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

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