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1,673 records · Page 79Linked to original sources
USGS2026

GST-1: A high-resolution global sediment thickness model

Global Sediment Thickness 1 (GST-1) is a high-resolution sedimentary thickness model calculated on a 0.125° x 0.125° grid. It modifies the sediment thickness of the 1° x 1° Earth Crustal Model 1 (ECM1) by means of 3D inversions of free air gravity anomalies. GST-1 is calculated by performing structural inversions on high-density contrasts across two crustal boundaries: the sediment – basement interface and the crystalline crust – upper mantle interface. The inversions are calculated in each of ten overlapping 3D models that span the globe. These ten models are merged to obtain the GST-1 global model, providing an eight-fold increase in lateral spatial resolution in comparison with ECM1 and CRUST 1.0. Our sediment thickness model exploits the nearly continuous sampling of gravity data when compared to the irregular, sparse sampling of seismic refraction data. Sediment thickness values in GST-1 are in excellent agreement with independently derived cross sections from well-studied sedimentary basins, and within expected resolution limits of seismic refraction data. GST-1 offers a robust, high resolution global model of sedimentary thickness to support studies of sedimentary basins.

Tectonophysics↗
USGS2026

Ground motions from finite faults with unknown geometry

Earthquake emergency response and loss modeling require accurate models of ground‐motion intensity metrics (IMs), such as those produced by ShakeMap. In the critical minutes and hours after an earthquake, however, knowledge of the earthquake source geometry limits the accuracy of these models, especially in areas where seismic instrumentation is insufficient to constrain the shaking intensity pattern. Previous attempts to overcome this limitation have centered on computing the mean distance metrics from a suite of assumed source geometries. That approach is inadequate with modern ground‐motion models (GMMs) because they typically include terms for the hanging wall effect, depth to top of rupture, and other nonlinear terms. Such approaches also propagate the distance uncertainty through the GMMs and may not properly allocate the additional uncertainty into the between‐ and within‐event components. Here we present Finite‐Fault SIMulation with Mixed Effects Regression (FFSIMMER), a method to address these limitations by computing IM distributions from a suite of rupture realizations that fully accounts for all geometry‐related GMM terms and allows for the separation of the between‐ and within‐event components of the total uncertainty. The accuracy of this method is limited by the available constraints on the source parameters. To address this, FFSIMMER can incorporate constraints based on knowledge of the source, such as the approximate strike and dip based on knowledge of the plate tectonics and focal mechanism of the earthquake. We demonstrate the improvement in accuracy that can be achieved with the 2025 M 7.7 Mandalay, Burma (Myanmar), earthquake by incorporating constraints on the range of plausible source parameters.

Bulletin of the Seismological Society of America↗
USGS2023

Paleomagnetism of the Harrat Rahat volcanic field, Kingdom of Saudi Arabia—Geologic unit correlations and geomagnetic cryptochron identifications

Paleomagnetic rock samples were collected from 173 drill sites in the Quaternary alkali basaltic volcanic field of northern Harrat Rahat, Kingdom of Saudi Arabia. Laboratory measurements on these samples established that lava flows and vent complexes—identified and mapped from field characteristics, rock types, and compositions as products of single or temporally close eruptions—typically record single, or very similar, directions of remanent magnetization. Correlations defined through geologic mapping, spatial association, geochemistry, geochronology, and identical mean remanent directions indicate at least 16 brief episodes of temporally clustered eruptions. These episodes had durations of a few centuries or less. Anomalous remanent magnetic directions were found for at least 13 mapped lavas of northern Harrat Rahat, which demonstrate that they were acquired during brief geomagnetic cryptochrons during the Brunhes Normal Polarity Chron. These uncharacteristic directions enhance the opportunity to identify common eruptive episodes, and to better understand and evaluate assessments of eruption ages based on 40 Ar/ 39 Ar geochronology. Combining paleomagnetic and regional archaeomagnetic results for the youngest eruptions allows us to evaluate their historical age assignments and, in one case, refute a previously assigned provisional age.

Harrat Rahat volcanic field↗
USGS2023

Surficial geologic map of the Owlshead Mountains 30' x 60' quadrangle, Inyo and San Bernardino Counties, California

The surficial geologic map of the Owlshead Mountains 30' x 60' quadrangle depicts the distribution and characteristics of surficial-deposit materials and neotectonic deformation for an area of approximately 5,000 square kilometers (km 2 ) located in the western Basin and Range Province of eastern California. The map represents a new compilation of the surficial geology that encompasses deposits within the late Pliocene to Quaternary. The map is based primarily on new mapping conducted between 2001 and 2009. Map compilation was supported by field observations distributed across the map area, combined with reference to several published and unpublished mapping sources that mostly emphasized neotectonic deformation. The surficial-deposit units included in the map follow a classification scheme that systematically denotes depositional process, relative age, and any secondary sedimentologic or morphologic characteristics. Identification, correlation, and age estimation of map units are based primarily on the relative degree of development of certain time-dependent characteristics such as surface morphology, including local dissection and surface preservation, surface clast modification, and degree of soil development; these characteristics are implicitly incorporated into unit designations. The map represents a detailed and regionally uniform synthesis of the late Neogene geology for this large area that provides a framework applicable to many interpretative studies, such as regional patterns of deposition and dissection; surface drainage development and evolution; and the distribution, style, and timing of neotectonic deformation.

California↗
USGS2023

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions↗
USGS2026

Tectonically driven integration of the 4.8 Ma Colorado River USA tracked with detrital sanidine and fish genetics

The development of the continental-scale Colorado River system, western USA, from 8 to 4.8 Ma, is revealed using 60-40 Ma detrital sanidine tracer grains and fish phylogeny. Here we show that precursor paleoriver segments became integrated north to south as traced by 60-40 Ma sand grains that were derived from the north and sequentially appeared in the 25-8 Ma Browns Park Formation of Utah, 7-6 Ma upper Bidahochi Formation of Arizona, and 4.8 Ma Bouse Formation of the lower Colorado River and proto Gulf of California. This timing is mimicked by molecular clock estimates of divergence times among fish lineages. River integration was a response to headwater uplifts in the Yellowstone hotspot track and Rocky Mountains. 40 Ar/ 39 Ar ages refine the timing for mantle-drips that caused subsidence, then uplift, of depositional basins that influenced the integration pathway and tempo. The ~ 3-million-year timescale suggests that multiscale mantle-driven uplift, rather than lake spillover, was the primary driver for integration of the proto-Colorado River through Grand Canyon.

Colorado River↗
USGS2025

Modeling interconnected minerals markets with multicommodity supply curves: Examining the copper-cobalt-nickel system

Demand for many of the metals used in the energy transition is expected to grow rapidly. Many of these are by-products, often considered critical because their production responds weakly to prices and is instead tied to the economics of the host mineral. We present a model of prices and production for jointly produced commodities that accounts for interconnectivity between host and by-product markets at the mine level. We demonstrate this method using the copper–cobalt–nickel system, in which approximately 99% of cobalt is a by-product of copper or nickel mining. Our results show that the model more accurately captures the economic benefits of diversified mine outputs than previous approaches. Furthermore, changes in demand drivers for any two commodities produce non-linear effects on production and price. We challenge the prior best-practice assumption that cobalt cannot impact the copper or nickel markets. Recognizing the importance of both copper and cobalt for future electrification, we emphasize that incentivizing the copper industry to reduce cobalt supply risks could inadvertently undermine copper supply.

Nature Communications↗
USGS2025

Mine waste as a potential source of critical minerals and other commodities: Examples from the Four Corners states, USA

The growing demand for critical minerals and other mineral resources has raised concerns about possible supplies of these essential commodities. Mine waste is a potential source of these essential commodities. We compiled a geospatial database of publicly available data of the largest non-fuel mine waste features (>200,000 m 2 in areal extent) in the Four Corners states of the United States, where most of those features are from porphyry Cu deposits. The combined volume of those large porphyry Cu mine waste features is approximately 17 cubic kilometers, 60% of which is ore-related material such as tailings. Using publicly available data on density, grade, and previous recovery values, we estimate the contained endowments of Ag, As, Au, Bi, Cu, Mo, Re, S, Sb, Se, Te, and W. These estimates indicate endowments within ore-related mine wastes are collectively comparable to endowments of giant to supergiant deposits. If fully recovered, these commodities could meet current global demand from less than 1 year (Sb) to more than 200 years (Re), underscoring the enormous untapped resource potential of mine waste.

Arizona, Colorado, New Mexico, Utah↗
USGS2023

Overview of the Cenozoic geology of the northern Harrat Rahat volcanic field, Kingdom of Saudi Arabia

The Harrat Rahat volcanic field, located in the west-central part of the Kingdom of Saudi Arabia, is one of the larger Cenozoic harrats among the more than 17 harrats situated upon the Arabia Plate. The map plate contained herein shows, at a scale of 1:100,000, the mapped volcanic geology of northern Harrat Rahat, which consists of the northernmost one-fifth of Harrat Rahat. Northern Harrat Rahat has an area of about 3,340 square kilometers (km 2 ), of which 2,567 km 2 is covered by Harrat Rahat volcanic rocks and deposits, and it encompasses more than 900 exposed vents (that is, craters, cryptodomes, maars, and scoria cones), 289 of which are isolated by younger volcanic deposits and have not been correlated with the 234 volcanic rock units distinguished by geologic mapping. Northern Harrat Rahat is of special interest owing to its proximity to the city of Al Madinah al Munawwarah, which sits within, and is continuing to expand southward over, the north end of the volcanic field. Al Madinah is home to an expanding population, currently at more than 2 million residents, together with the intermittent addition of approximately 3 million pilgrims during Hajj and Umrah (religious visitations). The center of Al Madinah is less than 8 km from lava flows of the only confirmed historically documented eruption, which occurred in 1256 C.E. (654 A.H.). Earlier prehistoric lava flows also encroached into the area of the present-day city limits, as demonstrated by volcanic rocks exposed widely throughout the city in roadcuts, parks, and excavations for new buildings, although no evidence has been found of any other than the 1256 C.E. lava having reached that area during times of human habitation. Geologic mapping was undertaken by the U.S. Geological Survey in collaboration with the Saudi Geological Survey. The features of primary interest within the map area are scoria cones, lava flows, lava domes, craters, and pyroclastic deposits from the Quaternary, which have compositions of basalt, hawaiite, mugearite, benmoreite, and trachyte. The geologic mapping was published by Downs and others (2019) on a single sheet at 1:75,000 scale and two detailed sheets at 1:25,000 scale, accompanied by detailed explanations of the geology. This report presents the geology on a single sheet at 1:100,000 scale and provides condensed geologic explanations for the convenience of readers of this volume. Some minor errors of nomenclature and lava source regions that do not change fundamental interpretations have been corrected herein.

Professional Paper↗
USGS2024

Preliminary observations of the April 5th, 2024, Mw4.8 New Jersey earthquake

On 5 April 2024, 10:23 a.m. local time, a moment magnitude 4.8 earthquake struck Tewksbury Township, New Jersey, about 65 km west of New York City. Millions of people from Virginia to Maine and beyond felt the ground shaking, resulting in the largest number (>180,000) of U.S. Geological Survey (USGS) “Did You Feel It?” reports of any earthquake. A team deployed by the Geotechnical Extreme Events Reconnaissance Association and the National Institute of Standards and Technology documented structural and nonstructural damage, including substantial damage to a historic masonry building in Lebanon, New Jersey. The USGS National Earthquake Information Center reported a focal depth of about 5 km, consistent with a lack of signal in Interferometric Synthetic Aperture Radar data. The focal mechanism solution is strike slip with a substantial thrust component. Neither mechanism’s nodal plane is parallel to the primary northeast trend of geologic discontinuities and mapped faults in the region, including the Ramapo fault. However, many of the relocated aftershocks, for which locations were augmented by temporary seismic deployments, form a cluster that parallels the general northeast trend of the faults. The aftershocks lie near the Tewksbury fault, north of the Ramapo fault.

New Jersey↗
USGS2025

The U.S. Geological Survey National Water Quality Network—Groundwater, 2024

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, 8 of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,089 wells in the network. All wells are sampled for physical properties, nutrients, major ions, trace elements, per- and polyfluoroalkyl substances (PFAS), and a subset of wells are sampled for pesticides, volatile organic compounds, radionuclides, and microbiological contaminants.

Contiguous United States↗
USGS2024

Parsimonious high-resolution landslide susceptibility modeling at continental scales

Landslide susceptibility maps are fundamental tools for risk reduction, but the coarse resolution of current continental-scale models is insufficient for local application. Complex relations between topographic and environmental attributes characterizing landslide susceptibility at local scales are not transferrable across areas without landslide data. Existing maps with multiple susceptibility classifications under-represent landslide potential in moderate and gently sloping terrain. We leverage an extensive landslide database ( N = 613,724), a high-resolution digital elevation model (10-m), and high-performance computing resources, to develop a new nationwide susceptibility map for the contiguous United States, Hawaii, Alaska, and Puerto Rico. We calculate four alternative linear and nonlinear thresholds of topographic slope and relief using an objective split-sample calibration. We down-sample our results to a 90-m grid to account for uncertainty in the digital elevation model and landslide position, and evaluate these thresholds' ability to differentiate areas of greater susceptibility. The less conservative nonlinear model optimally balances our priorities of capturing observed landslides (99%) while minimizing area covered by susceptible terrain (43%). Independent evaluation with four statewide landslide inventories ( N = 172,367) reinforces our model selection but highlights spatially variable performance. Therefore, we propose a novel approach to susceptibility classification using the concentration of landslide-prone terrain within each down-sampled grid. While landslides are possible within any cells containing susceptible terrain, those with the highest concentration capture the majority of observed landslides. Our new map characterizes landside susceptibility more consistently than prior models; our transparent classification approach also provides flexibility for accommodating different tolerances in risk reduction measures.

AGU Advances↗
USGS2024

New 10Be-26Al isochron burial dating informs the Pliocene and Pleistocene evolution of the lower Colorado River, southwestern United States

Four new 10 Be- 26 Al isochron burial ages ranging from 4.4 to 2 Ma on ancestral Colorado River deposits in the lower Colorado River corridor (LCRC) help constrain the river’s evolution during the Pliocene and early Pleistocene. They help fill a gap between previous work that focused on older and younger deposits: Older dated deposits include the 5 Ma Bouse Formation, which records the integration of the Colorado River through a series of preexisting basins to the Gulf of California and the ca. 4.5 - 3.5 Ma Bullhead Alluvium, a 200 to 300 m thick aggregational package that immediately followed integration. The much younger, 100 - 70 ka, Chemehuevi Formation is another major aggradation package mapped throughout the LCRC. The new burial ages on the facies of Santa Fe Railway (4.37 ± 0.71 Ma), boulder conglomerate of Bat Cave Wash (2.12 ± 0.26 and 2.05 ± 0.31 Ma), and the Palo Verde alluvium (3.03 ± 0.26 Ma) partially fill in a 3.5 M.y. gap between the deposition of the Bullhead Alluvium and the Chemeheuvi Formation and document the timescales over which the Colorado River was able to remove the Bullhead aggradational package and initiate newer and smaller aggradational pulses.

Arizona, California, Nevada↗
USGS2025

Borehole geophysical time-series logging to monitor passive ISCO treatment of residual chlorinated-ethenes in a confining bed, NAS Pensacola, Florida

In-situ chemical oxidation (ISCO) is a common method to remediate chlorinated ethene contaminants in groundwater. Monitoring the effectiveness of ISCO can be hindered because of insufficient observations to assess oxidant delivery. Advantageously, potassium permanganate, one type of oxidant, provides the opportunity to use its strong electrical signal as a surrogate to track oxidant delivery using time-series borehole geophysical methods, like electromagnetic (EM) induction logging. Here we report a passive ISCO (P-ISCO) experiment, using potassium permanganate cylinders emplaced in boreholes, at a chlorinated ethene contamination site, Naval Air Station Pensacola, Florida. The contaminants are found primarily at the base of a shallow sandy aquifer in contact with an underlying silty-clay confining bed. We used results of the time-series borehole logging collected between 2017 and 2022 in 4 monitoring wells to track oxidant delivery. The EM-induction logs from the monitoring wells showed an increase in EM response primarily along the contact, likely from pooling of the oxidant, during P-ISCO treatment in 2021. Interestingly, concurrent natural gamma-ray (NGR) logging showed a decrease in NGR response at 3 of the 4 wells possibly from the formation of manganese precipitates coating sediments. The coupling of time-series logging and well-chemistry data allowed for an improved assessment of passive ISCO treatment effectiveness.

Florida↗
USGS2024

A robust quantitative method to distinguish runoff-generated debris flows from floods

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post-event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric ( Q* ) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross-section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow-type observations.

Geophysical Research Letters↗
USGS2025

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

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

Scientific Data↗
USGS2025

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

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

California↗
USGS2025

Drone-based radiometric surveys provide high-resolution mine waste characterization

Airborne radiometric surveys use passive geophysical techniques to characterize geochemical variations at or near earth’s surface. These methods have been used for a variety of mapping applications, including mineral resource evaluation. However, detailed characterization of smaller geologic targets, including mine waste features, requires flying at lower altitudes and with tighter line spacing than is feasible with traditional aircraft. Here, a small uncrewed aircraft system (sUAS) equipped with a radiometric sensor was used to acquire high-resolution gamma-spectrometry over small mine waste features and a low-grade stockpile in southwestern New Mexico. The sUAS radiometric system mapped local variability within each survey area and revealed ~2–10 m wide zones where radioelements K, Th, and U may be elevated 2–10× the surrounding material. Additionally, the sUAS radiometric data revealed radioelement variability across survey sites, which correlated reasonably well with variability seen in geochemical samples at each survey site, even though samples collected from individual sites showed high local variability. The sUAS data characterized local heterogeneity within mine waste and other small geologic targets at scales of a few meters to tens of meters, which is not possible with traditional crewed aircraft, and with continuity of coverage that is not possible with ground surveys, thus filling a key gap in geophysical survey spatial resolution.

New Mexico↗