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USGS2025

A synthesis engine for constructing geologic maps of the United States

The geologic history of the United States is cataloged in thousands of geologic maps produced during many decades. However, the disparate nature of these individual maps makes it challenging to assess resources, research geologic histories, or characterize natural hazards holistically across the Nation. The U.S. House of Representatives 2020 appropriations bill for the U.S. Department of the Interior (H.R. 116-100) requires the U.S. Geological Survey to “bring together detailed national and continental-resolution [two-dimensional] and [three-dimensional] information produced throughout the Survey and by [F]ederal and [S]tate partners.” In response to this directive, this report presents a compilation and synthesis of geologic maps across the United States in the form of a relational database. The synthesis database includes thematic maps that synthesize the Nation’s geology, and retains the original input maps as well as linkages to standardized vocabularies to aid the discoverability of geologic information. Specifically, the synthesis database is targeted toward producing four National-resolution maps for the conterminous United States: Quaternary geology, the geology at the Earth’s surface, pre-Quaternary geology, and Precambrian geology. In addition, the synthesis database includes the infrastructure necessary to expand to additional resolutions in the future.

conterminous United States↗
USGS2024

Are field observations of surface rupture useful? An example from the 2023 Mw 7.8 Pazarcık, Turkey (Türkiye), earthquake

Field investigations have long been an important component of the scientific response to surface‐faulting earthquakes. However, in light of advances in remote data and models, the question arises whether field‐based observations of surface rupture remain useful for understanding rupture processes and seismic hazards. We approach this question using a field‐based study of the central 2023 M w 7.8 Pazarcık, Turkey (Türkiye), earthquake rupture, at the intersection of the east Anatolian fault (EAF) and Narlı fault. Our field observations include the surface rupture expression and extent of the central EAF and northernmost Narlı fault in generally forested and steep terrain and 68 measurements of left‐lateral surface displacement. These data improve our understanding of the Pazarcık rupture complexity, resolve the surface geometry of the Narlı fault–EAF connection, and exhibit a clear (>2 m) change in surface displacement across this intersection zone that confirms remote‐based coseismic slip models. Our study shows that focusing field efforts in areas of obscured or low‐resolution remote data can yield essential data for refining rupture extent, documenting perishable on‐fault displacement, and improving postearthquake situational awareness. A comparison of similarly large‐magnitude continental surface‐rupturing earthquakes indicates that displacement uncertainties relate to a complex set of factors, including measurement methods, rupture complexity, and displacement magnitude. Our study validates the need for postearthquake field observations, which, when driven by clear motivating questions and knowledge of methodological strengths and limitations, provide high‐resolution rupture data that complement remote‐based models.

Pazarcık↗
USGS2025

Site-specific, extended ShakeMaps for earthquake engineering applications

The U.S. Geological Survey (USGS) routinely produces ShakeMaps of shaking intensity across the globe. Due to practical constraints, the number of response spectral periods was limited to three standard periods (0.3, 1.0, and 3.0 sec). We have recently developed the tools that are necessary to expand this functionality to include 22 periods (matching the current U.S. National Seismic Hazard Model periods) as well as the orientation-independent components (e.g., “RotD50”). We refer to ShakeMap products that include these extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool called the “ShakeMap Sampling Tool” (SST) that gives all the estimated shaking metrics for a specific location (or list of locations). Additionally, we develop a web application where users can input locations of interest and view/download the SST results. We further familiarize users with the concept of “Composite ShakeMaps.” For earthquakes sequences such as a mainshock and larger foreshocks and aftershocks, this provides a map of the maximum value of each shaking metric, which is useful for overall loss estimates, the full extent of ground failure triggering potential, and a better portrayal of the repeated shaking levels at a given point for a series of earthquakes. Such a site-specific shaking history facilitates earthquake forensics at building or infrastructure sites for which damage may be of concern, as described in the Disproportionate Damage Earthquake trigger specified in the IEBC (2018, Section 405.2.2) and in developing ATC-145 guidelines (Guidelines for Post-Earthquake Assessment, Repair, and Retrofit of Buildings). The composite ShakeMap can be combined with the SST for a variety of earthquake-hazard applications, such as systematically inferring triggering shaking estimates at specific sites of geotechnical interest for landsliding, liquefaction, and lateral-spreading hazards.

Kahramanmaraş↗
USGS2024

Utilization of stochastic ground motion simulations for scenario-based performance assessment of geo-structures

Probabilistic seismic performance assessments of engineered structures can be highly sensitive to the seismic input excitation and its variability. In the present study, the scenario-based performance assessment recommended by Federal Emergency Management Agency (FEMA) P-58 guidelines is adopted to estimate seismic fragility of concrete dams for various seismic hazard scenarios. Due to the scarcity of recorded ground motions and thereby their poor representation of uncertainties, stochastic ground motion simulation methods are utilized to obtain the required input excitations. Moreover, to understand the uncertainty in ground motion simulation models, two broadband stochastic simulation models are used to generate input excitations representing six seismic hazard scenarios defined by earthquake magnitude, source-to-site distance, and soil conditions. Optimal intensity measure parameters for each scenario are identified using a systematic procedure that considers criteria such as efficiency, practicality, proficiency, sufficiency, and hazard compatibility. Fragility curves and surfaces are derived using the cloud analysis technique, taking into account various damage measures and limit state functions. The study finds that the derived fragility curves are particularly sensitive to the selection of earthquake scenarios, the choice of records, and the methods used to calculate fragility curves, with less sensitivity observed to different engineering demand parameters. Given this sensitivity, particularly to ground motion selection, the study highlights the necessity of incorporating both model-to-model variability (epistemic uncertainty) and record-to-record variability (aleatory uncertainty), alongside the established material and modeling uncertainties, in the probabilistic seismic assessment.

Reliability Engineering and System Safety (RESS)↗
USGS2026

Simulated ground motion dataset in the Azores Plateau, Portugal, on rock and soil sites

Building on a previously developed bedrock dataset, this study extends the Azores Plateau ground motion simulations to include soil-amplified records and introduces a comprehensive validation framework. Soil amplification is modeled using one-dimensional soil profiles. A stochastic source-based approach is employed to generate the dataset, incorporating randomization of input-model parameters to account for the aleatory uncertainty in seismic activity. The accuracy of the dataset is verified through a comprehensive validation framework, showing that the randomization effectively captures variance and inter-period correlation observed in records. This work provides a robust dataset for advancing seismic hazard and risk assessment in the Azores Plateau.

central and eastern Azores islands↗
USGS2025

Unlocking ecological insights from sub-seasonal visible-to-shortwave infrared imaging spectroscopy: The SHIFT campaign

We stand at the threshold of a transformative era in Earth observation, marked by space-borne visible-to-shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter- and intra-annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub-seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open-source processing methods and cloud-based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high-frequency time series data from space-borne VSWIR imaging spectrometers.

Ecosphere↗
USGS2025

Fiber-imaged supershear dynamics in the 2024 Mw 7 Mendocino Fault earthquake

Fault structure and rupture physics are deeply intertwined, and observations of this coupling are critical for understanding earthquake behavior. Rupture propagation is observable at fine scales using dense seismic networks. Fiber-optic sensing allows for long-term deployments of ultradense arrays that enable high-resolution measurements of infrequent, large earthquakes. We recorded the 2024 moment magnitude ( M w ) 7 Mendocino Fault earthquake with a nearby fiber-optic array and imaged its behavior with seismic beamforming. The rupture propagated to the east at subshear velocity; stagnated near the Mendocino Triple Junction, a zone of structural complexity; and subsequently transitioned to supershear velocity. The correlation between source physics and structure shows how lithospheric heterogeneity affects first-order characteristics of earthquake ruptures. Our results also demonstrate the potential for fiber-optic sensing to improve real-time estimation of key parameters for early warning.

California↗
USGS2024

Hyperspectral (VNIR-SWIR) analysis of roll front uranium host rocks and industrial minerals from Karnes and Live Oak Counties, Texas Coastal Plain

VNIR-SWIR (400–2500 nm) reflectance measurements were made on the surfaces of various cores, cuttings and sample splits of sedimentary rocks from the Tertiary Jackson Group, and Catahoula, Oakville and Goliad Formations. These rocks vary in composition and texture from mudstone and claystone to sandstone and are known host rocks for roll front uranium occurrences in Karnes and Live Oak Counties, Texas. Spectral reflectance profiles, 569 in total, were reduced to 125 representative spectral signatures, which were analyzed using the U.S. Geological Survey's (USGS) Material Identification and Characterization Algorithm (MICA). MICA uses an automated continuum-removal procedure together with a least-squares linear regression to determine the fit of observed sample spectral absorption features to those of reference mineral standards in a spectral library. The reference minerals include various clay, mica, carbonate, ferric and ferrous iron minerals and their mixtures. In addition, absorption feature band-depth analysis was done to identify rock surfaces exhibiting absorption features related to uranium and zeolite minerals, which were not included in the command files used to execute MICA. Rocks from each of the four geologic units produced broadly similar spectral signatures as a result of comparable mineral compositions, but there were some notable differences. For example, Ca- and Na-montmorillonite was matched most frequently to the spectral absorption features in 2-μm (∼2000–2500 nm) wavelengths, while goethite occurred often at 1-μm (∼400–1000 nm) wavelengths. The latter is related to limonitic iron-staining in and around oxidized zones of the uranium roll front as described in previous papers. Rocks of the Jackson Group differed from those of the Catahoula, Oakville and Goliad units in that the former exhibited spectral features we interpret as being due to the presence of lignite-bearing mudstone layers. Goliad rocks exhibit spectral features related to dolomite, gypsum, anhydrite, and an unidentified green clay mineral that is possibly glauconite . Jackson Group rocks also exhibit weak but well-resolved absorption features at 964 and 1157 nm related to either or both zeolite minerals clinoptilolite and heulandite. These zeolite minerals and a few spectra exhibiting hydrous silica absorption features are indicative of alteration of volcanic glass in tuffaceous mudstone and claystone layers. A few sample spectra exhibited strong absorption features at around 1135 nm related to the uranium mineral coffinite. Both the 1135 nm coffinite and 1157 nm zeolite absorption features overlap somewhat, potentially making them difficult to distinguish without additional hyperspectral field, laboratory or remote sensing data. The results of this study were compared to mixtures of minerals described for ore, gangue and alteration minerals in deposit models for sandstone-hosted uranium, sedimentary bentonite and sedimentary zeolite. Use of these spectra can help facilitate mapping of both waste materials from the legacy mining of the above commodities, as well as future exploration and resource assessment activities.

Texas↗
USGS2025

Surface-wave relocation and characterization of the October 2023 tsunamigenic seismic unrest near Sofugan volcano, Izu Islands, Japan

A moderate-magnitude earthquake swarm occurred in the remote Izu Islands region of Japan between October 1 and 8, 2023. The swarm included 151 shallow earthquakes cataloged by the U.S. Geological Survey, which notably included a roughly 2.5-hr episode of 15 successive magnitude (M) < 5.5 earthquakes. Origin times were coincident with regionally recorded tsunami waves, but tsunamigenesis for moderate-magnitude earthquakes is uncommon, indicating that volcanic activity generated the ocean displacements. Leveraging a surface-wave relative relocation approach, we estimate precise epicentroid locations for the remote swarm. Final epicentroids and caldera analogs indicate a three-stage model to explain swarm activity: (a) caldera pressurization due to magma intrusion, (b) depressurization via dike propagation away from the caldera, and (c) eruption corresponding with caldera reactivation either by collapse or additional intrusion.

Sofugan volcano, Izu Islands↗
USGS2026

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗
USGS2026

USGS 2025 critical minerals review

The United States Geological Survey (USGS) provides scientific information for the Department of Interior and the nation, consistent with its original mission expressed in the Organic Act of 1879 (43 U.S.C. 31): “the classification of the public lands and examination of the geological structure, mineral resources, and products within and outside the national domain.” Legislation such as the Energy Act of 2020 and the 2022 Infrastructure Investment and Jobs Act (43 USC 31l) and recent executive actions (Executive Orders 14154 , 14153, 14241 Secretary’s Orders 3417, 3418, 3422, 3436) underscore the importance of mineral resources and focus USGS activities on mapping and assessing mineral resources, with a particular focus on those presently identified as critical, both in ground and above ground in mine wastes. This article reviews selected activities and accomplishments by the USGS Mineral Resources Program related to critical minerals in 2025. Highlights include a new List of Critical Minerals, a first-ever national mine waste inventory, international minerals partnerships, mineral resource assessment advancements, and national data collection activities and outcomes of the Earth Mapping Resources Initiative (Earth MRI). The selected contributions are not comprehensive but are intended to demonstrate USGS leadership in critical mineral mapping and assessment, the importance of domestic and global partnerships, and the breadth of research activities that are responsive to national needs and priorities.

Mining Engineering↗
USGS2026

Assessing environmental drivers of denitrification in restored riverine floodplains

Restoration of impaired floodplains is an increasingly prevalent strategy for alleviating water quality concerns and reducing downstream flooding at watershed scales. Floodplains temporarily store water and slow flow velocity to promote sedimentation during overbank flooding and remove inorganic nitrogen from floodwater and groundwater via denitrification. Evaluating the impacts of different restoration strategies on denitrification can inform more strategic investments into floodplain modifications that improve water quality outcomes. Our research investigates how denitrification rates in floodplains respond to environmental factors that are actionable from an engineering perspective through design and water resources management. We seasonally measured soil denitrification enzyme activity and various environmental characteristics in 4 floodplains with different restoration design and management approaches at the confluence of the Wabash and Tippecanoe Rivers in Indiana, United States. Our results showed that denitrification rates in an agricultural floodplain were significantly lower than in restored floodplains with native vegetation. Certain soil conditions characteristic of floodplain wetlands were associated with higher denitrification, particularly elevated total nitrogen, moisture, silt, and organic matter contents. Vegetation species composition was correlated with denitrification rates. This link may reflect the direct effects of vegetation on soil conditions, such as supplying labile organic carbon, or indirect effects, such as vegetation acting as an indicator of hydrologic regime and land use. Denitrification seasonally varied, peaking in winter when nitrate supply from rivers draining agricultural watersheds in the region is also high. Substrate limitation of soil denitrification enzyme activity was most significant during the summer when overbank flooding, which replenishes soil nitrogen stocks, rarely occurs. Our findings indicate that denitrification capacity will likely be maximized in riverine floodplains that are restored as wetlands with diverse native vegetation and enhanced hydrologic connectivity. Such restoration activities promote higher denitrification rates via elevated moisture, fine sediment deposition, and soil organic matter.

Tippecanoe River, Wabash River↗
USGS2026

A process-based model for forecasting wave runup along the coast of Georgia

Wave runup is an important nearshore process that impacts total water level, sediment transport, and coastal design. Current methods for forecasting wave runup implement an empirical model that considers offshore wave height, wave period, and generalized beach slope. In this study, the authors generated wave runup forecasts from offshore wave conditions and a system of polynomial equations derived from numerical simulations at three different still water datums for each beach profile. They developed a process-based methodology that incorporated site-specific cross-shore topobathy into the phase-resolving numerical model. A comparison between the system of equations, deterministic hydrodynamic simulations, and observed high-water marks was made using Hurricanes Matthew (2016) and Irma (2017) for 12 cases, and it showed that the polynomials were capable of being consistent with the results from full simulation runs, while not requiring hours of runtime when a forecast was needed—the differences between the polynomial and the observed high water marks ranged from 3 to 32 cm for the Irma hindcast and 9–70 cm for Matthew. Then, using forcings from Hurricanes Ian and Nicole (2022), the model predicted the occurrence of dune collision, overwash, and inundation for the coast of Georgia and suggested that wave runup was impacted by the still water level and local topobathy.

Georgia↗
USGS2024

Framework for mapping liquefaction hazard–Targeted design ground motions

Liquefaction-induced ground failure poses substantial challenges to geotechnical earthquake engineering design. Current approaches for designing against liquefaction hazards, as specified in most seismic provisions, focus on estimating a liquefaction factor of safety ( 𝐹⁢𝑆𝐿 ) and typically characterize earthquake loading using design parameters based on probabilistic or deterministic ground motion levels. Because 𝐹⁢𝑆𝐿 is estimated deterministically, this basis of design neglects considerable uncertainties for estimating liquefaction triggering and its consequences and results in a lack of liquefaction-specific design criteria, particularly as structural design has advanced toward risk-targeted performance objectives. This study presents a framework for developing liquefaction-targeted design criteria based on a minimum acceptable return period of liquefaction, informed by probabilistic liquefaction hazard analysis (PLHA). PLHA quantifies annualized rates of liquefaction by considering contributions from (1) the full ground-motion probability space, and (2) uncertainties in liquefaction triggering using probabilistic models. PLHA is used in this study to characterize the current, effective return periods of 𝐹⁢𝑆𝐿 ( 𝑇𝑅,𝐹⁢𝑆 ) obtained from conventional liquefaction hazard analysis (CLHA) using uniform-hazard ground motions. 𝑇𝑅,𝐹⁢𝑆 is evaluated in a parametric study of nearly 100 sites throughout the conterminous United States. The results indicate large geographic variations in acceptable liquefaction hazard levels, with implied 𝑇𝑅,𝐹⁢𝑆 ranging between approximately 1,000 to 3,000 years. To address these inconsistencies without the computational demands of full PLHA, a framework is proposed for developing a liquefaction-targeted design peak ground acceleration, 𝑃⁢𝐺⁢𝐴𝐿 , for use in liquefaction models that result in consistent liquefaction design levels across all geographic locations. The mapped 𝑃⁢𝐺⁢𝐴𝐿 is shown to be somewhat sensitive to site-specific properties, and adjustment factors are developed and presented. The proposed 𝑃⁢𝐺⁢𝐴𝐿 mapping procedure produces 𝐹⁢𝑆𝐿 estimates that are consistent with those obtained from full PLHA at a target 𝑇𝑅,𝐹⁢𝑆 , providing a promising roadmap to incorporating PLHA concepts into current liquefaction design methods.

Journal of Geotechnical and Geoenvironmental Engin↗
USGS2026

HyFlood: A surrogate-model-based framework for compound coastal flooding

Compound coastal flooding is a major threat to low-lying coastal regions and is expected to intensify under future climate change projections. However, modeling the joint interaction of waves, storm surge, tides, and rainfall remains computationally demanding, limiting the development of fast and reliable forecast tools. Here we present HyFlood, a hybrid statistical-numerical downscaling framework capable of computing and mapping high-resolution compound flood hazards while substantially reducing the computational cost compared with fully process-based hydrodynamic modeling. HyFlood combines statistical sampling and selection algorithms with a cascade of reduced-complexity surrogate models that emulate nearshore wave transformation, surf-zone hydrodynamics, and coastal, fluvial, and pluvial flooding. The surrogate models employ machine-learning and regression algorithms applied to a low-dimensional representation of the flooding outputs, obtained through statistical dimensionality reduction. The framework is demonstrated in southern O'ahu, Hawai'i, a region exposed to elevated sea levels driven by tides, waves, and storm surge along with frequent precipitation-driven flash flooding. Validation of the surrogates against the physics-based model outputs demonstrates that HyFlood accurately reproduces daily maxima of spatially distributed flooding depths. This hybrid approach offers a scalable and efficient tool to better quantify how changes in flooding drivers translate into hazard and impact assessments, and to support compound-flood risk assessments and climate-change adaptation planning.

Hawaii↗
USGS2026

From landslide susceptibility to risk assessment in the conterminous U.S.

Understanding the spatial distribution of landslide prone-areas and what consequences they may have is important for risk management and land-use planning. In the United States, although landslides occur in every state, a comprehensive landslide risk assessment is still missing. Existing efforts, such as the Federal Emergency Management Agency (FEMA)’s National Risk Index, rely on aggregated products and coarse cartographic units, limiting their geomorphological and practical accuracy. In this study, we present a methodological advance for landslide risk assessment across large areas with incomplete and sparse data. We apply our procedures to the conterminous United States by integrating geomorphologically meaningful partitions and spatial and temporal probability data-driven models. Landslide susceptibility is estimated using a Generalized Additive Mixed Model incorporating a bias capture/correction scheme to account for inventory inaccuracies (reference Area Under the Curve = 0.75). The exceedance probabilities of landslide occurrence are defined for three temporal scenarios (2, 5, and 10 year). Then, we explore the associated potential economic consequences for human settlements and agricultural areas. The findings indicate that the spatial variability of risk is primarily controlled by exposure rather than by susceptibility/hazard alone. The mean risk increases by ∼170% from the 2-year to the 10-year scenario. Beyond its quantitative outcomes, this study offers a blueprint for continental or sub-continental scale landslide risk assessments, demonstrating both the opportunities and current limitations.

Engineering Geology↗
USGS2025

Global patterns of coseismic landslide runout mobility differ from aseismic landslide trends

Coseismic landslides significantly contribute to human and economic losses during and immediately following earthquakes, yet very little data on the runout of such landslides exist. While well-established behavior of aseismic (e.g., hydrologically triggered) landslide runout mobility suggests strong correlation between landslide size and mobility, limited studies of coseismic landslide runout find conflicting mobility trends. We present a global dataset of runout lengths produced from a new automated method for estimating landslide runout, developed and validated using 1726 manually mapped landslides from five unique earthquakes. We then apply the automated runout tool to 23 global earthquake-induced landslide inventories, producing a compiled database of 73,665 measured and estimated runout lengths of coseismic landslides to assess mobility trends. We find a significant divergence between well-established aseismic mobility trends and that of coseismic landslides, with far greater scatter and more complex mobility patterns in earthquake-triggered landslides. As a function of landslide size, we observe global coseismic landslide mobility patterns are bilinear, becoming increasingly less mobile with increasing size above some threshold. This discordance between aseismic and coseismic landslide mobility may be a function of landslide type, kinematics, hydrology, and or setting that systematically differ between triggering mechanisms and should be explored in more depth to develop predictive models of these unique runout patterns. These results suggest hazard and risk models for coseismic landslides may significantly under-predict or over-predict impacts, depending on the size of triggered landslides.

Engineering Geology↗