Carla Barnaba

The reliable estimation of site amplification is crucial for seismic hazard and risk assessment. Although the amplification estimates are traditionally site-specific, recent efforts have focused on developing site amplification models for large areas. To this aim, we compiled existing site amplification factor estimates in Italy derived from different empirical methods. We then employed goodness-of-fit metrics and statistical tests to assess their mutual consistency and their agreement with predictions from an available 1D simulation-based model. We found a high correlation between the period-dependent site amplification factor estimates, suggesting that empirical methods consistently measure the relative amplification levels of different sites. Systematic differences among empirical estimates, observed particularly in Central Italy, are primarily due to the choice of the reference ground motion and can be corrected for by applying a simple scaling factor to a common reference ground motion level, thereby confirming the robustness of empirical estimates. Conversely, the comparison between empirical data and 1D simulations revealed a poor correlation, with the latter failing to reproduce the full range of observed amplification. For rock and stiff sites, 1D simulations tend to overestimate empirical amplification. In contrast, for a smaller fraction of soft-soil sites (e.g. within large basins), 1D simulations underestimate empirical amplification, likely due to their inability to model complex 2D/3D effects. These results suggest that the development of regional or national site-amplification models should prioritize empirical site amplification estimates.

Reliable quantification of seismic site amplification is essential for seismic hazard assessment and engineering applications. At regional and national scales, 1D equivalent‐linear models are widely adopted due to their computational efficiency and limited data requirements; however, their capability to reproduce the real site response in geologically complex settings remains uncertain. In this study, we evaluate the reliability of three types of 1D numerical models—full‐stochastic, semi‐stochastic, and deterministic—in reproducing empirical site amplification functions at 21 seismic stations located in the western sector of the Val d’Agri basin (southern Apennines, Italy). The study area encompasses a broad range of geological conditions, from carbonate rock outcrops to shallow alluvial covers and deep intermontane basins exceeding 200 m in sediment thickness.,Empirical amplification functions were obtained using a non‐parametric Generalized Inversion Technique (GIT) applied to ~2,000 earthquake recordings, and frequency‐averaged amplification factors (FA) were computed in three period bands of engineering interest (0.1–0.5 s, 0.4–0.8 s, and 0.7–1.1 s). The numerical models were developed using the NC92Soil/STRATA engine and incorporate different levels of epistemic uncertainty related to shear‐wave velocity profiles, layer thicknesses, and bedrock depth.,Results show that 1D numerical models reproduce average amplification levels reasonably well at sites characterized by shallow and simple stratigraphic conditions. In contrast, in sites underlain by thick sedimentary successions, empirical AF values derived from GIT exhibit significantly larger variability and amplitudes (up to ~5) than those predicted by numerical models, which tend to cluster within a narrower range. Deterministic and stochastic simulations generally underestimate both the amplitude and the spatial variability of site response in deep basin settings, likely due to the contribution of 2D/3D effects, lateral heterogeneities, and complex basin geometry not captured by 1D assumptions.,Furthermore, the analysis highlights that frequency‐averaged amplification factors alone may represent an oversimplified descriptor of site response, as similar AF values can correspond to markedly different spectral shapes.,Overall, our study demonstrates that simplified 1D models have limited capability to reproduce real site response in geologically complex basins, and that their use for large‐scale amplification mapping should be accompanied by robust uncertainty quantification. The findings provide quantitative thresholds for the applicability of 1D approaches and highlight the importance of integrating empirical observations when assessing seismic site effects in morphologically and stratigraphically complex environments.

This research expands the experience and results acquired within the citizen science pilot project CEDAS (Censimento dell’Edificato per la stima del Danno Sismico), which involved more than 300 students from high schools in Udine (Italy) and allowed collecting more than 8000 building questionnaires (Peresan et al., 2023, http://dx.doi.org/10.3389/esss.2023.10088; Scaini et al., 2021, https://doi.org/10.1016/j.ijdrr.2021.102755) in different municipalities of the Friuli Venezia Giulia Region, including Udine and surrounding areas.The activity was implemented within five months, from January to May 2025, in the framework of the RETURN "multi-risk science for resilient communities under a changing climate" and the PRIN-SMILE (Statistical MachIne Learning for Exposure development) projects. It involved 60 students from the “Copernico” High School in Udine, Italy, and included general lectures on seismic hazard, exposure and risk, as well as interactive quizzes, all specifically designed to enhance seismic risk awareness.Besides technical training on buildings data collection, a lecture on statistical data exploration analysis was conducted. This allowed students were able to carried out multivariate and comparative analyses between the newly collected and existing datasets, including results interpretation. Finally, the results obtained by different groups of students were presented to an audience composed by representatives of local institutions, regional Civil Protection personnel, engineers, Researchers, and students from past editions.With respect to earlier editions, this study emphasized the social dimension of this citizen science activity, enriching the contents of the proposed experience, and quantitatively investigating the improvement perceived by participants with respect to the topics covered by the modules (lectures, data collection and analysis). To this end, a specific questionnaire was created, consisting of 38 items, with the aim of quantifying similar activities in a repeated cross-sectional perspective.The questionnaire outcomes were analysed using statistical software (e.g. RStudio and JASP). Internal consistency of the adapted scales was assessed using Cronbach’s alpha, while the perceived improvement reported by respondents was analysed using Paired t-test, Pearson’s Chi-squared test and ANOVA. The Pearson’s Chi-Square Test results (p=0.013, χ²=25.50, Df = 12) highlighted a statistically significant difference in the perceived improvement across the three assessed dimensions (Seismic Hazard, Built Environment and Territorial Context). In particular, participants reported the highest perceived improvement in the dimension of seismic hazard understanding. The Paired T-test revealed a statistically significant average improvement in perceived Data Exploration Skills (p-value=4.999^e-15; mean difference=1.10 points).We recall that risk depend on three elements: hazard, exposure and vulnerability. Awareness is a factor modulating individuals’ vulnerability to natural hazards, that therefore should be considered as a dynamic, rather than a static, element in risk assessment. The improvement in individual awareness, achieved in similar educational activities, may have positive feedback in modulating risks, especially in situations where hazards and context significantly vary over space and/or time.

For years, soil-structure interaction (SSI) has been a subject of interdisciplinary studies, although full-scale SSI experiments and the use of real data are rare. To study SSI in a well-known and controlled environment, a full-scale experiment, EuroMASS, was conducted at the Piana di Toppo test site in Northeast Italy. For the needs of the experiment, a simple structure consisting of a lumped mass overtopping a steel column on a concrete base was designed and assembled at the test site. In April 2022, a three-component instrumentation network was installed to record the seismic noise, weak earthquake motions, and active source signals to study the structure, the foundation, and the soil seismic responses. The experiment was designed to collect data that can be used for accurate dynamic characterization of the structure and analysis of wave propagation in the soil-structure system.

Citizen science has proven very useful to increase awareness and preparedness of societies prone to disaster risk. The active involvement of citizens is also strongly envisaged by strategic documents related to disaster risk reduction (e.g. SENDAI Framework, United Nations Global Assessment Report). Here, we describe the CEDAS (building CEnsus for seismic Damage ASsessment) project, which involved high-school students in citizen science activities related to seismic risk reduction. In particular, students collected data on building characteristics (e.g. height, material) near to their homes using their phone or personal computer. Prior to data collection students were trained on risk-related concepts (hazard, exposure and vulnerability) with specific focus on buildings exposure the area where the activity was carried out (northeastern Italy). CEDAS was implemented in 2021 and 2022 involving approximately 320 students who collected more than 6000 building forms. The CEDAS project is not only data collection: students also analyzed the data and compared the exposure parameters in different areas. Finally, the interpreted the results with the help of teachers and researchers. CEDAS has demonstrated its potential for collecting exposure data in seismic-prone areas and/or include characteristics useful for multi-hazard and multi-risk assessment. However, its generalization requires the adaptation of the training material to the specific context. This presentation will support the discussion on CEDAS based on active involvement of participants. Attendants will have the opportunity to test the CEDAS approach for selected buildings. Pictures of the building front and aerial view, together with a street view, will be displayed on the screen. The active involvement of participants will support the discussion both on technical (e.g. parameters to be prioritized during the collection) and communication (e.g. citizens engagement and training) aspects. The discussion will also cover future developments of CEDAS, in particular in relation to risk awareness and preparedness (e.g. definition of impact assessment metrics).

The National Institute of Oceanography and Applied Geophysics – OGS is engaged in a wide range of educational and training activities for more than a decade, mainly focused on seismic risk mitigation through data acquisition in the field and practical stages. To by-pass the restrictions imposed by the COVID-19 pandemic, in 2021 OGS started a new project, deployed in fully remote mode, to involve high-school students and increase their risk awareness and preparedness. The Project, named “CEDAS: building CEnsus for seismic Damage Assessment”, consists in the collection and elaboration of data which is included in the exposure database. Knowing the type and distribution of exposed assets, in particular buildings, is thus paramount for effective mitigation of disasters. The students classified and georeferenced the main residential buildings typologies of northeastern Italy, a seismically active area which suffered consequences from strong past earthquakes. During the project, 170 high school students collected reports on more than 3200 buildings, performing a statistical analysis of their results.The project activities consisted of two main phases: plenary virtual training meetings and individual data collection and processing. Tutors held intermediate meetings with students for verification and discussion and brainstorming sessions with their professors to discuss the efficacy of their actions. All the meetings, including those for direct training of students, were delivered in virtual mode. The training material (including the meeting recordings) was then shared remotely with students and teachers through cloud solutions, and remained available during the whole project. In this way the students were able to both collect basic data for exposure assessment, and carry out their preliminary analysis using standard statistical tools available online. The comparative data analysis, performed for selected sub-areas and for the overall dataset, allowed them for some basic interpretation and a better understanding of the exposed assets situation in sub-areas. The CEDAS project, though motivated by the need to provide a practical solution to the COVID-19-related restrictions, went well beyond the emergency situation, as it demonstrated that training activities can contribute to both enhancing the available exposure dataset and to increasing risk awareness among young students in the region. 

A multi-parametric approach, based on five different parameters quantifying seismicity, is proposed for investigating the space-time evolution of earthquakes occurrence in areas characterized by complex tectonics, namely by the interference of differently oriented faults and by the heterogeneous mechanical strength of the rocks. Specifically, the variations of entropy, the b-value from the Gutenberg-Richter law, the changes in fractal dimension, and the Nearest Neighbour distance (η) are used for assessing changes in the temporal patterns of seismicity. In parallel, the Principal Component Analysis (PCA) in 4D (space and time) is used to define the hypocentres distribution geometry and the propagation directions.In particular, we applied the methods mentioned above in a multi-parametric study of the seismicity space-time evolution from 2015 to the beginning of 2020 in a well-focused area. The study area, centred on the town of Tolmezzo, in Northeastern Italy, between the Alps and the Prealps, is characterized by a complex tectonic pattern resulting from the interference of differently oriented fault systems and involving mechanically heterogeneous rocks. After a long period of low seismic activity, lasting about 15 years, in 2018–2019, the area experienced a significant increase of radiated seismic energy, spatially clustered, with four sequences induced by earthquakes with MD (coda-duration magnitude) from 3.7 to 4.0 (http://www.crs.inogs.it/bollettino/RSFVG). Notably, the most energetic events are located in correspondence with the sharp transitions from zones of low damage to zones of intermediate damage. Two distinct periods of the seismic activity are identified, as revealed by the b-value and the fractal dimension, which show relevant fluctuations since the beginning of 2017. The temporal variation of the b-value can be related to crustal stress changes in the medium, which is characterized by different mechanical properties. The fractal dimension time evolution indicates a prevailing clustering of the earthquakes with a tendency to propagate linearly. The temporal variations of the Shannon entropy and η quantify the evolving organization and correlation of seismicity within an area; hence, they reflect a process of damage evolution in heterogeneous rocks that changes with time due to continuous strain energy redistribution. According to this view, the Shannon entropy and η can be considered parameters related to each other that reflect the memory of past deformations. The recovery of Shannon entropy and η to values preceding the crisis of 2018–2019 suggests that the system has reached a temporary new equilibrium.The solutions provided by the PCA analysis along a cross-section close to Tolmezzo confirm such observations. They reveal mostly vertical and sub-vertical planes changing orientation along the cross-section considered. The fracture propagates within the fracturing plane in the southernmost and northernmost parts of the cross-section. In contrast, the results suggest the activation of parallel planes in the central part of the section, closer to Tolmezzo. The orientation of the planes inferred from PCA analysis agrees with secondary NNE-SSW and E-W trends present in the region considered. 

The application of earthquake recordings to the estimation of an event’s magnitude and the construction of rapid‐response ground‐motion maps requires an adequate classification of the recording stations in terms of their site response. For permanent stations, this information can be obtained from a sufficiently large database of past recordings. In this work, we analyze more than 7300 three‐component recordings collected between 1996 and 2017 by 67 permanent stations in northeastern Italy to assess their site amplification. The signals come from 368 earthquakes with a magnitude range of M 3.2–5.8 and a distance range of 10–300 km. We evaluate the frequency‐dependent amplification function with respect to a reference station with a flat seismic noise horizontal‐to‐vertical spectral ratio. The evaluation relies on the decomposition of the S‐wave amplitude spectra in terms of source, propagation, and site response. We solve the decomposition with a nonparametric, single‐step generalized inversion in the frequency band 0.5–20 Hz. In addition, we compute the amplification factors for peak ground acceleration and velocity with respect to a well‐established ground‐motion prediction equation. The results highlight that only 11 stations show a relatively flat unitary response with respect to the reference site, whereas the frequency‐averaged amplification function at 23 out of 67 stations exhibits a value larger than 2. We classified the sites according to their surface geology and geomorphological scenario and found that amplification affects not only stations installed on the alluvial soil but also several stations installed on what are assumed to be rock sites. Sites in caves and mines exhibit deamplification, whereas the stations with sensors in boreholes exhibit the typical interference pattern. A good correlation between the amplification factors and the frequency‐averaged amplification functions suggests the possibility of predicting time‐domain peak ground‐motion values from amplification functions estimated by generalized inversion.