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901 records · Page 19Linked to original sources
USGS2026

3D semantic mapping of surface geological features

Semantic mapping in 3D is fundamental to a wide range of geoscientific studies and applications, including geomorphology, hazard assessment, and environmental monitoring. However, automatically segmenting geological features from large-scale photogrammetric datasets remains a significant challenge. We present a methodology to address this gap. Using overlapping images collected over environments of interest, Structure-from-Motion (SfM) produces georeferenced point clouds and estimates camera poses. Existing large vision models, such as Segment Anything Model, segment objects in the images, generating pixel-segmentation associations. To produce pixel-point associations, we project the points back onto the camera image planes. As objects are independently segmented across multiple images with different perspectives, we develop a segmentation mosaicking algorithm to build probabilistic point-segmentation associations that combines the pixel-segmentation associations and pixel-point associations. Our methodology is validated using both synthetic data generated by Kubric and real-world UAV-SfM data. The implementation is designed to be compatible with existing SfM software, including Agisoft and OpenDroneMap, for photogrammetry mapping in geoscience studies. As a case study, we apply our method to the semantic mapping of precariously balanced rocks (PBRs), which provide upper-bound constraints on historical ground motion shaking intensity. To support object-level identification of PBRs, we additionally integrated Grounding DINO, enabling text-prompted segmentation of features of interest within UAV imagery. This case study demonstrates the effectiveness of our method in generating a 3D semantic map of PBRs, enabling spatial distribution of PBR fragility for earthquake hazard analysis.

Computers & Geosciences↗
USGS2024

Cross-fade sampling: Extremely efficient Bayesian inversion for a variety of geophysical problems

This paper introduces cross-fade sampling, a computationally efficient Markov Chain Monte Carlo simulation method that uses a semi-analytical approach to quickly solve Bayesian inverse problems that do not themselves have an analytical solution. Cross-fading is efficient in two ways. First, it requires fewer samples to obtain the same quality simulation of the target probability density function (PDF). Secondly, it is much faster to evaluate the posterior probability of each sample than conventional sampling methods for simulating Bayesian posterior PDFs. Conventional methods require evaluating the prior probability (which describes your a priori constraints) and data likelihood (which describes the fit between the observations and the predictions of the model) for each sample model. However, cross-fading does not require evaluating the data likelihood, meaning that ‘big data’ can be fit with zero additional computational cost. Further, the cross-fading approach can be used to calculate the marginal likelihood associated with a model design, facilitating model comparison and Bayesian model averaging. Topics covered in this paper include derivation of the cross-fade approach and how it can be used to simulate Bayesian posterior PDFs and compute the marginal likelihood, discussion of the class of problems to which cross-fading can be applied (with examples from earthquake statistics, earthquake ground motion modelling, volcanic eruption forecasting, and finite fault slip modelling), demonstration of efficiency relative to existing sampling methods and discussion of how cross-fading can be used to account for prediction errors (i.e. epistemic errors) as part of the geophysical inverse problem.

Geophysical Journal International↗
USGS2025

Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa

From July to October 2022, a non-eruptive volcanic earthquake swarm occurred within ~15 km of Taʻū Island, located in eastern American Samoa. Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

American Somoa↗
USGS2025

Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020

Frequency analysis on annual peak streamflow (hereinafter, peak flow) is essential to water-resources management applications, including critical structure design (for example, bridges and culverts) and floodplain mapping. Nonstationarity is a statistical property of a peak-flow series such that the distributional properties (the mean, variance, or skew) change either gradually (monotonic trend) or abruptly (shift, step change or change point) through time. Not incorporating or accounting for observed nonstationarity into peak-flow frequency analysis might result in a poor representation of the true probability of large floods and thus misrepresent the actual flood risks to life and property. This report summarizes how hydroclimatic variability might affect the temporal and spatial distributions of peak-flow data in the State of Montana (and northern Wyoming) and is part of a larger study to document peak-flow nonstationarity and hydroclimatic changes across a nine-State region consisting of Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flows. This study was completed in cooperation with the Montana Department of Natural Resources and Conservation. The purpose of this report is to characterize temporal and spatial patterns of nonstationarity in peak flows and hydroclimatology in Montana and northern Wyoming. In this evaluation, peak-flow, daily streamflow, and model-simulated gridded climatic data were examined for monotonic trends, change points, and other statistical properties that might indicate changing climatic and environmental conditions. This report includes background information on the study area, the history of U.S. Geological Survey peak-flow data collection and frequency analysis in Montana, and the review of research relating to hydroclimatic variability and change in Montana. This study might help provide a framework for addressing potential nonstationarity issues in peak-flow frequency updates that commonly are completed by the U.S. Geological Survey in cooperation with other agencies throughout the Nation. The analytical structure of this study includes analyses of monotonic trends and change points in numerous hydroclimatic variables in assigned 30-, 50-, 75-, and 100-year analysis periods. For Montana and part of Wyoming, the 30-, 50-, 75, and 100-year analyses included 157, 70, 48, and 12 streamgages, respectively. For those streamgages, nonstationarities were analyzed in the following variables: (1) climatic variables, including annual and seasonal (winter, spring, summer, and fall) temperature and precipitation; (2) daily streamflow variables, including the annual center of volume duration, annual center of volume median, and peaks over threshold with a mean of four events per year; and (3) annual peak-flow variables, including peak-flow timing and magnitude. A likelihood approach was used to express statistical confidence and assign the nonstationarity results as likely upward or downward (highest statistical confidence), somewhat likely upward or downward (less statistical confidence), or about as likely as not (little statistical confidence; hereinafter, neutral). For the nonstationarity analyses of the climatic, daily streamflow, and peak-flow variables, the results are presented in detail and discussed with respect to statewide patterns and geographic variability. For each of the 30-, 50-, and 75-year analyses, peak-flow change-point and monotonic trend analyses were compiled for streamgages classified with likely downward or likely upward trends. For those streamgages, the associated basin characteristics and nonstationarity results for peak-flow timing, daily streamflow, and climatic variables were investigated and statistically compared to discern associations among other variables that might contribute to the peak-flow nonstationarity results. The 50- and 75-year peak-flow nonstationarities identified in this study are mostly downward, in association with mostly upward temperature and potential evapotranspiration:precipitation monotonic trends. For the 50-, 75-, and 100-year analyses, the peak-flow change points are predominantly downward and are concentrated in the 1970s and 1980s, which indicates general consistency among the longer trend periods. These findings are in association with substantial research documenting globally rising temperature and atmospheric greenhouse gas concentrations that might be largely attributed to anthropogenic activities. Anthropogenic effects might represent long-term (on the order of several decades to more than a century) climate changes that might happen within highly variable natural climate fluctuations. Several paleo studies in the north-central United States have indicated that hydroclimatic extremes (that is, low- and high-streamflow conditions) before European settlement have been outside of extremes since the 1900s. Depending on the interactions of anthropogenic effects and natural climate variability, extreme high-streamflow conditions might occur in the future, even in the presence of long-term downward peak-flow trends.

Montana, Wyoming↗
USGS2024

Testing rate‐and‐state predictions of aftershock decay with distance

We analyze aftershocks of the 2019 M 7.1 Ridgecrest mainshock and isolated M 5–6 mainshocks in southern California to test predictions made by the rate‐and‐state friction model of Dieterich (1994) . Rate‐and‐state friction predicts that the seismicity rate after a stress step follows Omori decay, where the Omori c ‐value, which is the saturation in aftershock rate observed at small times, is larger for smaller stress steps. Put in the context of an aftershock sequence, this predicts that the Omori c ‐value will be systematically larger at greater distances from the mainshock. To our knowledge, this predicted effect has not been observed. In part this may be because the Omori c ‐value is difficult to measure because it often reflects short‐term catalog incompleteness rather than a true saturation in aftershock rate. We explore the dependence of the Omori c ‐value on the distance to the mainshock by applying the “ a ‐positive” method ( van der Elst and Page, 2023 ). This method is insensitive to short‐term aftershock incompleteness and allows resolution of the true aftershock rate deep into the mainshock coda. For aftershocks of the Ridgecrest mainshock and stacked M 5–6 mainshocks, we observe systematic differences in early aftershock rates, relative to mainshock distance, consistent with the predictions of rate‐and‐state friction. Furthermore, for the larger Ridgecrest dataset, we observe that aftershocks nearer to the mainshock start earlier, and we resolve a flattening of the Omori curve consistent with a larger Omori c ‐value for the farthest aftershocks, as predicted by Dieterich (1994) .

Seismological Research Letters↗
USGS2025

Earthquake stress drop, source spectra from laboratory experiments, and the apparent unsteadiness of frictional slip

Over a range of co-seismic total energy release, high sample rate slip, stress, and slip velocity measurements were made during frictional failure to determine seismic source properties. The near-field measurements were used to estimate stress drops using spectral approaches that are analogous to the standard seismological moment-corner determined Δσ and acceleration amplitude Δσ arms stress drops. Rapid frictional sliding produces slip velocity amplitude spectra that vary with frequency -1 so long as the energy dissipated by friction approaches the total energy release. Under these conditions Δσ and Δσ arms are similar in size. Since these are nearly direct measurements of fault slip velocity and because they produce flat acceleration spectra between the corner and an apparent fmax, friction in these experiments seems to produce dynamic acceleration and deceleration at all resolved frequencies. The physical origin of this unsteady motion is not known exactly but likely reflects rapid dynamic variations in fault strength or applied stress. On the other hand, when the total energy stored prior to failure is artificially made somewhat larger relative to that which can be dissipated by friction the velocity spectra vary with frequency -2 immediately below the corner. At these conditions Δσ and Δσ arms diverge. The excess stored energy is preferentially partitioned into radiated energy upon failure. Collectively the experiments imply that to produce unsteady, white noise accelerations that are observed for natural earthquakes, requires that at least 95% of the energy released does not escape the source region to be radiated to the far-field.

Bulletin of the Seismological Society of America↗
USGS2000

Water quality of selected springs and public-supply wells, Pine Ridge Indian Reservation, South Dakota, 1992-97

This report presents results of a water-quality study for the Pine Ridge Indian Reservation, South Dakota. The study was a cooperative effort between the U.S. Geological Survey and the Water Resources Department of the Oglala Sioux Tribe. Discharge and water-quality data were collected during 1992-97 for 14 contact springs located in the northwestern part of the Reservation. Data were collected to evaluate potential alternative sources of water supply for the village of Red Shirt, which currently obtains water of marginal quality from a well completed in the Inyan Kara aquifer. During 1995-97, water-quality data also were collected for 44 public-supply wells that serve about one-half of the Reservation's population. Quality-assurance sampling was used to evaluate the precision and accuracy of environmental samples. Ten of the springs sampled contact the White River Group, and four contact the Pierre Shale. Springs contacting the White River Group range from calcium bicarbonate to sodium bicarbonate water types. Two springs contacting the Pierre Shale have water types similar to this; however, sulfate is the dominant anion for the other two springs. In general, springs contacting the White River Group are shown to have better potential as alternative sources of water supply for the village of Red Shirt than springs contacting the Pierre Shale. Nine of the springs with better water quality were sampled repeatedly; however, only minor variability in water quality was identified. Six of these nine springs, of which five contact the White River Group, probably have the best potential for use as water supplies. Discharge from any of these six springs probably would provide adequate water supply for Red Shirt during most periods, based on a limited number of discharge measurements collected. Concentrations of lead exceeded the U.S. Environmental Protection Agency (USEPA) action level of 15 µg/L for three of these six springs. Five of these six springs also had arsenic concentrations that exceeded 10 µg/L, which could be problematic if the current maximum contaminant level (MCL) is lowered. Blending of water from one or more springs with water from the existing Inyan Kara well may be an option to address concerns regarding both quantity and quality of existing and potential sources. All nine springs that were sampled for indicator bacteria had positive detections on one or more occasions during presumptive tests. Although USEPA standards for bacteria apply only to public-water supplies, local residents using spring water for domestic purposes need to be aware of the potential health risks associated with consuming untreated water. One spring contacting the White River Group and two springs contacting the Pierre Shale exceeded 15 pCi/L for gross alpha; these values do not necessarily constitute exceedances of the MCL, which excludes radioactivity contributed by uranium and radon. Additional sampling using different analysis techniques would be needed to conclusively determine if any samples exceeded this MCL. Nine springs were sampled for selected pesticides and tritium. The pesticides atrazine, carbaryl, and 2,4-D were not detected in any of the samples. The nine springs were analyzed for tritium in order to generally assess the age of the water and to determine if concentrations exceeded the MCL established for gross beta-particle activity. Tritium results indicated two springs are composed primarily of water recharged prior to atmospheric testing of nuclear bombs and two other springs have a relatively large percentage of test-era water. The remaining five springs had tritium values that indicated some percentage of test-era water; however, additional sampling would be needed to determine whether water is predominantly pre- or post-bomb age. Of the 44 public-supply wells sampled, 42 are completed in the Arikaree aquifer, one is completed in an alluvial aquifer, and one is completed in the Inyan Kara aquifer. Water from the alluvial well is a sodium bicarbonate water type, water from Arikaree aquifer ranges from calcium bicarbonate to sodium bicarbonate types, and water from the Inyan Kara well is a calcium sulfate bicarbonate type. Of the 44 wells sampled, 28 (64 percent) tested positive for indicator bacteria in presumptive tests. Because these were single samples that generally were collected upstream from chemical treatment feeders, positive detections do not necessarily constitute exceedances of drinking-water standards. A single sample from an Arikaree well exceeded the MCL for arsenic of 50 µg/L. Arsenic exceeded 10 µg/L for six additional Arikaree wells and for the alluvial well and the Inyan Kara well, which could be problematic if the current MCL is lowered. The alluvial well also exceeded the secondary maximum contaminant level (SMCL) for dissolved solids, which is non-enforceable, and the action level for lead. The Inyan Kara well exceeded the SMCL's for iron and for manganese and the MCL of 5 pCi/L for radium-226 and 228 combined. Several Arikaree wells exceeded SMCL's for either pH, sulfate, dissolved solids, iron, or manganese. One Arikaree well exceeded the MCL of 4.0 mg/L for fluoride and another exceeded the MCL of 10 mg/L for nitrite plus nitrate. Ten Arikaree wells equalled or exceeded 15 pCi/L for gross alpha; however, these values do not necessarily constitute exceedances of the MCL, which excludes radioactivity contributed by uranium and radon. Additional sampling using different analysis techniques would be needed to conclusively determine if any samples exceeded this MCL. Eight wells, all from the Arikaree aquifer, equalled or exceeded the proposed MCL of 20 µg/L for uranium and 33 wells (75 percent) equalled or exceeded one-half of the proposed MCL. Although this standard has only been proposed, additional information regarding the extent of elevated uranium concentrations in the Arikaree aquifer, and the geochemical processes involved, may be beneficial. It was determined from analyses of uranium isotope data for five wells that the source of elevated uranium concentrations is naturally occurring, rather than anthropogenic.

South Dakota↗
USGS2026

Small earthquake moment magnitude and implications for frequency–magnitude scaling of injection induced earthquakes of the Raton Basin

Accurate estimation of earthquake source parameters—such as moment magnitudes, corner frequencies, and stress drops—is essential for improving seismic hazard assessments and understanding earthquake physics. In this study, moment magnitudes ( M W ) are calculated for 31,581 earthquakes associated with wastewater injection in the Raton Basin (located along the border between northern New Mexico and southern Colorado) between 2016 and 2024 using radiative transfer theory to fit coda decay envelopes. Our results show that it is feasible to estimate moment magnitudes down to M W ~1 with coda envelopes from a small local monitoring network. Significant differences were found between M W and local magnitudes ( M L ) for small earthquakes ( M < 3.0). A linear relationship was optimized to convert M L to M W : M W = 0.7 M L + 0.96 and M W = 0.73 M L + 0.99 (for the events reported by the U.S. Geological Survey), which can be applied in future studies of Raton Basin seismicity. We find that b -values calculated employing different methods and using M L are approximately 1.0, while those using M W range from 1.2 to 1.4. A larger estimate of the b -value could influence interpretations of the statistical behavior of earthquakes associated with injection and consequently seismic hazard assessments based on a magnitude–frequency distribution. The potential differences between local versus moment magnitude-based earthquake statistics should be considered in other seismically active regions.

Colorado, New Mexico↗
USGS2026

Revisiting the utility of regional-scale, high-quality geophysical data in mineral exploration - A case study featuring the Mammoth Magnetic Anomaly, Pinal County, Arizona

Regional aeromagnetic surveys passively measure the total magnetic intensity (TMI) and are a foundational tool used in mineral exploration (Airo, 2015). With the increased global demand and the number of critical mineral resources required for manufacturing high-tech devices, developing high-quality, regional-scale geophysical surveys could aid critical mineral exploration efforts and geologic mapping. In 2019, the U. S. Geological Survey launched the Earth Mapping Resources Initiative (Earth MRI) to modernize the geologic and geophysical mapping of regions that have the potential to contain critical mineral resources within the United States. In support of planning Earth MRI geophysical surveys, Drenth and Grauch (2019) defined five aeromagnetic data quality rankings (rank 1 through rank 5) applying them to the airborne geophysical survey inventory of the United States (Johnson et al., 2021). Rank 1 aeromagnetic surveys are of the highest quality, meeting modern standards and allowing best practices for qualitative and quantitative interpretation; whereas rank 5 aeromagnetic surveys are of the lowest quality, being useful only for qualitative interpretation of broad features. Through the Earth MRI effort, 48 high-quality, regional-scale rank 1 and 2 airborne magnetic and radiometric geophysical surveys have been planned, collected, or publicly release through May 2025 (U. S. Geological Survey, 2025). Here, a portion of a rank 1 Earth MRI aeromagnetic survey in southeast Arizona is presented and compared to a legacy rank 5 aeromagnetic survey over the Mammoth Magnetic Anomaly (MMA), demonstrating how modern, high-quality aeromagnetic data improves our view of crustal geology, aiding mineral exploration.

Arizona↗
USGS2024

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and translational slides derived solely from high-resolution (≤3 m) elevation data and globally available estimates of the diffusion coefficient for sediment flux. The method applies a linear diffusion model to the roughest landslide deposits until they reach a representative non-landslide roughness distribution. This estimates the time for a landslide deposit to be unrecognizable in high-resolution digital elevation data, which we term the mean lifetime of the landslide. Using the mean lifetime and number of landslides within an area of interest, we can estimate the mean occurrence rate of landslides over that domain. We validate this approach using a comprehensive temporal inventory of landslides in western Oregon created using age-roughness curves that are calibrated with high-resolution elevation data and radiocarbon data. We find good agreement between our diffusion method and the existing age-roughness-derived estimates, producing mean lifetimes of 4500 and 5200 years (4% difference), respectively. Hazard maps produced using the two methodologies generally agree, with the maximum differences in landslide probability reaching 0.1. Due to the relative abundance of high-resolution elevation data compared with age-dated landslides, our method could help constrain landslide occurrence rates in areas previously considered unfeasible.

Oregon↗
USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗
USGS2024

Deep structure of Siletzia in the Puget Lowland: Imaging an obducted plateau and accretionary thrust belt with potential fields

Detailed understanding of crustal components and tectonic history of forearcs is important due to their geological complexity and high seismic hazard. The principal component of the Cascadia forearc is Siletzia, a composite basaltic terrane of oceanic origin. Much is known about the lithology and age of the province. However, glacial sediments blanketing the Puget Lowland obscure its lateral extent and internal structure, hindering our ability to fully understand its tectonic history and its influence on modern deformation. In this study, we apply map-view interpretation and two-dimensional modeling of aeromagnetic and gravity data to the magnetically stratified Siletzia terrane revealing its internal structure and characterizing its eastern boundary. These analyses suggest the contact between Siletzia (Crescent Formation) and the Eocene accretionary prism trends northward under Lake Washington. North of Seattle, this boundary dips east where it crosses the Kingston arch, whereas south of Seattle the contact dips west where it crosses the Seattle uplift (SU). This westward dip is opposite the dip of the Eocene subduction interface, implying obduction of Siletzia upper crust at this southern location. Elongate pairs of high and low magnetic anomalies over the SU suggest imbrication of steeply-dipping, deeply rooted slices of Crescent Formation within Siletzia. We hypothesize these features result from duplication of Crescent Formation in an accretionary fold-thrust belt during the Eocene. The active Seattle fault divides this Eocene fold-thrust belt into two zones with different structural trends and opposite frontal ramp dips, suggesting the Seattle fault may have originated as a tear fault during accretion.

Washington↗
USGS2024

The 17 January 1994 Northridge, California, earthquake: A retrospective analysis

The 17 January 1994 Northridge, California, earthquake was a watershed event, with far-reaching societal and scientific impacts. The earthquake, which occurred in the early days of both broadband seismic networks and the Internet, spurred advances in seismic monitoring, real-time systems, and development of data products. Motivated by the 30th anniversary of the earthquake, we present a brief retrospective of the earthquake and its impact, and reconsider both ground motions and the aftershock distribution using modern tools and best-available data. With improvements in instrumentation and analysis methodology, recent earthquakes continue to reveal increasing complexity of ground motions, fault systems, and earthquake ruptures. Even in the absence of data from state-of-the art instrumentation, a retrospective consideration of ground motion data from the Northridge earthquake reveals complexities beyond what could be characterized (and modeled) thirty years ago. Aftershock relocations for both the 1971 Sylmar and 1994 Northridge earthquakes also reveal an updated view of fault complexity. Our study does provide a cautionary tale regarding legacy data sets and research results that are not easily accessible, which can result in discrepancies between catalog data and products from best-available science. We also briefly describe outreach products produced as part of the anniversary commemoration.

California↗
USGS2024

Development of USGS NSHMs: Do small changes in hazard imply small changes in risk?

One of the flagship products from the U.S. Geological Survey (USGS) is the National Seismic Hazard Model (NSHM). Since 1976, the NSHM has been periodically updated to reflect newly published earthquake science and provide probabilistic estimates of seismic hazard for the United States. During each update cycle, alternative models are deliberated, analyzed, and documented through logic trees and their corresponding logic tree branch weights. For example, the decision to modify a logic tree branch weight may be influenced by sensitivity analyses of the logic tree branches in their effects on the mean hazard. However, do small changes in traditional measures of hazard imply small changes in risk? In this study, we make use of two update cycles of the USGS NSHMs and a National Bridge Inventory (NBI) from the Federal Highway Administration (FHWA) to explore the preceding question. Specifically, we first identify geographic locations in the conterminous United States in which the change in hazard from one cycle to another is relatively small. Next, we model the seismic risk to highway bridges for these locations and for each update cycle, while simultaneously distinguishing low hazard environments from high hazard environments. These data enable quantitative analysis of how much changes in risk can be expected given small changes in hazard, investigating the importance of risk models in decision-making during development of the USGS NSHMs.

Conference Paper↗
USGS2026

Geologic map of the Sierra Nevada, California and western Nevada

THE GEOLOGIC MAP OF THE SIERRA NEVADA is a core component of the Sierra Nevada Earth Science Atlas, which also includes geophysical, neotectonic, economic, and geochronologic data. The map illustrates the distribution of geologic units across the Sierra Nevada and related adjacent areas. Geologic units are grouped by type and age into three categories: Principally Paleozoic and Mesozoic metasedimentary and metavolcanic wall rocks, most of which are grouped into terranes; Paleozoic and Mesozoic plutons and intrusive suites, which intrude the wall rocks and form the core batholith of the range; and Late Cretaceous and Cenozoic sedimentary and volcanic rocks and surficial deposits that unconformably overlap the older units. Related rock units were combined and simplified for presentation at a scale of 1:400,000, as shown in the list of map units and associated correlation of map units (Plate 1B) and description of map units (Appendix A). Tectonic faulting, folding and uplift have overprinted the rocks and have strongly influenced the spatial distribution of units and the distinct morphology of the Sierra Nevada as we see it today. The Atlas is the result of collaborative work by scientists and mapmakers from the California Geological Survey and the U.S. Geological Survey. The Atlas was originally envisioned by the late geologist Warren Nokleberg (1939-2021), who contributed much to the initial geologic map compilation

California, Nevada↗
USGS2025

Multi-lithofacies alluvial characterization via airborne electromagnetic-borehole fusion using ordinary interval kriging and geologic constraints

Airborne electromagnetic (AEM) survey provides extensive spatial coverage and detailed resolution at the near surface and can be used to develop hydrogeological models. However, utilization of AEM data is not straightforward because AEM resistivity is an indirect measurement for inferring sediment types. This study develops an ordinary interval kriging (OIK) algorithm and a resistivity-to-multi-lithofacies (R2ML) data fusion workflow for multi-lithofacies alluvial characterization. OIK utilizes irregular interval data to construct three-dimensional (3D) resistivity fields from one-dimensional inverted AEM resistivity models. The R2ML workflow maps the resistivity field generated from OIK into a multi-facies lithological model, incorporating geologic constraints derived from well logs and geological observations. The numerical and real-world cases demonstrate that OIK is computationally efficient, accounts for 3D anisotropy, and minimizes the smoothing effect, thereby preserving resistivity contrasts and reducing interpolation uncertainty. The methodology is applied to lithologic characterization of the Mississippi River Valley alluvial aquifer (MRVA) in the Shellmound area, Mississippi, U.S. A frequency-domain AEM survey was conducted to support groundwater studies for the managed aquifer recharge (MAR) to the MRVA. The resulting lithological model, including four types of lithofacies—clay, very fine sand, fine-medium sands, and graveliferous sands, illustrates the geomorphological processes of the MRVA and implies potential MAR. The alignment between the lithological model and existing geological and hydrogeological investigations demonstrates that OIK and R2ML workflow effectively capture the subsurface architecture of the MRVA. The methods have broad applicability for characterizing alluvial aquifers through AEM-borehole data fusion, supporting sustainable groundwater management.

Mississippi↗
USGS2025

Advancing current understanding of Martian impact-generated hydrothermal systems through novel coupled modeling: Insights from Gale, Jezero, and other craters

Impact-generated hydrothermal systems are considered potentially habitable environments on Mars, Earth, and other planetary bodies for microbial life. However, there is an ongoing debate regarding what geological features on Mars provide definitive evidence for such systems. Although earlier studies have modeled hydrothermal processes in Martian craters, they often lacked integration with shock physics hydrocodes to constrain initial impact conditions. The importance of this two-code coupling was demonstrated by successfully replicating alteration signatures in the Earth's Haughton impact structure. In this study, we use a similar two-code approach, combining the iSALE hydrocode with the HYDROTHERM hydrothermal model to simulate the full evolution of impact-generated hydrothermal systems. We apply this method to craters the size of Jezero (∼50 km) and Gale (∼154 km) in diameter. Although Jezero's interior is largely buried, our results align with hypothesized hydrothermal vents and alteration minerals near central uplifts in similarly sized exposed craters, such as Toro and Auki. Furthermore, our models correspond to alteration patterns observed by the Curiosity in the lower layers of Mount Sharp, which may represent remnants of impact-driven hydrothermal activity. A key finding is that these systems may persist much longer than previously estimated. Our simulations suggest that a Jezero-sized system could remain habitable for thermophiles for approximately 720,000 years, whereas a Gale-sized system could persist for nearly 2 million years. Additionally, simulations under unsaturated crustal conditions reveal that air-dominated near-surface layers can suppress vertical fluid flow, enabling deep subsurface alteration without producing detectable mineral signatures at the surface.

Journal of Geophysical Research - Planets↗
USGS2026

Microclimate mediates the strength and direction of avian biotic interactions

Theory predicts that that the strength and direction of species interactions can shift from being competitive in benign environments toward being facilitative in stressful environments. However, the environmental context dependency of species interactions has rarely been tested in animal communities. We capitalized on a 15-year, landscape-scale dataset, collected annually in a relatively stable old-growth forest environment to test the long-held hypothesis that the strength and direction of species interactions might be mediated by climatic conditions. It is generally accepted that competitive and facilitative interactions drive the distributions of many species. Using multi-species dynamic occupancy models applied to long-term data, we tested whether annual settlement by bird species could affect either the persistence or settlement by other phylogenetically related species, and whether these interactions are mediated by microclimate. We found that species interactions were influenced by microclimate for some, but not all avian species pairs. Related species pairs more often showed settlement dynamics that were indicative of attraction rather than repulsion. In some cases, competitive interactions at warmer microclimates flipped to become facilitative in colder ones. However, the reverse was also true: facilitative interactions amplified for some species under warm conditions. Furthermore, species pairs that were closely related were more likely to exhibit competitive relationships along at least part of the microclimatic gradient. Our results highlight the importance of using long-term data to incorporate competitive and facilitative interactions into species distribution models and support the notion that the strength and direction of species interactions can be dependent on microclimatic environmental conditions.

Oregon↗