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1,711 records · Page 85Linked to original sources
USGS2025

Long‐period ground motions from dynamic rupture simulations of large earthquakes on the creeping Hayward–Calaveras–Rodgers Creek fault system

he Hayward, Calaveras, and Rodgers Creek faults in the San Francisco Bay region of California have a high probability of producing a large earthquake in the next decades. Although these faults creep, the creep is insufficient to keep up with their relatively rapid slip rates on their deepest sections, so they have been storing tectonic strain since their last large earthquakes, with the Hayward’s and Rodgers Creek’s more than 150 yr ago. We do not know what the next large Hayward–Calaveras–Rodgers Creek earthquakes will look like or how strongly they will shake the San Francisco Bay region. Harris et al. (2021) used the 3D dynamic (spontaneous) rupture method to simulate large earthquakes on these creeping faults. In this article, we examine the resulting simulated long‐period ( T > 1 s) ground shaking from 0 to 50 km distance, for earthquakes nucleating on the Hayward fault and earthquakes nucleating on the Rodgers Creek fault. We compare these simulated long‐period ground motions with the Boore et al. (2014) well‐established empirically based ground‐motion model suitable for the slowest material velocity in our 3D velocity structure. We find that the simulated long‐period ground motions from the creeping‐fault earthquake scenarios produce a reasonable agreement with the empirical expectations if frictional cohesion is included only where it is appropriate.

California↗
USGS1976

Ground magnetic and VLF studies at Midnite uranium mine, Stevens County, Washington

Ground magnetic and E-mode VLF measurements were made at more than 200 stations at the Midnite uranium Mine, Stevens County, Washington. The equipment was found to be light and foolproof, and each set of data was collected in one day, exclusive of surveying and marking the station points. The maps of contoured magnetic and VLF data resembled geologic maps of the area, showing many common features, as well as a few unique features on each map. Each showed some evidence of a small normal fault cutting the region; taken together, the evidence for this fault was judged to be much stronger, so that further structural details were inferred. Because of soil cover and inadequate outcrops, the presence of this fault had hitherto been unsuspected. A target area for further uranium mineralization north of the fault was indicated by this quick, inexpensive geophysical survey. The drilling program which Midnite Mine management had underway at that time had already outlined a mineralized zone in the indicated area.

Washington↗
USGS2025

AAPG Energy and Minerals Division Tight Oil and Gas Committee Activities and Commodity Report for 2021-2022: Tuscaloosa Marine Shale, Gulf Coast basin, Louisiana and Mississippi

The Upper Cretaceous Tuscaloosa marine shale (TMS) potential production area encompasses 20.4 million acres across central Louisiana (LA), southern Mississippi (MS), southwestern Alabama (AL), and a small southwestern section of the Florida panhandle (Hackley et al., 2018). It remains a minor and largely undeveloped unconventional shale oil play with production from the TMS confined along the east-west LA-MS State boundary (Fig. 1). The mean undiscovered, technically recoverable resources in the TMS are estimated at 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas (Hackley et al., 2018). Geochemical analyses of source rock solvent extracts and oil samples indicate that, in the play area, the TMS is the primary source of shale oil produced from the TMS as well as of accumulated oils in the underlying conventional reservoirs of the lower Tuscaloosa (Hackley et al., 2020). The API gravity of TMS oils ranges from approximately 34 to 46 degrees (Hackley et al., 2020; Croke et al., 2020).

AAPG Wiki↗
USGS2026

Ground-motion simulations for the 2024 Mw 4.8 Tewksbury, New Jersey, earthquake

Ground-motion simulations of notable earthquakes in the central and eastern United States are limited and typically assume one-dimensional (1D) Earth structure. In this study, we use a three-dimensional (3D) seismic velocity model to better constrain the depth and focal mechanism of the April 5th, 2024, moment magnitude 4.8 Tewksbury earthquake and investigate the spatial variability of earthquake ground motions and the effects of nearby sedimentary basins. We perform earthquake ground-motion simulations up to 0.5 Hz using the 3D spectral-element wave-propagation solver SPECFEM3D over a region 280-km wide by 260-km long by 77-km deep. Topography and subsurface geophysical structure are assigned using the U.S. Geological Survey National Crustal Model with a minimum shear-wave velocity of 200 m/s. We use earthquake time series from 13 broadband seismic stations in the region that have a uniform azimuthal distribution and epicentral distances ranging from 76 to 131 km to compare with synthetics and explore the effects of 1D versus 3D seismic structure on focal mechanism and depth solutions. Ground-motion intensity metrics are also presented relative to the NGA-East ground-motion models (GMMs) currently used in seismic hazard assessments for the region. We find that the 3D model, which reveals a wide spatial variability of period-dependent ground motions, yields better predictions of earthquake ground motions relative to the 1D model and the NGA-East ergodic ground-motion model, with 76 percent reduction of residual variance in observed ground motions averaged over 3-, 5-, 7-, and 10-second periods. Use of the 3D model to solve for a focal mechanism yields a shallower focal depth at 4 km and a shallower east-dipping focal plane relative to the U.S. Geological Survey regional moment tensor and Global Centroid Moment Tensor. Our study demonstrates that use of 3D seismic velocity models can improve estimates of earthquake focal mechanisms, ground motions, and seismic hazard.

New Jersey↗
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

The 3D Elevation Program—Supporting New Hampshire’s economy

Introduction The topography of New Hampshire ranges from the Coastal Lowlands to the Eastern New England Upland to the White Mountains region. High-quality statewide elevation data are useful in managing this very diverse landscape. For example, the short coastline, including the Great Bay estuary and the Hampton-Seabrook marshes, is of disproportionately high value to New Hampshire’s tourist economy. The vulnerability of the coast to the effects of sea-level rise underscores the need for accurate, high-quality nearshore topographic elevation data and offshore bathymetric data to effectively manage the coast’s valuable resources, which include important fisheries, habitat, and infrastructure. Another important use for accurate elevation data in New Hampshire is in the evaluation of flood hazards and their potential environmental and infrastructure effects. This evaluation includes mapping of inundation and sediment transport, and assessing the associated costs of flooding. Addressing this challenge requires detailed knowledge of both surface topography and inland bathymetry. Other important activities having a substantial economic element and needing accurate elevation data include geologic resource assessment and hazard mitigation, urban and regional planning, infrastructure and construction management, and cultural resources preservation and management. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional model of the Earth’s surface and aboveground features.

New Hampshire↗
USGS2026

Seasonal migrations and other movements

In the past 25 years new information has been obtained on the migrations and movements of mountain sheep (bighorn [Ovis canadensis], thinhorn [Ovis dalli]). This chapter provides a comprehensive overview of mountain sheep migration and other movements across their broad distribution in western North America. Across the range of mountain sheep, migrations and other seasonal movements define a complex movement portfolio that relates to and supports all aspects of mountain sheep ecology. Bighorn and thinhorn species have examples of migratory behaviors that span the continuum between annual residents and long-distance migrants. Migratory behaviors can be characterized as low- or high-elevation residents; elevational migrations and other variants; and geographic migrants. Native populations that have been extant on the landscape without notable human intervention have greater migratory propensity and more diverse migratory portfolios due to the maintenance of migration through cultural learning and social transmission. Restored and augmented populations, where the population-level knowledge of migration has been lost or greatly reduced, are largely nonmigratory, although translocations show some ability to restore short-distance elevational migrations. Seasonal spring and fall migrations are less common in desert bighorn sheep (O. canadensis spp.) or bighorn sheep living in canyon or prairie breaks landscapes. Mineral lick visitation is important and common across the range of mountain sheep. Managing for migratory diversity can help to sustain migratory behavior in the face of climate change and other anthropogenic pressures, which can limit landscape connectivity between seasonal ranges or alter the spatiotemporal dynamics of regional phenology with cascading effects to other biotic and abiotic interactions such as the need to balance forage and predation risk or the spatial refugia with increased temperatures.

Book chapter↗
USGS2026

Tectonic controls on volcanism and associated hydrothermal activity in a sediment-dominated mid-ocean ridge; Escanaba Trough

Mid-ocean ridges, the Earth's most extensive volcanic system, exhibit unique characteristics in sediment-dominant environments. Thick sediment cover insulates the crust and channels fluid along pathways that can lead to the formation of distinct crustal alteration patterns, exceptionally large mineral deposits, and specialized chemosynthetic ecosystems. This study presents an interdisciplinary investigation into the tectonics of the Escanaba Trough, a heavily sedimented axial valley at the southern Gorda Ridge in the Northeast Pacific Ocean. A primary challenge in such environments is overcoming the masking effect of thick sediments on basement structures that control magmatic and hydrothermal activity. We address this by employing three-dimensional (3D) magnetic modeling of high-resolution near-seafloor magnetic data collected by an autonomous underwater vehicle (AUV). The 2022 surveys with AUV Sentry provided data for 3D magnetic susceptibility models, refining our understanding of the geometry of sub-sediment laccoliths/saucer-shaped sills and hydrothermal alteration. In conjunction with a new 1:100,000 scale lithostratigraphic map, we outline the tectonic controls on the emplacement of Escanaba Trough's three main volcanic centers, characterize the geometry of its spreading segments, and provide volumetric data on the distribution of sub-sediment volcanism in the southern Gorda Ridge.

Escanaba Trough, Pacific Ocean↗
USGS2025

The Hardscrabble Creek complex: A newly discovered, mostly buried, Mesoproterozoic mafic-ultramafic pluton in the Wet Mountains, Colorado, USA

The origin of prolific ca. 1.4 Ga ferroan magmatism between the southwestern USA and eastern Canada is enigmatic and has been explained by various models, including extensional, mantle plume, and convergent plate-margin models. Rare mafic plutons are associated with the ferroan plutons, which may help constrain their mantle source and tectonic setting. In the southwestern USA, only two such mafic plutons are known to exist. We present the first evidence for a third, mostly buried, potentially layered, mafic-ultramafic Mesoproterozoic pluton, informally referred to as the Hardscrabble Creek complex, in the central Wet Mountains of Colorado, USA. Recent geophysical data show an elliptical magnetic and gravity high spatially coincident with local gabbroic outcrops. New field and petrographic analyses of these exposed rocks reveal that they consist of ultramafic to mafic cumulates, including orthopyroxenite, olivine norite, norite, and anorthosite. High-precision U-Pb dating of zircon from orthopyroxenite and norite yield weighted mean 206 Pb/ 238 U dates of 1352.36 ± 1.60 Ma and 1352.37 ± 1.71 Ma, respectively. These dates indicate that the complex formed over a narrow timeframe, after the adjacent 1362 ± 7 Ma ferroan San Isabel Granite, and during the waning stages of the regional ca. 1.4 Ga ferroan magmatism. Whole-rock geochemistry and Nd-Sr-Pb isotope compositions of samples from the Hardscrabble Creek complex are similar to those of the San Isabel Granite, suggesting that they were derived from the same or a similar mantle source. The mineral chemistry of the samples is comparable to Proterozoic massif-type anorthosites and related mafic intrusions, indicating that the Hardscrabble Creek complex and San Isabel Granite together represent a rare anorthosite-mangerite-charnockite-granite (AMCG) suite in the southwestern USA. The Hardscrabble Creek complex is unique because it formed ~80 m.y. after the other few mafic plutons in the southwestern USA, and it contains an ultramafic section that is absent from these plutons and rare to the AMCG suite in general. A combination of arc-like whole-rock geochemistry, chondrite uniform reservoir-like Nd-Sr-Pb isotopes, and ocean island basalt (OIB)-like zircon trace element chemistry suggests that the complex was derived from a partial melt of OIB-like mantle and interacted with metasomatically enriched lithospheric mantle. The enriched lithospheric mantle signature, combined with the long ~160 m.y. duration of magmatism in the region, is consistent with a period of protracted convergent tectonism.

Colorado↗
USGS2025

Enhanced geothermal systems electric-resource assessment for the Great Basin, southwestern United States

The U.S. Geological Survey recently (2025) completed a provisional assessment of the geothermal-electric resources associated with high-temperature, low-permeability rock formations of the Great Basin, Southwestern United States. If sufficient technological advances to commercialize enhanced geothermal systems occur, then a current best provisional estimate for electric-power generation capacity of 135 gigawatts electric are available from the upper 6 kilometers of the Earth’s crust. This estimate is a potential substantial increase of the installed geothermal electricity-generating capacity from <1 to 10 percent of current total U.S. power production capacity.

California, Idaho, Nevada, Oregon, Utah↗
USGS2025

Characterization and validation of tidally calibrated strains from the Alto Tiberina Near Fault Observatory Strainmeter Array (TABOO-NFO-STAR)

Six horizontal borehole tensor strainmeters (TSM1-6) installed from Fall 2021 to Spring 2022 comprise the Alto Tiberina Near Fault Observatory Strainmeter Array (STAR), providing an unprecedented opportunity to investigate seismic and aseismic deformation from hazardous high- and low-angle normal faults in Italy. Prior to use in tectonic applications, they require in-situ calibration and correction for non-tectonic signals. We tidally calibrate the instruments, characterize the calibration uncertainty, and test the results against environmental and earthquake signals originating from local to teleseismic distances. The STAR sites demonstrably deviate from assumptions common to the standard manufacturer's calibrations, including negative areal coupling at TSM3-6. While the tidally calibrated strains have ~3-56% uncertainty, the calibrated dynamic strains show interstation precision and accuracy to nanostrain levels, and static coseismic offsets in the array footprint are within uncertainty. TSM3 records a complex series of strains that may arise from dynamically triggered near-borehole fracture slip and fluid flow that does not appear to affect its sensitivity to lower strain rate deformation. Future calibration improvement may be afforded with longer stable timeseries, particularly for TSM4. Overall, our analyses demonstrate expanded geodetic capability for detecting deformation in the Alto Tiberina Near Fault Observatory.

Alto Tiberina Near Fault Observatory↗
USGS2025

Extracting data from maps: Lessons learned from the artificial intelligence for critical mineral assessment competition

The U.S. Geological Survey (USGS), Defense Advanced Projects Research Agency (DARPA), NASA Jet Propulsion Laboratory (JPL), and MITRE ran a 12-week machine learning competition aimed at accelerating development of AI tools for critical mineral assessments. The Artificial Intelligence for Critical Mineral Assessment Competition solicited innovative solutions for two challenges: 1) automated georeferencing of historical maps, and 2) automated feature extraction from historical maps. Competitors used a new dataset of historical map images to train, validate, and evaluate their models. Automated georeferencing pipelines attained a median root-mean square error of 1.1 km. Prompt-based extraction (i.e., with user input) of polygons, polylines, and points from geologic maps yielded median F1-scores of 0.77, 0.56, 0.35, respectively. Geologic maps pose numerous challenges for AI workflows because they vary significantly. However, despite its short duration, the competition yielded promising results that have since spurred further innovation in this area and led to the development of new AI tools to semi-automate key, time-consuming parts of the assessment workflow.

Applied Computing and Geosciences↗
USGS2025

ShakeAlert®—Communication, education, outreach and technical engagement strategic vision

Executive Summary In 2006, the U.S. Geological Survey (USGS) began directly supporting ShakeAlert ® research and in 2012 the ShakeAlert demonstration system began testing ( Given and others, 2018 ). The ShakeAlert earthquake early warning (EEW) system is a partnership between the U.S. Geological Survey (USGS) and the three West Coast States (Washington, Oregon, and California) served by the ShakeAlert System, which is part of the larger Advanced National Seismic System (ANSS). With more than 143 million people exposed to potentially damaging shaking in the United States ( Jaiswal and others, 2015 ), earthquakes are a national hazard. Most of our Nation’s earthquake risk is concentrated in the highly populated areas on the active plate tectonic boundaries on the West Coast of the conterminous United States. ShakeAlert is the first public alert system in the United States to provide rapid mass notification of earthquake detection, potentially offering seconds of warning before strong shaking arrives. A few seconds may not seem like much time, but the information in ShakeAlert Messages can be used to trigger automated actions that can prevent injury or death, reduce immediate damage, and speed recovery from earthquakes. The information product issued by the ShakeAlert system is called a ShakeAlert Message and is one of the information products and tools of the ANSS. The ShakeAlert System includes the USGS component, plus the pathways by which ShakeAlert-powered products and (or) services are delivered to end users. Alerts can be delivered to cell phones or be used to trigger automated systems to protect equipment, facilities, and infrastructure, such as slowing or stopping a train. ShakeAlert-powered automated actions can include fire house doors that can be opened to prevent jamming, heavy equipment (for example, trains, elevators, and cranes) that can be automatically stopped or parked in safe positions, and pipeline valves that can be closed to prevent surges and spills. A few seconds of warning also may be sufficient for people to take protective actions, such as drop, cover, and hold on or modified protective actions for a broad range of populations. Advance training may increase the benefit of a speedy response to an alert. Outreach and education about EEW may raise awareness of the overall earthquake threat and how people can best react when they receive an alert or feel shaking. ShakeAlert communication, education, outreach, and technical engagement (CEO&TE) efforts are highly collaborative and essential for the success of the ShakeAlert System. This strategic vision informs how the vast ShakeAlert CEO&TE Community operates and works together. The CEO&TE Community delineates a strategic framework that is intended to set the path for a long-term, sustainable approach to CEO&TE through three focus areas and five priorities. Focus Areas Technical engagement.— The objective of this focus area is to expand and broaden ShakeAlert technical engagement and implementation. External engagement.— This focus area targets engagement in long-term communication, education, and outreach planning, implementation, and evaluation. Internal engagement.— The purpose of this focus area is to build and sustain a robust infrastructure to optimize collaboration, information sharing, and project planning among the community of stakeholders charged with implementing ShakeAlert CEO&TE. Priorities The enumeration of the five priorities listed below does not suggest priority ranking. Public safety, preparedness, and resilience; Technical implementation and engagement; Consistent messaging and communication; Integration with other Federal and State earthquake hazards products; and Educational resources development and dissemination. This strategic vision is a tangible outcome of collaboration among many stakeholders beginning in July 2016. Since then, the work of the ShakeAlert CEO&TE Community has grown into an international effort. The USGS has developed, tested, and implemented a broad spectrum of communication, education, and outreach tools and resources—all of which recognize that seconds matter when it comes to safety and mitigating harm from earthquake hazards. The CEO&TE social science research effort has provided invaluable insights into the ShakeAlert System’s human interface. USGS-licensed technical partners develop, test, and implement real-world applications using ShakeAlert Messages. The success of ShakeAlert CEO&TE efforts is predicated on robust collaboration across numerous agencies, organizations, and groups. As such, this strategic vision outlines a “partnership model” that delineates roles and responsibilities to ensure alignment with focus areas and priorities. The partnership model includes the CEO&TE lead agency (USGS); its principal partners (State agencies and university partners); its implementation partners (for example, technical partners who build systems to deliver ShakeAlert-powered products and (or) services [focus area one]), earthquake education partners who work to increase public preparedness for seismic events (focus area two); and other organizations that work together to enhance the adoption and effectiveness of the ShakeAlert System. These partners collaborate and convene through a variety of working groups and forums, which are also described in this strategic vision and align with focus area three (internal engagement). The CEO&TE Community collaboratively developed its operating principles and a consensus-based, decision-making strategic framework to guide its collective work. Performance metrics are used to continually measure success. Ultimately, the USGS and ShakeAlert CEO&TE Community are advancing the ShakeAlert System that as of the publication of this strategic vision to “provide earthquake early warning for all” serves more than 50 million people.

Circular↗
USGS2025

Modeling interconnected minerals markets with multicommodity supply curves: Examining the copper-cobalt-nickel system

Demand for many of the metals used in the energy transition is expected to grow rapidly. Many of these are by-products, often considered critical because their production responds weakly to prices and is instead tied to the economics of the host mineral. We present a model of prices and production for jointly produced commodities that accounts for interconnectivity between host and by-product markets at the mine level. We demonstrate this method using the copper–cobalt–nickel system, in which approximately 99% of cobalt is a by-product of copper or nickel mining. Our results show that the model more accurately captures the economic benefits of diversified mine outputs than previous approaches. Furthermore, changes in demand drivers for any two commodities produce non-linear effects on production and price. We challenge the prior best-practice assumption that cobalt cannot impact the copper or nickel markets. Recognizing the importance of both copper and cobalt for future electrification, we emphasize that incentivizing the copper industry to reduce cobalt supply risks could inadvertently undermine copper supply.

Nature Communications↗
USGS2026

Estimating habitat availability for Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) to inform reintroduction planning in the middle Snake River basin, USA

Anadromous fishes have been blocked from the middle Snake River basin since the construction of flood control, irrigation, and hydroelectric projects during the 19 th and 20 th centuries, culminating with the construction of Hells Canyon Dam (river kilometer [rkm] 398) in 1967. Seven large watersheds in the blocked area of the basin are under consideration for Pacific salmon reintroduction. The primary objective of this study was to identify and characterize potential reintroduction sites with high-quality rearing and spawning habitat for Chinook salmon ( Oncorhynchus tshawytscha ) and steelhead ( O. mykiss ) upstream of the Hells Canyon Complex in Idaho, Oregon, and Nevada, USA. We created and tested habitat models to predict rearing presence/absence, rearing abundance, and spawning presence/absence using channel morphology, hydrology, and stream temperature variables obtained from regional peer-reviewed datasets. Habitat models were trained with salmonid presence and abundance records collected in the lower Snake River basin (downstream of Hells Canyon Dam), where anadromous fish can currently access, from 1993 to 2011. Model performance was tested with set-aside data comprised of randomly selected reaches and independent environmental DNA data. An index model was created in the middle Snake River basin for each species by combining results from the habitat models. Modeling covariates differed by species and life stage and included different combinations of August stream temperature, summer flow, channel slope, and quadratic terms for temperature and slope. The habitat models predicted high versus low Chinook salmon and steelhead probability and abundance with 66% to 85% accuracy depending on species and life stage. The index models predicted a total of 2,887 km of Chinook salmon habitat and 2,434 km of steelhead habitat in the blocked area. The three basins in the blocked area with the greatest amount of predicted habitat were the Powder River, South Fork Payette River, and North Fork Payette River for Chinook salmon, and the Powder River, South Fork Boise River, and South Fork Payette River for steelhead. The modeling approach presented here is complementary to other planning efforts for Chinook salmon and steelhead reintroduction in the blocked area of the Snake River basin, and similar approaches may be useful for reintroduction planning in other systems.

Idaho, Nevada, Oregon, Utah, Washington, Wyoming↗
USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗
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↗
USGS2024

Parameter ESTimation with the Gauss–Levenberg–Marquardt algorithm: An intuitive guide

In this paper, we review the derivation of the Gauss–Levenberg–Marquardt (GLM) algorithm and its extension to ensemble parameter estimation. We explore the use of graphical methods to provide insights into how the algorithm works in practice and discuss the implications of both algorithm tuning parameters and objective function construction in performance. Some insights include understanding the control of both parameter trajectory and step size for GLM as a function of tuning parameters. Furthermore, for the iterative Ensemble Smoother (iES), we discuss the importance of noise on observations and show how iES can cope with non-unique outcomes based on objective function construction. These insights are valuable for modelers using PEST, PEST++, or similar parameter estimation tools.

Groundwater↗