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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,673 records · Page 86Linked to original sources
USGS2026

CRESCENT earthquake dynamic rupture, earthquake cycle, and tsunami code verification platform

Physics-based simulations are critical for understanding natural hazards. The increasing complexity of numerical codes requires benchmark exercises to verify that different computational methods yield consistent results when solving the same governing equations. Here, we present an open-access web platform designed for the verification of earthquake dynamic rupture, seismic cycle, and tsunami simulations. The platform architecture utilizes a modular, serverless backend on Amazon Web Services (AWS) to provide scalable file processing and visualization. A lightweight static web application provides a secure interface for uploading and managing results, while the browser-based data visualization enables interactive analysis of time series and surface grid data. By using structured JavaScript Object Notation (JSON) text files to define benchmark structures, the system remains fully extensible, allowing the addition of new scenarios without modifying the underlying software logic. The platform hosts the "The Tsunami Problem Versions" (TTPV) 1 & 2, two benchmarks for 3D fully coupled earthquake dynamic rupture and tsunami generation, and provides a framework for earthquake cycle models. This community resource aims to build trust in numerical simulations and facilitate long-term collaborative code verification as modeling software continues to evolve.

Seismica↗
USGS2024

GRAPES: Earthquake early warning by passing seismic vectors through the grapevine

Estimating an earthquake's magnitude and location may not be necessary to predict shaking in real time; instead, wavefield-based approaches predict shaking with few assumptions about the seismic source. Here, we introduce GRAph Prediction of Earthquake Shaking (GRAPES), a deep learning model trained to characterize and propagate earthquake shaking across a seismic network. We show that GRAPES’ internal activations, which we call “seismic vectors”, correspond to the arrival of distinct seismic phases. GRAPES builds upon recent deep learning models applied to earthquake early warning by allowing for continuous ground motion prediction with seismic networks of all sizes. While trained on earthquakes recorded in Japan, we show that GRAPES, without modification, outperforms the ShakeAlert earthquake early warning system on the 2019 M7.1 Ridgecrest, CA earthquake.

Shimane/HiroshimaPrefectures↗
USGS2025

Preferential groundwater discharges along stream corridors are disregarded sources of greenhouse gases

Groundwater delivery of greenhouse gases (GHGs) to stream banks and riparian areas, before mixing with surface waters, has not been well quantified. We measured preferential groundwater delivery of GHGs to stream banks within three stream reaches, and found that stream banks with discharging groundwater emitted more CO 2 and were sources of N 2 O compared to stream banks without actively discharging groundwater, which emitted less CO 2 and were N 2 O sinks. At one of our stream reaches, groundwater CO 2 and N 2 O concentrations were 1.4–19.2 and 1.1–40.6 times higher than those in surface water, respectively, and groundwater delivery rates of CO 2 and N 2 O were 1.5 and 1.6 times higher than surface water emissions per unit area. On average, 21% (range 0%–100%) of CO 2 and N 2 O were emitted at the stream bank before mixing with surface waters. Preferential groundwater GHG emissions may contribute substantially to stream corridor emissions and may be underestimated when using a channel-centric approach to estimate riverine GHG budgets.

JGR Biogeosciences↗
USGS2025

Seamless Geologic Map Database for the Intermountain West, United States: A foundational dataset for mineral systems analysis

The Intermountain West has a complex geologic history, resulting in the formation of a diverse array of mineral deposits. Effective mineral exploration requires understanding the spatial and temporal relationships among geologic processes and events, a key focus of the mineral systems approach to exploration. This paper presents the Intermountain West Seamless Geologic Map Database, a unified dataset designed to support mineral exploration. Integrating geologic provinces, structural settings, and hydrothermal alteration, the database leverages the Seamless Integrated Geologic Mapping (SIGMa) extension to the USGS Geologic Map Schema (GeMS) to standardize geologic data from varied sources. SIGMa's hierarchical stratigraphic organization and feature-level metadata enhance data interoperability and reusability, enabling seamless query, analysis, and visualization of lithology, structural features, mineral deposits, geochronology, hydrothermal alteration. volcanic activity, and By providing a regionally consistent and dynamically evolving geologic map, this database provides a foundational framework for mineral exploration and geologic research. It also allows for an efficient workflow that expedites the publication of integrated geologic map databases.

Conference Paper↗
USGS2023

Reconnaissance basement geology and tectonics of North Zealandia

New rock dredge samples supply key information to establish the tectonic and geological framework of the northern two-thirds of the 95% submerged Zealandia continent. The R/V Investigator voyage IN2016T01 to the Fairway Ridge, Coral Sea, obtained poorly sorted poly-lithologic pebbly to cobbly sandstones, well sorted fine grained sandstones, mudstones, bioclastic limestones, and basaltic lavas. Post-cruise analytical work comprised petrography, whole rock geochemical and Sr and Nd isotopic analyses, and U-Pb zircon, Rb-Sr, and Ar-Ar geochronology. A Fairway Ridge cobbly sandstone has a ∼95 Ma (early Late Cretaceous) depositional age; two biotite granite cobbles are 111 ± 1 and 128 ± 1 Ma in age, and some volcanic pebbles are also likely Early Cretaceous. Fairway Ridge basalts have intraplate alkaline chemistry and are of Late Eocene age (∼40–36 Ma). By analogy with South Zealandia, we interpret strong positive continental magnetic anomalies of North Zealandia to mainly result from Late Cretaceous to Cenozoic intraplate basalts, many of them rift-related lavas. A new basement geological map of North Zealandia shows the position of the Mesozoic Gondwana magmatic arc axis (Median Batholith) and other major geological units. This study completes onland and offshore reconnaissance geological mapping of the entire 5 Mkm 2 Zealandia continent.

Tectonics↗
USGS2026

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation↗
USGS2023

3D Dynamic rupture modeling of the 6 February 2023, Kahramanmaraş, Turkey Mw 7.8 and 7.7 earthquake doublet using early observations

The 2023 Turkey earthquake sequence involved unexpected ruptures across numerous fault segments. We present 3D dynamic rupture simulations to illuminate the complex dynamics of the earthquake doublet. Our models are constrained by observations available within days of the sequence and deliver timely, mechanically consistent explanations of the unforeseen rupture paths, diverse rupture speeds, multiple slip episodes, heterogeneous fault offsets, locally strong shaking, and fault system interactions. Our simulations link both earthquakes, matching geodetic and seismic observations and reconciling regional seismotectonics, rupture dynamics, and ground motions of a fault system represented by 10 curved dipping segments and embedded in a heterogeneous stress field. The M w 7.8 earthquake features delayed backward branching from a steeply branching splay fault, not requiring supershear speeds. The asymmetrical dynamics of the distinct, bilateral M w 7.7 earthquake are explained by heterogeneous fault strength, prestress orientation, fracture energy, and static stress changes from the previous earthquake. Our models explain the northward deviation of its eastern rupture and the minimal slip observed on the Sürgü fault. 3D dynamic rupture scenarios can elucidate unexpected observations shortly after major earthquakes, providing timely insights for data‐driven analysis and hazard assessment toward a comprehensive, physically consistent understanding of the mechanics of multifault systems.

The Seismic Record↗
USGS2024

Mitigating climate change by abating coal mine methane: A critical review of status and opportunities

Methane has a short atmospheric lifetime compared to carbon dioxide (CO 2 ), ∼decade versus ∼centuries, but it has a much higher global warming potential (GWP), highlighting how reducing methane emissions can slow the rate of climate change. When considering the contribution of greenhouse gas (GHG) emissions to current global warming (2010–2019) relative to the industrial revolution (1850–1900) levels, methane contributes 0.5 °C or ∼ a third of the total. The most recent post-2023 global estimates of methane emissions by bottom-up (BU) and top-down (TD) approaches for the coal mining sector are in the range of ∼41 ± 3 Tg yr −1 and 33 ± 5 Tg yr −1 , respectively. This divergence, notwithstanding overlapping confidence intervals, is a result of differences between applied TD global inversion models and BU emission inventories. Further research can help to better refine emissions from the various contributing coal mine methane (CMM) emissions sources. The coal mining sector accounts for over 10 % of global anthropogenic methane emissions. The contribution of CMM emissions to the global budget have increased since 2000, although upward and downward regional trends have been observed.

International Journal of Coal Geology↗
USGS2026

Low-frequency earthquakes track the motion of a captured slab fragment

Accurate tectonic models are essential for assessing seismic hazard and fault interactions. However, the plate configuration at the complex Mendocino triple junction, where the San Andreas Fault and the Cascadia subduction zone meet, remains uncertain. We analyzed fault slip associated with a recently identified zone of tectonic tremor and low-frequency earthquakes (LFEs) near the southern edge of the subducting Gorda slab. Based on tidal sensitivity and P-wave first motions, we show that the LFEs are generated by dipping, strike-slip motion. This suggests that a former Farallon slab fragment, now captured by the Pacific plate, is translating northward beneath westernmost North America. This geometry effectively extends the slab interface fault, challenging prevailing interpretations of slab window formation and creating a potential unaccounted earthquake hazard in this region.

Science↗
USGS2026

USGS Geochron Database

Introduction Geochronology helps us understand Earth’s history by determining when important events, like volcanic eruptions, the rise of mountains, the formation of mineral resources, and changes in the landscape, happened. Geochronological data directly support geologic mapping and can inform decisions about geologic hazard mitigation, natural resource management, and infrastructure resilience. The U.S. Geological Survey (USGS) Geochron database provides access to more than 300,000 published, publicly available age measurements from more than 40,000 geological samples. This database is the result of a collaborative effort with State geological surveys and geoscientists from across the globe. The USGS Geochron database is the most comprehensive collection of geochronological data available for the United States. Users can view data through an interactive map explorer, download datasets, and integrate data into geospatial software or other analysis tools.

Fact Sheet↗
USGS2024

Geologic map of Scoggins Dam, Henry Hagg Lake, and Scoggins Valley, Washington County, Oregon

New geologic mapping (Wells and others, 2020b) and geophysical mapping (Blakely and others, 2000; McPhee and others, 2014; Wells and others, 2020a) document kilometers of Cenozoic right-lateral offset along the Gales Creek Fault Zone, a major, northwest-striking fault zone forming the boundary between the Tualatin Valley and the Coast Range. The Bureau of Reclamation’s (Reclamation) Scoggins Dam (fig. 1), in the Coast Range foothills west of Forest Grove, Oregon, lies within the Gales Creek Fault Zone as mapped by Wells and others (2020a, 2020b; fig. 2). Active faults of the Gales Creek Fault Zone defined by paleoseismic trenching (Redwine and others, 2017, 2019b, Horst and others, 2018, 2019, 2021, and Wells and others, 2020a) are presently mapped as projecting through the existing dam. The Pacific Northwest Region of Reclamation requested assistance with geologic studies around Scoggins Dam to provide better understanding of fault locations and their activity, which are needed to design a modification of the dam (Maguire, 2019a, b). The scope of this project includes detailed geology of the existing Scoggins Dam site, Henry Hagg Lake, the reservoir behind the dam, and Scoggins Valley downstream of the existing dam, particularly around a potential new dam site, where Scoggins Creek cuts through a narrow gap formed by a resistant felsic tuff bed that crosses the valley.

Oregon↗
USGS2026

New constraints on northeast Seattle basin structure from converted seismic waves

The Seattle basin is a deep sedimentary basin in the Seattle–Bellevue, Washington metropolitan area within the Puget Lowland of Washington State. We determine the structure of a portion of the basin and the underlying basement using analysis of P waves converted from direct S incident from below. A deep local crustal event beneath Monroe, about 35 km northeast of Seattle, was recorded by a 100‐station nodal array deployed in 2019. The event produced a variety of coherent seismic phases, including converted waves from the sediment—basement boundary, internal structure within the basin, and additional crustal discontinuities. Using observed Sp converted waves, we apply an adjoint‐based full waveform inversion (FWI) method to determine the amplitude and extent of seismic discontinuities at depth. We find the strongest source of converted waves for this event lies ∼6 to 7 km depth below northern Lake Washington, interpreted to be the local depth to basement rock. The newly imaged shallow basement structure may be part of a deformation zone associated with the Siletzia eastern boundary. Our results highlight the utility of converted seismic waves recorded by a dense array, combined with an FWI method, to illuminate crustal structure.

Washington↗
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↗
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↗
USGS2024

The projected exposure and response of a natural barrier island system to climate-driven coastal hazards

Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

North Carolina↗
USGS2024

System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor

Executive Summary This report addresses system characterization of the Earth Surface Mineral Dust Source Investigation (EMIT) sensor, an imaging spectrometer developed by the National Aeronautics and Space Administration. This report is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and radiometric performances. Results of these analyses indicate that the EMIT sensor has a band-to-band geometric performance in the range of −0.355 to 0.210 pixel with a few exceptions of shortwave infrared channels. Geometric offset relative to the Landsat 8 Operational Land Imager ranged from −15.966 meters (−0.266 pixel) to 43.844 meters (0.731 pixel). Offset of a radiometric comparison ranged from −0.016 to 0.025, and slope of a radiometric comparison ranged from 0.837 to 0.985. EMIT agreed with Radiometric Calibration Network measurements within 5 percent across most of the spectral channels.

Open-File Report↗
USGS2025

Multi-lithofacies alluvial characterization via airborne electromagnetic-borehole fusion using ordinary interval kriging and geologic constraints

Airborne electromagnetic (AEM) survey provides extensive spatial coverage and detailed resolution at the near surface and can be used to develop hydrogeological models. However, utilization of AEM data is not straightforward because AEM resistivity is an indirect measurement for inferring sediment types. This study develops an ordinary interval kriging (OIK) algorithm and a resistivity-to-multi-lithofacies (R2ML) data fusion workflow for multi-lithofacies alluvial characterization. OIK utilizes irregular interval data to construct three-dimensional (3D) resistivity fields from one-dimensional inverted AEM resistivity models. The R2ML workflow maps the resistivity field generated from OIK into a multi-facies lithological model, incorporating geologic constraints derived from well logs and geological observations. The numerical and real-world cases demonstrate that OIK is computationally efficient, accounts for 3D anisotropy, and minimizes the smoothing effect, thereby preserving resistivity contrasts and reducing interpolation uncertainty. The methodology is applied to lithologic characterization of the Mississippi River Valley alluvial aquifer (MRVA) in the Shellmound area, Mississippi, U.S. A frequency-domain AEM survey was conducted to support groundwater studies for the managed aquifer recharge (MAR) to the MRVA. The resulting lithological model, including four types of lithofacies—clay, very fine sand, fine-medium sands, and graveliferous sands, illustrates the geomorphological processes of the MRVA and implies potential MAR. The alignment between the lithological model and existing geological and hydrogeological investigations demonstrates that OIK and R2ML workflow effectively capture the subsurface architecture of the MRVA. The methods have broad applicability for characterizing alluvial aquifers through AEM-borehole data fusion, supporting sustainable groundwater management.

Mississippi↗
USGS2024

Preliminary ground and airborne-based geophysical mapping and modelling of an active hydrothermal system at Mammoth Lakes, California

Mammoth Lakes, California hosts a productive hydrothermal system within the seismically active south moat of Long Valley Caldera. Surficial evidence of the shallow hydrothermal system includes discrete zones of tree-kill dispersed between Shady Rest Park and the Casa Diablo Geothermal Power Plant (40 MW), as well as east of the power plant. The tree-kill areas are associated with elevated diffuse CO₂ emissions, heated ground, hydrothermal alteration, diffuse soil H₂S emissions, and gas vents. Previous mapping delineates prominent north and northwest trending structures within the south moat along the southwestern edge of the resurgent dome that may accommodate gas and fluid flow at the Shady Rest Park and Basalt Canyon Tree Kill Areas (SRTKA and BCTKA, respectively). Both tree-kill areas are also located along contacts between resurgent rhyolite, mafic lavas, and surficial deposits which may provide additional pathways for gas and fluid migration in the shallow subsurface. Characterizing structure and lithology using geophysical anomalies is critical to determining primary structural controls on the hydrothermal system and the extent of subsurface alteration at these sites. We conducted ground and airborne-based potential field geophysical surveys to map gravity and magnetic anomalies. These anomalies are then used to model subsurface geology, structure, and hydrothermal alteration. Here we present our preliminary geophysical mapping and modelling results at both tree-kill locations. Gravity and magnetic data suggest complex structural intersections are coincident with heated ground and gas emissions at the SRTKA and BCTKA. Hydrothermal systems are often observed or interpreted to exploit fault intersections which can serve as highly permeable pathways for hydrothermal fluid and gas discharge, enabling economic geothermal energy production. Geophysical mapping and modelling are an effective means of investigating such structural complexity at Mammoth Lakes due to the presence of unidentified and concealed structures.

California↗