Old Felt Reports, New Faults: A Workflow That Turns Historical Shaking Data Into Earthquake Sources

Every earthquake leaves behind two kinds of memory. The first is recorded by instruments: seismometers and accelerometers that capture the ground’s every twitch with digital precision. The second is far messier — the recollections of people who felt the shaking, saw their chimneys collapse, or watched cracks snake across the walls of a village church. For earthquakes that struck centuries before the first seismograph was ever switched on, this second kind of memory, encoded as macroseismic intensity data, is often all that remains. Now, a team of Italian researchers has built a rigorous, repeatable workflow that transforms those scattered historical observations into concrete, three-dimensional models of the faults that produced them.

The study, published in Natural Hazards and Earth System Sciences by Veronica Gironelli and colleagues at the Istituto Nazionale di Geofisica e Vulcanologia (INGV) in Milan, addresses a stubborn gap in seismic hazard assessment. Italy possesses one of the richest macroseismic archives in the world, with intensity data points — IDPs — stretching back nearly a millennium. Yet the association between large historical earthquakes and the specific geological structures that generated them has traditionally rested on qualitative interpretation. The new approach replaces that subjectivity with a standardised pipeline that can, in principle, be applied systematically to every strong Italian earthquake since 1117.

The workflow begins with a deceptively simple but crucial step: cleaning the data. Macroseismic intensity is an ordinal measure, graded on scales such as the Mercalli–Cancani–Sieberg (MCS) or the European Macroseismic Scale 1998 (EMS-98), each with twelve degrees of increasing shaking severity. Because intensities are assigned from documentary descriptions of effects on people, buildings and the environment, individual data points can be anomalously high or low relative to the expected pattern of attenuation with distance. Such outliers can poison downstream analyses. The team therefore compares each observed intensity with the value predicted by a regionally calibrated intensity prediction equation (IPE), and flags as outliers any observation deviating by more than three standard deviations — roughly 2.25 intensity units — from the model prediction. This conservative threshold respects the inherent uncertainty of about one intensity degree in the data while removing only the most egregious discrepancies.

The importance of this pre-processing is vividly illustrated by the 5 May 1990 Potenza earthquake in the Southern Apennines. The macroseismic epicentre computed from the raw intensity field sat tens of kilometres from any instrumental location, a mismatch serious enough that the solution was excluded from Italy’s parametric earthquake catalogue. The residual analysis revealed 116 outliers, including suspiciously high intensities clustered around Naples — far from the true source — that turned out to reflect cumulative damage from the catastrophic 1980 Irpinia earthquake a decade earlier. Once these contaminated points were removed, the recalculated macroseismic epicentre moved to within 16.7 kilometres of the instrumental location, down from a 37.3-kilometre misfit. A similar exercise on the well-documented 2016 Amatrice earthquake showed that removing a single inflated intensity value at Pescara del Tronto, where damage had been amplified by unstable landslide deposits, brought the macroseismic magnitude down from 6.46 to 6.26 — a difference with major consequences, since the larger value would imply a rupture area of roughly 270 square kilometres, far exceeding the approximately 180 square kilometres constrained by satellite radar and geological data.

With a cleaned macroseismic field in hand, the workflow moves into its constructive phase. Earthquake parameters — epicentral location and magnitude — are recomputed using the Boxer code, the same tool underpinning the Italian Parametric Earthquake Catalogue CPTI15. Boxer locates the epicentre as the barycentre of the sites recording the highest intensities and estimates magnitude from the areas enclosed by isoseismal contours. Fault dimensions are then derived from magnitude using the widely adopted empirical scaling relationships of Wells and Coppersmith, and a rectangular three-dimensional fault plane is constructed around the hypocentre, with its orientation, dip and slip direction drawn from authoritative repositories including the Italian Seismic Bulletin, the CLASS catalogue of absolute locations, and the Database of Individual Seismogenic Sources (DISS).

The critical innovation lies in how candidate sources are tested. For each proposed fault geometry, the team simulates ground shaking using the ITA18 ground motion model, calibrated for shallow crustal earthquakes in Italy, computing predicted peak ground acceleration and velocity across the affected region. These ground motion parameters are converted into expected intensities using two independent ground-motion-to-intensity conversion equations, allowing the simulated shaking scenario to be compared directly, point by point, with the observed macroseismic field. The best-fitting source is the one that minimises two statistical metrics: the between-event residual, which captures systematic bias, and the root-mean-square error, which captures scatter. Thresholds of half an intensity degree for the former and one intensity degree for the latter define when a source can be considered reliable.

The method was validated on three instrumentally recorded earthquakes of different character: the 1984 Monti della Meta event (moment magnitude 5.86), the 1989 Prealpi Vicentine earthquake (magnitude 4.85), and the 2008 Parmense earthquake (magnitude 5.36). For Monti della Meta, nine alternative fault configurations were tested, and the winning model — built on the CLASS hypocentral location and the global centroid moment tensor magnitude — not only minimised the intensity residuals but also aligned its surface projection with the Barrea–Castelnuovo fault system mapped in the ITHACA database of capable faults. Crucially, where accelerometric recordings existed, the residuals between predicted and recorded ground motions matched the intrinsic standard deviation of the ground motion model itself, providing an independent stamp of validation.

The true test, however, comes from the deep past. The team applied the workflow to the 3 June 1781 Cagli earthquake, one of the most damaging events to strike the interior of the Marche region, and one with no clear seismotectonic interpretation. Two alternative, equally credible macroseismic fields exist for this event, and no capable faults are mapped at the surface near the epicentral area. Four source hypotheses were simulated: two consistent with the Montiego thrust proposed in the DISS database, and two aligned with a system of shallow normal faults in the Monte Nerone area documented by field geologists. The residual analysis favoured the sources built from the alternative intensity dataset, and suggested that a slightly lower magnitude — 6.33 rather than 6.51 — fits the observations better. In effect, the workflow allowed the researchers to adjudicate between competing historical datasets and competing tectonic hypotheses using quantitative evidence rather than expert judgement alone.

The implications extend well beyond Italian borders. Seismic hazard models in many regions of the world depend on catalogues of historical earthquakes whose magnitudes and locations are derived from exactly the kind of documentary evidence used here — and whose assigned faults are frequently matters of conjecture. By providing standardised acceptance thresholds, a transparent chain of processing, and validation against multiple independent benchmarks including instrumental recordings and mapped geological structures, the workflow offers a template that other countries with long documentary records could adapt. The authors note that the approach can be systematically applied to reconstruct the seismogenic sources of all Italian historical earthquakes of moment magnitude 5.5 and above for which consistent intensity distributions are available.

There is also a forward-looking payoff. Once a historical earthquake’s source is credibly identified, realistic shaking scenarios can be generated for the event — showing modern planners precisely which towns and infrastructure would be shaken if the same fault ruptured again. In a country where centuries-old faults still lie beneath densely populated cities, turning the written testimony of past survivors into a map of future risk may prove one of the most consequential applications of historical seismology in decades.

Subject of Research: A methodological workflow for identifying earthquake seismogenic sources from macroseismic intensity data

Article Title: A methodological workflow for the identification of earthquake sources from macroseismic data

Article References: A methodological workflow for the identification of earthquake sources from macroseismic data. (n.d.). https://doi.org/10.5194/nhess-26-4569-2026

Image Credits: AI Generated

DOI: 10.5194/nhess-26-4569-2026

Keywords: macroseismic data, seismogenic sources, earthquake intensity, historical seismology, seismic hazard assessment, intensity prediction equation, ground motion simulation, Boxer method, Italian earthquakes, fault geometry, outlier detection, shaking scenarios