The work was led by Daniel Martinez-Jaramillo, a doctoral researcher at the Universidad Nacional Autónoma de México, together with Sreeram-Reddy Kotha of ISTerre in Grenoble, F. Ramón Zúñiga, and Pierre Lacan. Their starting point was the national seismic network of the Colombian Geological Survey, known by its FDSN code CM, which has operated since 1993 and currently comprises 506 seismological and accelerometric stations distributed across the country. Local networks monitoring volcanoes, mining districts, and oil and gas fields contributed additional stations. Upon request, the survey supplied more than 10,000 quality-checked acceleration time series. The team applied strict selection criteria: events between 0 and 14 degrees north latitude and 69 to 82 degrees west longitude, at depths shallower than 50 kilometres, with magnitudes above 4 and stations within 400 kilometres of the epicentre. After discarding volcanic signals and spurious spikes, 667 earthquakes and 7550 records survived the cut, forming what seismologists call a flatfile: a single table describing every earthquake, every recording site, and every measured level of shaking.

The technical care invested in processing these waveforms is what elevates the dataset from a raw archive to a scientific instrument. Each acceleration time series underwent the same sequence of corrections, following protocols established for the Italian strong-motion databases: baseline correction, cosine tapering, a second-order acausal bandpass Butterworth filter, double integration to obtain displacement, linear detrending of that displacement, and double differentiation back to corrected acceleration. The high-pass corner of the filter was made magnitude-dependent, ranging from 0.15 hertz for the smallest events down to 0.05 hertz for the largest, while the low-pass corner was fixed at a median value of 32.26 hertz. A sensitivity analysis showed that this fixed low-pass choice barely affects most records, shifting the orientation-independent RotD50 peak ground acceleration by an average of just 2.31 percent, though 6.4 percent of recordings, concentrated around magnitude 4.5 at distances beyond 250 kilometres, showed variations above 10 percent, likely reflecting high-frequency noise near the filter corner.

The intensity measures extracted from the corrected records are comprehensive. The dataset provides peak ground acceleration, velocity, and displacement for all three components, along with 5 percent-damped spectral accelerations at 31 oscillator periods spanning 0.01 to 8 seconds, computed as RotD50 values, the median over all non-redundant horizontal orientations, a measure now standard in modern ground-motion modelling. Fourier amplitude spectra for each component cover frequencies from 0.04 to 50 hertz, smoothed with the Konno-Ohmachi function, and the effective amplitude spectrum, a geometric combination of the two horizontal components, is also included. Crucially, the authors report the lowest and highest usable frequencies for every record, bounded by a safety factor of 1.25 around the filter corners so that users know exactly which spectral values are trustworthy. This usable-bandwidth information, often omitted from older compilations, allows engineers and seismologists to weight each record appropriately in downstream analyses.

Perhaps the most technically inventive element concerns magnitudes. Moment magnitude is the preferred scale for hazard analysis, but reliable agency-reported values were not available for every event. Where they were missing, the team estimated magnitudes from the recordings themselves by fitting a single-corner Brune omega-squared source model to each corrected spectrum, using a coarse grid search followed by non-linear least-squares refinement in log-log space. From the resulting corner frequency, the source radius was computed assuming a shear-wave velocity of 3.5 kilometres per second, and the seismic moment followed from the Eshelby circular-crack relation under an assumed constant stress drop. Testing stress drops of 1, 3, and 5 megapascals against independently reported moment magnitudes from the Global CMT catalogue and other agencies, the authors found that 5 megapascals reproduced catalogued values best. This procedure homogenised the entire catalogue, ultimately widening the magnitude range to 3.5 through 7.2, with 24 percent of events falling below magnitude 4 once recalculated.

Site characterisation received equal attention. The 227 recording stations are described by their time-averaged shear-wave velocity in the upper 30 metres, the widely used Vs30 parameter, together with horizontal-to-vertical spectral ratios and predominant site periods derived from seismograms. For 154 sites, these parameters come from a recent northwestern South America database, and 28 of them have in-situ, microtremor-based Vs30 measurements. The remaining stations rely on Vs30 values inferred from a topographic-slope-based map of Colombia, a pragmatic but imperfect proxy. The authors are candid about this limitation, noting that proxy-based site parameters introduce additional epistemic uncertainty that may inflate the site-to-site variability observed in their validation, and pointing to H/V spectral ratio classification schemes as a promising complement for future work. Distance metrics are equally thorough: epicentral and hypocentral distances are reported for all events, while finite-fault measures such as Joyner-Boore distance are computed for the 42 earthquakes larger than magnitude 5.5, with rupture dimensions scaled from published empirical relations.

Validation came through residual analysis, the standard test of whether a new dataset behaves consistently with established ground-motion prediction models. The team compared observed peak ground acceleration, spectral accelerations, and effective amplitude spectra against the global NGA-West2 model of Abrahamson and colleagues from 2014, its regional adaptation for northern South America published by Arteta and colleagues in 2023, and the Bayless-Abrahamson 2019 Fourier-spectrum model. The residuals, decomposed into between-event, between-site, and leftover components, showed no significant biases and followed Gaussian-like distributions confirmed by Shapiro-Wilk tests. As expected, the regional model produced lower overall variability than the global one, and the between-event trends support the internal consistency of the compilation. One instructive exception emerged: within the magnitude range of roughly 4.2 to 4.7, the regional model showed a negative trend in between-event residuals, suggesting that magnitude calibration at these moderate levels could benefit from future refinement.

The statistical footprint of the dataset reveals both its strengths and its character. About 85 percent of records lie beyond 100 kilometres from the epicentre, while only 5.3 percent come from within 50 kilometres, meaning near-source shaking remains comparatively sparse. Roughly 65 percent of the records originate from events shallower than 20 kilometres, confirming the dataset’s focus on shallow crustal seismogenic sources, with the remainder spanning depths down to about 55 kilometres. Strong events are well represented: 716 records, or 9.5 percent of the total, come from earthquakes above magnitude 5.5, including the magnitude 7.2 Pizarro earthquake of 2004 on the Pacific coast and the magnitude 6.1 San Juanito earthquake of 2023 in eastern Colombia. Epicentres of 488 events fall on continental territory and 179 offshore, and the authors deliberately leave tectonic classification, whether subduction interface, intraslab, or crustal, to users, since appropriate assignments depend on the slab models each analyst chooses.

The practical payoff could be substantial. Ground-motion datasets of this kind are the raw material for probabilistic seismic hazard assessment, the framework that underlies building codes, and for the emerging generation of partially non-ergodic ground-motion models, which replace globally averaged predictions with region-specific ones by exploiting dense, well-characterised observations. Colombian engineers designing buildings, and officials updating national hazard maps, will gain a resource calibrated to the actual faults and soils beneath their feet rather than to California or Japan. The Fourier spectra additionally open a window onto source physics, allowing researchers to constrain corner frequencies, seismic moments, and stress drops for Colombian earthquakes directly. Released openly under a Creative Commons Attribution 4.0 licence on Zenodo, with the underlying time series available through the Colombian Geological Survey’s acceleration catalogue and the FDSN network CM, the dataset invites reuse far beyond Colombia’s borders, offering a template for other seismically active but data-poor regions of the world where the next damaging earthquake is only a matter of time.

Subject of Research: A uniformly processed open dataset of ground-motion recordings from shallow earthquakes in Colombia for seismic hazard analysis

Article Title: Ground-motion dataset for shallow earthquakes in Colombia

Article References: Martinez-Jaramillo, D., Kotha, S.-R., Zúñiga, F. R., & Lacan, P. (2026). Ground-motion dataset for shallow earthquakes in Colombia. Earth System Science Data, 18(10), 7403-7415. https://doi.org/10.5194/essd-18-7403-2026

Image Credits: AI Generated

DOI: 10.5194/essd-18-7403-2026

Keywords: Colombia, ground-motion dataset, seismic hazard, earthquake engineering, strong-motion records, moment magnitude, spectral acceleration, Fourier amplitude spectrum, subduction, Vs30, flatfile, open data

Why does shear wave velocity matter so much? When an earthquake strikes, the ground does not shake uniformly everywhere. The speed at which shear waves, the transverse waves that produce most of the destructive shaking in buildings, propagate through the upper layers of soil fundamentally controls how strongly the ground amplifies seismic motion. Soft, loose sediments can slow these waves dramatically and trap their energy, turning a moderate distant earthquake into a locally violent shaking event. Hard, dense soils and rock, by contrast, transmit the waves quickly and tend to amplify them less. This is why modern seismic design codes around the world, from ASCE 7-16 in the United States to Eurocode 8 in Europe, classify building sites primarily by the average shear wave velocity in the top thirty meters, a parameter known as VS30. Getting this number right is one of the first and most consequential steps in designing an earthquake-resistant structure.

The gold-standard way to measure shear wave velocity is geophysical: techniques such as the Multichannel Analysis of Surface Waves, or MASW, record seismic waves at the ground surface and invert their dispersion to recover a velocity profile with depth. In the one-dimensional MASW variant used in this study, a seismic source generates Rayleigh surface waves, an array of geophones records them, and the analysis exploits the fact that different frequency components sample different depths. The method is non-invasive, relatively fast and reliable, and its good practice has been codified in international guidelines such as the InterPACIFIC project recommendations. But in many urban investigations, particularly in developing regions, budgets and schedules do not always allow dedicated geophysical surveys at every site of interest. Boreholes with penetration testing, however, are drilled routinely for ordinary building projects.

That is where the Standard Penetration Test enters the story. The SPT, standardized as ASTM D1586, is one of the most widely performed in-situ geotechnical tests in the world. A split-barrel sampler is driven into the soil at the bottom of a borehole by a standardized hammer, and engineers count the number of blows required to advance the sampler a specified distance, yielding the N value. This humble number encodes a great deal about soil density and consistency: loose sands and soft clays yield low blow counts, while dense gravels and stiff clays demand many more. Because SPT data already exist in thousands of archived borehole logs, an empirical correlation linking N values to shear wave velocity would allow engineers to retrofit velocity estimates onto decades of existing geotechnical records, effectively converting old borehole data into modern seismic site classifications without drilling a single new hole.

Correlations of this kind have been published for many cities and soil types worldwide, from Lucknow and Kolkata in India to Korean alluvial deposits and Norwegian clays, but the literature carries a consistent warning: these relationships are strongly region-specific. Soil genesis, mineralogy, stress history and cementation all influence both penetration resistance and shear stiffness, and a formula calibrated in one basin can be badly biased when exported to another. For Cochabamba, a city of more than a million people sitting in a seismically active intermontane valley of the Bolivian Andes, no locally calibrated relationship existed for its fine-grained soils. The Bolivian seismic design norm and the national geotechnical study standard both demand site characterization, yet practitioners lacked a validated tool tailored to local ground conditions. The new study set out to close that gap.

The researchers assembled their dataset by pairing two independent measurement streams at coincident locations across three representative zones of the city. On the geophysical side, they performed one-dimensional MASW surveys to extract shear wave velocity profiles. On the geotechnical side, they collected SPT records from boreholes in the same areas. The overlap produced 164 data points, each tying a measured velocity to a penetration resistance at a comparable depth. With this dataset in hand, they fitted power-law models of the form VS equals a coefficient multiplied by N raised to an exponent, the classic functional form used in essentially all such correlations, reflecting the nonlinear stiffening of soil as density increases. Crucially, they evaluated the models twice: once using the raw field blow count and once using the energy-corrected value N60, which normalizes the measured blow count to a standard hammer energy of sixty percent of the theoretical maximum, following the correction framework established in the liquefaction literature since the 1980s.

The verdict on energy correction was clear. The model built on N60 outperformed the one based on uncorrected field values, and the team’s recommended relationship is VS equals 129.59 times N60 raised to the power of 0.2836, with velocities in meters per second. The statistical indicators are respectable for an empirical soil correlation: a coefficient of determination of 0.6713, a correlation coefficient of 0.8209 and a root-mean-square error of 30.81 meters per second. In practical terms, the equation predicts that a soft soil with a corrected blow count of 5 would have a shear wave velocity of roughly 210 meters per second, while a stiff soil with N60 of 30 would reach around 320 meters per second, differences large enough to shift a site from one seismic soil class to another. The exponent of about 0.28 sits within the range reported in international studies, suggesting the Cochabamba soils behave in a broadly familiar way, while the local coefficient captures the specific character of the valley’s fine-grained deposits.

The implications for Cochabamba itself are significant. The city’s valley, whose geology and hydrogeology have been documented in German-Bolivian cooperative studies, is filled with alluvial and lacustrine fine-grained sediments that can amplify earthquake shaking, and the region has a documented seismic hazard that motivates the national design code. With the new correlation, engineers reviewing borehole logs for a school, hospital or apartment block can now estimate the shear wave velocity profile and hence the site class directly from the SPT data that every geotechnical campaign already produces. That means faster, cheaper preliminary seismic screening across the urban fabric, and a way to populate site-class maps from the enormous archive of existing penetration test records. The authors position the model as a reliable estimation tool that contributes to the local seismic characterization of the Cochabamba valley, complementing rather than replacing direct geophysical measurement where critical structures demand it.

The study also carries a broader lesson for earthquake engineering in data-scarce regions. The workflow demonstrated here, fusing routine geotechnical borehole data with targeted geophysical surveys and validating the result with transparent statistics, is replicable in cities across the Andes and beyond that face similar combinations of seismic exposure, soft soils and limited measurement budgets. Comparable efforts in Peru, Ecuador and India have shown how local correlations sharpen regional hazard assessments, and the Cochabamba equation now joins that growing library. The authors, who conducted the fieldwork and analysis at Universidad Mayor de San Simón with support from the university’s geotechnical laboratory, note that the underlying data will be made available on request, an important step for independent verification and future meta-analyses.

For a city where a single well-placed hospital or bridge must stand for decades, the difference between assuming a generic imported correlation and using one calibrated on 164 local measurements could translate into real margin of safety. The equation itself is compact enough to fit on a single line of a design report, but behind it lies an unglamorous and essential truth of earthquake engineering: the ground beneath a building is as much a part of the structure as its columns and beams, and the more precisely that ground is characterized, the better the odds when the next earthquake arrives. Cochabamba’s engineers now have one more tool, rooted in their own valley’s soils, to tip those odds in their favor.

Subject of Research: Empirical correlation between shear wave velocity and SPT blow counts for seismic site characterization of fine-grained soils in Cochabamba, Bolivia

Article Title: Empirical correlation between shear wave velocity (VS) and SPT results using 1D MASW in fine-grained soils of Cochabamba, Bolivia

Article References: Copa, P. A. D. C., Padilla, A. F. C., & Rocha, J. H. A. (2026). Empirical correlation between shear wave velocity (VS) and SPT results using 1D MASW in fine-grained soils of Cochabamba, Bolivia. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02663-x

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02663-x

Keywords: shear wave velocity, Standard Penetration Test, MASW, seismic site characterization, Cochabamba, Bolivia, fine-grained soils, geotechnical engineering, earthquake engineering, N60 correction, power-law correlation, VS30

The research, led by Guan Chen of the Earth Observatory of Singapore and the National University of Singapore, together with Siau Chen Chian, Michael Beer, and Shengji Wei, addresses a persistent gap in seismic hazard analysis. Engineers can already estimate how strong ground shaking will be at a given distance from an earthquake of a certain size using ground-motion prediction equations. What has been harder to quantify is the impulsive character of near-fault motion — how long the dominant pulse lasts, how large its velocity amplitude is, and how these quantities vary with the seismological setting. The new work links pulse parameters directly to magnitude, distance, and site stiffness, giving hazard analysts a physically grounded way to generate realistic near-fault ground motions for any scenario of interest.

The first technical challenge the team tackled was identification. Not every record close to a fault contains a clear pulse, and distinguishing pulse-like from non-pulse-like ground motions has traditionally relied on wavelet-based classification methods, most famously the approach introduced by Jack Baker in 2007. Many existing identification procedures, however, tend to extract a single type of pulse from a record, which can miss the richer structure of real near-fault motions. Records from large continental earthquakes frequently contain multiple pulses, arising from forward-directivity effects as the rupture front races toward the site, from fling-step associated with permanent tectonic deformation, or from constructive interference of seismic waves with basin geometry. A method that captures only one pulse type risks underrepresenting the destructive potential of the motion.

To overcome this limitation, the researchers developed a novel extraction procedure that integrates a parametric pulse model with the generalized continuous wavelet transform, or GCWT. The parametric model provides a mathematical description of the pulse shape, while the wavelet transform scans the velocity time series across scales and times to locate the energy concentration that corresponds to the pulse. By combining the two, the procedure can capture various types of pulses within a single record, preserving both the diversity and the accuracy of the extracted signals. The authors report that the pulses extracted by their method effectively match the pulse characteristics visible in the original records, a critical validation step before any statistical modeling can proceed.

Armed with this identification tool, the team mined the PEER NGA-West2 database, one of the largest curated collections of strong-motion recordings from shallow crustal earthquakes worldwide. Out of 21,222 records examined, 815 were identified as pulse-like ground motions. This carefully classified dataset forms the empirical backbone of the study. Each pulse-like record was decomposed into its pulse component and a residual component, and the parameters describing the pulse — including its period, amplitude, and the number of significant cycles — were tabulated alongside the corresponding earthquake magnitude, source-to-site distance, and Vs30 for each station.

The second major contribution is a set of empirical regression models that predict the pulse parameters from these three explanatory variables. The functional form of the models was developed with attention to the underlying physics: larger earthquakes produce longer rupture durations and hence longer pulse periods, pulses attenuate with distance as seismic energy spreads and is absorbed, and soft soil sites can amplify and lengthen the dominant velocity cycles relative to stiff rock. Model uncertainty was quantified through residual analysis, following the random-effects regression framework that has become standard in ground-motion modeling since the work of Abrahamson and Youngs in 1992. The proposed models were then validated against existing pulse models and against independent datasets not used in the calibration, providing confidence that the predictions generalize beyond the fitting sample.

A particularly valuable practical outcome of the study is a workflow for synthesizing near-fault broadband ground motions. The approach combines the empirical pulse model with a stochastic representation of the residual component — the high-frequency, incoherent part of the motion that remains after the coherent pulse is removed. Because the pulse and the residual are treated separately, the resulting artificial ground motions retain the distinctive impulsive features that govern structural response while simultaneously matching the spectral velocity and spectral acceleration of benchmark recordings across a broad frequency range. This two-component strategy echoes the spectral representation method in stochastic process simulation and offers a computationally efficient alternative to full physics-based rupture simulations, which remain expensive for routine hazard applications.

The implications for earthquake engineering are substantial. Previous research has demonstrated that near-fault pulses impose large deformation demands on flexible structures: moment-resisting frames subjected to pulse-like records accumulate damage differently than those subjected to ordinary shaking, and offshore wind turbines, tunnels, and seismically isolated buildings all show heightened vulnerability when the impulsive content of the motion is ignored. By providing pulse parameters conditioned on magnitude, distance, and site class, the new model allows analysts to construct scenario-consistent suites of near-fault motions without waiting for the next large earthquake to supply fresh recordings. The authors also note that the framework was informed by recent events, including the 2023 moment magnitude 7.8 Kahramanmaras earthquake in Turkey, whose near-fault recordings have become an important test case for pulse identification and simulation methods.

Accessibility is another notable feature of the work. The processed dataset, together with MATLAB code for identifying the optimal pulse in near-fault ground motions and for generating the empirical pulse model, has been released publicly through Zenodo, while the raw waveforms remain freely downloadable from the PEER NGA-West2 database. This open approach lowers the barrier for practicing engineers and researchers in seismically active regions to incorporate directivity and fling effects into their hazard and risk calculations. The study also acknowledges insightful discussions with Professor Jack W. Baker of Stanford University regarding pulse types and the functional form of the model, and it was supported by the Ministry of Education, Singapore, under the InVEST program for integrating volcano and earthquake science and technology.

For cities that sit directly above or beside active faults — from Los Angeles and Wellington to Istanbul and Kathmandu — the difference between ordinary shaking and a coherent velocity pulse can be the difference between repairable damage and collapse. By transforming decades of strong-motion recordings into a compact, predictive, and openly available model, this research moves the field closer to hazard assessments that reflect not just how hard the ground will shake, but how it will shake. As computational tools for seismic risk analysis grow more sophisticated, models of this kind provide the physically consistent input that engineers need to design structures capable of withstanding the sharpest blows an earthquake can deliver.

Subject of Research: Empirical modeling of near-fault velocity pulses in earthquake ground motion

Article Title: Empirical pulse model for near-fault ground motion considering magnitude, distance, and site characteristics

Article References: Chen, G., Chian, S. C., Beer, M., & Wei, S. (2026). Empirical pulse model for near-fault ground motion considering magnitude, distance, and site characteristics. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02650-2

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02650-2

Keywords: near-fault ground motion, velocity pulse, pulse-like records, NGA-West2, wavelet transform, seismic hazard, ground motion simulation, rupture directivity, fling-step, Vs30, earthquake engineering, Bulletin of Earthquake Engineering

The research, carried out by Nasser Laouami of the National Applied Research Centre in Earthquake Engineering in Algeria, tackles one of the most persistent gaps in seismic hazard assessment. Many strong-motion stations worldwide were installed decades ago, often on the roofs or basements of buildings, with little or no accompanying subsurface investigation. Drilling new boreholes at each site is costly and time-consuming, so the average shear-wave velocity of the top 30 metres, known as Vs30, remains unknown or poorly constrained for a large fraction of the global seismic network. Yet Vs30 is the single parameter that most building codes, including the American NEHRP provisions and Eurocode 8, use to assign a site class and therefore to determine the design forces a structure must withstand. Without reliable Vs30 values, the ground-motion predictions that feed into hazard maps carry an extra layer of uncertainty.

Laouami’s approach exploits a phenomenon that seismologists have long used as a diagnostic tool: the horizontal-to-vertical spectral ratio, or H/V. When earthquake waves arrive at a station, the horizontal components of motion are typically amplified relative to the vertical component at frequencies where the shallow soil column resonates. That resonance frequency depends on the thickness and stiffness of the sedimentary layers, while the shape and amplitude of the H/V curve encode information about the impedance contrasts between layers. In principle, the entire H/V spectrum is a fingerprint of the subsurface velocity structure. The challenge has always been to invert that fingerprint, meaning to find a layered velocity model whose predicted H/V curve matches the observed one, without falling into the trap of non-uniqueness, where many different models fit the data equally well.

What makes the new method notable is that it requires no prior information about the subsurface. Most inversion schemes in geophysics lean heavily on initial guesses: an approximate depth to bedrock, a rough velocity for the top layer, or a fixed number of layers. When such constraints are wrong, the inversion can converge to a misleading solution. The new technique instead assumes that the strong-motion wavefield at the station is dominated by vertically incident body waves, a reasonable approximation for stations recording earthquakes at regional distances, and then searches for the velocity profile that best reproduces the observed H/V spectrum. The inversion is statistical in character, exploring a wide space of possible layered models and identifying the family of solutions consistent with the data rather than committing to a single profile that may be an artefact of the starting conditions.

To test the method rigorously, Laouami turned to one of the best-characterized seismic datasets on Earth: Japan’s KIK-NET network, operated by the National Research Institute for Earth Science and Disaster Resilience. KIK-NET stations are paired with boreholes that reach stiff engineering bedrock, and the shear-wave velocity profile at each site has been measured directly. That makes the network an ideal proving ground, because the true answer is known. The study used strong-motion records and measured velocity profiles from 66 KIK-NET stations, spanning a wide range of soil conditions from soft alluvial basins to relatively stiff sites. The inverted profiles were compared layer by layer against the borehole measurements, and the key classification parameter, Vs30, was compared station by station.

The results were evaluated in two configurations. In the first, the inversion ran completely unconstrained, with no prior information whatsoever about the subsurface. In the second, a small piece of shallow information was supplied: the average shear-wave velocity of the top five metres, or Vs5, which can be obtained cheaply from non-invasive surface measurements. The comparison revealed a clear and useful pattern. Without any prior information, the method produced reliable velocity profiles for sites whose Vs30 values reach approximately 600 metres per second, which covers the softer end of the soil spectrum, including many of the most seismically hazardous sedimentary settings. For stiffer profiles beyond that threshold, the unconstrained inversion began to lose accuracy, but adding the modest Vs5 constraint restored performance, extending reliable estimates to stiffer sites as well.

The quantitative agreement is impressive for a technique that requires no drilling. For most of the 66 stations, the relative error between the observed and predicted Vs30 was less than 20 percent, and the error in the predominant frequency of the H/V curve, the frequency at which the site resonates most strongly, was around 15 percent. In geotechnical and geophysical practice, both levels of accuracy are generally considered acceptable for preliminary site characterization. Perhaps more importantly, the method captured the overall shape of the velocity profiles, including the depth of major impedance contrasts, rather than merely matching a single averaged number. That matters because site response is not determined by Vs30 alone; the full layering controls how ground motion is amplified across the frequency range that affects buildings of different heights.

The implications extend well beyond Japan. Dense seismic networks exist in many earthquake-prone countries, but borehole measurements are far rarer, particularly in developing regions where instrumentation has expanded faster than site characterization budgets. A technique that extracts velocity profiles from recordings that stations are already producing, at no additional field cost, could rapidly fill the characterization gap. It could also serve as a first-pass screening tool: stations flagged by the H/V inversion as sitting on unusually soft or strongly resonant soils could be prioritized for follow-up borehole investigation. In regions governed by seismic codes that rely on Vs30-based site classes, such as the Algerian RPA2024 regulations or the NEHRP provisions, even a preliminary estimate with 20 percent accuracy can meaningfully improve hazard maps and design decisions.

The method also fits into a broader scientific conversation about what the H/V spectral ratio actually measures. Earlier theoretical work, including diffuse-field formulations of the H/V ratio developed by researchers such as Kawase, Sánchez-Sesma and Matsushima, showed that the ratio can be interpreted through the properties of the wavefield and the layered medium beneath the receiver. Laouami’s contribution is to demonstrate, against ground truth, that a body-wave assumption applied to strong-motion records is sufficient to recover the velocity structure without prior constraints, at least for a substantial range of site stiffness. The technique complements rather than replaces established non-invasive methods such as surface-wave analysis, which suffers from its own well-documented non-uniqueness problems, and it inherits the practical advantage of requiring only a single three-component station rather than an array of sensors.

Limitations remain, and the author is careful about them. The assumption of vertically incident body waves may weaken at sites with complex three-dimensional structure or strong lateral heterogeneity, and the accuracy degrades for very stiff sites unless shallow information is supplied. The validation set, while diverse, comes from a single national network with high-quality borehole data, so performance in other tectonic and sedimentary environments will need independent confirmation. Nevertheless, the core result stands: for a wide range of soil profiles, the ground beneath a seismic station can be mapped from its own earthquake recordings, with errors small enough to support site classification. In a field where every unknown parameter translates directly into uncertainty in shaking estimates and building safety margins, a reliable, non-invasive, zero-drilling method for recovering shear-wave velocity profiles is a genuinely valuable addition to the earthquake engineering toolkit, and one that could be applied to thousands of existing stations worldwide almost immediately.

Subject of Research: Non-invasive estimation of S-wave velocity profiles from single-station H/V spectral ratio inversion of strong-motion records

Article Title: Estimating S-wave velocity profiles from single-station horizontal-to-vertical spectral ratio inversion without prior information: application for KIK-NET accelerometric stations

Article References: Laouami, N. (2026). Estimating S-wave velocity profiles from single-station horizontal-to-vertical spectral ratio inversion without prior information: application for KIK-NET accelerometric stations. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02660-0

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02660-0

Keywords: shear-wave velocity, H/V spectral ratio, inversion, Vs30, site characterization, KIK-NET, strong-motion records, seismic station classification, earthquake engineering, geophysics, non-invasive methods, soil amplification