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1,688 records · Page 74Linked to original sources
USGS2026

Black rails in Baja California

Summarizing records from 1905 to 2025, we document the presence and distribution of the California black rail ( Laterallus jamaicensis coturniculus ) in northwestern México, particularly Baja California and the Colorado River Delta. This subspecies has a restricted distribution in the western U.S. and northwestern México. We found few records over the past century: sparse detections in the early 1900s and an increase in reported records after 2000. Over 120 years, we compiled 35 documented records of California black rail occurrence in Baja California with a minimum reported count of 56 rails. Our call-broadcast survey methods reconfirmed previously occupied sites and documented the species at a previously unreported site. Surveys in the Baja California portion of the Colorado River Delta yielded 20 detections across nine survey events between 2000 and 2022. In April 2003, standardized surveys detected 12 California black rails: 7 in Bahía de San Quintín, 3 in Arroyo San Telmo, and 2 in Arroyo El Rosario. Our recent survey work (2022–2025) recorded maximum monthly counts of 31 detections at Bahía de San Quintín and 15 detections at Estero de Punta Banda, the latter representing a previously undocumented location for the subspecies. These surveys also yielded the first photographic and acoustic documentation of California black rail in México. The contribution of spatial and temporal data provided by citizen science platforms increased our understanding of the subspecies’ distribution. Enforceable protection of this subspecies’ habitat is needed to safeguard its persistence.

Baja California↗
USGS2026

Repeated coral bleaching events have eroded reef accretion potential in the Florida Keys

Coral bleaching is now the primary driver of coral-reef degradation globally, threatening the persistence of coral-reef functions and the invaluable ecosystem services they support. The Florida Keys have been impacted by four severe, regional-scale coral-bleaching events, which occurred in 1997–1998, 2005, 2014–2015, and 2023. Our aim in this study was to quantify the effects of those thermal-stress events on the persistence of coral-reef structures. We leveraged long-term coral-reef monitoring data to quantify the impacts of coral bleaching on coral cover, carbonate production, and reef-accretion potential throughout the Florida Keys from 1996–2024. Our study indicates that coral bleaching drove significant declines of reef-building corals, which successively diminished regional-scale reef-accretion potential (from 1.65 ± 0.33 mm y -1 in 1996) and culminated with a regional-scale transition to net reef erosion (-0.12 ± 0.08 mm y -1 ) following the 2023 event. Coral bleaching was the primary driver of declining reef-building capacity, with the cumulative impacts of the four coral-bleaching events accounting for >75% of total declines since 1996. The 1997–1998 event alone drove ~50% of overall declines, largely due to losses of the shallow-water ecosystem engineer, Acropora palmata . More moderate impacts of thermal stress on regional reef-accretion potential in 2005 (6%) and 2014–2015 (9%) could lend some support to the hypothesis that the remaining corals were more thermally tolerant; however, the unprecedented thermal stress event in 2023 caused widespread coral-bleaching and bleaching-related mortality, and caused an additional 12% of the total decline in reef-accretion potential. Stony-coral tissue loss disease accounted for an additional 6% of the decline, with the remaining 19% unexplained. Coral bleaching has already dramatically reshaped the structure and function of coral reefs in the Florida Keys over the last three decades. With the high likelihood that thermal stress will accelerate moving forward, the persistence of Florida’s essential coral-reef functions and services is uncertain.

Florida↗
USGS2026

Rapid characterization of the 2025 Mw 8.8 Kamchatka, Russia earthquake

The 29 July 2025 M w 8.8 Kamchatka, Russia, earthquake was the sixth largest instrumentally recorded earthquake. This event was seismically well observed at regional and teleseismic distances, but publicly available near‐source data were sparse at the time of the event, presenting unique challenges for rapid source and impact characterization. The U.S. Geological Survey (USGS) National Earthquake Information Center provides global real‐time monitoring for earthquakes, including rapid response information products that estimate source characteristics, shaking, and the resulting impacts. We describe the USGS rapid response earthquake information products following the Kamchatka event and discuss their implications for ongoing hazards in the region. We describe potential improvements to our response workflows motivated by this event, including more rapid constraints on source geometries and the automated selection of fault geometries for finite‐fault inversions. The rapid response products together support the interpretation of a unilateral southwestward rupture with significant slip on the southwestern end of the rupture extent. The M w 8.8–9.0 event in 1952, which ruptured a comparable extent of the Kuril–Kamchatka subduction interface, has many similarities to the 2025 rupture. This illustrates that slip deficits may remain following great earthquakes and highlights the usefulness of comparative studies between historic and modern events.

Kuril-Kamchatka subduction zone↗
USGS1976

Diamond drilling at the Ma'milah Mine, Kingdom of Saudi Arabia

The Ma'millah gold mine is about 90 km southeast of At Ta'if at lat 21°03'N., long 41°18'E., in southwestern Saudi Arabia. The deposit, which was worked extensively by ancient miners, consists of several veins and massive lenses of quartz along a regional fault. The extensive ancient mine workings, large size of some quartz outcrops, and significant gold content of several samples indicated that subsurface exploration was warranted. Accordingly, two holes were drilled into the deposit during the interval December 1972 to February 1973. The drill findings were disappointing; the grade of vein material was found to be too low to be of economic interest and the quartz bodies were found to pinch out both along strike and downdip. The drilling program therefore was terminated. The deposit is not worth further exploration

Ma'milah Mine↗
USGS2025

Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths

Mauna Loa volcano erupts crystal-poor material at its summit and more crystal-rich material on its rift zones. Some of the more olivine-rich lava flows contain xenoliths with diverse mineralogy, including cumulate harzburgites with high-Mg# orthopyroxenes and high-Fo olivines (both > 84). Previous experimental work and thermodynamic modelling has proposed that high-Mg# orthopyroxenes only crystallize from Mauna Loa melts at high pressures (> 6 kbar, > 20 km), leading to suggestions that there is a region of sub-Moho magma storage at Mauna Loa in addition to the geophysically imaged magma reservoir at 2–5 km depth below the summit. We use melt and fluid inclusion barometry combined with thermodynamic models to further investigate this suggestion. Fluid inclusion data from harzburgites and dunitic xenoliths yield storage depths remarkably similar to those found in non-xenolithic crystals from lavas and tephras, with a clear peak at ~ 2–3 km (below the summit). Depths from melt inclusions in these xenoliths overlap with fluid inclusion pressures, ruling out the possibility of fluid inclusion re-equilibration during a period of stalling in a shallower reservoir. We examine five different thermodynamic models and find that the minimum pressure of olivine-orthopyroxene co-saturation varies by ~ 4 kbar (~ 12 km). These models also fail to predict that orthopyroxene is stable in ~ 15–80% of compositionally relevant experimental charges which grew orthopyroxene. Overall, this shows that phase stability modelling is an unreliable method of determining magma storage depth at Mauna Loa. We suggest that model discrepancies reflect a lack of experimental constraints on orthopyroxene stability at > 1200 ℃ and 0.01–5 kbar. Based on the presence of large oikocrystic orthopyroxenes completely enclosing rounded olivine chadacrysts, we suggest that these harzburgitic xenoliths formed through the reaction of intruding melts with olivine mush piles within the Mauna Loa edifice at ~ 3 km depth below the summit, with no need for a deeper storage reservoir. The predominance of pre-eruptive shallow storage means that there is more chance of detecting reservoir destabilization with geophysical monitoring techniques compared to a scenario where melts are supplied from sub-Moho reservoirs.

Hawaii↗
USGS2026

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment↗
USGS2023

Advancing subsurface investigations beyond the borehole with passive seismic horizontal-to-vertical spectral ratio and electromagnetic geophysical methods at transportation infrastructure sites in New Hampshire

The U.S. Geological Survey (USGS), in cooperation with the New Hampshire Department of Transportation (NHDOT), surveyed transportation infrastructure sites using rapidly deployable geophysical methods to assess benefits added to a comprehensive site characterization with traditional geotechnical techniques. Horizontal-to-vertical spectral-ratio (HVSR) passive-seismic and electromagnetic-induction (EMI) methods were applied at 4 sites including a roadway-stream crossing, roadway-bridge rail-trail crossing, commuter-parking expansion, and a railroad-adjacent river-cutbank slope-failure site. Additionally, ground-penetrating-radar (GPR) was used at the slope-failure site. Typically, subsurface geotechnical properties are determined from boring data; however, borings are often spaced hundreds of feet apart, potentially missing important spatial variability between boreholes. Geotechnical site characterization including geophysical surveys helped provide a more accurate characterization by using continuous or near continuous profiling. Three-component ambient noise measured with HVSR methods were used to determine resonance frequency and estimate sediment thickness. The method works when there is a strong shear-wave acoustic impedance contrast (> 2:1) between sediment and bedrock. Sediment thickness estimates from HVSR measurements were combined with boring data to make detailed maps of the bedrock surface altitude. The bulk electrical conductivity of the subsurface was indirectly measured with EMI methods and was used to identify lithologic variations, shallow bedrock, and conductive groundwater. Ground penetrating radar, which transmits pulses of electromagnetic energy into the subsurface and records the amplitude and timing of reflected signals, was used to identify bedding and changes in lithology or water content. By combining geophysical and boring data analyses, transportation projects produced more spatially comprehensive representations of geotechnical subsurface conditions than would be determined using conventional borings alone.

New Hampshire↗
USGS2025

Accurate simulation of flow through dipping aquifers with MODFLOW 6 using enhanced cell connectivity

In simulations of groundwater flow through dipping aquifers, layers of model cells are often “deformed” to follow the top and bottom elevations of the aquifers. When this approach is used in MODFLOW, adjacent cells within the same model layer are vertically offset from one another, and the standard conductance-based (two-point) formulation for flow between cells does not rigorously account for these offsets. The XT3D multi-point flow formulation in MODFLOW 6 is designed to account for geometric irregularities in the grid, including vertical offsets, and to provide accurate results for both isotropic and anisotropic groundwater flow. A recent study evaluated the performance of the standard formulation and XT3D using a simple, synthetic benchmark model of a steeply dipping aquifer. Although XT3D generally improved the accuracy of flow simulations relative to the standard formulation as expected, neither formulation produced accurate flows in cases that involved large vertical offsets. In this paper, we explain that the inability of XT3D to produce accurate flows in the steeply dipping aquifer benchmark was not due to an inherent limitation of the flow formulation, but rather to the limited cell connectivity inherent in the most commonly used discretization packages in MODFLOW 6. Furthermore, we demonstrate that XT3D is able to produce the expected accuracy when adequate cell connectivity is introduced using MODFLOW's unstructured grid type and the aquifer is discretized vertically using at least two model layers.

Groundwater↗
USGS2025

Reply to, “Comment on ‘The 1886 Charleston, South Carolina, earthquake: Relic railroad offset reveals rupture,’ by Roger Bilham and Susan E. Hough”

We welcome this opportunity to respond to Pratt et al. (2024) (hereinafter P24). Bilham and Hough (2023) proposed a “first-cut” elastic deformation model for the 1886 earthquake, a quantitative source model constrained by identified coseismic constraints. A key observation was the measurement of a lateral offset of a railroad line south of Summerville, leading to a model with predominately dextral slip and minor convergence, from which we concluded that active faulting had raised the Penholoway Marine Terrace >6 m since ∼770 ka. P24 questioned these constraints and proposed an alternative rupture model with predominantly reverse slip. This alternative model is neither consistent with coseismic constraints nor with other geophysical data. In a revised model presented here, we recognize that uplift of the Penholoway Terrace is confined to the eastern edge of the terrace, which we conclude results from active folding and tectonic transpression centered on the dextral fault that offset the railroad in 1886.

South Carolina↗
USGS2023

Hidden system identification: Basin modeling as a tool for examining sedimentary geothermal resource potential

Three-dimensional (3D) geologic and temperature models have been developed for the onshore U.S. Gulf Coast. The results from these models identify areas of moderate- to high-temperature (90°-150°C and >150°C; respectively) geothermal resources at depths <6 km. This modeling study addresses the fundamental challenge of predicting where opportune temperature and lithology coincide. Unlike traditional geothermal systems with surface expressions of hydrothermal circulation (e.g., hot springs, fumaroles, sinter), sedimentary geothermal systems (SGS) are generally hidden. Historically, simplified efforts to predict subsurface temperatures in sedimentary basins have focused on linear temperature extrapolation that does not consider the variable thermal properties of different lithologies or lithologic changes with depth (e.g., compaction, lithification). Therefore, the need to understand basin architecture and predict temperatures in 3D within SGS is paramount to identifying geothermal resources and determining economic feasibility. Basin modeling software has long been used to characterize the subsurface conditions of sedimentary basins, including temperature, in the pursuit of finding hydrocarbons. This tool can also be adapted to evaluate the potential of geothermal resources in a sedimentary basin by predicting the confluence of desirable temperatures and reservoir lithologies. In this work, PetroMod basin modeling software was used to create a regional geologic model of the onshore U.S. Gulf Coast, covering over 500,000 km 2 calibrated to temperature data from wells. Inputs include structural surfaces from commercial databases, lithology information derived from published literature, and corrected bottom-hole temperatures (BHT) from over 6,000 wells. The resulting 3D geologic model can be used to predict temperatures throughout the basin. Maps were exported showing the depth, depositional unit, and reservoir lithology at which temperatures of 90°C and 150°C were reached, revealing over 400,000 km 2 of moderate- to high-temperature resources at depths <6 km. These maps function as a first-order screening tool to identify areas where low-, moderate-, or high-grade resource potential may exist, based on temperature and if optimal reservoir lithologies or depositional units of interest are present. Depending on the success criteria of a project, the same maps can be exported for any isotherm or incorporate other 1407 Gardner and Birdwell subsurface properties. The methodology employed in this work can be applied in any sedimentary basin with available subsurface data. Further calibration incorporating other data, including pressure and porosity, can expand the utility of basin modeling for geothermal evaluations. Basin modeling is a powerful but underutilized tool for identifying prospective geothermal resources in sedimentary basins.

Conference Paper↗
USGS2024

Streamflow depletion caused by groundwater pumping: Fundamental research priorities for management-relevant science

Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.

Water Resource Research↗
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↗
USGS2026

Preface to the focus section on intraplate earthquakes

More than a half century after plate tectonics provided an overarching framework to explain earthquakes along active plate boundaries, numerous theories have been proposed to explain where, why, and how often earthquakes occur well away from active plate boundaries, but a paradigm remains elusive. Even the classification of earthquakes away from active plate boundaries as "intraplate" raises issues, with potentially important distinctions between Stable Continental Regions and more actively deforming regions including passive margins and failed rifts. Some of the largest known intraplate earthquakes themselves remain enigmatic, having occurred before the modern instrumental era. Hazard assessments are often data-limited: low fault-slip rates relative to landscape modification rates result in poor discoverability of fault sources, challenging the characterization of source zones and earthquake recurrence; the completeness and homogenization of instrumental earthquake catalogs using uncertain magnitude conversions can lead to uncertainties in earthquake recurrence; and, limited strong-motion observations for large-magnitude events at near-source distances leads to uncertainties in the selection and development of ground-motion models for seismic hazard studies. Data from recent intraplate earthquakes around the world—from the moment magnitude M 7.7 2001 Bhuj, India, earthquake 25 years ago to the 2024 M 4.8 Tewksbury, New Jersey earthquake—have yielded both new insights and new questions. The papers in this special focus discuss many of the long-standing challenges involved with intraplate earthquake investigations and provide a snapshot of the state of the art with current research to advance our understanding.

Seismological Research Letters↗
USGS2025

Groundwater-storage change in the north Phoenix aquifer, Arizona, 2020–23

The city of Phoenix, Arizona, relies primarily on surface water for municipal water supply. The city also maintains wells to withdraw groundwater, particularly in times of drought and reduced surface-water supply, and to recharge groundwater when excess surface water is available. As of 2023, withdrawals from the aquifer in the northeastern part of the city are a small volume of water, less than 3,000 acre-feet in most years. Each year a similar volume of water is recharged through injection wells. The withdrawal wells are permitted to produce in total more than 20,000 acre-feet per year; increased pumping could lead to future groundwater-storage declines. To better understand groundwater-storage change in the north Phoenix aquifer, a repeat microgravity monitoring network was established in 2020. Measurements of changes in Earth’s gravity provide a direct, non-invasive measurement of subsurface mass change. Groundwater-storage changes were small during the 2020–23 study period, consistent with the relatively small volumes of pumping and recharge. Groundwater levels measured in monitoring wells were stable or increased slightly during this period, although the number of monitoring wells within the area of the gravity monitoring network is sparse. In total, about 15,000 acre-feet of water were pumped and 31,000 acre-feet recharged through injection in the north Phoenix aquifer during the 2020–22 period. Within the monitored area, groundwater storage increased by a small amount, about 1,000 acre-feet, in 2020, and decreased by a larger amount, about 6,000 acre-feet, each year in 2021 and 2022. Storage decreased at 89 of 102 stations from 2020 to 2023. Groundwater-storage decreases greater than the volume of net pumping indicate down-gradient subflow from the aquifer is greater than recharge plus incoming subflow, drying of the unsaturated zone resulting from decreased land-surface recharge, or both. At present (2023), the aquifer appears able to store and supply the relatively small amounts of water needed without excessive drawdown or harmful effects, such as land subsidence and surface inundation. If pumping or recharge increases in the future, the established repeat microgravity network is well suited to capture the spatial extent and magnitude of groundwater-storage changes in the aquifer.

Arizona↗
USGS2024

Subducting plate structure and megathrust morphology from deep seismic imaging linked to earthquake rupture segmentation at Cascadia

The origin of rupture segmentation along subduction zone megathrusts and linkages to the structural evolution of the subduction zone are poorly understood. Here, regional-scale seismic imaging of the Cascadia margin is used to characterize the megathrust spanning ~900 km from Vancouver Island to the California border, across the seismogenic zone to a few tens of kilometers from the coast. Discrete domains in lower plate geometry and sediment underthrusting are identified, not evident in prior regional plate models, which align with changes in lithology and structure of the upper plate and interpreted paleo-rupture patches. Strike-slip faults in the lower plate associated with oblique subduction mark boundaries between regions of distinct lower plate geometry. Their formation may be linked to changes in upper plate structure across long-lived upper plate faults. The Juan de Fuca plate is fragmenting within the seismogenic zone at Cascadia as the young plate bends beneath the heterogeneous upper plate resulting in structural domains that coincide with paleo-rupture segmentation.

Oregon, Washington↗
USGS2025

Utilizing downhole datasets for modelling the aeromagnetic signature of the Iron Creek Co-Cu deposit in the Idaho Cobalt Belt

The Idaho Cobalt Belt in east-central Idaho is host to some of the largest domestic Co resources, including the informal Iron Creek deposit. The two main ore zones of this deposit, the Iron Creek and the Ruby, are hosted in greenschist-grade interbedded argillite/siltstone and quartz-rich units of the Mesoproterozoic Apple Creek Formation of Lemhi Group. The primary ore mineral is cobalt-bearing pyrite, which occurs with pyrrhotite, chalcopyrite, and magnetite. This study integrates mineralogical and core-scale geophysical measurements with regional-scale aeromagnetic surveys. The high magnetite content within the Ruby zone produces elevated magnetic susceptibility, but the relatively limited spatial footprint of the ore zone would produce a small-scale anomaly that may be overlooked in regional surveys. The low magnetite content in the Iron Creek zone results in low magnetic susceptibility, creating a relatively low amplitude geophysical response. By characterizing the magnetic properties and mineralogy of these ore zones, this study enhances the interpretation of aeromagnetic data, enabling the identification of small or faint anomalies as potential Co targets. These findings improve can improve exploration strategies, both within the Idaho Cobalt Belt as well as for similar deposit types globally.

Idaho↗
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↗
USGS2024

A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (𝑀 w ) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from 𝑀 w 3.5–4.5 earthquakes but includes three well-recorded 𝑀 w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (𝑉 S30 ) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The 𝑉 S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments.

California↗