous events manifest. Regional simulations of subduction zones provide a tool to synthesize the tectonic history of a region and investigate how geologic features lead to variations in the state of stress across the subduction system. However, it is challenging to design regional models that provide a force-balance that is consistent with the large-scale motion of surrounding tectonic plates while also not over-constraining the solution. Here, we present new models for the Cascadia subduction zone that meet these criteria and demonstrate how the motion of the subducting Juan de Fuca plate can be used to determine the along-strike variations in the viscous (long-term) coupling across the plate boundary. All successful models require lower viscous coupling in the northern section of the trench compared to the central and southern sections. However, due to uncertainties in the geometry of the Cascadia slab, we find that there is a trade-off between along-strike variation in viscous coupling and slab shape. Better constraints on the slab shape, and/or use of other observations are needed to resolve this trade-off. The approach presented here provides a framework for further exploring how geologic features in the overriding plate and the properties of the plate boundary region affect the state-of-stress across this and other subduction zones.

Cascadia subduction zone↗
USGS2025

New constraints on location and timing of the Great Lakes tectonic zone, central Upper Peninsula, Michigan, USA

The Great Lakes tectonic zone (GLTZ) forms the boundary between the Wawa–Abitibi and Minnesota River Valley subprovinces within the Archean Superior Province. The GLTZ is concealed for all of its 1100 km length, except for a segment in the central Upper Peninsula of Michigan. There, it is exposed as a northwest-striking mylonite zone along a 11 km segment, extending to the onlap of Paleozoic rocks to the east. Farther east, its location has been unknown. Here, we use aeromagnetic and gravity data to develop interpretations of the expression of the GLTZ and to define its extent under cover. Aeromagnetic gradients over the mylonite zone are interpreted to be produced by structurally juxtaposed rocks with varying magnetizations. Gravity data show a regional gradient along the GLTZ, produced by the juxtaposition of a dense greenstone belt on the north against lower-density gneisses and granites on the south. The GLTZ is interpreted to extend ∼55 km under cover to the east. The GLTZ is terminated on the east by the buried eastern arm of the ca. 1100 Ma Midcontinent Rift. An undeformed granitic dike that cuts the mylonitic foliation produces a U–Pb apatite age of 2523 ± 33 Ma, implying no major post-Archean shearing occurred, and is at odds with previous interpretations of major Proterozoic reactivation. A granite intrusion in the Minnesota River Valley subprovince produces a Pb–Pb zircon age of 2606.9 ± 3.6/7.4 Ma. This suggests that magmatism related to the Sacred Heart orogeny, previously known in Minnesota, extended to Michigan.

Michigan↗
USGS2026

Geophysical architecture and geochronology of the Neoarchean Mentor anorthosite intrusive complex, northwestern Minnesota: Largest anorthosite complex of the Superior Province?

The Neoarchean Mentor anorthosite intrusive complex (MAIC) lies within the Wawa subprovince in northwestern Minnesota, in a region where the Wawa, Quetico, and Wabigoon subprovinces are juxtaposed in close proximity. Archean rocks are entirely concealed, and interpretations are developed from aeromagnetic, gravity, and borehole samples. The MAIC includes both anorthosite (dense, weakly magnetized) and oxide-rich gabbro (strongly magnetized) lithologies. Anorthosite is coarse-grained to megacrystic, intensely altered, and locally brecciated. Pervasive epidote alteration enhanced the density of the anorthosite via introduction of higher-density mineral assemblages, explaining why the MAIC produces a significant gravity high. Oxide-rich gabbro forms a border phase of the MAIC and has potential for vanadium, chromium, and titanium mineralization, and produces a strong aeromagnetic high. The MAIC is interpreted to extend over an area of 640 km 2 , making it the largest known anorthosite complex of the Superior Province, as measured by preserved areal extent. Modeling indicates the MAIC extends more than 6 km into the subsurface. A new Pb–Pb zircon age of 2737.2 ± 4.5 Ma is interpretated as the crystallization age of anorthosite within the MAIC, showing that the MAIC formed well before the ca. 2690 Ma Shebandowanian orogeny, and raising new questions about correlations with other parts of the Wawa subprovince. A low-density batholith, here informally called the Fertile batholith, is interpreted to intrude the southern part of the MAIC. A new Pb–Pb zircon age of 2701.1 ± 6 Ma is interpreted as the magmatic age of the Fertile batholith.

Minnesota↗
USGS2026

Channel morphology and large wood control postfire debris-flow erosion and deposition

Runoff-generated debris flows are a known response to wildfire, and accurately predicting the volume of these debris flows is important for estimating the magnitude of downstream hazards. Prior data collection efforts have focused on debris-flow volume measurements at catchment outlets, but few studies have considered how erosion and deposition modulate the volume of sediment arriving at catchment outlets. This study takes advantage of a high-resolution dataset to document the factors that control the total debris-flow volume reaching the catchment outlet during a fatal postfire debris flow. Using pre- and post-event airborne lidar, satellite imagery and field mapping, we found that a postfire debris flow in the Black Hollow catchment in northern Colorado eroded 136,000 ± 30,000 m 3 and redeposited 27,000 ± 7,500 m 3 in the main channel. Most of the in-channel deposition (52% by volume) occurred where a confined channel reach transitioned to an unconfined channel reach downstream, allowing the flow to widen and deposit material. Wood jams played multiple roles in the debris-flow dynamics, both nucleating deposition (25% of the deposit volume was stored behind wood jams) and exacerbating erosion (50% of the total erosion occurred downstream from a wood dam break). The remaining deposition occurred due to spatial changes in channel slope as well as deposition observed at newly formed channel bars. Using these data in this study, we identified topographic and vegetation metrics that can be used (pre-event) to anticipate where deposition may occur in channels prior to a debris flow.

Colorado↗
USGS2024

Enhanced microplastic fragmentation along human built structures in an urban waterway

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

New Jersey↗
USGS2026

Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland

The Outer California Borderland (OCB) is an active transform plate boundary offshore Southern California, where the relationship between faulting and submarine mass transport deposits (MTDs) remains poorly understood. Onshore paleoseismic data provide high-resolution earthquake records, whereas marine geophysical data capture longer-term histories. Offshore fault systems pose hazards to infrastructure and dense coastal populations, particularly when linked to submarine landslides. We present new high-resolution geophysical data set (cruise SR2303), including bathymetric and CHIRP sub-bottom data integrated with legacy seismic reflection data and chronostratigraphic constraints from ODP Site 1012 to examine Quaternary MTD recurrence and tectonic controls in the Cortes Basin, OCB. Bathymetry shows deformational features, including slide scarps and previously unmapped fault segments with evidence of Holocene activity. CHIRP profiles reveal 10 stacked MTDs in the East Cortes Basin and 8 in the West Cortes Basin, spanning ∼752 ka with an average recurrence of ∼83.6 ± 1 ka. Acoustic imaging shows 7 MTD intervals coinciding with fault offset increments and fault growth suggesting earthquake-triggered mass wasting. A strong association between MTD occurrences and sea-level extremes also supports glacio-eustatic contribution to slope failure. Stratigraphic correlations suggest quasi-synchronous MTDs across the eastern and western areas, likely triggered by larger eathquakes in the Quaternary. Although the identified MTDs occur relatively far from the Southern California coast, they still pose a potential tsunamigenic hazard requiring further assessment. Moreover, if linked to earthquakes along major strike-slip faults, for example, the Ferrelo fault, the MTDs may provide valuable proxies to constrain rupture scenarios and fault connectivity within the understudied OCB.

California↗
USGS2026

Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database

The global demand for critical mineral commodities is rapidly increasing, making domestic production an important factor in supporting the economy and national security. Large scale, publicly available geochemical databases allow for the application of data informatics methods to interrogate critical mineral commodities data for correlations in deposit formation and distribution, particularly for identifying enrichment of multiple critical mineral commodities at the same deposit. In this study, we applied network analysis to the Critical Minerals Mapping Initiative (CMMI) ore geochemistry (Critical Minerals in Ores, CMiO) database to identify the high concentration (defined as 10× bulk crustal abundance) co-occurrence of different critical mineral commodities across a mineral system hierarchy from deposit environments to individual deposits. Identifying patterns or unique outliers in enrichment in network communities will allow for the location of secondary critical mineral commodity resources from under-utilized deposits. We find trends in the enrichment of critical mineral commodities in network-communities between the elements praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) across multiple CMiO database deposit environments and groups down to specific deposit types and sites. A separate trend in network community deposition is observed as well between iridium (Ir) and platinum (Pt) in deposit environments, groups, types, and sites. Network analysis focused on critical minerals in magmatic-hydrothermal deposits identified multiple deposit sites from different deposit types within the CMiO database with concentrations of Dy, Nd, Tb, Pr, Ir, and Pt that are at least ten times greater than the crustal average. This approach can be applied to any target element(s) or deposit(s) of interest, allowing broad investigation of co-enriched critical mineral commodities.

Journal of Geochemical Exploration↗
USGS2025

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

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

California↗
USGS2025

Searching for seismic precursors - The Barry Landslide hazard clean up

The Barry Landslide, located in Barry Arm of Prince William Sound, Alaska, poses a major hazard due to its steep, unstable slopes and the potential for a massive landslide-generated tsunami. With an estimated volume of 500–700 million cubic meters, the Barry Landslide could trigger highly destructive waves. In this study, we focus on seismic signals from the Barry Landslide, which are critical for providing timely tsunami warnings. Since the summer of 2020, the region has been instrumented to monitor the landslide, but the seismic record is complicated by the presence of nearby glaciers and frequent regional earthquakes. Among these signals, we analyze a specific class of short-duration, high-frequency seismic events that exhibit strong seasonal variability, increasing in rate from late summer to mid-winter before ceasing abruptly in late winter or early spring. Our analysis suggests that the source of these signals is likely near or beneath Cascade Glacier, adjacent to the landslide, rather than within the landslide mass itself. We apply detection algorithms to construct a time history for this signal type, which we then compare with environmental factors like precipitation, temperature, and slope displacement data from ground-based radar and remote sensing. Correlations indicate that these seismic events may be driven by seasonal hydrological changes, particularly the freeze-up of subglacial water pathways. While these events are not directly linked to landslide motion, they serve as indirect markers of subsurface hydrological conditions that influence slope stability. Our findings highlight the complex interplay between glaciers, groundwater, and landslide dynamics, emphasizing the need for multi-parameter monitoring to assess evolving geohazards in the region.

Alaska↗
USGS2024

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

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

Indiana↗