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USGS2026

Abandonment of the Upper Devonian Greenland Gap Group and Scherr Formation and revision of the Upper Devonian Brallier and Foreknobs Formations in the central Valley and Ridge Province

This study revises the lithostratigraphic framework of the Upper Devonian interval traditionally assigned to the Greenland Gap Group across the central Appalachian Valley and Ridge Province. The work aims to modernize and standardize lithostratigraphic nomenclature, establish a new reference section and demonstrate how the revised stratigraphy improves edge-matching of 1:24,000 scale geologic maps and supports compilation mapping at scales of 1:100,000 and larger. The revision eliminates the names Greenland Gap Group, Scherr Formation and the Minnehaha Springs Member of the Scherr Formation; reassigns all strata previously designated as Scherr Formation by Dennison (1970) to the upper Brallier Formation; and abandons the basal Mallow Member of the Foreknobs Formation, placing its strata within the upper Brallier as originally defined by Butts (1918). The contact between the Brallier and Foreknobs formations is placed at the base of the first mappable, ridge-forming package of fine- to coarse-grained, cross-bedded, sandstone beds, often containing rounded quartz pebbles with minor interbeds of shale and siltstone. This contact may be gradational in places but, even in absence of good exposure, can usually be distinguished topographically in recently produced lidar-derived imagery as having elevated relief due to the presence of more resistant, compositionally mature coarse-grained sandstone-rich strata. Applying this criterion for mapping the contact between the Brallier and Foreknobs formations has resulted in reconciliation of mismatches of geologic contacts along several 7.5-minute quadrangle boundaries in the states of Virginia, West Virginia, Maryland and Pennsylvania. A new reference section at Baker, West Virginia showcases the contacts between the Harrell Shale, Brallier Formation, Foreknobs Formation and Hampshire Formation. A digital outcrop model of the reference section is provided for future preservation.

Maryland, Pennsylvania, Virginia, West Virginia↗
USGS2025

Using public participatory geographic information systems (PPGIS) to explore uses and values for Mojave Trails National Monument, California

Many people ascribe a variety of values to public lands and waters, but some values are more difficult to assess and quantify than others. Public participatory geographic information systems (PPGIS) are tools that have been used to help quantify and map the public’s diverse values for a landscape. This work describes the first known Office of Management and Budget–approved use of PPGIS by a Department of the Interior bureau. The U.S. Geological Survey developed an internet-based application to aid in gathering PPGIS data, called Values Mapping for Planning in Regional Ecosystems (VaMPIRE). Further, this work describes the first pilot of the VaMPIRE application in coordination with the Bureau of Land Management to collect spatial data and other survey data regarding the public’s uses of and values for locations within Mojave Trails National Monument. We emailed the link to the VaMPIRE application to an interested party email list in 2024 with 207 valid emails and received 74 responses; we also received 47 responses from members of an off-roading social media group. Of the list of 16 value options, recreation was the most popular value for the monument, followed by wilderness and inspirational. Over 1,000 points were placed throughout the monument, indicating locations people use or value, with the locations spread throughout the entire monument. Additionally, most survey respondents stated their ability to receive benefits in locations they mapped would not change in response to a hypothetical scenario related to recreational facility development. This report describes exploratory results from the first use of the VaMPIRE tool in Mojave Trails National Monument and includes reflections on how the process went and considerations for future use of VaMPIRE.

California↗
USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗
USGS2025

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

Alaska↗
USGS2026

Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system

Computation of detailed groundwater flow budgets for subdivisions of the Virginia Coastal Plain aquifer system has enabled quantification and more thorough understanding of groundwater flow within this important water resource. A zone budget analysis based on previously published groundwater models of the Virginia Coastal Plain and Virginia Eastern Shore indicates that groundwater conditions vary substantially throughout the Coastal Plain aquifer system because of local variations in hydrogeology and historical and ongoing variations in groundwater use and management. Decades of substantial groundwater withdrawal from the Coastal Plain aquifer system have altered groundwater flow from predevelopment conditions. Rates of sustainable withdrawal are limited because the downward groundwater flow rate into confined aquifers is a relatively small part of the total groundwater budget for the aquifer system compared to the rate of recharge at the land surface. Analyses of groundwater budgets from the Virginia Coastal Plain model indicate that groundwater flow is generally outward from the surficial aquifer to rivers and coastal waterbodies and downward through a series of underlying aquifers and confining units to the Potomac aquifer, which is the deepest aquifer and the source of most groundwater withdrawals. Downward flow into the Potomac aquifer is estimated to be only 7 percent of total net precipitation-derived net recharge at the land surface but makes up about 66 percent of inflow to the aquifer in Virginia, with much of the remaining inflow occurring laterally from outside of defined groundwater budget regions in Virginia. For several decades prior to 2010, high rates of withdrawal from the Potomac aquifer resulted in substantial decline in groundwater storage in the aquifer and in most overlying aquifers and confining units. From 2010 to 2023, rates of withdrawal substantially lower than the historical maximum resulted in small net increases in groundwater storage in the confined aquifer system for most regions of the Virginia Coastal Plain. Nevertheless, for the same period, groundwater storage for the entire model domain continues to incrementally decline, indicating that storage recovery in Virginia is offset by a continued decrease in storage in areas beneath the Chesapeake Bay or adjacent areas of Maryland and North Carolina. Withdrawals from the Potomac aquifer have induced substantial downward flow which is a large part of groundwater budgets for confined aquifers such as the Potomac. For the most recent simulated conditions (2023) downward groundwater flow continues, but because vertical flow rates are a function of the difference between water pressure in the upper surficial systems and lower confined units, rates of downward flow are lower than those in earlier decades as the confined water levels partially recover from larger groundwater withdrawals in the past. Geographically, groundwater flow is generally inward from perimeter regions of the Virginia Coastal Plain toward central regions with the largest withdrawal rates. Groundwater inflow from coastal regions could be contributing to saltwater intrusion, even though that was not measured in this study. Analyses of groundwater budgets from the Virginia Eastern Shore peninsula, a geographic region of the Virginia Coastal Plain, indicate that groundwater flow for that isolated aquifer system is generally outward from the surficial aquifer to coastal water bodies and downward into the confined Yorktown-Eastover aquifer system, which is the source of most withdrawals. Downward groundwater flow into the confined Yorktown-Eastover aquifer system is estimated to be less than 2 percent of total recharge and less than 9 percent of net recharge at the water table but makes up more than 93 percent of all inflow to the confined aquifer system. Decades of substantial but relatively consistent groundwater withdrawals have induced greater downward flow rates into the confined aquifer system but also have resulted in loss of groundwater from storage. For the most recent simulated period (2023), estimated storage loss accounts for slightly under 7 percent of withdrawals from the confined aquifer system. The reported withdrawal rate for this period from the confined Yorktown-Eastover system is near the highest reported rate for the Virginia Eastern Shore, which means that the storage depletion is expected to continue, even though groundwater levels appear to be relatively stable. Estimated groundwater flow rates upward from the confining unit underlying the Yorktown-Eastover system and low rates of inflow from coastal water bodies underscore ongoing concerns about up-coning and lateral intrusion of salty groundwater.

Virginia↗
USGS2024

Recent advances in characterizing the crustal stress field and future applications of stress data: Perspectives from North America

The stress field controls patterns of crustal deformation, including which faults are likeliest to cause earthquakes or transmit fluids. Since the 1950s, maps of maximum horizontal stress ( S Hmax ) orientations have advanced dramatically, and the style of faulting (relative principal stress magnitudes) has recently been mapped in some regions as well. This perspectives paper summarizes developments in characterizing stress orientations and (relative) magnitudes, including new seismic and borehole methods, as well as progress in identifying the causes of stress variations. Despite these advances, adding far more spatiotemporal detail would allow geoscientists to address many of today's key challenges regarding natural hazards, energy development, and geodynamics. In particular, it is critically important to characterize stress heterogeneity at multiple scales while also recognizing the coherent variability of the stress field. The second part of the paper considers how more detailed stress datasets could prove essential to addressing some of the grand questions in geoscience, including deciphering the poorly understood feedbacks between crustal dynamics and surface processes, improving earthquake and eruption forecasts, and determining the origins and shared properties of plate boundaries.

Geological Society, London, Special Publications↗
USGS2025

Revisiting an enigma on California's north coast: The Mw6.5 Fickle Hill earthquake of 21 December 1954

Many earthquakes occur along the North Coast of California in the vicinity of the Mendocino Triple Junction (MTJ), where the Pacific, Gorda, and North American (NA) plates meet, and on the adjacent plate boundaries. The MTJ marks the nexus of the Mendocino and San Andreas faults with the Cascadia subduction zone (CSZ). Historically, most large earthquakes around the MTJ have been within the offshore Gorda plate and its subducted portion beneath the NA plate. North of the MTJ, active faults mapped in the NA plate are part of the CSZ fold‐and‐thrust belt. Although some events have been detected in the NA plate, no large historic events have been associated with mapped surface faults. The 21 December 1954 M w 6.5 earthquake in Humboldt County is one possible exception. Using published data from catalogs and articles, unpublished data from Berkeley’s archives, and S ‐ P times interpreted from two U.S. Coast and Geodetic Survey (USCGS) accelerometers, we determine a probability cloud for the earthquake’s hypocenter using NonLinLoc. The highest probability location lies beneath Fickle Hill just east of the city of Arcata, California, at 40.87° N, 124.03° W, and ∼11 km depth. Using P ‐wave polarities from Berkeley stations and the digitized waveforms from the accelerometers, we find that the focal mechanism most consistent with the data indicates thrust movement with strike, dip, and rake of 350°, 10°, and 90°, respectively, at a depth of 14 km. Given the depth uncertainties of both this event and the megathrust, this implies that the earthquake most likely took place on the subduction interface rather than on the mapped faults in the Mad River fault zone that trend 322° and dip to the northeast. The revisited intensity in the epicentral region also supports a location beneath Fickle Hill to the east of the city of Arcata, California.

California, Idaho, Nevada, Oregon, Washington↗
USGS2025

Preliminary field report of landslide hazards following Hurricane Helene

Executive Summary This report reflects our knowledge regarding the widespread landslide activity associated with Hurricane Helene observed during the U.S. Geological Survey’s (USGS) mission assignment to North Carolina in October 2024. The material in this report was originally prepared for the Federal Emergency Management Agency under mission assignment DR-4827-NC. The data and commentary in this report are reflective of a report provided to the Federal Emergency Management Agency (FEMA) on October 18, 2024, as well as information provided in briefings at the Buncombe County Emergency Operations Center. The report has been modified for public dissemination. This assessment was based on systematic visual examination and mapping of landslide locations from aerial and satellite imagery, visual and photographic observations from low-level helicopter overflights and conversations with local landslide experts from the North Carolina Geological Survey and Appalachian Landslide Consultants PLLC, and more than 50 years of combined landslide hazard professional experience of the mission-assigned field team. No systematic field investigations were done by the USGS. While responding to the event, the USGS did not identify any landslides that posed an immediate major threat to recovery personnel in parts of nine counties in North Carolina (Avery, Buncombe, Henderson, McDowell, Mitchell, Polk, Rutherford, Watauga, and Yancey); however, threats from renewed landslide activity may remain heightened in localized areas for months or even years. Known areas of the most abundant landslide occurrence include Bat Cave, Lake Lure, Chimney Rock, Swannanoa, Black Mountain, Fairview, steep areas in Asheville, and the Blue Ridge Parkway. The USGS shared detailed locations of known landslides with the Emergency Operations Centers. The thousands of landslide scars on hillsides and landslide deposits on flatter ground may present some threat to recovery activities. Soil and rocks will continue to erode from newly exposed landslide scars and may pose a threat to people and infrastructure who are immediately nearby. In general, the steeper and taller the landslide scar, the greater the potential threat. This threat is heightened during periods of rainfall and increases with the duration and intensity of rainstorms. Very heavy rainfall, or repeated rainfall events during short periods, could also initiate new landslides on steep slopes. Excavation of landslide deposits, particularly excavation of those deposits directly adjacent to steep slopes, may also pose a threat to nearby people and equipment. An interagency collaborative mapping effort led by the USGS that informed this assessment identified 1,155 landslide locations by the October 2024 briefings, but that number increased to 2,217 in a final reviewed version of the locations published in January 2025. Locations were mapped from satellite imagery, fixed-wing and helicopter surveys, media and social media, and field reports in the 3 weeks following the passage of the remnants of Hurricane Helene. USGS products outlined in this report are publicly available and include geotagged photographs from aerial reconnaissance, hazard models, an interactive view of mapped landslide locations, and landslide safety and education resources.

North Carolina, South Carolina, Tennessee, Virgini↗
USGS2025

Land cover change within wetland complexes at Dixie Meadows, Churchill County, Nevada: 2015 – 2023

Dixie Meadows, Nevada, is a system of geothermal springs and seeps that feed a complex of marshes and wetland meadows that are located within lands managed by the Bureau of Land Management (BLM) and the Department of Defense (DOD). A previous U.S. Geological Survey report documented variability in satellite imagery-based land cover classifications for seven wetland complexes at near monthly time intervals between October 2015 and January 2022. This report presents additional data, extending analysis to November 2023. Land cover classifications between October 2015 and November 2023 demonstrated an association between vegetation cover characteristics and surface moisture, with Class 1 having dry, bare soil or sparse upland vegetation, Class 2 having moist, bare soil or sparse to small vegetation, Class 3 having dense green vegetation with potentially saturated soil conditions, Class 4 having a mix of shallow surface water, saturated soil, and dense green vegetation, and Class 5 having open surface water. Most of the wetland complexes occur close to spring outflows primarily within land managed by the DOD, though portions are also within BLM lands. The intervening and surrounding landscape outside of the wetland complexes assessed in this study are managed by the BLM. As a result, Class 1 land covers had the largest areal coverage for BLM managed lands. Classes 2 and 3 land covers were primarily mapped inside the wetland complexes and thus had the largest area coverage within DOD managed lands. Class 4 was almost exclusively mapped within the wetland complexes and thus was largely contained within DOD managed lands. Class 5 (open water) was exclusively mapped in and adjacent to a single wetland complex with catchment ponds on land managed by the BLM. The distribution of these land cover classes over the study period was seasonally and annually variable. Land cover areas of Classes 1 and 2 were larger during the spring months. Conversely, land cover areas of Classes 3 and 4 tended to be greatest during the summer or fall. These patterns might be influenced by differences in seasonal water sources and phenology.

Nevada↗
USGS2024

Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning

Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies, and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. High concentrations of lithium in brines have been observed in the Smackover Formation in southern Arkansas (>400 milligrams per liter). We used published and newly collected brine lithium concentration data to train a random forest machine-learning model using geologic, geochemical, and temperature explanatory variables and create a map of predicted lithium concentrations in Smackover Formation brines across southern Arkansas. Using these predicted lithium maps with reservoir parameters and geologic information, we calculated that there are 5.1 to 19 million tons of lithium in Smackover Formation brines in southern Arkansas, which represents 35 to 136% of the current US lithium resource estimate. Based on these calculations, in 2022, 5000 tons of dissolved lithium were brought to the surface within brines as waste streams of the oil, gas, and bromine industries.

Arkansas↗
USGS2025

Exploration for blind geothermal systems in the eastern Great Basin of Utah: An update on the “Lund North” INGENIOUS detailed study site

Existing geothermal production in Utah is commonly collocated with surficial expressions of geothermal heat including active hot springs and hot spring deposits. However, geothermal potential across the Great Basin region is thought to be much higher for hidden or blind geothermal systems. Accordingly, exploration techniques that can locate geothermal resources that lack surface thermal features could support future development of these systems. The goal of the INGENIOUS project is to reduce exploration risk and discover new, economically viable hidden geothermal systems in the Great Basin region. This paper summarizes the efforts and preliminary results of blind geothermal resource prospecting in Utah as part of the larger INGENIOUS project. The Lund North site in the Basin and Range province of southwest Utah was designated as the fourth detailed study site for the project. The site was initially identified from the preliminary Play Fairway Analysis (PFA) geothermal favorability map, which is based on various data elements, and the identification of favorable structural settings across Utah. This site contains existing legacy data including a thermal gradient borehole with a heat-flow value exceeding 220 mW/m 2 . New data collected at this site include terrestrial gravity, magnetotellurics, transient electromagnetics, fluid geochemistry, geologic mapping, UAV-based lidar, paleomagnetism, aeromagnetic surveys, and a shallow temperature survey. Preliminary data and model interpretations corroborate the presence of a large, east-dipping, northeast-southwest-trending normal fault on the edge of a typical Basin and Range graben. Quaternary fault mapping refined by high-resolution lidar surveys suggests a complex step over fault geometry. Utilizing multi-disciplinary datasets for further site assessment at Lund North will facilitate the development of a local-scale PFA and geothermal conceptual model. This new data will be used to site successive thermal gradient drilling to verify heat flow with temperatures at depth at the Lund North site and further investigate the existence of a local geothermal system.

Utah↗
USGS2024

Perspectives on transportable array Alaska background noise levels

Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.

Book chapter↗
USGS2025

Total uncertainty quantification in inverse solutions with deep learning surrogate models

We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.

Journal of Computational Physics↗
USGS2026

Deformed submarine terraces in Puget Sound, Pacific Northwest, indicate only one M >~7.5 earthquake on the Seattle fault zone in the past 11,000 yr

Submerged marine terraces in Puget Sound, deformed across the Seattle fault zone (SFZ), indicate that only one earthquake as large as M~7.5 has occurred in at least the past 11 kyr. Previous paleoseismic studies document a M~7.5 earthquake between 923–4 CE, which uplifted coastal marine terraces by as much as 8 m. We demonstrate that this earthquake was the only such event since ~11 ka by mapping and quantifying deformation of older marine terraces, now submerged in Puget Sound. The submerged terraces, attributed to a late-glacial sea-level lowstand, record both glacial isostatic rebound and tectonic deformation. Vertical offset of the ~11 ka terraces within the SFZ is comparable to that of the marine terraces uplifted in 923 CE, implying no additional large (M>~7.5) earthquake on the SFZ since ~11 ka. This result implies a longer recurrence interval than current hazard estimates, which assumes recurrence of M>7.1 events every 5 kyr. Our mapping of SFZ deformation since ~11 ka also supports fault segmentation and contiguous block uplift between the Seattle and Tacoma fault zones.

Washington↗
USGS2024

Greater sage-grouse habitat of Nevada and northeastern California—Integrating space use, habitat selection, and survival indices to guide areas for habitat management

Executive Summary Greater sage-grouse populations ( Centrocercus urophasianus ; hereafter sage-grouse) are threatened by a suite of disturbances and anthropogenic factors that have contributed to a net loss of sagebrush-dominant shrub cover in recent decades. Declines in sage-grouse populations are largely linked to habitat loss across their range. A key component of conservation and land use planning efforts for sage-grouse involves the continued monitoring and modeling of habitat requirements and suitability across its range. The Bureau of Land Management (BLM) is addressing the management of sage-grouse habitats on BLM-authorized public lands throughout the western United States through a land use planning amendment and associated environmental impact statement (86 FR 66331). More than 25 percent of the range-wide distribution of sage-grouse is within Nevada and northeastern California, and information on sage-grouse distribution and habitat requirements is important to guide appropriate management decisions. Therefore, the BLM has identified the need for updated spatially explicit information on sage-grouse habitat in Nevada and northeastern California to guide the land use planning amendment and associated management decisions. To address this need, researchers with the U.S. Geological Survey, in close cooperation with multiple State and Federal resource agency partners, including BLM, Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW), sought to map sage-grouse distribution and produce example habitat designations in these states. Herein, we report results of our primary study objective, which was to map sage-grouse habitat and create example habitat management areas, based on more than a decade of location and survival data collected from marked sage-grouse across the study region coupled with lek count survey data managed by the NDOW and the CDFW. We expanded on previously developed methodology to incorporate information on habitat selection and survival during reproductive life stages and specific seasons with updated sage-grouse location and known fate datasets, while also including brood-rearing areas that are understood to be threatened and important for population persistence. We combined predictive habitat map surfaces for each life stage and season with updated information on current occupancy patterns to classify habitat based on its suitability and probability of occupancy. We carried out additional steps to delineate specific example habitat management areas, specifically (1) incorporated corridors connecting key nesting and brood-rearing habitat, (2) corrected outputs for pre-wildfire habitat conditions within areas burned in the last 16 years, and (3) masked out areas of anthropogenic development. Our methodological example of deriving habitat management areas was intended to help inform decisions by BLM and other land managers regarding conservation and management of sage-grouse. Associated data products in the form of habitat maps provide updated, detailed, and comprehensive information about the status of habitats and can be useful to partner agencies in their efforts to designate and rank habitats for this species of high conservation concern in Nevada and California, with full recognition that on-the-ground field data and local sources of information and expertise should be used in conjunction with inferences from these models.

California, Idaho, Nevada↗
USGS2024

Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning

Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.

Michigan, Wisconsin↗
USGS2026

Use of precariously balanced rocks to constrain postglacial earthquake magnitudes in New England, United States

We use the age and fragility of 13 precariously balanced rocks (PBRs) in Massachusetts, New Hampshire, and southwestern Maine to evaluate the estimated probabilistic seismic hazard (PSH) from the U.S. Geological Survey’s National Seismic Hazard Model (NSHM), and also develop a map of maximum postglacial earthquake magnitudes in the region. The PBRs are erratic boulders left behind by the retreat of the Laurentide ice sheet between 13 and 18 ka, and published ice retreat maps are used to estimate their fragility ages. The fragilities and ages of the rocks appear to be consistent with the NSHM, in that the estimated earthquake magnitudes and resulting ground motions that would topple them are only expected on timescales longer than their fragility ages. This result, on the North American passive margin, contrasts with PBR studies at active plate boundaries, where the PBR constraints imply large reductions to estimated PSH. It may be that the PBRs are not old enough in the eastern United States to reveal the same PSH modeling issues as those revealed in the plate boundary settings. The study provides constraints on maximum magnitudes of postglacial earthquakes across much of Massachusetts, New Hampshire, and southwestern Maine, with the constraints limited to the ages of the PBRs.

Maine. Massachusetts, New Hampshire↗
USGS2024

StreamStats—A quarter century of delivering web-based geospatial and hydrologic information to the public, and lessons learned

StreamStats is a U.S. Geological Survey (USGS) web application that provides streamflow statistics, such as the 1-percent annual exceedance probability peak flow, the mean flow, and the 7-day, 10-year low flow, to the public through a map-based user interface. These statistics are used in many ways, such as in the design of roads, bridges, and other structures; in delineation of floodplains for land-use zoning and setting of insurance rates; for regulatory purposes, such as the permitting of wastewater discharges; and for hydrologic and climate change studies. StreamStats was first developed for Massachusetts and released in 2001. The application provided users with the ability to obtain streamflow statistics computed from data collected at USGS streamgages and to obtain estimates of streamflow statistics for user-selected ungaged sites. Massachusetts StreamStats used geographic information system software and digital mapping to compute drainage-basin characteristics, which were then used in statistical models to estimate streamflow statistics for the user-selected sites. The statistical models were in the form of equations that were developed through a process known as regression analysis. StreamStats was the first known web application with the ability to do interactive geoprocessing. The utility of Massachusetts StreamStats was instantly apparent, leading the USGS to develop a version of StreamStats that could be implemented nationally. USGS State offices normally were required to develop custom regression equations and prepare local digital mapping data needed for implementing StreamStats for their States. Funding needed to complete this work usually was provided through cooperative agreements between the USGS and State agencies. In 2004, Idaho became the first to be released in the national version of StreamStats. By 2023, 44 States were fully implemented and six were undergoing implementation. StreamStats has undergone many modifications over the years to keep up with changes to the underlying software and to add functionality. Customized functionality and separate linked StreamStats applications were developed for several States. Meeting the high demand for additions and improvements to StreamStats while also adhering to budgetary constraints has, at times, been challenging. The StreamStats development team has identified numerous additional improvements that could be made to provide better performance and more functionality. The lessons learned from the experience of building and operating StreamStats for nearly 25 years could be relevant to others interested in pursuing efforts of a similar scale.

Circular↗