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Results for “Arizona Geological Society Digest”

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

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USGS2025

Low-sulfidation epithermal deposits of the central Basin and Range Province, USA

The Basin and Range Province is host to many important low-sulfidation epithermal deposits. Within this broad zone of extension, epithermal deposits are hosted by specific areas of Miocene and younger bimodal volcanism. In northern Nevada, rifting and related volcanic activity occurred in response to thermal bulging during the development of the Yellowstone hotspot. The Colorado River Extensional Corridor in southern Nevada, adjoining eastern California and northwestern Arizona, is a major zone of Miocene crustal extension formed during the transformation of the western margin of North America from a convergent to a transform plate boundary. The style of mineralization in the low-sulfidation epithermal deposits in these areas is strongly controlled by the nature of the volcanic successions. Highgrade, low-tonnage deposits are commonly found in flow-dominated volcanic successions where ore deposition occurred through short-lived periods of fluid flashing. In contrast, low-grade, large-tonnage deposits are more commonly located in clastic-dominated successions where fluid infiltration of the permeable hosts and cooling predominated.

Arizona, California, Nevada, Oregon↗
USGS2026

Characterizing precariously balanced rocks (PBRs) in the eastern United States for estimating maximum past earthquake ground motions

Fragile geologic features (FGFs) can be used to estimate an upper bound to the strength of earthquake ground shaking in the past thousands to tens of thousands of years. FGFs could be especially useful in the eastern United States, where few active faults are available for paleoseismic studies and where low seismic attenuation means that an earthquake could damage FGFs at large distances. This article describes a pilot study of one form of FGF, precariously balanced rocks (PBRs), in the Blue Ridge of Virginia, ∼160 km from the central Virginia seismic zone (CVSZ) and ∼100 km from Virginia’s Giles County seismic zone (GCSZ). The main goal is to develop and refine methods for studying PBRs in the eastern United States. Photogrammetric 3D models of the rocks were used to locate their centers of mass and delineate their basal contacts, with the latter corroborated by wrapping a wire around the bases to verify the circumferences. Relations between hill geometry and amplification were used to estimate topographic amplification. Seismometers on the PBRs provided the frequencies, amplitudes, and directions of rocking after giving the rocks gentle pushes. The levels of ground shaking likely to topple the rocks were compared with the median hazard curves from the U.S. Geological Survey’s National Seismic Hazard Model and were used to map magnitudes of earthquakes in the nearby region likely to topple the rocks. Results indicate that an M w ≥ 7.5 earthquake is needed in the CVSZ or near the 2020 Sparta, North Carolina, earthquake to topple the two most fragile PBRs and that an earthquake of ~ M w 7–7.5 in the GCSZ is needed. The fragilities and estimated ages of the PBRs (20–40 ka) are thus consistent with the absence of such events in the historical record in the nearby region.

eastern United States↗
USGS2025

Seismic response of rock towers at the Trona Pinnacles (U.S.A.) to the 2019 Ridgecrest earthquake sequence: Theory, observations, and models

We analyze the seismic response of a class of fragile geologic features (FGFs), referred to as rock towers (RTs) at the Trona Pinnacles, a group of RTs in southern California that suffered strong shaking during the 2019 Ridgecrest earthquake sequence. FGFs, including RTs, may provide maximum constraints on past earthquake shaking intensity, and thereby support probabilistic seismic hazard assessments (PSHAs). In a rare case study, we explore the hypothesis that RT structural integrity is time dependent, as damage accumulates progressively. We develop finite‐element method (FEM) models of the RTs using photogrammetric shape models. We validate the models by comparing numerical simulations of their response to broadband ground shaking with low‐intensity seismic recordings obtained at the Pinnacles. Results of our simulations are in good agreement with the seismic recordings of actual earthquake aftershocks. We next use the results of the FEM models to analyze the response and evolution of RTs. Our analyses elucidate the influence of geometry over their seismic response, providing a rationale that may explain the rarity of slender RTs at Trona: high‐aspect‐ratio structures that respond in bending develop detrimental tensile stresses that crack the rock, whereas low‐aspect‐ratio ones’ response also includes shearing, which does not compromise material integrity as much as tension. Field measurements with a rebound hammer support this finding, suggesting that the material around the base of slender rocks has been weakened relative to other parts of the RT. We also study how to define simplified mechanical models (“archetypes”) to predict the natural frequencies of RTs. Results from our work illuminate the fundamental mechanisms of seismic response and progressive failure of RTs, and open new avenues of research to potentially incorporate these geologic features as long‐return period constraints on PSHA, in ways analogous to those of the widely used precariously balanced rocks.

California↗
USGS2025

Scoping decision-maker needs and science availability to support regional natural capital accounting in the U.S. Colorado River Basin

Natural capital accounting has the potential to yield important policy insights at multiple scales, but there remains a disconnect between regional-scale natural capital accounts and their use for informing policy. In this paper, we propose a roadmap that could lead to the creation of policy-relevant regional accounts, with steps split across an initial scoping phase and a subsequent development phase. We demonstrate the scoping steps in action with an application to the Colorado River Basin (“Basin”), a large watershed in the southwestern United States (U.S.) that has faced aridification and substantial high-profile tradeoffs around the use of its water and other natural resources. Drawing on prior U.S. Geological Survey science co-production efforts, we conducted a series of eight discussion sessions with 41 scientists and science representatives whose work is relevant to Basin water, riparian and riverine ecosystems, upland ecosystems and energy and minerals. We summarise participants' thoughts on key topics and economic linkages, their insights and questions of interest and their recommendations on existing scientific data sources and gaps. We evaluate the suitability of the available data for construction of System of Environmental-Economic Accounting (SEEA) Central Framework and SEEA Ecosystem Accounting accounts, including those for land, water, forests, energy and minerals and ecosystems (covering extent, condition and ecosystem services). We present a series of lessons learned during the scoping phase, as well as lessons that could be relevant for future practitioners engaging in the development phase. The information can help guide the development of timely and relevant regional-scale environmental-economic accounts in the U.S. and beyond.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2025

Do bighorn sheep use desert tortoise burrow spoil piles as mineral licks in southern California?

In a previous study, bighorn sheep ( Ovis canadensis ) were periodically photographed by trail cameras when they visited desert tortoise ( Gopherus agassizii ) burrows in the San Bernardino Mountains near Palm Springs, California, USA. The authors suggested that bighorn sheep may utilize the excavated spoil material from burrows as a mineral lick. To test that supposition, we collected soil samples from the spoil piles and undisturbed surface soil up to 1 m away at two desert tortoise study sites with bighorn sheep at the aforementioned site and another nearby site. We hypothesized that sodium concentrations would be greater in spoil than in nearby surface soil samples. Common major cations were quantified in soil samples using inductively coupled plasma-mass spectrometry following microwave-assisted digestion to solubilize the fraction of elements that could become biologically or environmentally available. Mean sodium concentrations were greater in burrow spoil samples than in undisturbed soil samples at both sites, likely due to aqueous leaching of sodium from surface to subsurface soil horizons. Although we did not collect evidence of geophagy by bighorn sheep, the behavior is well known. However, trail camera photographs of bighorn sheep with their head next to the entrance of tortoise burrows suggests that they may periodically utilize sodium and other elements brought to the surface by desert tortoises that are otherwise unavailable to bighorn sheep on the surface.

California↗
USGS2026

Final project peport for “Mapping riparian vegetation response to climate change on the San Carlos Apache Reservation and Upper Gila River watershed to inform restoration priorities: 1935 to present – Phase 2: Focus on tamarisk vegetation”

Riparian ecosystems play a critical role in supporting wildlife habitats, maintaining water quality, and sustaining ecological resilience in arid landscapes. In the Upper Gila River level-4 Hydrologic Unit Code (HUC-4; Identification Number – 1504) watershed of Arizona and New Mexico, and across areas of the San Carlos Apache Tribe of the San Carlos Apache Reservation (hereafter, Tribe/Tribal – entity; or Reservation - place), riparian ecosystems have been substantially altered by the widespread expansion of tamarisk ( Tamarix spp.), an invasive and non-native riparian species. Tamarisk has high water use and increased flammability, making it a growing concern as droughts intensify across the southwestern United States (U.S.). Recent research indicates that tamarisk is increasingly stressed under prolonged drought conditions, which can elevate wildfire risk and further degrade riparian habitat. In response, the U.S. Geological Survey (USGS) Western Geographic Science Center, in collaboration with the Tribe, developed remote sensing–based tools to map riparian vegetation composition and monitor vegetation condition over time. These tools enable accurate identification of tamarisk extent, detection of vegetation stress, and comparison with native species such as cottonwood and willow. This information directly supports restoration and management actions, including targeted tamarisk removal, protection of endangered species habitat, and prioritization of areas for native vegetation recovery. The tools also provide insight into how riparian vegetation responds to changing climate and hydrologic conditions, strengthening long-term planning for riparian forest management. Findings from this work demonstrate that riparian vegetation responses vary across river systems, indicating differences in plant composition and hydro-climatic conditions. Tamarisk on both the Gila and San Carlos Rivers generally exhibit greater declines in greenness in response to higher temperature as well as lower precipitation and river flow, while cottonwood ( Populus fremontii ) and willow (Salix spp.) are particularly sensitive to changes in discharge along the San Carlos River and respond more directly to both high and low flows, with more moderate responses to precipitation and temperature. By providing actionable, science-based information, this research supports climate adaptation planning, wildfire risk reduction, and improved riparian ecosystem health, with benefits that extend beyond the Reservation to regional water and wildlife conservation efforts.

Arizona, New Mexico↗
USGS2025

A scientific vision and roadmap for earthquake rupture forecast developments, a USGS perspective

We articulate a scientific vision and roadmap for the development of improved Earthquake Rupture Forecast models, which are one of the two main modeling components used in modern seismic hazard and risk analysis. One primary future objective is to provide fully time-dependent models that include both elastic rebound and spatiotemporal clustering nationwide, which is particularly important for shorter-term hazard and risk considerations (e.g., earthquake insurance products). We also discuss the importance and perennial challenges associated with quantifying epistemic uncertainties, including those associated with deformation-model slip rates, un-quantified sampling errors with respect to off-fault seismicity, and any spatial covariances. The need for more physics-based approaches is also emphasized, as is the benefit of adding model valuation (quantifying usefulness) to our verification and validation protocols. Given the multidisciplinary and system-level nature of this activity, modular design is critical. Future updates will also draw from best-available science by both the United States Geological Survey and the external community. The primary goal of this paper is to highlight plans that guide research and facilitate community engagement with model development, especially with respect to lowering the entry barrier for early career scientists and engineers. The paper is written so readers can focus on the sections that interest them most (see table of contents), with the Introduction and Discussion providing a stand-alone overview and summary.

Bulletin of the Seismological Society of America↗
USGS2025

Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study

We illustrate the systematic difference between moment magnitude and local magnitude caused by underlying earthquake source physics, using seismic moments submitted to the Statewide California Earthquake Center/United States Geological Survey Community Stress Drop Validation Study 2019 Ridgecrest data set. While the relationship between seismic moment and moment magnitude ( M or M w ) of log 10 ( M 0 ) ~ 1.5* M is uniformly valid for all earthquake sizes by definition (Hanks and Kanamori, 1979), the relationship between local magnitude M L and moment is itself magnitude dependent. For moderate events, ~3< M < ~6, M and M L are coincident; for earthquakes smaller than ~3, M L ~ 1.0 log 10 M 0 (Hanks and Boore, 1984). This is a physical consequence of the corner frequency fc becoming larger than the upper frequency of observation and implies that M L and M differ systematically by a factor of 1.5 for these small events. While this idea is not new, we propose a new, continuous relationship between local magnitude and moment, for magnitudes 2 to 6 which extrapolates to smaller and larger magnitudes, applicable to southern California specific to the Ridgecrest region. We make use of the plethora of seismic moments as submitted by many participants of the Community Stress Drop study, compared to the Southern California Seismic Network (SCSN) catalog magnitudes. Overall, the seismic moments in the Community Study recover moment magnitude well, so we use our new M L - M 0 to convert M L to M , refining the SCSN operational M Lr scale. This systematic difference of 50% in slope between local and moment magnitude at small magnitudes has implications for spectral stress drop estimates, earthquake ground motion modeling, as well as other magnitude scales and earthquake occurrence statistics.

California↗
USGS2024

Predicting hydrothermal reservoir depth from chemical geothermometers using a three-dimensional temperature model in the Great Basin, USA

Recent work in the Great Basin region of the western United States has made it possible to predict the depth of hydrothermal reservoirs (i.e., the depth at which heat is accumulated prior to ascent via hydrothermal upflow) identified through geochemistry and to contextualize the spatial patterns of these reservoir depths. Chemical geothermometers use the chemical and mineral constituents of hydrothermal fluids to predict the temperature at which fluids equilibrated with the host rocks at depth. Assuming that most of the Great Basin is dominated by conductive conditions until a vertically connected hydrothermal flow path is created (e.g., by faulting), geothermometers reflect the chemical and thermal conditions at the depth interval that the fluid has conductively equilibrated over a long period before a vertical conduit allows convective upflow. By pairing geothermometer temperature estimates with our recent three-dimensional temperature model of conductive heat flow in the Great Basin, we estimate the corresponding reservoir depths and construct a map of circulation depths. The predicted depths from geothermometers have spatial patterns across the Great Basin that relate to patterns seen in other geologic and geophysical data. Deeper springs generally occur disproportionately in areas with higher strain rates and in basins. We posit that current elevated strain rates reflect patterns of historic deformation where ongoing tectonic activity maintains permeable pathways to deeper reservoirs, some of which are estimated to exceed 6 km depth. Basins, as expected, contain a disproportionate number of these deep systems, because the underlying aquifers are closer to the surface in basins, thus requiring less water pressure to reach the surface than in mountain ranges. Most springs estimated to have their source in a deep reservoir occur at places known to host a hydrothermal system; these refined depth estimates of the source reservoir can help to better constrain the source depth for many known hydrothermal systems across the Great Basin.

Arizona, California, Idaho, Nevada, Oregon, Utah↗
USGS2025

Combining multisite tsunami and deformation modeling to constrain slip distributions for the 1700 C.E. Cascadia earthquake

A major earthquake ruptured the Cascadia subduction zone (CSZ) on 26 January 1700. Key paleoseismic evidence associated with this event include tsunami deposits, stratigraphic evidence of coastal coseismic subsidence, written Japanese records of a tsunami unaccompanied by earthquake shaking, and margin‐wide turbidites found offshore and in lacustrine environments. Despite this wealth of independent clues, important details about this event remain unresolved. Dating uncertainties do not conclusively establish whether the proxies are from one earthquake or a sequence of them, and we have limited knowledge of the likely slip distributions of the event or events. Here, we use a catalog of 37,500 candidate synthetic ruptures between M w 7.8 and 9.2 and simulate their resulting coseismic deformation and tsunami inundation. Each model is then compared against estimated Japan tsunami arrivals, regional coastal subsidence records, and local paleotsunami deposits mapped at six different coastal marshes and one coastal lake along the CSZ. We find that seven full‐margin ruptures with a median magnitude of M w 9.1 satisfy all three constraints. We favor one M w 9.11 model that best matches all site paleoseismic observations and suggests that the Cascadia megathrust slipped up to ∼30 m and must have shallow geodetic coupling. We also find that some sequences composed of three or four ruptures can still satisfy the observations, yet no sequences of two ruptures can. Sequences are differentiated into three groups based on whether they contain a mainshock rupture located in the south (>44° N) or further north. All sequences contain unruptured portions of the megathrust and most contain mainshocks with peak slip above 40 m. The fit of the geologic evidence from sequences is poor in comparison to single‐event models. Therefore, sequences are generally less favored compared to full‐margin events.

British Columbia, California, Oregon, Washington↗
USGS2024

Precariously balanced rocks in northern New York and Vermont, U.S.A.: Ground-motion constraints and implications for fault sources

Precariously balanced rocks (PBRs) and other fragile geologic features have the potential to constrain the maximum intensity of earthquake ground shaking over millennia. Such constraints may be particularly useful in the eastern United States (U.S.), where few earthquake‐source faults are reliably identified, and moderate earthquakes can be felt at great distances due to low seismic attenuation. We describe five PBRs in northern New York and Vermont—a region of elevated seismic hazard associated with historical seismicity. These boulders appear to be among the most fragile PBRs in the region, based on reports from hobbyists. The PBRs are glacial erratics, best evidenced by glacial striations on bedrock pedestals. The pedestals themselves are locally high knobs, often situated on regionally high topography; this setting limits soil development and indicates that any outwash deposits were likely ephemeral. As a result, PBR ages can be reliably established by the retreat of the last continental ice sheet, ∼15–13 ka. To quantify the fragility of the PBRs, we surveyed them with ground‐based light detection and ranging and calculated geometric parameters from the point clouds, field observations, and seismic responses. Preliminary validation of the 2023 time‐independent U.S. National Seismic Hazard Model (NSHM) shows that the existence of PBRs is generally consistent with the median site‐specific hazard curves. Only the Blue Ridge Road site suggests a modest reduction in hazard. To visualize the ensemble of data, we mapped the minimum permissible distance to potential source faults around each PBR site as a function of source magnitude by using the ground‐motion models from the 2023 NSHM. Viewed in this manner, our data are consistent with potential M ∼6.5 earthquake‐source faults in many parts of the Lake Champlain Valley and northern Adirondack Mountains. Our work illustrates a potential pathway for better constraining earthquake‐source faults in regions of cryptic faults.

Bulletin of the Seismological Society of America↗
USGS2025

Characterizing Meteor Crater impact melts through geochemistry and textural analysis

The U.S. Geological Survey Astrogeology Science Center houses the Meteor Crater sample collection, an assemblage of over 2,500 meters of cuttings from 161 drill holes into Meteor Crater’s rim, flanks, and ejecta blanket. We have utilized this unique collection to study the composition and spatial distribution of impact-generated materials from within the ejecta blanket. Meteor Crater has historically been known to have generated only a relatively small amount of impact melt compared to other terrestrial craters of similar size. A detailed compositional and textural dataset of impact-derived melts from this impact can therefore be a useful asset in improving our understanding of crater formation, and in particular impact melt formation. We have characterized 42 impact-melt particles from Meteor Crater using a scanning electron microscope and an electron microprobe for textural and compositional analysis. We analyzed samples from six drill holes in the ejecta blanket, situated to the northwest, southeast, south, and southwest of the crater (ejecta northeast of the crater is devoid of impact melts). Impact melts were collected from drill cuttings at various depths within the ejecta blanket, ranging from a few centimeters below the surface down to ~6.5 meters. Backscattered electron (BSE) images were acquired for each analyzed impact-melt particle. To characterize the various textures and phases present in each impact melt, we also took many detailed BSE images. Our geochemical analyses include full spectral profiles using energy dispersive X-ray spectrometry and well-calibrated wavelength dispersive spectrometry for a number of phases, including minerals (olivine, pyroxene, and so on), pristine glass, and metallic inclusions. The full dataset is available in ScienceBase as a data release (Gullikson and others, 2024), accessible at https://doi.org/10.5066/P9OGAJ8P . Our goal for this Open-File Report is to provide a summary of this immense dataset, details on data collection, descriptions of the different phases observed within impact-melt particles (both geochemically and texturally), and observable trends.

Arizona↗
USGS2026

The role of groundwater in contributing to surface water salinization in the Upper Colorado River Basin

Freshwater salinization impacts the availability of water for human use and ecosystem needs worldwide. It has been estimated that total dissolved solids (TDS) in the Colorado River Basin cause $350 million/year in damages and substantial resources are devoted to reducing TDS loading to streams. This study describes the development and application of coupled watershed models that enable TDS source tracking through the subsurface and across the landscape at a seasonal timestep for 35 years in the Upper Colorado River Basin. Results indicate that, on average, 75% of TDS loading to streams originates as baseflow, and 50% of loading is lagged in delivery by longer than one season. Snowmelt was identified as a dominant process controlling the transport of lagged TDS to streams. This approach informs when and where TDS mitigation efforts may be effective in a watershed that serves as a critical water supply for the southwestern United States.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California↗
USGS2025

Update of the 2008 provisional Enhanced Geothermal Systems (EGS) assessment for the Great Basin, USA

In response to the Energy Act of 2020, the U.S. Geological Survey (USGS) is updating the Enhanced Geothermal Systems (EGS) resource assessment for the Great Basin, USA. The previous 2008 provisional assessment estimated how much electricity could be generated from EGS resources of the western United States using models of electric-grade heat, models of heat extraction over time, and estimates of how much rock might be stimulated to produce viable amounts of heat. Herein, a similar conceptual strategy is applied, using updated models of heat extraction as a function of fracture spacing and well distance. Previously used reservoir heat delivery models are updated to have a dependence on fracture and well spacing, potentially improving future estimates of EGS resources as ongoing research provides a better understanding about the success of reservoir stimulation as a function of geology and location. For a range of well distances (250-1000 m) and fracture spacings (1-50 m), heat extraction efficiency ranges from 25-62%, demonstrating the importance of accounting for the most likely results of proven viable fracturing technologies. Although fracturing is important, the biggest uncertainty by far in estimating the EGS resource for the Great Basin is estimating which geologic units at what depths can be stimulated sufficiently to produce geothermal energy economically and efficiently. Uncertainties in these factors yield estimates that range over two orders of magnitude with an upper limit of ~174 terawatts-thermal (TWth) produced for 30 years from the upper 7 km of the crust. This upper limit would require significant technological advances to access most of the electric-grade resource across the Great Basin. Assuming that 1% of this estimate will be accessible in the next few decades gives a resource estimate similar to that made in the 2008 provisional assessment. These estimated EGS heat extraction rates far exceed ( greater than 100x) the natural geothermal heat production rate, thus geothermal electricity production at these rates might not be sustainable unless heat is also recharged from other sources (e.g., excess solar energy when supply exceeds demand). In addition to assessment maps and cumulative estimates, the new models of fractured reservoirs developed herein can be used to estimate steady power production given a set of fractures and well spacing, and estimates can be made for setback distances to ensure no thermal interference with nearby powerplants.

Arizona, California, Idaho, Nevada, Oregon, Utah↗
USGS2026

Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon

The timing and mechanism of the integration of the Colorado River and incision of the Grand Canyon remain among geology’s enduring controversies. A key question is the configuration of the upper Colorado River watershed between 11 and 6 million years ago. In this study, we present new evidence from zircon uranium-lead geochronology for the arrival of distinctive Colorado–Green River sediment in the Bidahochi basin by 6.6 million years ago derived from the Browns Park Formation. This is coeval with an order-of-magnitude increase in depositional rate, an increase in carbonate strontium isotope ( 87 Sr/ 86 Sr) ratios, the appearance of large fish species characteristic of fast-flowing waters, and other sedimentological changes. This evidence is consistent with the Colorado River supplying water and sediment to the Bidahochi basin before spillover integration of the river through the Grand Canyon.

Arizona, Nevada, Utah↗
USGS2024

The impact of source time function complexity on stress drop estimates

Earthquake stress drop—a key parameter for describing the energetics of earthquake rupture—can be estimated in several different, but theoretically equivalent, ways. However, independent estimates for the same earthquakes sometimes differ significantly. We find that earthquake source complexity plays a significant role in why theoretically (for simple rupture models) equivalent methods produce different estimates. We apply time‐ and frequency‐domain methods to estimate stress drops for real earthquakes in the SCARDEC (Seismic source ChAracteristics Retrieved from DEConvolving teleseismic body waves, Vallée and Douet, 2016 ) source time function (STF) database and analyze how rupture complexity drives stress‐drop estimate discrepancies. Specifically, we identify two complexity metrics—Brune relative energy (BRE) and spectral decay—that parameterize an earthquake’s complexity relative to the standard Brune model and strongly correlate with the estimate discrepancies. We find that the observed systematic magnitude–stress‐drop trends may reflect underlying changes in STF complexity, not necessarily trends in actual stress drop. Both the decay and BRE parameters vary systematically with magnitude, but whether this magnitude–complexity relationship is real remains unresolved.

Bulletin of the Seismological Society of America↗
USGS2025

Capturing the uncertainty of seismicity observations in earthquake rate estimates: Implications for probabilistic seismic hazard analysis and the USGS National Seismic Hazard Model

The rate of earthquakes in a region is a fundamental input to Probabilistic Seismic Hazard Analysis. We present a Monte Carlo method for computing that rate from seismicity catalogs while including a range of data and analysis uncertainties. This method is applied to regions for which the b value is assumed to be spatially invariant. Each region is broken down into epochs for which each epoch is estimated to have a uniform magnitude of completeness ( ⁠⁠ M c ). The distribution of earthquake rates for M ≥ M c is determined for each epoch by considering the Poisson likelihood of rates given the number of observed earthquakes with M ≥ M c ⁠ . We use a Monte Carlo process to include the uncertainty in b , ⁠ M c , and individual event magnitudes. The result for each epoch is the joint distribution of the Poisson rate of earthquakes with magnitudes larger than the minimum value used to calculate hazard ( ⁠⁠ M 1 ) and the Gutenberg–Richter b values, which control the extrapolation to other magnitudes. The rate for each region is either the duration‐weighted average over the epochs or, to better capture temporal variations, we also consider mixture models. The mixture models also provide an avenue to allow temporal variations in b values. To implement this joint distribution in a logic tree, we use the mean and 95% confidence branches, each of which is parameterized with an M ≥ M 1 rate and b value. We explore different ways of defining those branches, as well as non‐Gutenberg–Richter branches, and their impact on hazard estimates. The mean hazard, but not the fractiles, is robust with respect to these choices. To illustrate these new methods, we use synthetic data and catalogs from recent U.S. Geological Survey National Seismic Hazard Models for the Central and Eastern United States and for Puerto Rico and the U.S. Virgin Islands.

central and eastern United States, Puerto Rico, U.↗