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USGS2021

Remote sensing-based actual evapotranspiration assessment in a data-scarce area of Brazil: A case study of the Urucuia Aquifer System

The large groundwater reserves of the Urucuia Aquifer System (UAS) enabled agricultural development and economic growth in the western Bahia State, in northeastern Brazil. Over the last several years, concern has grown around the aquifer’s diminishing water levels, and water balance (WB) studies are in demand. Considering the lack of measured actual evapotranspiration (ET a ), a major component of the water cycle, this work uses the Operational Simplified Surface Energy Balance (SSEBop) model to estimate ET a , and compares it to basin-scale estimates from the Soil Moisture Accounting Procedure (SMAP) monthly model and from an annual WB closure method, based on gridded meteorological data and the Gravity Recovery and Climate Experiment (GRACE) product. Additionally, a comparative assessment of different versions of the SSEBop parameterization was performed. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used to implement eight different versions of the SSEBop algorithm over the UAS between 2000 and 2013. SSEBop and SMAP ET a yielded similar seasonal patterns, with correlation coefficient (r) up to 0.65, mean difference (MD) of 0.8 mm/month and mean absolute difference (MAD) of 18.5 mm/month. Comparison of SSEBop annual ET a estimates to annual SMAP and WB closure estimates yielded low MD (12.1 and −7.3 mm/year, respectively) and MAD (82.5 and 82.8 mm/year, respectively), but also low r values (0.00 and 0.37, respectively). The comparison of the different SSEBop versions indicated the need to incorporate a calibration step of the aerodynamic heat resistance (r ah ) parameter. SSEBop results were also used for land cover and drought monitoring. Analysis indicates that agriculture, associated with an increasing trend of atmospheric evaporative demand, is responsible for the decrease in groundwater levels and streamflow in the studied time period.

Urucuia Aquifer System↗
USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗
USGS2025

Evaluation of solid bitumen created from marine oil shale bituminite under hydrous and anhydrous pyrolysis conditions

To test the influence of environmental conditions on aromaticity of solid bitumen generated during petroleum generation, four organic-rich (26–36 wt% total organic carbon) oil shale samples collected from the Neoproterozoic–Lower Cambrian restricted marine Salt Range Formation in the upper Indus Basin, Pakistan, were pyrolyzed under hydrous and anhydrous conditions. Experiments used closed system batch reactors at subcritical water temperatures between 300 and 370°C for 72 h. Thermal conversion of bituminite in the Salt Range oil shales created a newly formed solid bitumen, similar to previous observations from experiments on the Eocene lacustrine Green River Formation Mahogany zone oil shale. Newly formed solid bitumen in the Salt Range Formation oil shales generally has higher reflectance (R o ) in hydrous residues compared to anhydrous experiments subjected to the same time-temperature conditions, also similar to prior observations. This finding supports the hypothesis that radical disproportionation is favored in the presence of hydrogen contributed by water, promoting aromatization in the solid bitumen residue with concomitant increased expulsion of saturated hydrocarbons. Indigenous solid bitumen (and vitrinite in a comparison sample) also shows higher reflectance values in hydrous versus anhydrous residues, indicating that additional aromatization in the presence of exogenous hydrogen occurs both in newly formed organic matter and in organic matter that is present throughout the experiment. Despite similarities in their bulk rock geochemical screening parameters, R o evolution shows different trajectories amongst the four Salt Range oil shales, suggesting as-yet undetermined differences in kinetic properties which are probably related to differences in a priori chemical composition. These results have implications for the use of solid bitumen reflectance (BR o ) as a thermal proxy, suggesting BR o values and appearance could vary as a function of the concentration of water. Variation in water concentration may be present at the reservoir or formation scale, but may also be present at a much finer scale in tight oil shales where permeability is several orders of magnitude lower than conventional reservoirs. Therefore, local variations in the presence of water potentially could explain substantial variation in BR o values and appearance in closely spaced source rock samples and even within an individual microscope field.

Journal of Analytical and Applied Pyrolysis↗
USGS2025

Reaction kinetics and accelerant effects of sulfides in early mature hydrocarbon generation using hydrous pyrolysis

Hydrocarbon generation in organic-rich sediments is influenced by the molecular organic composition and relative abundance of associated minerals. Certain mineral-derived elements act as catalysts and reaction intermediaries, facilitating early-stage hydrocarbon formation in potential source rocks. This study investigated the role of sulfur contributed from pyrite as an accelerant in thermal reaction, focusing on its effects on early maturation and consequent hydrocarbon generation from gilsonite (low-sulfur solid petroleum). Hydrous pyrolysis (HP) experiments were conducted on mixtures of gilsonite and pyrite in varying ratios (1:0.1, 1:0.5, 1:1, 1:2, and 1:10 w/w gilsonite:pyrite) at 320, 350, and 370 °C for 72 h. Untreated and thermally altered residues were analyzed using solid bitumen reflectance (BR o , %), total organic carbon (TOC) content, programmed temperature pyrolysis, scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), and X-ray diffraction (XRD) to evaluate the potential accelerant role of pyritic sulfur in hydrocarbon formation. The results show HP residues at 320 and 350 °C with greater pyrite concentrations had higher BR o , while reflectance values were similar in the 370 °C residues, regardless of pyrite concentration, suggesting enhanced reaction at lower thermal conditions. Increasing pyrite content systematically decreased hydrogen index (HI) values while increasing the transformation ratio (TR) and production index (PI), indicating enhanced conversion of organic matter to hydrocarbons with increasing pyrite concentrations. Gas yields increased with pyrite addition, particularly at 350 °C, confirming secondary cracking effects. However, gas production stabilized or declined at higher pyrite loadings (1:10), suggesting alternative reaction pathways such as coke formation. Our data indicate the presence of pyrite lowers the activation energy for thermal cracking, shifting peak experimental hydrocarbon generation temperatures downward by 20–30 °C, with the most pronounced accelerant effects observed at moderate pyrite concentrations (1:0.5 and 1:1). The thermodynamic framework reveals that pyrite stability is influenced by experimental conditions, with pyrrhotite formation favored in the presence of gilsonite due to reduced oxygen fugacity. Pyrite transformation to pyrrhotite, as observed through XRD, SEM-EDS, and predicted by thermodynamic data, further supports the accelerant role of S, as pyrrhotite exhibits a higher hydrogen transfer potential, promoting early oil generation. These findings highlight the importance of pyrite in modulating hydrocarbon generation pathways in organic-rich systems.

Journal of Analytical and Applied Pyrolysis↗
USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗
USGS2024

Imaging of seismic discontinuities using an adjoint method

For imaging of seismic discontinuities at depth, reverse time migration (RTM) is a powerful method to apply to recordings of seismic events. It is especially powerful when an extensive receiver array, numerous seismic sources, or both, permit adequate reconstruction of incident and scattered wavefields at depth. Reconstructing either the incident or scattered wavefield at depth becomes less accurate when relatively few recordings of seismic events are available. Here we explore an inverse scattering approach to imaging discontinuities based on an adjoint method, employing sensitivity kernels (Frechet derivatives) that represent jumps in material properties across seismic-discontinuity surfaces. When combined with ray-based requirements on scattering geometry, it constitutes a powerful approach to determining the locations and amplitudes of the discontinuities, recovering only those properties that can be resolved by a spatially limited source and/or receiver distribution. This is illustrated by synthetic examples with local sources followed by a field example in a subduction zone setting

Washington↗
USGS2024

Self-guided decision support groundwater modelling with Python

The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.

Journal of Open Source Education↗
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

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire↗
USGS2026

PFAS remediation in a bioelectrochemical system inoculated with the west branch consortium (WBC-2)

Groundwater contamination by per - and polyfluoroalkyl substances (PFAS) poses a persistent environmental and public health concern. This study evaluates a two-chambered bioelectrochemical system (BES) inoculated with the West Branch Consortium (WBC-2) for PFAS remediation. Under an applied cathodic potential of −450 mV (versus Ag/AgCl), the BES with active WBC-2 achieved >99.0% perfluorooctanesulfonic acid (PFOS) removal within 21 days in deionized water with culture medium and > 98.9% removal of PFOS, perfluorooctanoic acid (PFOA), perfluorohexanoic acid (PFHxA), and perfluorohexanesulfonic acid (PFHxS) in contaminated groundwater after 102 days. Intermediate formation (e.g., PFOA, 6:2 fluorotelomer sulfonate (6:2 FTS), perfluoropropionic acid (PFPrA), perfluorobutanoic acid (PFBA)) and background-corrected fluoride release were consistent with PFOS transformation under anaerobic reducing conditions potentially involving defluorination. Following repeated PFOS spikes (100 μg/L on Days 0, 50, and 399), PFOA, PFPrA, and PFBA accumulated over 664 days. Despite being the dominant accumulated compound, PFOA accounted for <1.8% of the total spiked PFOS mass. Minimal PFOS transformation occurred in controls without active WBC-2, highlighting the importance of microbial metabolism. Biofilm analysis revealed dense colonization of rod-shaped bacteria on carbon fiber brushes. Enrichment of Bacillus , Agrobacterium , and other low-abundance taxa suggests selective adaptation to BES and PFAS conditions. These findings highlight BES driven by electrochemically stimulated microbial activity as a promising strategy for PFAS remediation.

Journal of Water Process Engineering↗
USGS2024

Cross-fade sampling: Extremely efficient Bayesian inversion for a variety of geophysical problems

This paper introduces cross-fade sampling, a computationally efficient Markov Chain Monte Carlo simulation method that uses a semi-analytical approach to quickly solve Bayesian inverse problems that do not themselves have an analytical solution. Cross-fading is efficient in two ways. First, it requires fewer samples to obtain the same quality simulation of the target probability density function (PDF). Secondly, it is much faster to evaluate the posterior probability of each sample than conventional sampling methods for simulating Bayesian posterior PDFs. Conventional methods require evaluating the prior probability (which describes your a priori constraints) and data likelihood (which describes the fit between the observations and the predictions of the model) for each sample model. However, cross-fading does not require evaluating the data likelihood, meaning that ‘big data’ can be fit with zero additional computational cost. Further, the cross-fading approach can be used to calculate the marginal likelihood associated with a model design, facilitating model comparison and Bayesian model averaging. Topics covered in this paper include derivation of the cross-fade approach and how it can be used to simulate Bayesian posterior PDFs and compute the marginal likelihood, discussion of the class of problems to which cross-fading can be applied (with examples from earthquake statistics, earthquake ground motion modelling, volcanic eruption forecasting, and finite fault slip modelling), demonstration of efficiency relative to existing sampling methods and discussion of how cross-fading can be used to account for prediction errors (i.e. epistemic errors) as part of the geophysical inverse problem.

Geophysical Journal International↗
USGS2024

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and translational slides derived solely from high-resolution (≤3 m) elevation data and globally available estimates of the diffusion coefficient for sediment flux. The method applies a linear diffusion model to the roughest landslide deposits until they reach a representative non-landslide roughness distribution. This estimates the time for a landslide deposit to be unrecognizable in high-resolution digital elevation data, which we term the mean lifetime of the landslide. Using the mean lifetime and number of landslides within an area of interest, we can estimate the mean occurrence rate of landslides over that domain. We validate this approach using a comprehensive temporal inventory of landslides in western Oregon created using age-roughness curves that are calibrated with high-resolution elevation data and radiocarbon data. We find good agreement between our diffusion method and the existing age-roughness-derived estimates, producing mean lifetimes of 4500 and 5200 years (4% difference), respectively. Hazard maps produced using the two methodologies generally agree, with the maximum differences in landslide probability reaching 0.1. Due to the relative abundance of high-resolution elevation data compared with age-dated landslides, our method could help constrain landslide occurrence rates in areas previously considered unfeasible.

Oregon↗
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↗
USGS2025

Advancing current understanding of Martian impact-generated hydrothermal systems through novel coupled modeling: Insights from Gale, Jezero, and other craters

Impact-generated hydrothermal systems are considered potentially habitable environments on Mars, Earth, and other planetary bodies for microbial life. However, there is an ongoing debate regarding what geological features on Mars provide definitive evidence for such systems. Although earlier studies have modeled hydrothermal processes in Martian craters, they often lacked integration with shock physics hydrocodes to constrain initial impact conditions. The importance of this two-code coupling was demonstrated by successfully replicating alteration signatures in the Earth's Haughton impact structure. In this study, we use a similar two-code approach, combining the iSALE hydrocode with the HYDROTHERM hydrothermal model to simulate the full evolution of impact-generated hydrothermal systems. We apply this method to craters the size of Jezero (∼50 km) and Gale (∼154 km) in diameter. Although Jezero's interior is largely buried, our results align with hypothesized hydrothermal vents and alteration minerals near central uplifts in similarly sized exposed craters, such as Toro and Auki. Furthermore, our models correspond to alteration patterns observed by the Curiosity in the lower layers of Mount Sharp, which may represent remnants of impact-driven hydrothermal activity. A key finding is that these systems may persist much longer than previously estimated. Our simulations suggest that a Jezero-sized system could remain habitable for thermophiles for approximately 720,000 years, whereas a Gale-sized system could persist for nearly 2 million years. Additionally, simulations under unsaturated crustal conditions reveal that air-dominated near-surface layers can suppress vertical fluid flow, enabling deep subsurface alteration without producing detectable mineral signatures at the surface.

Journal of Geophysical Research - Planets↗
USGS2025

Impact of gas/liquid phase change of CO2 during injection for sequestration

CO 2 sequestration in deep saline formations is an effective and important process to control the rapid rise in CO 2 emissions. The process of injecting CO 2 requires reliable predictions of the stress in the formation and the fluid pressure distributions – particularly since monitoring of the CO 2 migration is difficult – to mitigate leakage, prevent induced seismicity, and analyze wellbore stability. A key aspect of CO 2 is the gas–liquid phase transition at the temperatures and pressures of relevance to leakage and sequestration, which has been recognized as being critical for accurate predictions but has been challenging to model without ad hoc empiricisms. This paper presents a robust multiphase thermodynamics-based poromechanics model to capture the complex phase transition behavior of CO 2 and predict the stress and pressure distribution under super- and sub- critical conditions during the injection process. A finite element implementation of the model is applied to analyze the behavior of a multiphase porous system with CO 2 as it displaces the fluid brine phase. We find that if CO 2 undergoes a phase transition in the geologic reservoir, the spatial variation of the density is significantly affected, and the migration mobility of CO 2 decreases in the reservoir. A key feature of our approach is that we do not a priori assume the location of the CO 2 gas/liquid interface – or even if it occurs at all – but rather, this is a prediction of the model, along with the spatial variation of the phase of CO 2 and the change of the saturation profile due to the phase change.

Journal of the Mechanics and Physics of Solids↗
USGS2025

Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed

Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.

Colorado↗
USGS2025

Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning

As probabilistic tsunami hazard analysis (PTHA) focuses more on assessments for localized, populous regions, techniques are needed to identify a subsample of representative earthquake ruptures to make the computational requirements for producing high-resolution hazard maps tractable. Moreover, the greatest epistemic uncertainty in seismic PTHA is related to source characterization, which is often poorly defined and subjective. We address these two salient issues by applying streamlined earthquake rupture forecasts (ERFs), based on combinatorial optimization methods, to an unsupervised machine learning workflow for identifying representative ruptures. ERFs determine the optimal distribution of a millennia-scale sample of earthquakes by inverting the observed slip rate on major faults. We use two previously developed combinatorial optimization ERFs, integer programming and greedy sequential, to produce the optimal location of ruptures with seismic moments sampled from a regional Gutenberg–Richter magnitude–frequency distribution. These ruptures in turn are used to calculate peak nearshore tsunami amplitude, using computationally efficient tsunami Green's functions. An unsupervised machine learning workflow is then used to identify a small subsample of the earthquakes input to ERFs for onshore PTHA analysis. We eliminate epistemic uncertainty related to source distribution under traditional PTHA analysis; in its place, a quantifiable, less subjective and generally smaller uncertainty related to the input to ERFs is included. The Nankai subduction zone is used as a test case, where previous ERFs have been conducted. Results indicate that the locations of representative earthquakes are sensitive to choice of magnitude–area relation and to whether a minimum cumulative stress objective is imposed on the fault. In general, incorporating ERFs into PTHA provide a physically self-consistent method to incorporate fault slip information in determining representative earthquakes for onshore PTHA, eliminating a major source of epistemic uncertainty.

Nankai subduction zone↗
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↗