The event in question, catalogued as S0976a, was recorded on Sol 976 of the InSight mission, corresponding to 25 August 2021. It is the only marsquake ever detected in the Martian western hemisphere, originating roughly 146 degrees away from the lander near Ius Chasma in western Valles Marineris. Because InSight operated a single seismic station rather than a network, determining where and how the quake occurred demanded unusual ingenuity. The team, led by Jung-Hun Song of Imperial College London, exploited the fact that seismic waves from such a distant source bounce off the surface before reaching the station, producing reflected phases known as PP and SS that carry information about the quake’s location, depth and faulting style.

By jointly inverting the polarities and relative amplitudes of these reflected phases, the researchers recovered a focal mechanism, the seismic fingerprint that reveals the orientation and slip direction of the rupturing fault. The result was unambiguous: S0976a was a strike-slip event, the kind of sideways shearing motion familiar from California’s San Andreas Fault, occurring on steeply dipping fault planes within the middle to lower crust. The centroid depth lies between roughly 20 and 40 kilometres, well above the estimated Moho boundary of 55 to 65 kilometres beneath western Valles Marineris. Across five different models of the Martian interior, the preferred depths remained within this range, and more than 82 percent of all acceptable solutions belonged to the strike-slip family, with rakes clustering near pure lateral slip.

Ruling out alternatives was as important as identifying the mechanism. Meteoroid impacts on Mars produce distinctive high-frequency seismic signatures, but S0976a is a low-frequency event, and force-based models designed to mimic landslides or other mass-wasting processes could not reproduce the observed phase polarities, arrival times or the strong horizontal ground motion. The team also scoured post-event images from the Context Camera on the Mars Reconnaissance Orbiter, covering roughly half of the candidate source region, and found no fresh landslide deposits or new impact craters. An energy balance calculation showed that a landslide large enough to generate a magnitude 3.6 event would need to move at least ten million cubic metres of rock, leaving a collapse scar several hundred metres to a kilometre across that would be plainly visible in orbital imagery. Nothing of the sort exists.

With a tectonic origin established, the structural geology of the source region came into focus. Digitising normal faults, grabens and wrinkle ridges from high-resolution orbital images across western Valles Marineris revealed a bimodal population of grabens with dominant strikes of about 15 and 115 degrees, defining an orthogonal fault network. Near the inferred epicentre, on the plateaus between Ius, Tithonium and Candor Chasmata, these orthogonal sets intersect in dense, well-developed patterns. Critically, the compressional axis inferred from the marsquake runs subparallel to the canyon system and to the dominant WNW-ESE fault set, while the tensional axis lies roughly perpendicular to it, aligning with the secondary NNE-SSW structures. The seismic source therefore appears to sit within a structurally complex transfer zone where inherited fabrics are favourably oriented for renewed shear.

The stress geometry carries a deeper message about Martian history. Kinematic analyses of the canyon’s Hesperian-era development, more than three billion years ago, suggest a maximum compressive axis oriented roughly east-west, between 090 and 100 degrees. The present-day compressive axis inferred from S0976a sits at about 95 degrees, an almost perfect match. In other words, the stress field that shaped Valles Marineris during its violent youth appears to have survived essentially intact, and the faults it created remain mechanically favourable for reactivation today. This directly contradicts models invoking gravitational collapse of overthickened crust, which predict dominantly vertical loading and axisymmetric extension, and instead supports a transtensional origin for the canyon system involving significant oblique slip.

What keeps these stresses alive on a planet that has lost most of its internal heat? The study points to a combination of forces. Long-term planetary cooling imposes a background horizontal compression as the interior shrinks. The immense volcanic load of the Tharsis rise, home to the largest volcanoes in the solar system, flexes the lithosphere and modifies the orientation and magnitude of horizontal stresses, with recent gravity-topography models suggesting a deep buoyant anomaly contributes about a fifth of the present Tharsis uplift. Meanwhile, the deep incision of the canyon itself acts as an erosional unloading that reduces vertical stress and promotes horizontal compression. At depths of 20 to 40 kilometres, the basaltic crust experiences confining pressures of several hundred megapascals, conditions that suppress tensile opening and favour brittle shear failure, exactly the strike-slip regime observed.

The absence of aftershocks, initially puzzling, turned out to be an expected consequence of Martian geometry. Simulations of aftershock sequences, generating a thousand synthetic catalogues conditioned on S0976a as the mainshock, showed that ground displacements from events in western Valles Marineris would rarely exceed the ambient noise level at the InSight landing site. Core shadowing, in which the planet’s core blocks direct seismic paths, and attenuation by the deep interior conspire to make distant source regions nearly invisible. The probability of detecting even a single sizeable aftershock within 50 days was calculated at just 0.1 percent. The quiet record after S0976a therefore says little about the true level of activity in the canyon and much about the limits of single-station seismology on another planet.

Placed alongside earlier InSight results, the new findings sketch a planet whose deformation is strikingly partitioned. Normal faulting dominates beneath Cerberus Fossae, compressional faulting occurred near the crustal dichotomy in southern Elysium Planitia during the mission’s largest recorded quake, and now strike-slip faulting has been documented beneath Valles Marineris. Three tectonically distinct regions, three contrasting failure styles, all within a lithosphere that lacks plate boundaries. This partitioning implies that broad stresses act on a mechanically heterogeneous shell, where long-lived structural and rheological variations dictate where strain is released. Limited viscous relaxation allows these stress heterogeneities to persist, so that ancient weaknesses keep localising deformation rather than new faults forming from scratch.

The broader implication extends beyond Mars. Plate tectonics appears to be rare among rocky worlds, with most terrestrial planets and large moons inferred to operate in a stagnant-lid regime, where the exterior shell does not recycle into the interior. The Valles Marineris results suggest that in such worlds, seismicity preserves a mechanical imprint of ancient tectonics: slow fault healing and slowly evolving stress fields jointly control where activity continues long after the structures themselves were first established. A fault system born during the Tharsis-building upheavals of the Hesperian can still rupture today, four billion years later, releasing strain in modest, MPa-scale stress drops on inherited fault patches. For planetary scientists, the message is that a planet’s tectonic past is never truly past; it sleeps in the crust, waiting for the right stress to wake it.

Subject of Research: Seismic evidence of present-day strike-slip fault reactivation on inherited crustal structures in Valles Marineris, Mars

Article Title: Active crustal straining and fault reactivation at Valles Marineris

Article References: Song, J.-H., Kim, D., Kolawole, F., Davis, J. M., Parry, R., & Maguire, R. (2026). Active crustal straining and fault reactivation at Valles Marineris. Nature Communications, 17(1), Article 10530. https://doi.org/10.1038/s41467-026-78193-6

Image Credits: AI Generated

DOI: 10.1038/s41467-026-78193-6

Keywords: Mars, Valles Marineris, marsquake, InSight, seismology, fault reactivation, strike-slip faulting, tectonics, stagnant-lid planets, Tharsis, crustal deformation, Nature Communications

The key player is bridgmanite, the magnesium-iron silicate that makes up roughly 80 percent of the lower mantle in the standard pyrolite model. Like many minerals, bridgmanite crystals are intrinsically anisotropic: seismic waves travel faster along some crystallographic directions than others. When rocks deform slowly over millions of years, dislocation creep causes grains to rotate and align into a crystallographic preferred orientation, or CPO, and the aggregate as a whole becomes anisotropic. In the average lower mantle, diffusion creep is often cited as the dominant deformation mechanism, which would scramble any fabric. But numerical models and seismic observations agree that in high-stress regions such as subduction zones, dislocation creep remains active, allowing fabrics to persist and grow to great depths.

What makes the new work possible is a recent set of laser-heated diamond anvil cell experiments that deformed pyrolitic material at true lower-mantle pressures and temperatures. Those experiments revealed something unexpected: bridgmanite does not deform the same way at all depths. Below about 24 gigapascals, the easiest slip system is (100)[001], but as pressure climbs toward 50 gigapascals, corresponding to roughly 1,250 kilometers depth, the critically resolved shear stresses of the (100)[001] and (010)[100] systems cross at about 40 gigapascals, near 1,050 kilometers. Past that crossover, (010)[100] takes over as the dominant slip system. The transition is gradual, spread across the depth range from about 670 to 1,250 kilometers, yet its consequences for seismic imaging turn out to be sharp.

To translate this mineral physics into a seismic prediction, the team coupled a two-dimensional thermo-mechanical model of intraoceanic subduction, built with the open-source geodynamics code ASPECT, with viscoplastic self-consistent fabric calculations that track the orientations of 3,000-grain aggregates advected through the simulated mantle flow. They modeled a slab that flattens near 1,000 kilometers depth, the so-called deeply flattened configuration seen in regions such as the Western Java subduction zone, and compared it with a shallowly stagnating slab trapped near the 660-kilometer boundary. Bridgmanite was treated as the only phase that develops meaningful texture, since davemaoite and ferropericlase showed no coherent fabrics in the experiments and were assigned random orientations.

The result is a deformation-induced anisotropic discontinuity. As mantle material is entrained around the slab and accumulates strain, the pressure-dependent slip transition produces a layer where the anisotropy index, a scalar measure of the total anisotropy in the elastic tensor, shows a persistent local minimum. In the mantle wedge and subslab regions, this discontinuity emerges near 1,000 kilometers and progressively deepens toward the slab, reaching about 1,400 kilometers directly beneath it. Remarkably, even though the underlying change in slip systems is smooth, the resulting seismic boundary appears sharp: at locations where natural strain exceeds 2, the half-width of the discontinuity is only about 40 to 54 kilometers, compared with roughly 80 kilometers where strain is weaker. Where the slab stagnates shallowly and strains stay low, the discontinuity persists near 1,000 kilometers but becomes markedly fainter.

The crucial question is whether such a subtle feature could actually be seen by seismometers. The team computed reflection coefficients for underside reflections, the SS precursor phases that seismologists use to probe mantle discontinuities, at three locations along the modeled boundary. Because the medium is anisotropic, the reflection coefficients vary with both azimuth and epicentral distance, and their polarities flip depending on the local flow pattern: negative for all azimuths where poloidal flow dominates, predominantly positive where slab-driven flattening stretches entrained aggregates. At the most strongly strained location, reflection amplitudes reach about 0.02, comparable to coefficients computed for textural interfaces invoked to explain deep-mantle reflections and to those generated by the well-known transition-zone discontinuities. P-wave reflections, by contrast, were negligible, indicating that the boundary is essentially a shear-wave feature.

Full waveform simulations sealed the detectability argument. Using the spectral-element code AxiSEM3D, the researchers built a three-dimensional global model of the anisotropic mantle and recorded synthetic seismograms at a virtual array of 3,000 stations. Array processing with slowness vespagrams revealed a clear SS precursor generated by the anisotropic discontinuity alone, with no isotropic velocity contrast required. The precursor-to-SS amplitude ratio of 0.0084 exceeds the global detectability threshold of 0.0065 established in earlier surveys of mid-mantle reflectors. An isotropic model containing only the slab’s compositional velocity anomaly produced a much shallower and closer-in reflection from the slab-mantle interface, suggesting that where both a shallow and a deep reflector are observed, as in some global SS precursor studies, a flattened slab and its deformation halo could simultaneously supply both.

The pressure-dependent fabric also reconciles long-standing puzzles in mantle anisotropy. Previous forward models that imposed a single bridgmanite slip system could match some features of radial anisotropy, expressed as the ratio of horizontally to vertically polarized shear-wave speeds, but always failed somewhere: one fabric produced too little subslab anisotropy, another generated strong anisotropy everywhere including the mantle wedge where observations show the opposite sign. The new models, with slip systems shifting smoothly with depth, reproduce the fast horizontal shear beneath the slab and the faster vertical shear in the mantle wedge, matching tomographic images of the Western Java subduction zone. Modeled shear wave splitting also matches source-side observations beneath Western Java, with trench-parallel fast directions for downdip rays and trench-perpendicular fast directions for updip rays, although computed delay times remain somewhat low, plausibly because anisotropic phases such as akimotoite and phase D, shape-preferred orientation, and receiver-side complexity all add to the path-integrated signal.

The implications reach beyond subduction zones. The enigmatic 1,000-kilometer discontinuity has been variously attributed to a viscosity jump caused by grain-size variations in ancient bridgmanite-enriched domains, to stiff periclase-rich material, or to sluggish pyroxene-to-garnet transformations in cold slabs. The new mechanism does not replace these thermo-chemical hypotheses, the authors stress, but adds a purely deformation-driven alternative that requires no compositional contrast at all, only accumulated strain and the pressure sensitivity of bridgmanite’s crystal plasticity. Candidate testing grounds include the Cocos, Northern Peru, and Kamchatka slabs, which all show mid-mantle flattening, while vertically penetrating slabs such as the Marianas should instead produce narrow, slightly dipping anisotropic boundaries hugging the slab tip, an equally plausible explanation for the dipping reflectors imaged there. Looking ahead, the team proposes that fabric evolution in bridgmanite may even feed back on slab dynamics, softening the mantle around descending plates much as olivine fabric eases plate motion in the asthenosphere. If so, the deepest architecture of our planet may be written not only in chemistry and temperature, but in the strained, aligned grains of its most abundant mineral.

Subject of Research: Deformation-induced seismic anisotropy and mid-mantle discontinuities beneath subduction zones caused by depth-dependent bridgmanite deformation

Article Title: Mid-mantle discontinuities beneath subduction zones linked to depth-dependent deformation of bridgmanite

Article References: Magali, J. K., Merkel, S., Pisconti, A., Gay, J., Wookey, J., & Thomas, C. (2026). Mid-mantle discontinuities beneath subduction zones linked to depth-dependent deformation of bridgmanite. Nature Communications, 17(1), Article 10494. https://doi.org/10.1038/s41467-026-78212-6

Image Credits: AI Generated

DOI: 10.1038/s41467-026-78212-6

Keywords: bridgmanite, subduction zones, mid-mantle discontinuity, seismic anisotropy, crystallographic preferred orientation, mantle dynamics, SS precursors, shear wave splitting, mineral physics, lower mantle, geodynamics, seismology

In a study published in the Bulletin of Earthquake Engineering, Anabella Cotovanu, Elisei Cojan and Radu Vacareanu of the Technical University of Civil Engineering Bucharest and the Military Technical Academy Ferdinand I present a unified framework that decomposes the variability of Vrancea ground motions into source, path and site contributions. Their conclusion is striking: the apparent anomalies that have caused Vrancea to be treated as an exception and excluded from global comparative studies do not reflect fundamentally different physics. They arise from pronounced structural heterogeneity and the strong interdependence of source, path and site effects, which previous approaches failed to separate coherently.

The scale of the problem becomes clear when you consider how divergent the published estimates of key parameters have been. Stress drop, a measure of how much energy an earthquake releases per unit of fault area, has been variously reported for major Vrancea events at around 50 bar, 100 to 200 bar, as high as 850 bar statically and 950 to 1400 bar dynamically, and in the range of 300 to 1200 bar by researchers using empirical Green’s function methods. One influential series of analyses by Oth and colleagues employed stress-drop values roughly twenty times higher than commonly adopted reference values simply to make their models consistent with observations. Stress drop, in other words, had effectively become a correction dial rather than a physically constrained quantity.

The situation was hardly better for wave propagation. The literature contains six different attenuation functions describing how ground-motion amplitudes decay with distance outside the Carpathian Arc, split into two camps based on contradictory assumptions about geometrical spreading, with one group assuming amplitude decay proportional to the inverse of distance and the other to the inverse square root. Seismic refraction profiles from the VRANCEA99 and VRANCEA2001 experiments and the CALIXTO tomography project revealed why: the crust and upper mantle beneath the region are dramatically heterogeneous, with the asthenosphere lying at very different depths on either side of the arc, and sedimentary strata in the Focsani Basin bent to depths exceeding 30 kilometers.

Then there is the data problem, which is arguably the most severe constraint of all. Since the beginning of the twentieth century, Vrancea has produced fourteen earthquakes with moment magnitudes of at least 6.3, yet only four have been instrumentally recorded: the events of 1977, 1986, and the two shocks of May 1990. The devastating 1977 magnitude 7.4 earthquake, which killed roughly 1,500 people in Bucharest, was recorded within Romania at a single station. Attempting statistically robust source and path analyses with such a sparse database of major events is a formidable challenge, and one reason Vrancea has been left out of global ground-motion studies for decades.

The new framework tackles this problem head-on with a series of methodological innovations. First, rather than letting the recordings themselves define the grouping of data, the researchers built a zonation of the affected region from independent geological, tectonic, geophysical and geomorphological evidence, together with maps of the fundamental resonance frequency of near-surface sediments. This produced eight zones, from the Dobrogea Platform with its shallow ancient bedrock, through the deeply sedimented Dacian Basin accumulation zone, to the Focsani Basin with its exceptional sediment thickness and strong local topographic effects. Because the zoning is defined without reference to strong-motion data, it avoids circular reasoning and serves as an external pivot for organizing the region’s heterogeneity.

A preliminary spectral comparison across these zones immediately revealed systematic differences. The Dobrogea region showed a narrow amplification band peaking near 0.1 seconds, matching its independently mapped resonance frequency, while for larger earthquakes the Focsani Basin and the southern Moesia accumulation zone displayed pronounced amplification in the 0.5 to 2.5 second range. Critically, the two accumulation zones behaved similarly for moderate earthquakes but diverged sharply for large ones, suggesting that bigger ruptures activate deeper sedimentary packages. This supports what the authors call a dynamic boundary between path-controlled and site-controlled behavior, rather than a fixed depth dividing local site conditions from the deeper propagation medium.

The framework then performs what the team calls a uniformization of site effects. Because moderate-magnitude and large-magnitude datasets exhibit different site responses, an average ratio between their amplification patterns was computed and applied to the large-event data, bringing both datasets to a common reference site condition. This allowed the sparse large-event recordings and the more numerous moderate events to be combined into a single database for estimating path parameters. Stress drop was deliberately fixed at a physically plausible 100 bar and never used as a fitting parameter, a choice designed to avoid the source-site trade-offs that have plagued earlier work. Strikingly, when the analysis was repeated with stress-drop values ranging from 50 to 300 bar, the derived attenuation parameters did not change at all; the variations were absorbed entirely by site amplification, revealing the hidden coupling that had made earlier stress-drop estimates so unstable.

The results are internally consistent and, crucially, unremarkable. Geometrical spreading follows the physically expected inverse-distance decay for body waves, which dominate intermediate-depth ground motions. Frequency-dependent anelastic attenuation was determined independently for each zone, with coefficients of determination exceeding 85 percent for most zones and reaching about 98 percent in the best-constrained one. The zone-to-zone differences in attenuation, lowest over the North Moesia ridge and strongest around the Focsani Basin and Transylvanian side, directly explain why previous non-zonated studies produced such wildly different attenuation functions: they were averaging over irreducibly heterogeneous propagation paths. Site amplification envelopes derived for each zone are physically plausible and match independent stratigraphic evidence, with the deep basins amplifying long-period motion and the shallow-bedrock zones concentrating their response at short periods.

The implications extend well beyond Romania. Vrancea belongs to a very small global class of highly active intermediate-depth seismic nests, alongside Bucaramanga in Colombia and the Hindu Kush in Afghanistan, and its earthquakes shape seismic design requirements across more than two-thirds of Romanian territory. The long-period amplification characteristic of Vrancea ground motions is already embedded in the Romanian design code through spectral corner periods of 0.7, 1.0 and 1.6 seconds, far longer than the 0.3 to 0.5 second bands typical elsewhere, pushing the most severe seismic demand from low-rise buildings toward mid- and high-rise structures. The new framework, the authors argue, is transferable to any tectonic setting characterized by sparse strong-motion data and non-standard ground motions, provided sufficient independent geological and geophysical information exists to structure the regional heterogeneity. The broader lesson is perhaps the most satisfying one in science: what looks like an exception to the rules may simply be a complicated case in which the rules have not yet been applied coherently. Vrancea, it turns out, was never breaking the laws of seismology. It was just hiding them behind layers of complexity that no one had thought to peel apart.

Subject of Research: Seismic complexity and ground-motion characterization of the Vrancea intermediate-depth seismic source in Romania

Article Title: Defining and resolving seismic complexity through a unified source–path–site framework: the Vrancea intermediate-depth ground motions

Article References: Cotovanu, A., Cojan, E., & Vacareanu, R. (2026). Defining and resolving seismic complexity through a unified source–path–site framework: the Vrancea intermediate-depth ground motions. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02713-4

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02713-4

Keywords: Vrancea, intermediate-depth earthquakes, seismic hazard, stress drop, anelastic attenuation, geometrical spreading, site amplification, ground motion prediction, Romania, Carpathians, sedimentary basins, seismology

The research, led by Dongyeon Lee of Hanyang University together with colleagues from Korea Hydro and Nuclear Power and the Korea Advanced Institute of Science and Technology, tackles a long-standing gap in earthquake engineering practice. Spatial coherency describes how the similarity between ground motions at two locations decays as the separation between them grows and as the frequency of the shaking increases. Empirical models built from dense arrays such as those at Lotung in Taiwan or Chiba in Japan have long served as the reference standard, but they are inherently site-specific. Extending them to a new site means installing instruments and waiting for earthquakes to happen, which is neither practical nor economical for most engineering projects. The Korean team’s alternative is to predict coherency from first principles, using the measured spatial statistics of the soil itself as the input.

The physical basis of the new framework is the recognition that incoherency at a single site arises largely from the heterogeneity of the subsurface. Shear waves traveling upward through soil encounter pockets and layers of varying stiffness, and each encounter scatters and delays the wavefield slightly differently at every location. If the spatial distribution of shear wave velocity, denoted Vs, is known in statistical terms, the resulting distortion of the wavefield can, in principle, be computed. The researchers therefore set out to measure Vs variability directly and feed those statistics into a two-dimensional finite-element model of the soil deposit, generating Gaussian random fields whose coefficient of variation and correlation lengths match the field measurements.

Validating such a framework requires ground truth, and this is where the centrifuge enters the story. Geotechnical centrifuges allow engineers to test scaled physical models of soil deposits under properly scaled gravitational stress, reproducing the stress-dependent stiffness and damping behavior that governs wave propagation at full scale. The team constructed two soil models in the centrifuge, one a single-layered deposit and the other a double-layered deposit, and subjected them to recorded earthquake motions using an on-board earthquake simulator. Crucially, they characterized the spatial variability of the models themselves using bender elements and cone-penetration tests at multiple locations, obtaining the coefficient of variation and correlation lengths needed to build representative random fields. This pairing of physical testing and statistical characterization is what gives the study its unusual rigor.

On the computational side, each physical model was represented by a two-dimensional finite-element mesh, and the researchers ran a substantial campaign of simulations: ten bedrock motions recorded during the centrifuge tests were combined with thirty random-field realizations for each model, producing three hundred time-history analyses per deposit. Each realization represents one plausible arrangement of the measured soil heterogeneity, and the ensemble captures the range of responses that variability can produce. From the simulated surface motions at multiple locations, the team computed coherency functions in the same manner used for array recordings, binning results by separation distance so that they could be compared directly with the coherency derived from the centrifuge sensors.

The agreement reported is striking. The numerical models closely reproduced the measured response spectra and the shear stress-strain behavior observed in the centrifuge, confirming that the wave propagation physics was being captured correctly. More importantly for the study’s central claim, the coherency models computed from the simulations showed strong agreement with the centrifuge-derived coherency across all separation-distance bins. In other words, once the spatial variability statistics of the soil are known, the simulation does not merely approximate the general character of incoherency; it tracks the measured decay of coherency with distance and frequency in detail.

The implications extend well beyond the laboratory. Sites hosting critical infrastructure, particularly nuclear facilities, increasingly demand site-specific coherency models for soil-structure interaction analysis, and regulators in several countries have pressed for models tailored to local conditions. In Korea, for example, recent work has focused on generating coherency models suitable for nuclear power plant sites where no dense arrays exist. A validated simulation-based framework means that a project team could characterize a site with conventional geotechnical investigation tools, bender element tests and cone-penetration soundings are routine in practice, and then compute a coherency model numerically rather than waiting years for array data to accumulate. The study’s authors present this as a practical alternative to empirical models whenever site-specific spatial variability parameters are available.

The work also connects to a broader trend in geotechnical engineering: the treatment of soil spatial variability as a quantifiable random field rather than a nuisance to be averaged away. Probabilistic approaches using random-field theory have transformed reliability analysis of slopes, foundations, and liquefaction assessments over the past two decades. What this study adds is a bridge between that statistical tradition and the wave-propagation community concerned with spatially varying earthquake ground motion. By demonstrating that measured Vs statistics suffice to predict coherency, the researchers effectively show that the two communities’ toolkits can be combined, with site investigation data flowing directly into ground-motion incoherency predictions.

There are, of course, boundaries to what the framework has so far demonstrated. The validation was performed on idealized laboratory deposits in a centrifuge, where the soil variability could be measured exhaustively and the input motions were fully known. Real field sites present additional complications, including three-dimensional subsurface topography, deeper and more variable layering, and uncertainty in bedrock input motions. The authors note that their findings establish the feasibility of simulation-based coherency estimation, and extending the approach to field conditions is the natural next step. Even so, the core result stands: the physics linking soil heterogeneity to ground-motion incoherency is now demonstrably reproducible in a validated numerical setting.

For engineers designing the next generation of long-span bridges, lifeline networks, and nuclear structures, the message is that coherency analysis need no longer be the exclusive privilege of instrumented sites. A well-characterized soil profile, a finite-element model, and a modest computational campaign of random-field realizations can deliver a defensible, site-specific coherency model, one that has now been checked against physical reality at centrifuge scale. As seismic design codes continue to move toward performance-based criteria that explicitly account for the spatial character of shaking, tools of this kind are likely to move from research papers into standard practice, changing how the profession thinks about what lies beneath the foundations of everything it builds.

Subject of Research: Centrifuge-validated numerical simulation of spatial seismic ground-motion coherency in heterogeneous soil deposits

Article Title: Centrifuge-validated numerical framework for estimating seismic coherency

Article References: Centrifuge-validated numerical framework for estimating seismic coherency. (n.d.). https://doi.org/10.1007/s10518-026-02714-3

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02714-3

Keywords: seismic coherency, spatial variability, shear wave velocity, centrifuge testing, finite element analysis, Gaussian random fields, site response, soil-structure interaction, earthquake engineering, geotechnical engineering, dense seismic arrays, Bulletin of Earthquake Engineering

The study, published in Communications Earth & Environment, was led by Rikuto Fukushima of Stanford University, together with Masayuki Kano of Kyoto University and the Japan Agency for Marine-Earth Science and Technology, Kazuro Hirahara of RIKEN and Kagawa University, and Makiko Ohtani of Kyoto University. Their target was the 2010 Bungo slow slip event, a well-documented episode of silent fault motion that struck the Bungo Channel region between the islands of Shikoku and Kyushu. What the team found was a striking picture of frictional heterogeneity: the slow slip event nucleated in a localized patch off southwest Shikoku, where frictional properties differ sharply from their surroundings, and then propagated westward along the plate boundary.

To understand why this matters, it helps to grasp the long-standing puzzle of fault behavior. Laboratory experiments on rock samples have shown that faults obey friction laws — mathematical rules describing how resistance to sliding depends on slip rate, contact time, and other variables. When modelers feed these laboratory-derived laws into simulations of fault slip, the simulations naturally produce a rich diversity of behavior: some patches rupture rapidly as earthquakes, others creep slowly, and still others remain locked for centuries, accumulating the strain that eventually powers the largest quakes. The agreement between such simulations and real observations has long supported the hypothesis that the observed diversity of slip — from fast earthquakes to slow transient events — arises from spatial variations in frictional properties stamped into the fault by geology.

But there has been a stubborn gap between that elegant hypothesis and hard data. Confirming it quantitatively would require taking real geodetic observations — the millimeter-to-centimeter shifts of GPS stations as an unseen fault slips below — and working backwards to infer the frictional parameters that must have produced them. That inverse problem is brutally difficult. A fault plane is a two-dimensional surface, and frictional properties vary across it point by point, meaning the unknowns number in the thousands or more. Traditional optimization methods buckle under this high-dimensional search space, so most studies have settled for estimating only the distribution of fault slip itself, leaving the underlying friction physics unconstrained. The new work was designed precisely to close that gap.

The team’s solution was to deploy physics-informed neural networks, or PINNs, a technique that has swept through computational physics in recent years. In a conventional neural network application, the network learns patterns purely from data. In a PINN, the network is additionally constrained to obey the governing equations of the physical system — in this case, the equations of quasi-dynamic fault slip based on rate- and state-dependent friction laws. The researchers used the neural network to represent the spatially variable frictional properties on the fault surface. Because a neural network can encode smooth, structured fields with relatively few internal parameters, it tames the high-dimensional optimization problem that had defeated earlier approaches. The network’s outputs are fed into the fault mechanics equations, and the mismatch between the resulting predicted surface displacements and the actual GPS observations drives the training, pulling the estimated friction field toward one that is simultaneously mechanically consistent and consistent with the data.

Applying this framework to the 2010 Bungo slow slip event, the researchers estimated the heterogeneous frictional parameters along the subducting plate interface beneath southwest Japan. The resulting picture showed frictional properties varying systematically along the fault, with a localized region off southwest Shikoku standing out as the nucleation zone where the slow slip event began. From there, the event propagated westward, a pattern that emerged naturally from the estimated friction distribution. Crucially, the calculated fault slip produced by those frictional properties successfully reproduced the spatio-temporal pattern of the observed surface displacements — not just how much the ground moved, but the sequence and geography of that motion through time.

This dual consistency is what sets the result apart. Many previous slip models could fit geodetic data, but they said nothing about whether the inferred slip was physically achievable given plausible fault friction. Conversely, forward simulations of fault cycles could produce realistic slow slip events, but only for assumed friction distributions, not ones verified against observations. The PINN-based inversion delivers a model that is validated on both fronts: it is a mechanically consistent fault slip model, grounded in laboratory-derived friction physics, and it is quantitatively checked against real measurements. In effect, the team has demonstrated that the frictional heterogeneity hypothesis — the idea that patchy friction generates the spectrum of slip behavior — can be tested against data rather than merely assumed.

The study did not stop at reconstructing the past. The researchers also used their estimated friction model to forecast the future evolution of fault slip, and in doing so they uncovered a practical lesson for the emerging field of earthquake forecasting. The accuracy of such forecasts depends heavily on how much observational history is assimilated into the model. By assimilating observations spanning multiple slow slip event cycles, rather than a single event, the forecasts become substantially more reliable. This finding carries a clear message for monitoring networks: continuous, long-term geodetic observation is not just an archive of past behavior but an essential ingredient for anticipating future fault motion.

The implications reach well beyond the Bungo Channel. Slow slip events are now recognized along many of the world’s subduction zones, including Cascadia in the Pacific Northwest, Mexico, Chile, New Zealand, and Alaska. In several of these regions, slow slip episodes have been linked to heightened stress on adjacent locked patches capable of producing large earthquakes — most notably in the lead-up to the 2011 Tohoku-oki earthquake in Japan, where precursory slow slip near the hypocenter has been documented. If physics-informed inversion can map the frictional architecture of these faults from routine GPS data, it could eventually help scientists identify which slow slip events are routine and which signal dangerous stress transfer toward locked, earthquake-ready patches.

The methodological advance may prove just as consequential as the specific findings. High-dimensional inverse problems pervade geophysics, from imaging Earth’s interior to modeling magma chambers and groundwater flow. By showing that a neural network can serve as a compact, physically constrained representation of a complex field like fault friction — and that training it against both physical laws and observational data yields a solution previously out of reach — the study opens a template that other researchers can adapt. The work was supported by Japan’s MEXT STAR-E and STAR-E NEXT projects, the Earthquake Research Institute at the University of Tokyo, and JSPS KAKENHI grants, reflecting a sustained national investment in earthquake science and machine learning.

For a field that has spent half a century bridging laboratory rock mechanics and field observation, the arrival of a tool that finally connects the two at scale is a genuine milestone. The 2010 Bungo slow slip event slipped silently, registering only as a gentle drift of GPS antennas across Shikoku and Kyushu. Yet within that quiet drift lay the frictional blueprint of the fault itself — and now, with physics-informed deep learning, scientists have learned to read it. The same approach, applied to longer and richer observational records, promises not only a deeper understanding of how faults work but a step toward the long-sought goal of physics-based fault slip forecasting, where the slow whispers of a fault today inform the assessment of its roar tomorrow.

Subject of Research: Physics-informed deep learning estimation of spatially variable fault friction from geodetic observations of slow slip events

Article Title: Physics-informed deep learning links geodetic data and fault friction

Article References: Fukushima, R., Kano, M., Hirahara, K., & Ohtani, M. (2026). Physics-informed deep learning links geodetic data and fault friction. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04138-y

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04138-y

Keywords: physics-informed neural networks, slow slip events, fault friction, geodesy, subduction zone, Bungo Channel, rate-and-state friction, machine learning, seismology, earthquake forecasting, southwest Japan, fault mechanics

The physics behind the approach rests on how earthquakes nucleate. Before a fault ruptures in the plastic, seismic stage, rock undergoes a slow, elastic stage of stress accumulation. Laboratory experiments on glass samples, used as analogues for rock, have shown that this pre-plastic creep stage manifests in the development of small cracks that coalesce into larger splits, accompanied by measurable electromagnetic radiation. In a confined aquifer, this slow deformation changes the pressure field: in zones of preliminary extension, the groundwater system responds to a lower hydrostatic load before the event and a higher load afterward, while in zones of compression the trend is reversed, with a water-level rise expected before the shock. Because the duration of the elastic stage lengthens as the coming earthquake grows in magnitude, these subtle pressure changes should cross a sensor’s detection threshold earlier for larger events, which is precisely what makes wells a plausible forecasting tool rather than merely a post-event recorder.

History has long hinted at this connection. Abnormal water-level changes were documented in many Japanese wells before both the 1978 magnitude 6.8 Izu-Oshima earthquake and the devastating 1995 Kobe earthquake, alongside shifts in groundwater temperature, radon emission, chloride and sulfate concentrations, and dissolved gas ratios in mineral springs. Those recurring hydrologic precursors prompted the Japanese government to maintain water-level monitoring at more than 30 wells in seismically active areas. In Israel, earlier work along the Dead Sea Transform found indications of two moderate earthquakes in 2004 about one hour before the first seismographic record, in wells located roughly 100 kilometers apart. What has been missing, the researchers argue, is a constant, reliable, high-temporal-resolution dataset capable of turning such sporadic observations into a systematic alert scheme.

To build one, the team selected non-operational wells owned by Mekorot, the Israeli national water company, that satisfied a strict set of hydrogeological criteria. Each borehole had to tap a confined aquifer, because the higher water head in confinement amplifies the tectonic stress-imposed pressure reaction, and had to sit near an active tectonic system that acts as a vector of the regional stress field. The wells also had to be dedicated to observation only, disconnected from pumping systems, and located far enough from neighboring production wells to avoid artificial interference. The final network included the Carmel 13, Ta’anach 4, Nurit 1 and, later, Hindaj 2 wells, all positioned along major faults of the Dead Sea Transform, which links the Red Sea and Suez rifting to the great fault systems of the Eastern Mediterranean, including the Hellenistic arc and the North Anatolian system.

The instrumentation evolved through three research phases. Early observations relied on sporadic water-level readings caught by Mekorot’s maintenance system, then on a SCADA telemetry platform with a 15-minute sampling resolution that proved too coarse. The final configuration paired MSI Scantech potentiometric pressure sensors with GLI International combined temperature and electrical conductivity probes, connected to a 3Gtrack GS282-H2 GPRS data logger that samples every minute and transmits to a central Hydrogeological and Seismological Information Center every 15 minutes. Minute-level resolution matters because the precursory signals are small: groundwater level responses during the study ranged over just a few centimeters, and conductivity shifts of a few hundred micro-Siemens had to be separated from natural daily oscillations of several hundred micro-Siemens driven largely by tidal effects.

The analytical core of the system is short-term forward modeling. Water level, which descends gradually in summer and rises in winter, is modeled with linear regression whose slope and intercept are continually updated from a moving average over the previous 48 hours. Groundwater conductivity, which oscillates with a daily rhythm attributed to lunar tidal effects even in inland confined aquifers, is modeled with a nonlinear cosine-based regression whose amplitude, frequency and datum coefficients are fitted over roughly a day of training data. The model’s forward trajectory is then extrapolated four training-period lengths into the future and compared against incoming measurements. When the correlation between modeled and measured data falls below 0.8, the divergence is flagged as distinct. Anomaly detection combines Seasonal and Trend decomposition using Loess and Differential Seasonal Rolling Z statistics for the linear water-level series with a short-term memory autoencoder and Z-score methods for the nonlinear conductivity series, all applied to raw sorted data because preprocessing steps such as band-pass filtration were found to introduce bias.

The decisive test came on 27 June 2015, when the magnitude 5.5 earthquake struck offshore Saudi Arabia. Both the Hindaj 2 and Carmel 13 wells diverged from their predicted water-level trajectories several hours before the event: Hindaj 2 showed a rise of about one centimeter against its descending trend, while Carmel 13 showed a relaxation of its own decline. More strikingly, groundwater conductivity at both sites increased by approximately 200 micro-Siemens per square centimeter about six hours before the shock, while the correlation with the baseline model dropped by about 20 percent. When the automated detection system was later run on the archived data, it registered four independent indicators across the two wells, generating an alert more than an hour before the earthquake. By contrast, most smaller events, including quakes as weak as magnitude 2.3 offshore Cyprus and twin magnitude 3.1 events near Sinai and Beirut in October 2014, produced only post-event reactions or sporadic single indications that could not be distinguished from natural fluctuation.

The statistical architecture is designed to suppress false positives, the historic Achilles heel of earthquake prediction research. A single anomaly carries no significance, since anomalies attributed to earthquakes have repeatedly appeared only after events or in unsystematic patterns days, weeks or months beforehand. The system therefore requires three independent indications within a single time frame. With a three-day scanning window at five-minute sampling resolution, yielding 432 points per series, the joint probability of three coincidental independent anomalies is calculated as roughly 1.24 times 10 to the minus 8, giving a confidence level above 0.99999 that the pattern is not random. Independence is established both spatially, through multiple monitoring stations, and physically, through different measured parameters drawn from separate sensors. Validation on held-out datasets from 2016 to 2019 showed the calibrated platform reliably identifying events above magnitude 3, including advance identification of a magnitude 3.4 event on 6 March 2019, while smaller magnitude 2.6 events escaped detection.

The study’s conclusion formally rejects the null hypothesis that groundwater pressure and conductivity anomalies are unrelated to tectonic stress. The authors propose that pre-seismic slow motion, part of the pressure accumulation that precedes fault rupture, is reflected in aquifer properties before the seismic event, and that seismic stress is routed along fault systems to hydrologically reactive pressure joints, a mechanism also reported for distant earthquakes in Iran. The practical sensitivity threshold aligns with operational needs: since early warning for events below magnitude 6 is largely redundant, the system’s ability to statistically validate events of that scale and above, using single indicators for shocks above magnitude 3.5 and triple-indicator alerts above magnitude 5.5, matches the hazard that matters. Future development outlined by the team includes an automated warning platform for magnitude 6 and greater events, expanded coverage of both the Dead Sea Transform and the Carmel-Gilboa fault system, a minimum of three monitoring wells per fault system, and a triangulation algorithm that could use indications from different locations to estimate the epicenter of a coming quake.

If the approach matures, the implications extend well beyond the eastern Mediterranean. Confined, fractured rock aquifers near active faults exist along most of the world’s major plate boundaries, and the required sensors, pressure transducers and conductivity probes, are inexpensive compared with seismological networks. The method would not replace P-wave-based early warning systems such as Japan’s, which provide seconds of notice at the epicenter, but it targets a different and potentially more valuable window: hours of lead time, enough for task forces to mobilize, infrastructure to be shut down safely and populations to be alerted. For a field that has chased reliable short-term prediction since the 1970s through foreshocks, geodetic changes, radon emission and even unusual animal behavior, the sight of four independent groundwater sensors agreeing on an impending rupture, an hour in advance, marks a rare and tantalizing step from anomaly hunting toward operational forecasting.

Subject of Research: Groundwater monitoring as an early indicator of tectonic ground movements and earthquakes along the Dead Sea Transform

Article Title: Potential early indication of tectonic ground movements by water-well monitoring datasets, with short-term forward modeling

Article References: Potential early indication of tectonic ground movements by water-well monitoring datasets, with short-term forward modeling. (n.d.). https://doi.org/10.1007/s12665-026-13154-2

Image Credits: AI Generated

DOI: 10.1007/s12665-026-13154-2

Keywords: earthquake prediction, groundwater monitoring, Dead Sea Transform, confined aquifer, early warning systems, hydrogeology, seismology, water level anomalies, electrical conductivity, forward modeling, anomaly detection, Jordan Rift Valley

The technique in question is seismic interferometry applied to coda waves, the long, reverberating tail of shaking that follows a large earthquake. When two seismic stations record the same big quake, and researchers cross-correlate the late portions of those recordings, something remarkable emerges: a waveform that looks as if a wave had traveled directly between the two stations, even though no earthquake ever sat at either one. Among the arrivals that appear in these stacked correlations are core phases such as ScS, which reflects off the core-mantle boundary, and PKIKP squared, which passes through the inner core itself. These reconstructed signals have already been used to probe the fine structure of the inner core, including its anisotropy and shear-wave speed.

The trouble is that the classical theory behind interferometry makes demands that coda waves simply do not meet. Cross-correlating noise records converges to the true Green’s function, the complete description of wave propagation between two points, only under idealized conditions, such as a perfectly uniform distribution of noise sources surrounding the stations or a wavefield whose energy is equipartitioned among all directions. Late coda waves violate these conditions. The result has been a persistent unease in the community: reconstructed core phases show anomalously high amplitudes compared with real earthquake data, and their travel times are known to be influenced by earthquake-station geometry, focal mechanisms, and the particular coda time window chosen for correlation. In short, nobody could say with rigor whether the extracted arrival times were true measurements or artifacts.

Yingjie Xia, Xuping Feng, and Xiaofei Chen, of Chengdu University of Technology and the Southern University of Science and Technology, tackled this problem in a study published in Solid Earth in June 2026. Rather than relying on the asymptotic approximations, such as the stationary phase method, that previous theoretical treatments employed, they built a perturbation-based framework. The strategy is elegant: start with a solvable reference model, a bounded homogeneous medium bounded by two discontinuous surfaces that mimics reflections between the Earth’s surface and the core-mantle boundary, and then perturb it to see how much the answer can drift. The reference model allows exact ray-path calculations, with path lengths expressed in closed form for waves that undergo any number of reflections before reaching each station.

From this foundation, the authors derived a strikingly simple and practical result. They introduced a dimensionless parameter defined as the ratio of the seismic wave period to the inter-station travel time, and showed that it establishes a critical angular threshold. For a reconstructed arrival to be free of interference from spurious waves, the incident wavefield must be locally uniform over an angular range at least as large as this threshold, which equals twice the arcsine of half the period-to-travel-time ratio. The perturbation analysis then revealed something even more useful: the error in the reconstructed travel time scales with the cube of this threshold angle. Small thresholds therefore mean tiny errors, and core phases, with their extraordinarily long propagation paths, naturally have very small thresholds.

The numbers make the point vividly. Consider the ScS phase, which has a dominant period of about 50 seconds and a travel time of roughly 1,000 seconds between stations separated by 10 degrees. The threshold angle works out to about 18 degrees. Converting to radians and applying the cubic error formula yields a timing uncertainty on the order of the third derivative of the deviation function divided by 220, which is negligible whenever the wavefield varies smoothly around the inter-station ray path. For PKIKP squared, which takes about 2,500 seconds and has a threshold angle near 11 degrees, the situation is even more favorable. In other words, the very phases that matter most for probing the deep interior are precisely the ones that interferometry reconstructs most accurately.

The framework also resolves a long-standing puzzle about which earthquakes actually contribute to the reconstruction. Intuition might suggest that only quakes lying on the great-circle plane connecting the two stations matter. The theory says otherwise. Because core phases arrive at steep incidence angles, the stable angular range they require encompasses waves arriving from planes that deviate substantially from the inter-station plane. The authors quantify this with a geometric parameter relating the threshold angle to the incidence angle of the target phase. For ScS at 10 degrees of station separation, this parameter reaches about 6; for PKIKP squared it climbs to about 11. When the parameter exceeds one, even coda waves radiated from earthquakes in planes perpendicular to the inter-station plane fall within the stable range and contribute constructively. This explains why a modest, globally scattered set of earthquakes can suffice, relaxing the traditionally assumed requirement for a uniform source distribution.

Numerical simulations confirmed the theory before it faced the real Earth. When the researchers truncated the angular integration at values corresponding to a single pi phase shift, spurious waves interfered with the reconstructed arrival and shifted its phase. At the critical 2-pi threshold, the two wave packets aligned and the true travel time was recovered exactly. Beyond that, at 4 pi, the packets separated entirely and the reconstruction remained clean. A further test with a deliberately non-cosine distribution of travel-time differences, chosen to mimic the complexities of real coda including P-to-S conversions, produced reconstructions nearly identical to the ideal case, validating the perturbation approach.

The decisive test came from real data. The team selected 205 large earthquakes of magnitude 6.8 or greater between 2010 and 2020, downloaded broadband waveforms from stations of the USArray Transportable Array, and cross-correlated coda windows extending from 10,000 to 40,000 seconds after each event’s origin time, bandpass filtered between 15 and 50 seconds of period. The stacked correlograms showed prominent PcP, ScS, and PKIKP squared arrivals at travel times matching the ak135 reference model. A bootstrap analysis, progressively increasing the number of earthquakes in each stack from 10 to 120 across 250 random realizations, showed that mean travel times stabilized and standard deviations shrank as events accumulated. With fewer than roughly 20 earthquakes, deviations exceeded one second; convergence emerged with about 50 to 100 well-distributed events. Crucially, when the data were split by the deviation angle between earthquake and inter-station planes, ScS travel times wandered by up to 3 seconds across different deviation ranges, while PKIKP squared times remained nearly identical, exactly as the high geometric parameter predicted.

The implications reach beyond a single method. The study proposes that a long-running debate, over whether coda-correlation phases represent true inter-station arrivals or a modified wavefield whose timing depends on source distribution, dissolves into a matter of degree. Two conditions jointly determine the outcome: the illumination condition, meaning the incident waves must sample the critical angular range, testable through bootstrap convergence, and a smoothness condition, meaning the velocity structure along the path must yield a smoothly varying deviation function, which ray theory generally guarantees. When both hold, the reconstructed phase is the true arrival; when they fail, the biased measurement appears instead. For researchers mapping the inner core, tracking its rotation, or estimating its shear-wave speed, this framework provides something previously missing: a quantitative, practical criterion for knowing when their measurements can be trusted. The echoes of distant earthquakes, it turns out, were speaking clearly all along; now seismologists finally have the mathematics to prove it.

Subject of Research: Travel-time accuracy of core phases reconstructed by seismic coda-wave interferometry

Article Title: Perturbation analysis of travel-time accuracy for core phases reconstructed from seismic interferometry

Article References: Xia, Y., Feng, X., & Chen, X. (2026). Perturbation analysis of travel-time accuracy for core phases reconstructed from seismic interferometry. Solid Earth, 17(6), 855-866. https://doi.org/10.5194/se-17-855-2026

Image Credits: AI Generated

DOI: 10.5194/se-17-855-2026

Keywords: seismology, seismic interferometry, coda waves, core phases, Earth's inner core, travel-time accuracy, perturbation analysis, Green's function retrieval, core-mantle boundary, PKIKP, ScS, deep Earth imaging

A team of Czech seismologists led by Pavla Hrubcová has analysed two earthquakes that struck near Mirotice, one of magnitude 3.5 in March 2024 and a smaller magnitude 3.1 event in April 2025, combining conventional seismological data with more than 1,500 citizen-filled macroseismic questionnaires for each event. Their study, published in the journal Solid Earth, demonstrates that ordinary people describing their experiences can effectively constrain deep geological structures in a region where earthquakes, and therefore seismic instruments’ chances of illuminating the subsurface, are few and far between.

What made these earthquakes scientifically remarkable was not their size but their depth. Both events originated at approximately 24.5 kilometres beneath the surface, an unusually large focal depth for the Bohemian Massif, where present-day seismicity is low and typically confined to the upper crust at depths of less than 12 kilometres. The 2024 event was followed by four minor aftershocks within an hour and further weak events over the following weeks; the 2025 earthquake produced a similar modest aftershock sequence. A small magnitude 1.7 earthquake in 2012, located at nearly the same position and at 19 kilometres depth, had already hinted that something unusual was happening deep beneath this quiet corner of Bohemia.

Pinpointing the events required assembling waveforms from a patchwork of seismic networks spanning the Czech Regional Seismic Network, Saxon and German networks, local Czech networks, temporary stations from the ongoing AdriaArray experiment, and even industrial monitoring arrays. Hypocentres were computed using a three-dimensional location program with a one-dimensional gradient velocity model calibrated against travel times from deep seismic refraction experiments and quarry blasts. The depth estimates were cross-checked using the sP depth phase recorded at epicentral distances of 140 to 210 kilometres, and by verifying that independent focal mechanism inversions yielded consistent solutions. Both earthquakes showed normal faulting on a steeply dipping, northwest-southeast striking fault plane, derived from full waveform moment tensor inversion using the Bayesian ISOLA method and a velocity model drawn from the nearby CEL09 refraction profile of the CELEBRATION 2000 experiment.

But the real revelation came from the public. Despite the epicentral area being rural and sparsely populated, with roughly 20 to 50 people per square kilometre, the Institute of Geophysics collected 1,512 questionnaires for the 2024 earthquake and 1,679 for the 2025 event, submitted through online forms and a smartphone application. Media interviews following unusual events in Czechia regularly encourage citizens to report their experiences, and the response rate was so reliable that only about 2 percent of questionnaires had to be discarded for inconsistent timing, duplication, or effects not clearly attributable to the earthquake. Notably, the weaker 2025 earthquake actually generated more reports than the stronger 2024 event, a testament to both public engagement and unusually efficient transmission of seismic energy from depth.

Respondents described shaking felt across distances of 70 to 100 kilometres from the epicentre, reaching the towns of Písek, Strakonice, and Tábor and the Šumava Mountains. For the 2024 event, 66 percent of respondents reported light shaking and 17 percent strong shaking, while around 90 percent of reports in both years included acoustic phenomena such as rumbling or booming sounds. Individual responses were converted into intensities on the European Macroseismic Scale EMS-98, with qualitative terms like few, many, and most quantified into percentage ranges. Reports that the earthquake was heard but not felt were treated separately as heard-only observations, since acoustic effects alone are not diagnostic for intensity assignment. Maximum intensities reached IV to V for the 2024 event and IV for the 2025 event, with occasional hairline cracks in plaster reported near the epicentre.

The striking feature, however, was not how strong the shaking was but where it was felt. Rather than spreading in a roughly circular pattern around the epicentre, as would be expected in a geologically homogeneous region, the observations formed a distinctly trapezoidal patch, sharply bounded on the west by the contact between the Teplá-Barrandian Unit and the Moldanubian Domain, and on the east by the Rödl-Blanice Fault System. Crucially, this asymmetry could not be explained by population distribution. The more densely populated region around Pilsen to the west produced almost no reports, while the sparsely settled epicentral area yielded dense coverage. Normalising the observations by population density would only sharpen the contrast.

The geological explanation lies in the contrasting rocks on either side of those boundaries. The trapezoidal zone of strong reports is dominated by the felsic granites and granodiorites of the Central Bohemian Plutonic Complex and the high-grade metamorphic rocks of the Moldanubian Domain, crystalline rocks that attenuate seismic energy weakly and allow waves to propagate efficiently, possibly with resonant effects. West of the pluton, the early Palaeozoic sedimentary sequences of the Teplá-Barrandian Unit, with their steeply oriented, highly anisotropic deformation structures near the contact, appear to absorb seismic energy far more effectively, and observations drop off sharply. To the east, the attenuation coincides with the Rödl-Blanice Fault System, a crustal-scale discontinuity reactivated during the Cretaceous and Miocene. These subvertical structures, the authors argue, are not clearly resolved by conventional seismic investigations, yet the citizen reports delineate them with remarkable clarity.

The tectonic story behind these boundaries stretches back hundreds of millions of years. The Bohemian Massif, the largest exposure of the European Variscan orogenic belt, formed between roughly 500 and 250 million years ago during the convergence of the ancient continents Gondwana and Baltica. The closure of the Saxothuringian ocean and subsequent continental underthrusting created the Central Bohemian Plutonic Complex as a magmatic arc at the boundary between the Teplá-Barrandian and Moldanubian units. Deep seismic profiling has revealed that the Moldanubian crust is cold and mechanically strong, with a sharp Moho discontinuity reaching depths of up to 39 kilometres and surface heat flow below 50 milliwatts per square metre. That low geothermal gradient, the study suggests, is what allows brittle failure, and therefore earthquakes, to occur in the lower crust at depths where rocks elsewhere would deform plastically. The hypocentres of the Mirotice events coincide with a reflective interface identified along the CEL09 profile, which may represent a structural or rheological discontinuity controlling earthquake nucleation.

The implications reach well beyond Czechia. In regions of sparse seismicity and limited instrumentation, crowdsourced macroseismic observations offer a cost-effective way to gather large volumes of data that reflect geological controls on seismic wave propagation, complementing instrumental networks that may record only a handful of events per decade. The Mirotice study shows that the pattern of who felt an earthquake, and who did not, can trace deep, steeply dipping tectonic boundaries rooted in the lower crust, structures that pre-Permian thrusts in the Variscan belt are known to follow. Two modest earthquakes, felt by thousands of ordinary people and dutifully reported through a web questionnaire, have drawn a portrait of the deep crust that no amount of waiting for the next big event could have produced. In seismology’s quiet corners, it seems, the public itself has become the most sensitive array of all.

Subject of Research: Crowdsourced macroseismic observations of two rare deep earthquakes constrain crustal structure in the south Bohemian Massif

Article Title: Public response to two rare earthquakes: crowdsourcing constraints on crustal structure in south Bohemian Massif

Article References: Hrubcová, P., Machek, M., Vackář, J., Pohořalá, A., Kampfová Exnerová, H., Špaček, P., & Zedník, J. (2026). Public response to two rare earthquakes: crowdsourcing constraints on crustal structure in south Bohemian Massif. Solid Earth, 17(8), 979-989. https://doi.org/10.5194/se-17-979-2026

Image Credits: AI Generated

DOI: 10.5194/se-17-979-2026

Keywords: earthquakes, Bohemian Massif, crowdsourcing, macroseismic intensity, crustal structure, seismology, Czechia, Mirotice, intraplate seismicity, seismic attenuation, Variscan orogeny, citizen science

The q-Pareto distribution, or q-PD, belongs to a broader family of q-exponential distributions that emerged from the work of Constantino Tsallis, who introduced the q-logarithmic and q-exponential functions in the 1990s as generalizations of the ordinary logarithm and exponential. These functions arise naturally in the study of complex systems, where they maximize a generalized entropy known as Tsallis entropy, extending the classical Boltzmann-Gibbs framework that governs systems at equilibrium. The single parameter q controls how slowly the tail of the distribution decays, and this is precisely what makes the q-PD attractive for phenomena dominated by rare, extreme events. When q equals one, the familiar exponential behavior is recovered; when q differs from one, power-law-like tails emerge, allowing small changes in parameters to translate into enormous changes in the predicted frequency of catastrophic outcomes.

Heavy-tailed distributions of this kind are not merely academic curiosities. Earthquake magnitudes are measured on logarithmic scales, meaning that each incremental increase in magnitude corresponds to roughly a tenfold increase in shaking amplitude and about a thirty-two-fold increase in the energy released. The Richter scale, developed in 1935, works reasonably well for small to moderate local events but loses accuracy for the largest earthquakes, exactly where accurate statistical modeling matters most. Distributions related to the Pareto family, including the log-Pareto, tapered Pareto, and generalized Pareto distributions, have therefore become standard tools for describing the energy released by major seismic events. The q-PD, proposed in its current form by de la Barra and Vega-Jorquera in 2021, has proven especially effective for modeling the magnitudes of the largest, most extreme earthquakes in global catalogues, and it also finds use in insurance and actuarial statistics for pricing reinsurance premiums against catastrophic losses.

The theoretical foundation of the new work rests on a deep connection between the q-PD and extreme value theory. A cornerstone result of extreme value theory, established independently by Balkema and de Haan in 1974 and by Pickands in 1975, states that for data drawn from almost any unknown distribution, the values that exceed a sufficiently high threshold converge, in distribution, to the generalized Pareto distribution. This is the mathematical justification for the peak-over-threshold method used across hydrology, climatology, finance, and geophysics. Benatia and Kouider prove a theorem showing that the generalized exponential distribution they define, obtained by transforming the q-exponential function, overlaps exactly with the generalized Pareto distribution under a simple reparameterization. Because the q-PD is linked to this generalized exponential distribution through an exponential transformation of the data, the q-PD inherits the same status as a limiting distribution for threshold exceedances, making it a legitimate and principled model for extreme earthquakes rather than an ad hoc curve fit.

Estimating the two parameters of the q-PD, a positive shape parameter q and a positive scale parameter b, is where the practical difficulty lies. Maximum likelihood estimation is the gold standard in statistics because it produces consistent estimators with asymptotically normal distributions and is asymptotically efficient in many settings. However, the likelihood equations for the q-PD do not admit closed-form solutions. Setting the partial derivatives of the log-likelihood to zero yields a nonlinear equation in a transformed parameter that must be solved numerically, and the solution space is constrained: the shape parameter must remain strictly positive, and the admissible range of the data depends on the unknown parameters themselves. The authors show that when the shape parameter is negative, the density becomes unbounded and the standard regularity conditions underpinning maximum likelihood theory fail, so the search must be confined to a carefully defined feasible region.

To navigate these complications, the researchers built their algorithm around a modified bisection algorithm for multiple roots, a numerical technique previously developed by Kouider. Compared with the more commonly used combination of bisection and Newton’s method, the modified bisection approach offers distinct advantages: it does not require computing derivatives of the objective function at reference points, and it does not depend on an initial solution, a factor that can cause Newton’s method to converge to spurious points if the starting values are poorly chosen. The authors prove a theorem that provides explicit lower and upper bounds for the transformed parameter, derived using Jensen’s inequality and properties of the order statistics of the sample. These bounds guarantee that the root-finding procedure operates within a known interval, and a small tolerance parameter, scaled to the sample, keeps the iterative solutions from straying outside the feasible set. Once candidate roots are located, the algorithm evaluates the log-likelihood at each corresponding parameter pair, distinguishes genuine local maxima from boundary maxima, and selects the pair that achieves the highest likelihood.

The algorithm also delivers something that raw point estimates cannot: uncertainty quantification. By computing the second-order partial derivatives of the log-likelihood, the authors assemble the observed Fisher information matrix, whose inverse provides the asymptotic variance-covariance structure of the estimators. For samples larger than thirty observations, confidence intervals are constructed using quantiles of the standard normal distribution; for smaller samples, the algorithm switches to Student’s t-distribution with the appropriate degrees of freedom. This built-in machinery for confidence intervals is essential for applied seismologists, who need to know not just a best guess for the tail behavior of earthquake magnitudes but also how reliable that guess is given limited data.

To validate the method, the authors ran a simulation study using the R statistical software. They generated a sample of fifteen values from a q-Pareto distribution with known parameters, choosing a shape parameter of 0.5, a scale parameter of 1, and a threshold of 1, by inverting the distribution function applied to uniform random numbers. Applying their algorithm to this synthetic data recovered maximum likelihood estimates of approximately 0.504 for the shape parameter and 1.024 for the scale parameter, remarkably close to the true values used to generate the data. The corresponding 95 percent confidence intervals, spanning roughly 0.039 to 0.969 for the shape parameter and 0.369 to 1.680 for the scale parameter, comfortably contained the generating values, demonstrating that the procedure is both accurate and honest about its uncertainty even with a very small sample.

The real-world test came from tectonic earthquake activity in and around the British Isles. Using a catalogue of 38 earthquake exceedances recorded over a sixty-day window from late March to late May 2024, drawn from data published by the British Geological Survey, the authors applied their algorithm to the logarithms of the recorded values. The analysis yielded a maximum likelihood shape parameter estimate of about 0.477 and a scale parameter estimate of about 0.557, with 95 percent confidence intervals of roughly 0.211 to 0.743 and 0.345 to 0.768 respectively. A shape parameter well below one indicates a heavy but ultimately manageable tail, quantifying how quickly the probability of larger events decays with magnitude in this region. The authors note that earthquake intensity measurement itself carries subtleties, since intensity scales such as the Modified Mercalli Inventory assess shaking and damage at specific locations rather than the energy emitted at the source, and they treat the threshold selection accordingly in their analysis.

Beyond the immediate application to seismology, the study lays groundwork that other researchers can build upon. Because the generalized exponential distribution the authors define coincides with the generalized Pareto distribution under their reparameterization, the same estimation machinery can be used to estimate the extreme value index, the fundamental quantity that governs how heavy the tail of any underlying distribution is. The approach also connects to a growing body of work on estimating generalized Pareto parameters under difficult conditions, including random censoring, which the authors and collaborators have explored in earlier publications. As extreme events, from earthquakes to floods to financial crashes, increasingly dominate public risk assessments, tools that make sophisticated heavy-tailed modeling fast, robust, and accessible could prove indispensable. The q-Pareto distribution, once a theoretical curiosity from the mathematics of complex systems, is now a practical instrument for reading the seismic signature of the planet’s most violent moments.

Subject of Research: Maximum likelihood estimation of q-Pareto distribution parameters and its application to modeling extreme earthquake magnitudes

Article Title: On computing the maximum likelihood estimates for the q-Pareto distribution and application to earthquakes

Article References: On computing the maximum likelihood estimates for the q-Pareto distribution and application to earthquakes. (n.d.). https://doi.org/10.5194/ascmo-12-211-2026

Image Credits: AI Generated

DOI: 10.5194/ascmo-12-211-2026

Keywords: q-Pareto distribution, maximum likelihood estimation, extreme value theory, earthquakes, seismology, heavy-tailed distributions, Tsallis entropy, generalized Pareto distribution, numerical algorithms, peak-over-threshold, statistics, risk modeling

The mission, known as the Geophysical Instruments for Marius Lunar pit Investigation, or GIMLI, is led by Than Putzig, Associate Director and Senior Scientist at the Planetary Science Institute. PSI is partnering with Honeybee Robotics, a Blue Origin company, which will build much of the equipment and instrumentation and help integrate it onto a lander and rover supplied through the CLPS initiative. The effort will also be carried out in partnership with the Norwegian Space Agency, which is providing the mission’s ground-penetrating radar. Co-Investigators from Boise State University, Johns Hopkins University, the Lunar and Planetary Institute, and the University of Oslo round out a team that spans two continents and multiple disciplines.

The target of the investigation is the Marius Hills Pit, a large hole punched into one of the most volcanically diverse regions on the Moon. Like other lunar pits discovered by orbiting spacecraft, MHP may be a skylight, an opening into a subsurface cavity that formed during ancient volcanic activity. From orbit, scientists have gathered compelling evidence that caves and lava tubes may thread their way beneath the Moon’s surface, but orbital data alone cannot settle the question of what lies beyond the pit’s rim. GIMLI is designed to find out directly, by measuring the subsurface from the ground for the very first time at this site.

Putzig, who has spent much of his career probing planetary interiors with radar and geophysical methods, described the mission as the fulfillment of a long-held ambition. He noted that it has long been a desire of his to reintroduce intentional active-source seismic methods to planetary science, a technique that has essentially not been used since the Apollo astronauts conducted the first seismic surveys on the Moon more than five decades ago. Combining that method with ground-penetrating radar and gravity measurements, he explained, will allow the team to achieve a much better understanding of subsurface properties, including the anticipated detection of a lava tube extending away from the Marius Hills pit.

The technical approach is a masterclass in complementary geophysics. Ground-penetrating radar will transmit electromagnetic pulses into the regolith and record the echoes returned by buried boundaries between rock layers, revealing changes in composition and structure at shallow depths. Seismic sensors, energized by an active source rather than waiting for natural moonquakes, will measure how elastic waves travel through the ground, exposing voids and density contrasts that radar might miss. A gravimeter will detect the minute gravitational signature of an empty space beneath the surface, since a large cavity produces a measurable local deficit in mass. Cameras, meanwhile, will image the surface terrain and the exposed walls of the pit itself, tying the subsurface measurements to visible geology.

Together, these instruments will not only search for an underground void extending from the Marius Hills Pit; if such a void exists, they will also help determine its size. That distinction matters enormously for future human exploration. A cave large enough to shelter hardware and habitats would be a strategic asset for any long-term lunar presence, offering protection from radiation, micrometeorite impacts, and the roughly 300-degree Celsius temperature swings between lunar day and night. Confirming the dimensions and stability of such a space from the surface would transform it from an orbital curiosity into a mapped destination.

Honeybee Robotics will serve as the commercial partner to PSI, providing project management services and building the instrumentation for the active-source seismic system, the gravimeter, and the cameras. The company will also work to integrate all of the instruments onto the lander and rover and, together with PSI, will lead their operations on the lunar surface. The division of labor reflects a growing model in lunar exploration, in which government scientists team up with commercial aerospace firms to fly sophisticated payloads on robotic missions at a fraction of the cost of traditional flagship programs.

Crucially, the mission’s scientific value does not hinge entirely on finding a cave. Even if GIMLI fails to detect a lava tube beneath the surface, the data it collects could still resolve an important mystery: how did the pit form in the first place? Measurements of the surrounding subsurface will speak to the origin of MHP and provide a far better understanding of the geology and volcanic history of the site. The pit walls themselves expose layers of regolith and lava flows that are normally hidden underground, and studying those layers could reveal how lava once traveled across the Moon and whether long stretches of time separated successive eruptions.

The team is also looking beyond the pit itself. The Marius Hills region preserves a long history of volcanic activity, and the interiors of any potential underground spaces could hold a record of the processes that shaped the Moon’s volcanic plains. Gareth Morgan, PSI Senior Scientist and Deputy Principal Investigator on the GIMLI program, explained that confirming a substantial lava tube would give scientists insight into how volcanism operated on the Moon. Lava tubes are a common feature of basaltic volcanism on Earth, he noted, so identifying them on the Moon means researchers could apply knowledge of such terrestrial caves to better understand lunar history.

For the Planetary Science Institute, the selection marks a milestone in its evolution from an organization known primarily for orbital data analysis to one leading surface operations on another world. PSI Director and CEO Amanda Hendrix called GIMLI the type of ambitious planetary science that PSI was built to pursue, saying that Putzig and his team have taken a scientific question the institute has been studying from orbit and developed a way to investigate it directly on the Moon. She expressed excitement about partnering with NASA and Honeybee Robotics to learn more about the Moon and its volcanic past. If the instruments perform as designed, humanity may soon peer, for the first time, into the hidden architecture beneath one of the Moon’s most enigmatic openings, and perhaps take an early step toward making a lunar cave humanity’s first off-world shelter.

Subject of Research: Investigation of a potential lunar lava tube at the Marius Hills Pit using surface geophysical instruments under NASA's PRISM program

Article Title: PSI-led team selected for NASA PRISM program to explore potential lunar cave

Article References: PSI-led team selected for NASA PRISM program to explore potential lunar cave. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Moon, lunar caves, lava tubes, Marius Hills Pit, NASA PRISM, CLPS, Planetary Science Institute, Honeybee Robotics, ground-penetrating radar, seismology, gravimetry, lunar volcanism