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USGS2024

Satellite interferometry landslide detection and preliminary tsunamigenic plausibility assessment in Prince William Sound, southcentral Alaska

Regional mapping of actively deforming landslides, including measurements of landslide velocity, is integral for hazard assessments in paraglacial environments. These inventories are also critical for describing the potential impacts that the warming effects of climate change have on slope instability in mountainous and cryospheric terrain. The objective of this study is to identify slow-moving landslides in the Prince William Sound region, southcentral Alaska, United States, which has had rapid deglaciation since the mid-1800s, and assess their tsunamigenic plausibility. We use an automated time series persistent scatterer interferometric synthetic aperture radar processing method with 7 years of Sentinel-1 data (2016–22) to identify 43 slow-moving slopes with average velocities ranging from approximately 0.2 to 21 millimeters per year. Landslide presence is confirmed using aerial imagery and previous landslide inventory records. We assess the tsunamigenic plausibility of the landslides using empirically derived estimates of landslide mobility based on modeled landslide volumes. Of the identified landslides, our preliminary analysis suggests that 11 have tsunamigenic potential if they were to fail rapidly and catastrophically. Although our estimate of tsunamigenic plausibility is preliminary and can be refined with additional observations and analyses, it can be used to prioritize ongoing and future hazard assessment, surveillance, and research efforts.

Alaska↗

USGS2025

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater-dependent ecosystems in areas with industrial land use are at risk of exposure to a PFAS chemicals. We investigated one such system with several known PFAS source areas, where high and low permeability sediments (glacial) coupled with groundwater-lake and groundwater/surface-water interactions created complex ‘source to seep’ dynamics. Using heat-tracing and chemical methods, numerous preferential groundwater discharge zones were identified and sampled across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, downgradient of Joint Base Cape Cod (JBCC). Surface-water and groundwater samples were analyzed for 40 PFAS compounds between March and October 2022. Samples were collected from groundwater seeps identified as preferential discharge points (PDPs), wells upgradient of the stream-wetland system, contributing flow-through kettle lakes, and along Quashnet River surface-waters. PFAS from sampled waters contained perfluorinated carboxylates (PFPea, PFHxA, PFNA), perfluorinated sulfonates (PFBS, PFPeS, PFHxS, PFOS), fluorotelomer sulfonates (6:2, 8:2 FtS), and perfluoroalkyl sulfonamides (PFOSA). Samples from PDPs and wells had measured PFAS concentrations ranging from non-detect to 4677 ng/L ng/L (mean = 418 ng/L, std. = 709 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to groundwater flowpath emergence at PDPs. Correlations ( p < 0.01) between deuterium excess, %PFAS precursors, and terminal PFAS compounds highlighted potential precursor transformations associated with lake-groundwater exchange along flowpaths sourcing PDPs. However, some seepages had higher total PFAS concentrations (>1000 ng/L) than upgradient kettle lakes despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. Results from these synoptic surveys address gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations and mass loading in preferential groundwater discharge zones.

Massachusetts↗

USGS2025

Hydrogeology, water budget, and simulated groundwater availability in the Salt Fork Arkansas River and Chikaskia River alluvial aquifers, northern Oklahoma, 1980–2020

The 1973 Oklahoma Groundwater Law (Oklahoma Statute §82–1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s aquifers to determine the maximum annual yield for each groundwater basin. The U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, conducted an updated hydrologic investigation of the Salt Fork Arkansas River and Chikaskia River alluvial aquifers in northern Oklahoma for the study period spanning 1980–2020 and evaluated the simulated effects of potential groundwater withdrawals on groundwater flow and availability in the Salt Fork Arkansas River alluvial aquifer. A hydrogeologic framework and conceptual model were developed to guide the development of a numerical model. Three groundwater-availability scenarios were evaluated by using the calibrated numerical model, which was focused on the Salt Fork Arkansas River alluvial aquifer. These scenarios were used to (1) estimate equal-proportionate-share groundwater withdrawal rates, (2) quantify the potential effects of projected well withdrawals on groundwater storage over a 50-year period, and (3) simulate the potential effects of a hypothetical 10-year drought. The 20-, 40-, and 50-year equal-proportionate-share groundwater withdrawal rates for the Salt Fork Arkansas River alluvial aquifer under normal recharge conditions were about 0.63, 0.58, and 0.57 acre-foot per acre per year, respectively. Projected 50-year groundwater withdrawal scenarios were used to simulate the effects of modified well withdrawal rates. Because well withdrawals were less than 2 percent of the calibrated numerical-model water budget, changes to the well groundwater withdrawal rates had little effect on simulated Salt Fork Arkansas River base flows and groundwater storage in the Salt Fork Arkansas River alluvial aquifer. A hypothetical 10-year drought scenario was used to simulate the potential effects of a prolonged period of reduced recharge on groundwater storage. Groundwater storage at the end of the hypothetical drought period was 14.5 percent less than the groundwater storage of the calibrated numerical model without the simulated drought.

Oklahoma↗

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

Evaluating mass flow meter measurements from chambers for greenhouse gas emissions from orphan wells and other point sources

This study evaluates the performance of a rigid gas flux chamber equipped with a mass flow meter (MFM) for measuring gas emissions from leaking orphan wells and similar pressure-driven gas point sources. We conducted a series of laboratory and field experiments to evaluate the sensitivity, stability, and dynamic range of an MFM chamber system and found an optimal method for sealing the chamber to the ground to isolate the emission source. From these results, we estimate the effects of different soil gas permeabilities on measurements and identify the uncertainty of environmental processes that can impact measurements. Simulations of an MFM chamber are compared to those of a dynamic flux chamber to contrast the data derived with both methodologies and illustrate the potential for measuring high variability leaks with the MFM chamber. Using a low flow resistance MFM and a chamber well-sealed to the ground, it is possible to measure leaks down to 1.08 x 10 -3 cubic meters per hour (m 3 h −1 ) (refenced to 25°/1 atm), corresponding to 0.77 grams per hour (g h −1 ) methane or 2.11 g h −1 carbon dioxide, with a mean uncertainty of 0.89 % relative standard deviation. Environmental processes such as heated gas inside the chamber from solar gain, wind blowing across the chamber vent, and changing humidity in the chamber, can cause variation in MFM measurements. Over 11 d of continuous monitoring under varying weather conditions, the standard deviation of the environmentally sourced signals was found to be 7.40 x 10 -3 m 3 h −1 (equivalent to or 5.27 g h −1 methane or 14.45 g h −1 carbon dioxide). Strategies to obtain the highest quality data from MFM chambers include burying the edges of the chamber below the surface sufficiently deep to seal the chamber edges against gas flow and soaking the dirt with water to lower the chances of escaping gases, while monitoring the gas flow and adjusting the chamber seal to achieve a maximum flow rate.

Atmospheric Measurement Techniques↗

USGS2026

Mid-Cretaceous porphyritic magmatism in the Beartooth Mountains of the northern Laramide foreland and its connection to Frontier Formation sediment dispersal in Bighorn basin, Montana-Wyoming (USA), and Cordilleran tectonism

Porphyritic intrusions in the southeast Beartooth Mountains and porphyritic cobbles from the Torchlight conglomerate of the Cenomanian Frontier Formation in Bighorn basin (Montana-Wyoming, USA) bear striking resemblance. We utilize geologic mapping, petrography, geochemistry, and geochronology to characterize rocks from both locations and test whether the Beartooth Mountains area was the provenance for Bighorn basin cobbles. Mapping on Line Creek Plateau in the Beartooth Mountains shows three units with porphyritic phenocrysts consisting dominantly of plagioclase, plagioclase + potassium feldspar, and plagioclase + quartz. Petrography shows embayed quartz, opacitic rims, and zoned plagioclase. Geochemistry characterizes the intrusions as trachydacite to trachyte and trace elements exhibit enrichment in light rare earth elements and slight depletion in heavy rare earth elements relative to primitive mantle. Zircon U-Pb dating shows substantial Archean inheritance and ca. 104−92 Ma dates; some samples display multiple mid-Cretaceous date populations. Bighorn basin porphyritic cobbles exhibit similar modal mineralogy, near-identical geochemistry, and Archean inheritance and mid-Cretaceous geochronology. We suggest the porphyritic cobbles were sourced from basement-hosted porphyritic intrusions now exposed in the Beartooth Mountains, given that geochemistry does not agree with coeval volcanic sources along the Frontier Formation depositional fairway (Idaho batholith) or sedimentary-hosted Beartooth Mountains porphyritic sills intruded into Cambrian shale. Stratigraphic evidence does not support kilometer-scale mid-Cretaceous Beartooth Mountains exhumation to expose basement-hosted porphyritic intrusions, and we therefore present a volcanic hypothesis to bring rocks to the surface. This mid-Cretaceous multimillion-year magmatism is unexplained by tectonic models for the north-central Laramide foreland, and thus we further explore the emplacement processes, spatiotemporal significance, and tectonic implications of these rocks.

Montana, Wyoming↗

USGS2025

World minerals outlook—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029

Given the rapid expansion in the demand for mineral commodities that underpin worldwide economic growth and technological advancement, information regarding expected country-level mine production and production capacity is becoming increasingly important to industry stakeholders, end users, and policymakers. Production capacity can limit future supply, depending on how rapidly that capacity is able to expand. Current capacity can be evaluated on the basis of past production. Decreases to future capacity can be taken into account from announcements of planned shutdowns of mines or processing facilities, which are frequently publicized well in advance of such closures. Likewise, capacity expansions, which usually involve multiple stages—such as permitting, financing, and construction (all of which take time)—can also be estimated. As such, it is possible to evaluate midterm future capacity based on estimates of today’s capacities along with consideration of future investment plans. This World Minerals Outlook provides estimated capacities for cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium for 2025 through 2029. The results of this analysis indicate that two mineral commodities important to the manufacture of lithium-ion batteries—cobalt and lithium—are expected to have large capacity growth in the next few years, likely owing to expectations for increased demand for these batteries. For gallium, helium, palladium, and platinum, capacity is expected to remain stable or exhibit moderate growth. Still, these expected capacity levels are higher than current production, allowing for future production growth. The production capacity outlook is opaque for magnesium and titanium metal, which have a significant fraction of current production in nonmarket economies, such as China and Russia. Ultimately, though, where free market conditions prevail, full utilization of capacity potential for those commodities is likely to depend on supply deficits and prices that are above production costs.

Scientific Investigations Report↗

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↗

USGS2025

Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration

Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.

Water Resources Research↗

USGS2025

Prospectivity mapping for geologic hydrogen

Geologic, or naturally occurring, hydrogen has the potential to become a new, low-carbon, primary energy resource. Often referred to as “white” or “gold” hydrogen, this gas occurs naturally in the Earth’s subsurface, similar to petroleum resources. However, unlike petroleum, which releases carbon dioxide when burned, burning hydrogen only produces water as a byproduct. Exploration for geologic hydrogen remains in an early stage and discoveries of high concentrations of subsurface hydrogen are still relatively rare. To facilitate research and exploration for this potential resource, this report presents the first publicly available prospectivity map of geologic hydrogen accumulations in the conterminous United States. Prospective regions are those regions in which all major components necessary for a hydrogen accumulation likely are present—a source of sufficient hydrogen generation, porous reservoirs for storage, and seals to prevent leakage. The midcontinent region of the United States and the central California coast are revealed as having high prospectivity. This analysis also identifies previously unrecognized prospective regions that may be favorable due to long distance lateral migration of subsurface hydrogen, such as the offshore eastern seaboard of the United States, and can provide a linkage between surface observations of hydrogen degassing and far-field source regions. The methodology developed to create this map is expandable and flexible and may be adapted to incorporate new concepts in the hydrogen system and for application to other regions of the world.

conterminous United States↗

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↗

USGS2026

Groundwater budget for the Mountain Home area, southern Idaho, 2022–23

The U.S. Geological Survey, with funding from the Idaho Department of Water Resources, developed a groundwater budget for the Mountain Home area in southern Idaho for irrigation year 2023 (November 1, 2022–October 31, 2023). This study focused on the water balance across the Cinder Cone Butte Critical Groundwater Area (CGWA), Mountain Home Groundwater Management Area (GWMA), and the rest of the study area (RoSA), compiling data from various sources, including precipitation records, groundwater level measurements, metered groundwater pumpage data, surface water diversions and evapotranspiration (ET) estimates derived from remote sensing satellite imagery, and ground-based reference data. Key inflow components included recharge from applied surface water irrigation (which incorporates incidental recharge from irrigation practices and conveyance losses), estimated tributary streamflow, and estimated mountain block recharge. The key outflow components were groundwater pumpage for irrigation, municipal, industrial, and domestic uses, and ET. Recharge from applied irrigation and mountain block recharge were the largest inflows, and groundwater pumpage for irrigation was the largest outflow. The CGWA had a positive groundwater budget residual of 2,170 acre-feet (acre-ft), which contrasts with observed long-term groundwater level declines and historical trends of storage depletion. This positive residual is likely associated with unquantified outflows, including lateral groundwater flow out of the subregion, or other complexities, such as overestimated tributary contributions relative to the actual recharge for the 2023 water budget. The GWMA exhibited a positive residual of 56,563 acre-ft, primarily owing to recharge from applied surface water irrigation and areal recharge during a wetter-than-average year, which allowed irrigation entities to deliver more water from in-basin and out-of-basin reservoirs. The RoSA showed a large positive residual of 124,933 acre-ft. The interpretation of these positive residuals must account for significant uncertainties, including estimations of areal recharge, tributary streamflow (particularly losses and diversions), ET, the volume of surface water loss to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and the unquantified groundwater discharge to the Snake River. These uncertainties, in combination with the complex hydrogeologic controls on water movement and limitations of remotely sensed data, directly affect the accuracy of water availability assessments. Future data collection efforts would help reduce these uncertainties and support water resource management decisions in the Mountain Home area. Key efforts could include installing additional streamflow gaging stations (particularly to quantify tributary losses and gains and surface water losses to the Snake River), improving groundwater pumpage metering, and validating remotely sensed ET data with ground-based measurements. Furthermore, to better quantify unrepresented or highly uncertain fluxes, focused investigations on groundwater discharge to the Snake River, lateral groundwater flows between subregions and across study area boundaries, and a more robust determination of the actual influence and volume of mountain block recharge would help refine future water availability assessments for the Mountain Home area.

Idaho↗

USGS1990

Recharge rates and aquifer hydraulic characteristics for selected drainage basins in middle and east Tennessee

Quantitative information concerning aquifer hydrologic and hydraulic characteristics is needed to manage the development of ground-water resources. These characteristics are poorly defined for the bedrock aquifers in Middle and East Tennessee where demand for water is increasing. This report presents estimates of recharge rate, storage coefficient, diffusivity, and transmissivity for representative drainage basins in Middle and East Tennessee, as determined from analyses of stream-aquifer interactions. The drainage basins have been grouped according to the underlying major aquifer, then statistical descriptions applied to each group, in order to define area1 distribution of these characteristics. Aquifer recharge rates are estimated for representative low, average, and high flow years for 63 drainage basins using hydrograph analysis techniques. Net annual recharge during average flow years for all basins ranges from 4.1 to 16.8 in/yr (inches per year), with a mean value of 7.3 in. In general, recharge rates are highest for basins underlain by the Blue Ridge aquifer (mean value11.7 in/yr) and lowest for basins underlain by the Central Basin aquifer (mean value 5.6 in/yr). Mean recharge values for the Cumberland Plateau, Highland Rim, and Valley and Ridge aquifers are 6.5, 7.4, and 6.6 in/yr, respectively. Gravity drainage characterizes ground-water flow in most surficial bedrock aquifer in Tennessee. Accordingly, a gravity yield analysis, which compares concurrent water-level and streamflow hydrographs, was used to estimate aquifer storage coefficient for nine study basins. The basin estimates range from 0.002 to 0.140; however, most estimates are within a narrow range of values, from 0.01 to 0.025. Accordingly, storage coefficient is estimated to be 0.01 for all aquifers in Middle and East Tennessee, with the exception of the aquifer in the inner part of the Central Basin, for which storage coefficient is estimated to be 0.002. Estimates of aquifer hydraulic diffusivity are derived from estimates of the streamflow recession index and drainage density for 75 drainage basins; values range from 3,300 to 130,000 ft^2/d (feet squared per day). Basin-specific and site-specific estimates of transmissivity are computed from estimates of hydraulic diffusivity and specific-capacity test data, respectively. Basin-specific, or areal, estimates of transmissivity range from 22 to 1,300 ft^2/d, with a mean of 240 ft^2/d In general, areal transmissivity is highest for basins underlain by the Cumberland Plateau aquifer (mean value 480 ft^2/d) and lowest for basins underlain by the Central Basin aquifer (mean value 79 ft^2/d). Mean transmissivity values for the Highland Rim, Valley and Ridge, and Blue Ridge aquifer are 320,140, and 120 ft^2/d respectively. Site-specific estimates of transmissivity, computed from specific-capacity data from 118 test wells in Middle and East Tennessee range from 2 to 93,000 ft^2/d with a mean of 2,600 ft^2/d Mean transmissivity values for the Cumberland Plateau, Highland Rim, Central Basin, Valley and Ridge, and Blue Ridge aquifers are 2,800,1,200, 7,800, 390, and 65Oft Id, respectively.

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