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Results for “Contributions to Mineralogy and Petrology”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,674 records · Page 66Linked to original sources
USGS2001

Water, ice, meteorological, and speed measurements at South Cascade Glacier, Washington, 1999 balance year

Winter snow accumulation and summer snow, firn, and ice melt were measured at South Cascade Glacier, Washington, to determine the winter and net balances for the 1999 balance year. The 1999 winter snow balance, averaged over the glacier, was 3.59 meters, and the net balance was 1.02 meters. Since the winter balance record began in 1959, only three winters have had a higher winter balance. Since the net balance record began in 1953, only 2 years have had a greater positive net balance than 1999. Runoff was measured from the glacier and an adjacent non-glacierized basin. Air temperature, precipitation, and humidity were measured nearby, and ice speed was measured. This report makes these data available to the glaciological and climatological community.

Washington↗
USGS2025

Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes

Great subduction earthquakes ( M w ≥ 8.0) can generate devastating tsunamis by rapidly displacing the seafloor and overlying water column. These potentially tsunamigenic seafloor offsets result from coseismic fault slip and deformation beneath or within the accretionary wedge. The mechanics of these shallow rupture phenomena and their dependence on subduction zone properties remain unresolved, partly due to the sparsity of offshore observations of shallow megathrust earthquake deformation. Here, we analyze how offshore structure influences shallow rupture mechanics and slip partitioning using 3D dynamic earthquake simulations of the Cascadia subduction zone (CSZ) megathrust with and without variably dipping seaward- or landward-vergent splay faults in the wedge that sole into the megathrust. Resulting tradeoffs between splay and megathrust slip reveal structural controls on rupture partitioning, with greater splay slip leading to less shallow megathrust slip updip. Gently dipping and seaward-vergent splays host more slip than those with steeper, landward-vergent splays. To isolate the underlying mechanisms, we compare models with Andersonian and plunging principal stresses. Results suggest distinct static and dynamic processes control the dip- and vergence-dependence of splay rupture: static (mis)alignment relative to far-field tectonic loading favors slip on more optimally oriented, shallowly dipping splay faults. In contrast, dynamic stress interactions of an updip-propagating megathrust rupture front with the free surface and potential branch faults favor forward branching onto seaward-vergent splays and inhibit backward branching onto landward-vergent splays. Resulting seafloor displacements suggest splay fault structure may influence coseismic tsunami source processes, highlighting the importance of dynamically viable rupture scenarios in subduction hazard assessments.

Cascadia subduction zone↗
USGS2025

Paleoseismology and paleogeodesy using coral microatolls

Establishing the rupture extent and slip distribution of individual paleo-earthquakes is vital for assessing fault behavior including the persistence of rupture segmentation, recurrence patterns, and similarity of successive events, key issues in both fault mechanics and hazard assessment. Techniques with high temporal and geodetic precision as well as a wide distribution of study sites are necessary to investigate past earthquakes in such detail. Coral microatoll growth is one of the best types of geologic record for paleoseismology and paleogeodesy given these needs, as it provides long, continuous, widely distributed records of centimeter-scale vertical tectonic motion with potentially annual-level temporal precision. This chapter describes the process of interpreting microatoll growth records to obtain time series of relative sea level, tectonic vertical deformation fields, and finally slip and coupling parameters on an underlying fault interface.

Book chapter↗
USGS2025

Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20

We present an assessment of water supply across the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico covering water years 2010–20. Our analysis drew on two national hydrologic models, the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system. Both models produced estimates of streamflow, evapotranspiration, soil moisture, snow water equivalent, and other hydrologic states and fluxes. The models were driven by the bias-adjusted 4-kilometer-resolution, long-term regional hydroclimate simulation over the conterminous United States dataset (CONUS404). We assessed spatial and temporal error distributions by comparing monthly simulations at the 12-digit hydrologic unit code and regional scale from both models against external benchmarking datasets. Results showed that average annual rainfall across the CONUS was 857 millimeters per year for the period of analysis, with water year 2012 the driest year (729 millimeters) and water year 2019 the wettest year (995 millimeters). Key interannual variability results included the following: (1) the California–Nevada hydrologic region had the highest variability in precipitation and snow accumulation, and (2) the Texas hydrologic region was among hydrologic regions with the highest variability in precipitation. We related interannual variability in precipitation to storage volumes in soil moisture, snow water equivalent, and lakes and reservoirs to highlight areas with little storage and large year-to-year variability in precipitation. These areas included the Southern High Plains, Central High Plains, Texas, Souris–Red–Rainy, Mississippi Embayment, and Midwest regions. Our analysis of groundwater-level data showed that several of these areas overlap aquifers where groundwater levels were considerably lower than historical averages, including the Colorado Plateaus aquifers, the Rio Grande aquifer system, and the Central and Southern regions of the High Plains aquifer. Many of these lowered groundwater levels are continuations of decades-long declines from overpumping that started well before the assessment period. The resulting water budgets and their analyses provide a high-resolution foundational assessment of the mean state and variability of the terrestrial hydrologic cycle across the CONUS and Alaska, Hawaii, and Puerto Rico to support a wide range of water resource management applications.

Professional Paper↗
USGS2024

U.S.-Mexico Borderland & vegetation community map

People on both sides of the United States-Mexico border need a high-resolution, binational vegetation community map that spans the entire United States-Mexico borderlands. Traditionally, mapping efforts in this region were impeded by complex logistics related to the international border, differing national needs and plans, and resource allocations and priorities. To address this need, scientists from the U.S. Geological Survey (USGS) Southwest Biological Science Center partnered with the Sonoran Joint Venture, the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program, data engineers from the Department of Biosystems Engineering at the University of Arizona, and collaborators from the Wildlands Network, the Borderlands Program to produce the first prototype land cover map within the overlapping Mojave Desert, Sonoran Desert, and the North American Bird Conservation Initiative’s Bird Conservation Region 33 (BCR33) using Landsat satellite data . BCR33 is an area of high biodiversity, providing habitat for bird species of concern and other wildlife. The land cover map supports FWS recovery plan efforts related to conservation planning activities for many species, including Yellow-billed Cuckoo ( Coccyzus americanus ), Cactus Ferruginous Pygmy-Owl ( Glaucidium brasilianum cactorum ), Southwestern Willow Flycatcher ( Empidonax traillii extimus ), Yuma Ridgway’s Rail ( Rallus obsoletus yumanensis ), Bendire’s thrasher ( Toxostoma bendirei ), LeConte’s thrasher ( Toxostoma lecontei ), Masked Bobwhite ( Colinus virginianus ridgwayi ), jaguar ( Panthera onca ), and endangered plants such as Bartram’s stonecrop ( Graptopetalum bartramii ) and the Pima pineapple cactus ( Coryphantha robustispina ssp. robustispina ). In 2024, a Phase-II map for the full BCR33 region was completed, increasing the understanding of the binational nature of natural communities. The published map and associated paper can be found here .

Borderland↗
USGS2025

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California↗
USGS2025

U.S. Geological Survey research and assessments supporting carbon dioxide removal

Both carbon capture and storage (CCS) and carbon dioxide removal (CDR) are methods to limit future global temperature rise and ocean acidification. CCS sequesters (stores) carbon dioxide (CO2) captured from industrial sources thereby preventing the CO2 from reaching the atmosphere. The captured CO2 is injected into underground geologic reservoirs or is converted into stable industrial products. CDR enhances natural processes or uses technical approaches to remove excess CO2 from the atmosphere. Carbon dioxide is sequestered in natural sinks such as vegetation and soil, or injected into underground reservoirs or converted into durable products. The U.S. Geological Survey (USGS) conducts research and resource assessments that support biologic and geologic CDR approaches. This report will review some of the ongoing USGS CDR research and assessment efforts.

Conference Paper↗
USGS2024

Uncertainty in ground-motion-to-intensity conversions significantly affects earthquake early warning alert regions

We examine how the choice of ground‐motion‐to‐intensity conversion equations (GMICEs) in earthquake early warning (EEW) systems affects resulting alert regions. We find that existing GMICEs can underestimate observed shaking at short rupture distances or overestimate the extent of low‐intensity shaking. Updated GMICEs that remove these biases would improve the accuracy of alert regions for the ShakeAlert EEW system for the West Coast of the United States. ShakeAlert uses ground‐motion prediction equations (GMPEs), which calculate spatial distributions of peak ground acceleration (PGA) and peak ground velocity (PGV) from earthquake source estimates, combined with GMICEs to translate GMPE output into modified Mercalli intensity (MMI). We find significant epistemic uncertainty in alert distances; near‐source MMI estimates from different GMICEs can differ by over 1 MMI unit, and MMI extents used for public EEW alerts can differ by hundreds of kilometers for larger magnitude earthquakes ( M ∼6.5+). We use a catalog of “Did You Feel It?” shaking reports to evaluate how well GMICEs predict observed shaking. Our preferred GMICE is the one that computes MMI using PGV for high intensities and transitions to using PGA for nondamaging intensities. These results motivate updating GMICE relationships more generally, including in ShakeMap applications.

The Seismic Record↗
USGS2024

Separating signals in elevation data improves supervised machine learning predictions for hydrothermal favorability

A recent study identified topography (land surface elevation above sea level) as an important input dataset (feature) for predicting the location of hydrothermal systems in the Great Basin in Nevada. Yet, topography is generally a result of more than one geological process and may consequently contain multiple distinct signals. For example, the geologic evolution of the Great Basin has produced both crustal thickening (i.e., regional-scale trends in elevation) and thinning via Basin and Range extensional faulting (i.e., valley-scale topographic relief). We postulate that these geologic processes may affect the occurrence of hydrothermal systems differently. Therefore, we separate the regional trend from the valley-scale signal in the Great Basin, and then use them separately to evaluate the importance of each as predictors for hydrothermal favorability. Our prior work applying supervised machine learning (ML) using the data from the Nevada Machine Learning Project demonstrated that employing a training strategy that randomly selects negative training sites produces better performing models for predicting hydrothermal favorability than a training strategy that uses expert-selected negatives. The models created using both training strategies exhibited a west-east geographic trend in the predictions for the favorability of hydrothermal resources. These models generally predicted higher favorability in western Nevada and lower favorability in eastern Nevada. This west-east trend in predicted favorability correlates with elevation across the Great Basin, which trends higher from west to east. By separating the original elevation feature into distinct features for elevation trend (i.e., regional-scale topography) and detrended elevation (i.e., valley-scale or local relative topography), we find that models using the separated topographic signals consistently outperform competing models that use the original elevation feature. Although western Nevada still exhibits higher favorability than eastern Nevada, using separated signals for regional elevation and local structure reduces the west-east prediction trend in the region and emphasizes structures associated with hydrothermal upflow. This work emphasizes how carefully engineering features to represent geological conditions relevant to hydrothermal systems allows ML algorithms to detect important patterns for predicting hydrothermal resource favorability and leads to better model performance.

Conference Paper↗
USGS2026

Forecasting volcanic activity in Germany—A multi-criteria approach

Igneous activity, including shallow intrusions and volcanism, has the potential to disrupt underground critical infrastructure. Notably, future underground infrastructure projects like high-level radioactive waste repositories must be sited in areas of extremely low disruption probability by igneous activity. In Germany, according to the Repository Site Selection Act of 2017 (Standortauswahlgesetz, or StandAG), areas in which Quaternary volcanism is either present or future volcanic activity is expected within the next 1 million years (m.y.) must be excluded from the site selection process. Although the locations of regions with Quaternary volcanism are reasonably well known in Germany, forecasting potential igneous activity at intraplate volcanic fields is challenging, as many processes and their interactions control the spatial distribution of volcanic centers. Here, a semi-quantitative, multi-criteria approach is proposed for a regional evaluation of the relative potential of future igneous activity in Germany. A variety of geoscientific indicators are used, including seismic anomalies in Earth’s mantle, gravity data, tectonic activity, sutures, ground motion, earthquakes, mantle degassing centers, and geochronological data of volcanic rocks. The indicators describe the sequence of processes from potential melt generation in Earth’s mantle, through ascent and accumulation of melt within the lithosphere, to eruption at Earth’s surface. In total, 15 out of 30 proposed geoscientific indicators are selected and quantified using 20 total assigned parameters. Defined threshold values are used to spatially delimit relevant parameter properties to focus on areas with higher potential of future magmatic activity. To consider uncertainties of parameters and their underlying processes, which are usually more spatially extensive below ground, buffer zones are defined in which values of relevance decrease with increasing distance from the initial lateral shape of a parameter. Normalized parameters are combined into an index, whose spatial value distribution is used to differentiate the relative potential of future igneous activity (within the next 1 m.y.). The sensitivity of the results is shown by varying the weighting factors for the relevant parameters in country-wide index maps. Thereby, profiles illustrate the distribution of the resulting index values and respective index fractions of various parameters. Different index maps for the relative potential of future igneous activity are presented and can be used for hazard assessments.

Professional Paper↗
USGS2025

Reservoir thermal energy storage pre-assessment for the United States

Storing thermal energy underground for later use in electricity production or direct-use heating/cooling is a promising, viable, and economical green energy option. Reservoir thermal energy storage (RTES) is one such option, which stores energy in underutilized permeable strata with low ambient groundwater flow rates and more geochemically evolved (e.g. brackish/saline) waters relative to overlying principal aquifer systems. The U.S. Geological Survey has begun assessing RTES potential nationally by focusing on five generalized geologic regions (Basin and Range, Coastal Plain, Illinois Basin, Michigan Basin, Pacific Northwest) across the United States. Hydrogeologic reservoir models are developed for the following eight metropolitan area cities within those regions to evaluate RTES performance across different climates and subsurface conditions: Albuquerque, New Mexico; Charleston, South Carolina; Chicago and Decatur, Illinois; Lansing, Michigan; Memphis, Tennessee; Phoenix, Arizona; and Portland, Oregon. Evaluated metrics include estimated required well spacing, thermal storage capacity, and thermal recovery efficiency through time. Also considered for each reservoir are potential complicating factors, including reservoir depth, thermally driven free convection, and groundwater salinity. This work focuses on direct-use cooling because the need for cooling modern office buildings greatly exceeds that for heating in most parts of the country (Falta and others, 2016); however, the evaluated metrics are also relevant to heating and electricity applications. Results indicate that favorable RTES conditions exist in each region, with the Coastal Plain and Basin and Range being especially favorable for thermal storage capacity, while the Pacific Northwest and Michigan Basin excel at energy recovery for the evaluated cooling application. The results underscore the utility of developing maps of thermal storage capacity, subsurface temperature models, and volumetric estimates of thermal storage capacity to serve as key RTES resource classification standards. Overall, this pre-assessment provides a basic understanding of RTES potential in several cities and geologic regions throughout the country and will aid ongoing thermal energy storage assessment efforts.

Arizona, Illinois, Michigan, New Mexico, Oregon, S↗
USGS2025

Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity

Since the vast majority of carbon dioxide (CO 2 ) storage resources in the United States are in deep saline aquifers, optimizing the use of these saline storage resources could be crucial for efficient development of geologic CO 2 storage (GCS) resources and basin- or larger-scale deployment of GCS in the country. Maximum CO 2 injection rates can be enhanced by extracting brine from the CO 2 storage unit. However, disposal of the extracted brine is both a technological and economic challenge. The lowest-cost option would likely be reinjection of the extracted brine into another formation above or below the CO 2 storage unit. Therefore, it is important to estimate brine injectivity as it will constrain the potential to increase CO 2 injectivity at an injection site that has access to multiple geologic storage units where either CO 2 or brine can be injected. Using a simulation-optimization framework, coupled with a non-isothermal, multiphase CO 2 -water-salt equation-of-state module, we developed a computationally efficient method for evaluating optimization of simultaneous CO 2 injection, brine extraction, and brine (re)injection at hypothetical injection sites deployed across a geologic basin. The Illinois basin is ideal for testing our methodology because it contains multiple geologic storage units with seals in between them to isolate injection of CO 2 in one unit from interfering with the injection of either brine or CO 2 in another unit above or below it. In addition, we investigated the relative effects of variation in key geologic parameters as well as two reservoir structures (hydrogeologic heterogeneity/anisotropy and homogeneity/isotropy) on CO 2 injectivities and enhancement of CO 2 injectivity through extracting brine. Results suggest that permeability, depth, and especially thickness of the storage unit could be the most influential parameters determining CO 2 injectivity. They also suggest that only injecting CO 2 into the storage unit with the greatest injectivity, enhancing that unit’s injectivity by extracting brine, and disposing of the produced brine in other suitable units could maximize total CO 2 injectivity in limited regions of the basin. At the majority of simulated injection sites, however, we found that injecting CO 2 into all of the accessible and suitable storage units was more likely to maximize the CO 2 storage resource.

Illinois, Kentucky, Indiana↗
USGS2024

Three-dimensional hydrogeologic framework model of the Russian River watershed, California

The Russian River watershed is in northern Sonoma County and southern Mendocino County, California, in the northern part of the California Coast Ranges. The Russian River serves as a supply for agricultural irrigation and for municipal, domestic, and commercial uses. Through a cooperative agreement with the California State Water Resources Control Board and Sonoma County Water Agency, the U.S. Geological Survey has completed studies to better understand the hydrogeologic system and develop numerical hydrologic modeling tools to evaluate and aid in managing groundwater resources. This report focuses on the development of a digital three-dimensional hydrogeologic framework model of the Russian River watershed for use in groundwater resource assessment and numerical models. The digital three-dimensional hydrogeologic framework model of the Russian River watershed portrays the altitude, thickness, and extent of five hydrogeologic units. These five hydrogeologic units include (1) a basement unit, (2) the Sonoma Volcanics, (3) a consolidated sedimentary rock unit, (4) an unconsolidated sediment unit, and (5) channel alluvium. Model input data were compiled from published geologic maps, interpreted well data, and a model of the top of basement derived from gravity data. These data were used to construct surfaces that represent the upper and lower subsurface boundaries of each hydrogeologic unit. Top surfaces were created for the five hydrogeologic units and then stacked in three dimensions to create a solid-volume digital model. The digital three-dimensional hydrogeologic framework model described in this report and the corresponding data represent the generalized geometry of the subsurface geologic units; the model reproduces the input geologic data with reasonable accuracy and is consistent with previously published subsurface conceptualizations of the region. The model indicates the overall geometry of the basement within the watershed and the spatial extent, altitude, and thickness of the basin-filling units. The hydrogeologic framework model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.

California↗
USGS1984

Techniques for estimating magnitude and frequency of floods on streams in Indiana

Equations are presented for estimating the magnitude and frequency of floods at ungaged sites on unregulated and nonurban streams in Indiana. The equations were developed by multiple-regression, analysis of basin characteristics and peak-flow statistical data from 242 gaged locations in Indiana, Ohio, and Illinois. The State of Indiana was divided into seven areas on the basis of the regression analysis. A set of equations for estimating peak discharges with recurrence intervals of 2, IO, 25, 50, and 100 years was developed for each area. Significant basin characteristics in the equations are drainage area, channel length, channel slope, mean annual precipitation, storage, precipitation intensity, and a runoff coefficient. Standard errors of estimate for the equations range from 24 to 45 percent. Methods are also presented for estimating flood magnitude and frequency at sites on gaged streams. Flood-frequency data based on observed peaks are given for 270 gaged locations. Twenty of these are on regulated streams, and six are on urban streams. Basin characteristics are also included car 245 of the gaged locations on unregulated and nonurban streams. No techniques are given for estimating flood magnitude and frequency at ungaged sites on regulated or urban streams. A rainfall-runoff model was tlsed to synthesize long-term peak data at 11 gaged locations on small streams. Flood-frequency curves developed from the long-term synthetic data were combined with curves based on short-term observed data to provide weighted estimates of flood magnitude and frequency at the rainfall-runoff stations.

Indiana↗
USGS2025

Climate-driven sulfate export in alpine watersheds may stimulate methylmercury production

Climate change is increasing sulfate export and changing wetland extent in mountain regions. These changes may increase microbially mediated production of the neurotoxic substance methylmercury due to enhanced sulfate metabolism in mountain environments. Here, we assess methylmercury concentrations and formation rates across high-elevation wetlands in the Colorado Rocky Mountains. We also investigate sulfate controls on methylmercury production within subalpine peatlands by amending soils with sulfate to mimic increased stream export of sulfate from the alpine zone and measuring methylmercury formation rates for different sulfate treatments. We found that subalpine peatlands have statistically significant higher methylmercury concentrations and formation rates compared to alpine, mineral-soil wetlands. Methylmercury production in subalpine peatlands also increased significantly ( p < 0.05) following sulfate additions; the highest rates occurred in sediments with intermediate extractable sulfate concentrations (∼0.60–1.4 mg sulfate g −1 dry soil). Our study is the first to identify soil sulfate-related thresholds for methylmercury production and sulfate-limitation of methylmercury production in subalpine peatlands. These findings highlight important linkages between climate-driven mineral weathering and mercury cycling in mountain regions globally.

Colorado↗
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↗
USGS2025

Structural analysis of brittle-plastic shear zones in the Sangre de Cristo Range, southern Colorado USA: Superposition of Rio Grande rift extension on Laramide contraction

The Sangre de Cristo Range in southern Colorado exposes some of the deepest Cenozoic structural levels in the Rocky Mountain region, including mylonitic shear zones associated with both the Laramide orogeny and Rio Grande rift. We investigated the relation between Laramide contraction and Rio Grande rift extension with detailed geologic mapping, kinematic analysis, and geochronometry in a 50 km 2 area centered on the Independence Mine shear zone (IMSZ). The 15−100-m-thick IMSZ is one of several shallowly to moderately (∼45° ± 20°) W-SW−dipping brittle-plastic shear zones along the western flank of the range. These shear zones display microstructural evidence of initiation as top-NE contractional mylonite zones, consistent with regional Laramide kinematics, which have been pervasively overprinted by shear fabrics indicating top-SW extensional reactivation. Both top-NE and top-SW shear fabrics involve cataclasis and quartz dislocation creep, although top-SW shear is more commonly localized along phyllosilicate-lined shear bands. Shear zones are hosted predominately within Proterozoic gneiss, and contain abundant chlorite and white mica derived from alteration of hornblende and feldspar, which indicates that weakening driven by fluid reactions played an important role in localizing strain. Extensional overprinting appears to be most pervasive along more steeply dipping portions of shear zones and where secondary phyllosilicates form an interconnected weak phase, which suggests that reactivation was primarily controlled by geometry and rheological contrasts inherited from contraction. One top-SW shear zone adjacent to the IMSZ cuts a late Oligocene gabbro stock, and monazite grains synkinematic with top-SW shear in the IMSZ yielded late Oligocene to Early Miocene U-Th-Pb dates that correspond with initiation of the Rio Grande rift. Reactivation of weak reverse faults may represent an important structural control during initial extension in the middle crust, prior to slip along the high-angle Sangre de Cristo normal fault system.

Colorado↗
USGS2025

Do Graviquakes exist?

The “Graviquake” model, proposed in 2015 as an alternative to the elastic dislocation model, posits that normal faults are passive features dominated by coseismic gravitational collapse into a dilated crustal wedge, and that normal faulting is fundamentally distinct from strike‐slip and reverse faulting. Developed using finite‐element modeling before the 2016 central Apennines earthquake sequence, the model was revamped based on interpreted Differential Interferometric Synthetic Aperture Radar data from these events and used as evidence for a gravitational collapse episode. However, this interpretation relies on miscalculated elevation changes and is not corroborated by independent geophysical and seismological observations. Our analysis exposes fundamental flaws in the Graviquake model. By assuming that faults are passive players, it underrepresents the dynamic role of strain accumulation and release in rocks adjacent to faults. The hypothesized rapid expulsion of overpressurized fluids appears inconsistent with observed diffusion rates and lacks supporting seismological evidence. Part of the uplifted–subsided volume imbalance is likely an artifact arising from data processing, and in part is a transient effect due to the delayed response of the lower crust. Moment tensor analyses detect no isotropic components indicative of gravitational collapse, and observed ground motion and stress‐drop levels remain fully consistent with elastic dislocation theory. In addition, finite‐element modeling of normal faulting replicates observed surface deformation without invoking a collapsing wedge. The Graviquake model proposes a representation of normal‐faulting mechanics that differs significantly from established models and observations. Gravity does play a role in normal faulting, but the elastic dislocation theory remains the definitive framework of fault mechanics. Reinterpreting the 2016 earthquakes as a cascade of gravitational episodes, based on incorrect data processing and modeling, fails to substantiate the Graviquake hypothesis. Persistence in advocating this model could mislead seismic hazard assessment and undermine our understanding of normal faulting.

Bulletin of the Seismological Society of America↗