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USGS2024

Assessment and characterization of ephemeral stream channel stability and mechanisms affecting erosion in Grand Valley, western Colorado, 2018–21

The Grand Valley in western Colorado is in the semiarid Southwest United States. The north side of the Grand Valley has many ungaged ephemeral streams, which are of particular interest because (1) the underlying bedrock geology, Late Cretaceous Mancos Shale, is a sedimentary rock deposit identified as a major salinity contributor to the Colorado River and (2) despite infrequent streamflows of short duration, monsoon-derived floods in these ephemeral streams can carry substantial amounts of sediment downstream, affecting upstream and downstream banks and channel cross sections. The study area is of interest, because salinity, or the total dissolved solids concentration, in the Colorado River causes an estimated $300 million to $400 million per year in economic damages in the United States, and it is estimated 62 percent of the Upper Colorado River Basin’s total dissolved solid loads originate from geologic sources. In an effort to minimize salt contributions to the Colorado River from public lands administered by the Bureau of Land Management, a comprehensive salinity control approach is typically used to reduce nonpoint sources of salinity through land management techniques and practices. In 2018, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, began an assessment of ephemeral streams located on the north side of the Grand Valley, western Colorado, to characterize stream channel stability and identify mechanisms affecting erosion. The U.S. Geological Survey developed a method for automatically extracting channel cross-section geometry from existing remotely sensed terrain models. Based on estimated flood stage and surrogate streamflows, hydraulic characteristics were calculated. Furthermore, the channel geometries and hydraulic characteristics were used to estimate channel stability using a statistical model. Cross-section stabilities were determined from a stream channel stability assessment for a subset of 1,406 visited (field observed) locations out of 13,415 cross sections, which were delineated from remotely sensed terrain models. The application of Manning’s resistance equation in combination with multiple logistic regression models demonstrated channel stability can be estimated with a 0.845 goodness of fit for a validation dataset when using a combination of drainage area, width-to-depth ratio, sinuosity, and shear stress as the explanatory variables. Stream channel stability was extrapolated for 13,415 unvisited (not field observed) cross sections using the multiple logistic regression model and defined explanatory variables. Mapping of the ephemeral streams and their associated stabilities may be used by the Bureau of Land Management to prioritize areas for remediation or changes in management strategies to reduce sediment and salinity loading to the Colorado River. The study found channel stability within the ephemeral streams to be spatially variable, longitudinally discontinuous, and dictated by changes in channel bed slope. The stable ephemeral streams were relatively wide and shallow and often had smaller drainage areas with less potential for producing shear stresses capable of overcoming channel adhesion. A change in channel bed slope can provide the means necessary to generate shear stresses appropriate to initiate erosion and a subsequent stability transition to incising channels. Channel widening happens when either or both banks of an incising channel reach a critical height for mass wasting, or when channel curvature causes higher sidewall stress. Regardless, widening channels can promote increases in sinuosity and subsequently reduce steep channel bed slopes. Consequently, stable and widening channels can have comparable bed slopes, making channel bed slope a poor explanatory variable to predict channel stability overall, despite its function to initiate channel instability. The results were based on a surrogate 0.10 annual exceedance probability (AEP; return period equal to the 10-year flood) interval streamflow, although it was recognized fluctuations in streamflow would also affect channel stability. Past and current changes within the study area affect streamflow; therefore, mechanisms affecting erosion include land use disturbances, soil compaction, loss of vegetation cover, drought, less frequent and more extreme precipitation, and fires—which all intensify the potential runoff and erosion within the study area.

Colorado↗
USGS2024

Examining 22 years of ambient seismic wavefield at Mount St. Helens

An increase in seismic activity precedes most volcanic eruptions. Whereas event-based forecasting approaches have been successful, some eruptions remain unanticipated, resulting in casualties and damage. Our study leverages the recent advancements in ambient field seismology. We explore features extracted from continuous ambient fields using traditional methods, for example, peak ground velocity, peak ground acceleration, root mean square, root median square, real-time seismic amplitude measurement, and novel methods (displacement seismic amplitude ratio and spectral width). In addition, we explore unsupervised learning of higher order wavelet features using scattering networks. We find that combining all the methods was necessary to disentangle the effects of seismic sources from structural changes at Mount St. Helens. Although the ambient wavefield-based approach does not yield additional or more significant precursory signals than event-based methods at Mount St. Helens, our study demonstrates that the ambient wavefield provides supplementary information, mainly about structural changes and complements traditional methods. The ambient seismic wavefield offers additional insights into long-lasting processes. We find enhanced wave attenuation correlating with geochemical measurements. We interpret this as ongoing structural changes, such as dome growth or the evolution of the volcanic conduit system. On annual and decadal timescales, we interpret seasonal seismic attenuation in the shallow subsurface as groundwater fluctuations, corroborated by observations at the nearby Spirit Lake level. This multimethod approach at Mount St. Helens sheds light on a volcanic system’s underlying dynamics and structure.

Washington↗
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↗
USGS1996

Magnitude and frequency of floods in the Suwannee River Water Management District, Florida

Flood-frequency statistics for 2-, 5-, 10-, 25-, 50-. 100-, 200-, and 500-year recurrence intervals, based on three methods of analysis, are presented for 25 continuous-record and seven peak flow partial-record gaging stations in the Suwannee River Water Management District. The first method, for gaged stations, utilizes station records; the second method, for ungaged sites, utilizes regional regression analysis; and the third method uses a weighted combination of the station and regional values. Because the weighted values utilize two more or less independent estimates of the peak flow statistic, they are considered more accurate than the station estimates or the regression estimates alone. Also, the use of another weighting scheme to improve estimates of flood frequency statistics at ungaged sites is demonstrated. The karstic nature of much of the Suwannee River Water Management District significantly attenuates flood peaks in some streams by providing substantial subsurface storage when river stages are high. At such times, springs discharging into rivers may reverse flow temporarily and become sinks.

Florida↗
USGS2026

Moment magnitude for small earthquakes in the Delaware basin of west Texas and southeast New Mexico, USA

The Delaware Basin region of west Texas and southeast New Mexico has become one of the most prolific regions of seismic activity in the continental United States due to widespread hydraulic fracturing and wastewater disposal injection. In response to the increased number of earthquakes in this region, rapid and accurate characterization of earthquake sources is necessary to understand the evolution of seismic activity and level of seismic hazard associated with these earthquakes. This study re-evaluates earthquake magnitudes, estimating moment magnitude (MW) for small earthquakes in the Delaware Basin using 1) moment-rate spectra derived from S-wave coda envelopes, and 2) a relative magnitude method that relies exclusively on the ratio of waveform amplitudes between highly correlated waveform pairs. The coda-envelope method produces accurate M W estimates for small earthquakes ( M 1.5 – 3) that are consistent with independent, waveform modeled moment magnitudes for events with M W > 3 . Using the relative amplitudes method to extend these M W magnitudes to many other events, we successfully provide relative moment magnitude ( M W,rel ) values for 81% of the Texas Seismological Network catalog in the Delaware Basin region, and 45% of the USGS Induced Seismicity Project’s catalog of events in southeast New Mexico. The adoption and integration of the calibrated M W,rel method with current magnitude estimation methods offers valuable insights into the relationships between local and moment magnitude and will contribute to improved characterization of widespread induced seismicity.

New Mexico, Texas↗
USGS2025

Assessing flood water infiltration and storage in a restored floodplain

In urban areas, floodplain restoration is gaining prominence as a strategy for restoring the natural functions of floodplain ecosystems and reducing flood risk. This has spurred research into potential interactions between floodwaters, the hyporheic zone, and the floodplain aquifer. An urban restored stream in Wisconsin, USA, was used as a case study to examine four methods to estimate floodplain infiltration and storage during overbank floods. We characterised flood-related infiltration over a 4-year period from 2018 through 2021 by simultaneously and continuously measuring groundwater levels and vertical temperature profiles with stream water levels linked to high-resolution flood inundation maps. High-resolution topographic data helped to quantify surface floodplain storage and the unsaturated soil volume relative to flood stage. Infiltration estimates from the simple methods align well with those from the more complex methods; however, the complex methods provide additional insights about the factors influencing infiltration. Results from all methods indicate that the volume of water that vertically infiltrates during floods is likely small relative to the total volume of the flood, with 0.08%–0.52% of flood water infiltrating into the floodplain, on average. Spatially variable vertical hydraulic gradients, driven by flood depth, groundwater level, and permeability, imply heterogeneous patterns of infiltration across the floodplain. Gradients favourable for infiltration typically occurred during the onset of flooding but, over the study period, were mostly (98% of the time) favourable for groundwater discharge to the channel (non-flood periods). These findings highlight the importance of considering surface-groundwater dynamics, floodplain soils, and unsaturated floodplain volume in defining the benefits of floodplain infiltration for flood attenuation.

Wisconsin↗
USGS2025

Understanding market sensitivity: Estimation of supply and demand elasticities for non-fuel minerals

In today’s rapidly changing economic landscape, understanding market responsiveness to price changes and the factors influencing commodity prices has become increasingly relevant. Price elasticities serve as indicators of how variations in market conditions affect supply and demand, providing insights into the sensitivity of commodity markets to price fluctuations. This paper presents a comprehensive analysis of price elasticities of supply and demand for 74 non-fuel mineral commodities including precious metals, base metals, minor metals, and industrial minerals that are utilized across various industries. We employ various econometric techniques, including fixed effects models for panel data and two-stage dynamic ordinary least squares (2S-DOLS) alongside autoregressive distributed lag (ARDL) models for time series analysis, to derive robust estimates of price elasticities. Our findings reveal variability in elasticities among different commodities and indicate that all studied mineral commodities exhibit price inelastic supply and demand in the short run, which we define as one year for the purposes of our analysis, given that the data is all annual. This research provides original estimates of price responsiveness for a wide range of commodities that have not been previously addressed in the literature, thereby enhancing the understanding of market dynamics in the mineral sector. Given that price elasticities can be influenced by factors such as market structure, technological advancements, mining costs, and industry-specific demand drivers, we use variables that serve as proxies for these factors.

Mineral Economics↗
USGS2024

The importance of nodal plane orientation diversity for earthquake focal mechanism stress inversions

Inversions of earthquake focal mechanisms are among the most accessible and reliable methods for determining crustal stress. However, the use of this method varies widely, and assumptions that underpin it are often violated, potentially compromising stress estimates. We investigate the consequences of violating the little-studied assumption that the focal mechanisms have diverse orientations. Our approach is to employ data-informed synthetic mechanisms, with nodal plane orientations defined by recent earthquake lineaments in the Midland Basin, western Texas, and rakes consistent with slip in the mapped stress field. Using both the traditional stress inversion method that assumes constant shear stress magnitudes on the causative faults as well as a recently published variable shear stress method, we show that low fault plane diversity can cause maximum horizontal stress ( S Hmax ) orientation and relative principal stress magnitude (faulting regime) estimates to differ markedly from the true values. This problem is compounded for catalogs with even modest amounts of noise (≤15°) or few (e.g., 20) mechanisms. Significantly, traditional approaches for quantifying uncertainty such as the bootstrap can severely underestimate the true uncertainty under these circumstances. To remedy this, we provide simple tools to quantify nodal plane orientation diversity and stress inversion reliability.

Geological Society of London Special Publications↗
USGS2025

Sand provenance boundary in the Mu Us Sandy Land of northern China

Desert dunes are often assumed to have uniform mineral compositions due to extensive mixing during lateral transport, which complicates provenance studies. The Mu Us Sandy Land in north-central China, near the East Asian summer monsoon precipitation boundary, experiences a wetter climate than most deserts. Climate wetting as a result of a warming climate, and the ‘Sand Control Project’ implemented by the Chinese government to decrease the lateral movement of sand dunes in this area provide an opportunity to study surface processes of sand production and transport. Previous studies using zircon U Pb geochronology and heavy mineral composition indicate distinct sand sources for the Mu Us Sandy Land: local basement-derived middle Yellow River sediments and recycled dried-up lacustrine sediments for the eastern part, and northeastern Tibetan Plateau-derived upper Yellow River sediments for the western part. However, zircons and heavy minerals only represent trace amounts of the bulk mineralogy within a sand dune, so broader provenance analysis targeting common minerals is essential. We focus on the area near the proposed provenance difference boundary between the western and eastern Mu Us Sandy Land, using comprehensive sampling and provenance techniques to confirm distinct provenance characteristics and delineate the provenance boundary. Our findings reveal that sand from most of the Mu Us Sandy Land originated from the erosion of local basement by the middle Yellow River and recycled local dried-up lacustrine sediments, whereas the southwestern corner and the neighboring western-central Chinese Loess Plateau received sediments from the distal northeastern Tibetan Plateau.

Mu Us Sandy Land↗
USGS2025

Detection of viral, bacterial, and protozoan pathogens and microbial source tracking markers in paired large- and small-volume water samples

When sampling for waterborne microbes, researchers may need to diverge from recommended sample volumes due to logistical constraints, novel targets, or challenging matrices, with little guidance about the potential impact on results. In field studies, we measured bacteria, viruses, and protozoa (15 quantitative polymerase chain reaction assays) in paired large- and small-volume samples to evaluate method performance and relevant factors. Concordance between methods was low. Large-volume ultrafiltration yielded more detections than small-volume sampling, especially for pathogens in groundwater. Greater microbial concentrations were associated with more frequent detections in small-volume samples and greater concordance between paired samples. Large-volume samples appeared to be more susceptible to diminished sensitivity from complex sample matrices. In laboratory studies, recovery of microbes was poorer for large- than small-volume methods, although large-volume methods more reliably detected low-concentration targets. Large-volume samples were less stable than small-volume samples during storage. Overall, large-volume sampling was superior for detecting pathogens but may underestimate concentrations; small-volume sampling was more prone to false negatives but was adequate when concentrations were relatively high, like we observed for microbial source tracking in surface waters.

Wisconsin↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS2025

Using gridded seismicity to forecast the long-term spatial distribution of earthquakes for the 2025 Puerto Rico and U.S. Virgin Islands National Seismic Hazard Model

Gridded (or background) seismicity models are a critical component of probabilistic seismic hazard assessments, accounting for off‐fault and smaller‐magnitude earthquakes. They are typically developed by declustering and spatially smoothing an earthquake catalog to estimate a long‐term seismicity rate that can be used to forecast future earthquakes. Here, we present new gridded seismicity models for use in the 2025 National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The previous PRVI NSHM was released in 2003, and our new models incorporate updates to both data and methodology. We utilize an updated earthquake catalog based on improved Puerto Rico Seismic Network data with newly characterized completeness epochs. The catalog is divided into crustal, subduction interface, and intraslab seismicity using new methods and Slab2 subduction zone geometries. To forecast the long‐term spatial distribution of earthquakes, we use an updated methodology developed for the 2023 U.S. 50‐state NSHM, considering three declustering methods and two spatial smoothing methods based on 2D Gaussian kernels. To adapt it for the complex seismotectonics of the region, we also adopt probabilistic methods to account for events with unknown depths and uncertainties in tectonic classification, and develop a new method for spatial scaling to counteract the effects of spatial variability in network coverage while maintaining the use of smaller events. Finally, we test the performance of these spatial models in forecasting the location of M w ≥ 5earthquakes in the region. Our updated methodology improves the representation of epistemic uncertainty relative to the 2003 model, and our results demonstrate the effectiveness of the new measures we have introduced to address heterogeneities in network detection and systematically evaluate forecast performance.

Puerto Rico, U.S. Virgin Islands↗
USGS2024

Using surficial geologic maps, vegetation, and monitoring to address erosion impacts from grazing in Channel Islands National Park, California

Employing a map-unit classification scheme based on geomorphic process and age, the U.S. Geological Survey (USGS) mapped Quaternary surficial deposits of the five islands comprising Channel Islands National Park (CHIS), California, as no such maps previously existed. Mapping was motivated through an agreement with the National Park Service (NPS) to aid natural resource assessments, including post-grazing disturbance recovery and identification of mass wasting and tectonic hazards. The resulting detailed (1:12,000 scale) maps portray areas of upland erosional transport processes and alluvial, fluvial, eolian, beach, marine terrace, mass wasting, and mixed depositional processes at a scale commensurate with the process signal on the landscape. Detailed, GPS-located observations of sedimentology, pedogenic development, landscape position, and geomorphology constrain map unit identification. In addition, map-unit boundary delineation was determined in a GIS using a variety of high-resolution (sub-meter) aerial imagery and lidar-based DEMs complemented by derivative raster products. The GIS geodatabase schema used is GeMS compliant. Resolvable map-unit widths are as small as 10-15 meter. Locational accuracy of unit boundaries is estimated to be as low as 10 m or better. Detailed mapping is at a scale allowing determination of geomorphic transport processes operating on the landscape and conveys geologic information to land managers at a resolution commensurate with park resources. Map unit ages are constrained by relative soil chronostratigraphy, vertebrate and invertebrate fossils, and materials collected for dating control using radiogenic, luminescence, and cosmogenic radionuclide techniques. Associated topical studies examined connections between geology, surface water, and vegetation distribution and restoration.

California↗
USGS2024

High resolution identification and quantification of diffuse deep groundwater discharge in mountain rivers using continuous boat-mounted helium measurements

Discharge of deeply sourced groundwater to streams is difficult to locate and quantify, particularly where both discrete and diffuse discharge points exist, but diffuse discharge is one of the primary controls on solute budgets in mountainous watersheds. The noble gas helium is a unique identifier of deep groundwater discharge because groundwater with long residence times is commonly enriched in helium. In this study, a portable mass spectrometer was used to measure longitudinal variation in dissolved helium concentrations in two mountainous rivers at high spatial resolution not feasible with traditional sampling techniques. Helium profiles were then simulated using a mass-balance model to quantify longitudinal variation in groundwater discharge to the receiving rivers. Results indicate helium concentrations were enriched by multiple orders of magnitude above atmospheric equilibrium in both rivers and that this persisted for up to 18 km below observed pulse inputs in the Colorado River. Helium mass-balance models match observed longitudinal patterns with the exception of sharp initial increases in helium observed in the rivers. Increased longitudinal groundwater discharge rates correspond to mapped geologic structures in both watersheds that likely transport deep geothermal water. Models show variable sensitivity to spatial assignment of input variables representing the groundwater source, illustrating the importance of collecting data from discrete groundwater discharges where possible. The methodology shows promise for field experiments designed to assess air–water exchange rates and to quantify total groundwater discharge from a combination of discrete and diffuse sources.

Colorado, Utah↗
USGS1976

An environmental assessment of impacts of coal development on the water resources of the Yampa River basin, Colorado and Wyoming; Phase I work plan

Coal resources of the western United States are being developed at ever-increasing rates, causing concerns of the effects of mining and associated activities on the environment. The Yampa River basin in northwestern Colorado and south-central Wyoming is undergoing economic development of its coal, oil and gas, and uranium resources. The Yampa River basin assessment is a 21-year program of the U.S. Geological Survey. It is designed primarily to assess the availability and quality of the basin's water resources. The basin assessment also will evaluate potential environmental and selected socioeconomic impacts of energy-resource development plans proposed by mining and power companies. This report serves as a project work plan for the basin assessment's first-phase work activities. Economic development in the Yampa River basin will result in higher levels of residuals (noneconomic byproducts) being discharged into the environment. Residuals-management encompasses the technological and economic interrelationships that should be considered in order to comply with Federal and State environmental-control regulations regarding air quality, water quality, and disposal of solid wastes. The basin assessment, the first phase that is described by this report, is designed to provide Federal, State, and local decision-makers with the basic environmental information needed to formulate and to evaluate policies for the development of energy resources. The techniques applied and conclusions reached in the Yampa River basin assessment should aid similar studies of other energy-rich basins in the western United States.

Colorado, Wyoming↗
USGS2025

Magnitude, depth and methodological variations of spectral stress drop within the SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Sequence

We present the first ensemble analysis of the 56 different sets of results submitted to the ongoing Community Stress Drop Validation Study using the 2019 Ridgecrest, California, earthquake sequence. Different assumptions and methods result in different estimation of the source contribution to recorded seismograms, and hence to the source parameters (principally corner frequency, f c ⁠ , spectral stress drop, Δσ, and seismic moment, M 0 ⁠ ) obtained from modeling calculated source spectra. For earthquakes smaller than magnitude (M) 2.5 there is negligible correlation between the f c values obtained by different studies, implying that no present method is reliable using available data. For larger magnitude events, correlation between f c measurements of different studies, within even a small M range is always higher than spectral ⁠Δσ , because the f c measurements simply reflect the underlying physical decrease in f c with increasing M. We model the observed trends of submitted f c with both magnitude and depth. Most methods report an increase in spectral Δσ with M, although a magnitude‐invariant spectral Δσ is within the confidence limits. The depth dependence is smaller and depends on whether a study allows attenuation to vary with source depth; a combination of depth‐dependent attenuation correction, and depth‐dependent shear‐wave velocity can compensate for reported depth trends. We model the submitted values to remove differing M and depth variation to investigate the relative interevent variability. We find consistent relative variation between individual events, and also lower relative spectral Δσ in the northwest of the aftershock sequence, and higher on the cross fault and in the region of main fault intersection. This large‐scale comparison implies that absolute spectral Δσ estimates are dependent on the methods used; studies of different regions or using different methods should not be directly compared and improved constraints on path and site corrections are needed to resolve these absolute spectral Δσ differences.

California↗
USGS2025

40Ar/39Ar geochronology supporting mineral resources research at USGS Denver

The 40 Ar/ 39 Ar geochronology method is used to date potassium-bearing rocks and minerals, based on the decay of 40 K to 40 Ar, which provides important temporal constraints for geological events. The USGS Denver Argon Geochronology Laboratory dates samples from a variety of projects, mainly in the USGS Mineral Resource Program and the National Cooperative Geologic Mapping Program, facilitating in-depth research into the timing of geological events and processes. Recent applications of this method include geochronological studies in the Yellow Pine district, revealing mineralization ages that range from 51 to 70 Ma, and investigations into the Bear Lodge alkaline complex, providing insights into the timing of REE carbonatite formation. Additionally, studies at Alunite Ridge highlight the method's potential for understanding concealed mineral deposits. Ongoing projects continue to leverage 40 Ar/ 39 Ar data to enhance understanding of geologic frameworks and mineral resources, underpinning its importance in modern geochronology and mineral resource assessment.

Conference Paper↗
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↗