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1,673 records · Page 79Linked to original sources
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↗
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↗
USGS2024

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research↗
USGS2026

Controls on natural hydrogen generation during serpentinization of mantle rocks

Mantle rocks undergoing serpentinization can generate significant amounts of natural hydrogen, yet the rates and controlling processes remain poorly understood. Here, we constrain the possible hydrogen generation rates in two distinct mantle rock types, the fertile lherzolites of the Western Pyrenees and the depleted harzburgites of Northern California, to relatively low rates of ~0.1 to ~0.5 tonnes H₂ yr⁻¹ km⁻³ of reactive rock. When integrated over the full reactive volumes, this corresponds to total production rates of ~300 to ~600 tonnes H₂ yr⁻¹. By combining three-dimensional geophysical inversion with numerical modelling of fluid-rock processes, we show that hydrogen generation rates are mainly limited by H₂ saturation in the fluid and reaction kinetics. Under these constraints, hydrogen generation in mantle-derived serpentinization systems proceeds slowly, making rapid large-scale replenishment unlikely and suggesting that large, economically relevant accumulations, would require timescales of thousands to tens of thousands of years to develop.

northern California, western Pyrenees↗
USGS1976

Uranium analysis of single drops of natural waters using the fission-track technique

The fission-track technique has been applied to uranium analysis of natural waters using a single drop of water. Samples may be collected in the field by evaporating a drop of water on a detector, and samples may then be analyzed by returning the detector to the laboratory. A sample collecting kit has been assembled, which facilitates the designed sampling method. Some unique advantages of this technique are picogram sensitivity (10 -12 g) for uranium on single drops of water, maintenance of sample integrity during transport and storage, and the ability to discern whether the uranium is in solution or in the suspended material. Counting the tracks is the most time-consuming part of the analysis, but it can be reduced by using automatic counting systems. The analytical error is generally ± 10 percent over the entire range of concentrations.

Open-File Report↗
USGS2024

How does the onset of offset influence geologic slip rates?

Geologic slip rates are typically based on the displacement accrued by a geomorphic or stratigraphic feature and the age of the offset feature. Because slip rates are commonly calculated by dividing the displacement of a faulted marker by its age, they contain two open time intervals: the elapsed time between the age of an offset feature and the age of the earthquake that displaced the feature, and the time between the present‐day and the most recent earthquake. Here, we explore the influence of including unconstrained open intervals in geologic slip rate calculations. We test the degree to which these open intervals affect geologic slip rates and their uncertainties, and we find that their influence depends primarily on mean earthquake recurrence intervals (RIs). Slip rates on faults with longer RIs, such as the Wasatch fault, can be greatly influenced by an increase of up to 20% when accounting for open intervals. In contrast, slip rates on faults with shorter RIs, such as the San Andreas fault, are only slightly influenced by the assumption that slip rates calculated over open intervals approximate those calculated over closed intervals. Our analyses indicate that faults with moderate slip rates (∼0.2–5 mm/yr) are sensitive to both open interval effects themselves, as well as methods to quantify and account for these effects. We re‐evaluate how slip rates are calculated and defined in displacement–time space using published deformation records. We explore the utility of assigning a probability distribution to the initiation of offset of the oldest faulted feature and the timing of the most recent earthquake (MRE). We find that calculating geologic slip rates without using probability distributions that capture the timing of the MRE and the onset of offset of the oldest faulted feature, especially on slow‐to‐moderate slip rate faults, can lead to systematic underestimation of average geologic slip rates.

Seismological Research Letters↗
USGS2025

Rainfall thresholds for postfire debris-flow initiation vary with short-duration rainfall climatology

The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris-flow initiation are commonly expressed as rainfall intensity-duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass-movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff-generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris-flow initiation thresholds vary systematically with short-duration rainfall-intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much-needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field-based hazard assessment. Furthermore, if the observed variation in thresholds reflects long-term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris-flow likelihood.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2026

Albuquerque Seismological Laboratory strategic vision

This circular presents a strategic outlook for the U.S. Geological Survey (USGS) Albuquerque Seismological Laboratory (ASL) for the next 10 years (2026–36). The ASL is a USGS field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. The strategic outlook is categorized into two types of tasks: “Foundational Tasks” and “Aspirational Tasks.” Foundational Tasks are those that maintain the laboratory’s basic operations and services, including regional and global seismic monitoring, improving data quality, and providing instrument testing and support. A suite of Aspirational Tasks is also articulated; these can be considered priority targets of ASL that could improve ASL’s seismic monitoring capabilities and mission. Such tasks include improvements to remote stations, testing capabilities of nonseismic geophysical instruments, detection threshold monitoring, rapid aftershock deployments, and expanding seismic monitoring networks. This report was written with input from the USGS Geological Hazards Science Center, the USGS Earthquake Hazards Program (EHP), and colleagues with an interest in the work done by the ASL. Although the details of these tasks may change, this document can provide guidance on the overarching tasks at the ASL from 2026 to 2036 and an overview of the various components of the ASL and how they fit into the EHP and the Global Seismographic Network Program.

Circular↗
USGS2025

Fault displacement model for surface principal rupture of strike-slip faults

The probability distribution model for principal displacement accommodated on the surface main trace is a critical input to the fault displacement hazard analysis. This article presents a new model for strike-slip ruptures in the moment magnitude ( M ) range of 6 to 8.3. The new model is the outcome of a multi-year research effort to update the widely used model developed by Petersen and others in 2011. Updates include the adoption of the Fault Displacement Hazard Initiative database and enhancements to rupture and displacement data preparation. Statistical formulation and estimation have also been updated substantially. A three-parameter modified normal distribution that we refer to as the negative Exponentially Modified Gaussian distribution is adopted to model the probability distribution of the natural logarithm of principal displacement. Formulation for the mean parameter of the modified normal includes a random earthquake term, a nonlinear scaling relation with M , and an ellipse function for along-main-trace variation. The aleatory variability of the updated model now depends on M as well as site’s along-main-trace position. These updates not only significantly improve the fit to the distribution of the observed displacements but also yield reasonable 95th percentile predictions for M > 7.5 events. Alternative models representing the estimation uncertainty of the M -scaling relation are also developed. These new models are compared to the previous model in terms of percentile predictions and the calculated hazard curves. The steeper hazard curves from the new models yield a lower exceedance rate than the normal-distribution based model developed previously by Petersen and others.

Earthquake Spectra↗
USGS2026

Methodology for construction of a three-layer geologic model of the conterminous United States using land surface, top of bedrock, and top of basement

This report describes the methodology used for the construction of a digital three-layer geologic model of the conterminous United States by mapping the altitude of three surfaces: land surface, the top of bedrock, and the top of basement. These surfaces are mapped through the compilation and synthesis of published stratigraphic horizons from numerous topical studies. The mapped surfaces create a three-layer geologic model with three geomaterial-based subdivisions: unconsolidated to weakly consolidated sediment; layered consolidated rock strata that constitute bedrock; and crystalline rocks that are described as “basement,” consisting of either igneous, metamorphic, or highly deformed rocks. The data compilation and synthesis are highly dependent on the definition of the informal terms “bedrock” and “basement,” which may describe different ages or types of rock in different parts of the conterminous United States. This report presents the conceptualization of the three mapped layers, describes the datasets used, and summarizes the decisions made while compiling the three-layer model from the various sources. This digital dataset was created as part of efforts by the U.S. Geological Survey to develop subsurface geologic data in geospatial form as part of a broad directive to develop two-dimensional and three-dimensional geologic information at detailed, national, and continental scales. This digital dataset partly fulfills the goal of the U.S. Geological Survey’s National Cooperative Geologic Mapping Program to construct a national-scale three-dimensional geologic model.

conterminous United States↗
USGS2025

Constraining large magnitude event source and path effects using ground motion simulations

The purpose of this study is to use ground motion simulations to investigate ways in which source and path effects for large magnitude events can be represented in non-ergodic GMMs. While we initially developed computation techniques using CyberShake simulations, the range of magnitudes and source-site combinations is not adequate to replicate what is observed empirically. We therefore designed a new ground motion simulation study, which includes earthquakes with a large range of magnitudes distributed uniformly on a fault plane, and sites covering a large range of rupture distances and azimuths. After running a large suite of simulations (M4-M7), we then develop a non-ergodic GMM with the simulation data. We find that the within-site residuals are dominated by the radiation pattern, rupture directivity, and slip patterns. Next, we modify an existing rupture directivity model to fit and remove the observed radiation pattern and rupture directivity from the residuals. We also minimize the contributions of slip patterns by averaging the within-site residuals among multiple source realizations. Finally, after removing the source effects from the within-site residuals, we compare the path effects computed with different magnitude groups using two approaches. The first approach only considers the small events that have the same shortest path to a site with the large events, while the second approach considers all small events on the fault plane. The results indicate that the path effects of large events cannot be satisfactorily approximated with that of small events using either approach.

Conference Paper↗