Valerio Poggi

Hybrid seismic arrays composed of collocated building-borehole sensors are essential for gaining better insight into the behavior of soil-structure systems using real data; however, they remain infrequent and are rarely supported by open, long-duration datasets. To help address this gap, we present a new long-term seismic monitoring installation and the associated seismic dataset. The network is installed on and around Terza Torre, a 20-story reinforced concrete building located in Bologna, Northern Italy. It comprises eight three-component stations deployed along the building’s height, including a basement reference station, and a nearby borehole station equipped with a surface and a downhole sensor at 50 m depth. The array was deployed in 2023 as part of a collaborative effort between the Emilia-Romagna Regional Government and the National Institute of Oceanography and Applied Geophysics to investigate the seismic response of a strategic building and possible soil-structure interaction (SSI) effects in urban environments typical of the Po Plain. The dataset includes recordings of 30 local and regional earthquakes (ML 3.0–4.8) and continuous ambient vibration. The quality of the dataset is analyzed in terms of signal-to-noise ratio, including possible applications and limitations. Three applications are exemplified, demonstrating its potential to estimate the building’s fundamental frequencies and the corresponding modes, and to assess the local site response. Should stronger seismic events be recorded in the future, SSI effects may be studied using earthquake recordings from the infrastructure. The dataset provides a rare opportunity to investigate the dynamic response of a tall building founded on soft soil and serves as a reference for validating numerical models and studying nonstationary structural behavior. Data and metadata of the first two years of the network operability will be made publicly available under findable, accessible, interoperable, reusable principles two years from publication.

Seismic source parameters, such as seismic moment, stress drop, and radiated energy, are key to understanding earthquake dynamics and rupture processes. In this study, we apply a non‐parametric Generalized Inversion Technique (GIT) to characterize the source properties of 735 earthquakes (local magnitudes 1.65 ≤ ML ≤ 4.55) recorded between 2016 and 2024 in the area of the European Southeastern Alps characterized by the presence of the Adriatic indenter. The high‐density seismic network coverage in the region allows for a robust, data‐driven inversion of Fourier amplitude spectra to separate source, path, and site effects. Our results highlight significant spatial variations in seismic source parameters, revealing distinct mechanical properties of fault systems. We find a general increase in stress drop with depth and observe deviations from self‐similar scaling, with apparent stress increasing with event size. The spatial distribution of the Savage‐Wood efficiency suggests differences in dynamic fault strength, with high‐efficiency events concentrated in the northeastern Italian Alps and Snežnik Mt. seismic area, respectively located in the Southeastern Alps Western sector and in the Dinarides seismotectonic domains, while lower‐efficiency events are more common along the Tolmin‐Idrija and Gemona‐Tarcento fault systems and in the Schio‐Vicenza‐Lessini seismotectonic domain. These findings provide new constraints on the mechanical behavior of faults in the northeastern Adriatic indenter section and have implications for seismic hazard assessment and ground motion modeling. The study underscores the importance of accurate source parameter estimation in improving our understanding of regional seismotectonic and earthquake generation processes.

In recent years, fibre optic sensing methods, in particular Distributed Acoustic Sensing (DAS), have been experimentally demonstrated to be suitable for monitoring Earth System parameters in submarine cables. The SUBMERSE project (SUBMarinE cables for ReSearch and Exploration) aims to develop blueprints for using telecommunication fibre optic cables as sensors by attaching fibre optic interrogators at selected landing stations, also building a data infrastructure for both temporary storage of full resolution data and permanent archival of reduced data sets.We analyse data from interrogating the East/West oriented Ionian Submarine System cable from both end points, i.e., Preveza, Greece, and Crotone, Italy, along the same fibre. This cable is operated by Islalink and located to the north of the Kefalonia Transform Zone. This fault zone marks the western termination of the Hellenic subduction system and is one of the most active seismic zones in Greece, with large damaging earthquakes above M > 6 occurring every few years on average.In addition to acquiring the full-resolution dataset, decimated channels (~100 in each case) acted as virtual seismic stations offshore, acquired at the NOA datacenter for real-time monitoring purposes. We explored various approaches to automated phase picking and magnitude determination on a reduced data set as well as the full-resolution data. We also consider other test sites on the Ellalink cable branches extending from Sines in southern Portugal and from Madeira.In order to support these and other acquisitions, we have developed a range of tools that can be deployed at future sites. We have enabled real-time streaming of DAS data following the standard Seedlink protocol, which allows straightforward integration into existing workflows at earthquake observatories. We have developed an automated, machine-learning-based algorithm for analysing earthquake waveforms and assembled a benchmark data set of earthquake recordings from DAS cables worldwide with labels of P and S arrival times that can serve to further refine machine learning and other automated analysis approaches. Finally, leveraging the Xdas platform (Trabattoni et al. 2025), we have extended the popular SeisBench platform (Woollam et al, 2022) for machine learning in seismology with the ability to efficiently process dense DAS datasets with algorithms/machine learning models operating across either single or multiple channels.

Distributed Acoustic Sensing (DAS) is rapidly emerging as a powerful complement to conventional seismic networks, enabling dense and continuous ground-motion monitoring by exploiting existing fiber-optic telecommunication infrastructures. In this contribution we present the design, implementation, and first results of a regional-scale DAS seismic monitoring network deployed in Friuli Venezia Giulia (NE Italy), developed through a close collaboration between the regional authorities, the public ICT provider INSIEL, and the scientific community.The DAS infrastructure is an integral part of the SMINO network, the multi-sensor seismic and geodetic monitoring system for north-eastern Italy operated by OGS, and is fully integrated within its operational framework. The network is based on five strategically distributed interrogation points across the region, collectively instrumenting nearly 250 km of telecommunication fibers belonging to the regional backbone. This configuration provides several tens of thousands of virtual sensing channels with meter-scale spatial sampling, covering urban areas, transportation corridors, and heterogeneous geological settings. To our knowledge, this represents one of the most extensive—and likely the largest—operational regional DAS seismic monitoring networks currently deployed in Europe.We describe the criteria adopted for fiber selection, network geometry, and acquisition parameters, with particular emphasis on signal optimization, performance, and long-term operational robustness. Examples of recordings from local and regional earthquakes demonstrate the capability of the system to capture coherent seismic wavefields, clear phase arrivals, and spatial variability of ground motion. The network also systematically records anthropogenic signals, which are discussed both as a challenge for data quality control and as an opportunity for multi-purpose environmental monitoring.Finally, we address the integration of DAS data into existing seismic and civil protection workflows, including real-time data streaming, event detection, and rapid situational awareness. The Friuli Venezia Giulia experience demonstrates the maturity and added value of fiber-optic sensing for operational seismology at regional scale.

ORFEUS (Observatories and Research Facilities for European Seismology, www.orfeus-eu.org; orfeus.readthedocs.io; forum.orfeus-eu.org) is a non-profit foundation that coordinates the collection, archival, and distribution of seismic waveform (meta)data, services and products based on international standards. It serves a broad community of seismological data users, on behalf of the Euro-Mediterranean seismic networks and monitoring agencies (orfeus.readthedocs.io/en/latest/governance.html). ORFEUS core domains comprise: (i) the European Integrated waveform Data Archive (EIDA; orfeus-eu.org/data/eida), providing access to raw seismic waveform data and basic station metadata; (ii) the European Strong-Motion databases (orfeus-eu.org/data/strong), offering automatically/manually processed waveforms, advanced station/site metadata, and associated products ; and iii) the European Mobile Instrument Pools (orfeus-eu.org/data/mobile), facilitating access to seismic instrumentation for temporary deployments. Currently, ORFEUS services distribute waveform data from more than 33,000 stations, including DAS deployments and dense temporary regional experiments (eg., orfeus.readthedocs.io/en/latest/adria_array_main.html), with an emphasis on FAIR principles, open access, and high data quality. ORFEUS services constitute a core component of EPOS (www.epos-eu.org/tcs/seismology) and are seamlessly integrated into the EPOS Data Access Portal (www.ics-c.epos-eu.org). Access to data and products relies on state-of-the-art information and communication technologies, with a strong emphasis on web services (www.orfeus-eu.org/data/eida/webservices; https://esm-db.eu/webservices) enabling programmatic interaction. ORFEUS promotes transparent data policies and licenses and acknowledges the indispensable contribution of data providers. Ongoing activities focus on further development of existing services and on facilitating access to massive and multidisciplinary datasets through collaboration with global and regional initiatives, including the FDSN (www.fdsn.org) and EarthScope (www.earthscope.org), as well as through support from EC-funded projects (e.g., www.geo-inquire.eu). ORFEUS implements community-oriented services that include software and travel grants, a sustained training/outreach programme of webinars and workshops (www.orfeus-eu.org/other/workshops), and editorial initiatives supporting best practices in seismological data use and dissemination.

In the last years, fibre optic sensing methods, in particular Distributed Acoustic Sensing (DAS), have been experimentally demonstrated to be suitable for monitoring Earth System parameters in submarine cables. The SUBMERSE project (SUBMarinE cables for ReSearch and Exploration) aims to develop blueprints for using telecommunication fibre optic cables as sensors by attaching fibre optic interrogators at selected landing stations, also building a data infrastructure for both temporary storage of full resolution data and permanent archival of reduced data sets.We analyse data from interrogating the East/West oriented Ionian Submarine System cable from both end points, i.e., Preveza, Greece, and Crotone, Italy, along the same fibre. This cable is located to the north of the Kefalonia Transform Zone. This fault zone marks the western termination of the Hellenic subduction system and is one of the most active seismic zones in Greece, with large damaging earthquakes above M > 6 occurring every few years on average.In addition to acquiring the full large dataset, decimated channels (~100 in each case) acted as virtual seismic stations offshore, acquired at the NOA datacenter for realtime monitoring purposes. We explored various approaches to automated phase picking and magnitude determination on a reduced data set as well as the full resolution data. We also consider other test sites on the Ellalink cable branches extending from Sines in southern Portugal and from Madeira.In order to support these and other acquisitions, we have developed a range of tools that can be deployed at future sites. We have enabled real-time streaming of DAS data following the standard Seedlink protocol, which allows straightforward integration into existing workflows at earthquake observatories. We have developed an automated, machine-learning-based algorithm for analysing earthquake waveforms and assembled a benchmark data set of earthquake recordings from DAS cables worldwide with labels of P and S arrival times that can serve to further refine machine learning and other automated analysis approaches. Finally, leveraging the Xdas platform (Trabattoni et al. 2025), we have extended the popular SeisBench platform (Woollam et al, 2022) for machine learning in seismology with the ability to efficiently process dense DAS datasets with algorithms/machine learning models operating across either single or multiple channels.

Field surveys focused on detailed mapping and measurements of coseismic surface ruptures along the causative fault of the 6 February 2023, Mw 7.8 Kahramanmaraş earthquake. The aim was filling gaps in the previously available surface-faulting trace, validating the accuracy of data obtained from remote sensing, refining fault offset estimates, and gaining a deeper understanding of both the local and overall patterns of the main rupture strands. Measurements and observations confirm dominating sinistral strike-slip movement. An integrated and comprehensive slip distribution curve shows peaks reaching over 700 cm, highlighting the near-fault expressing up to 70% of the deep net offset. In general, the slip distribution curve shows a strong correlation with the larger north-eastern deformation of the geodetic far field dislocation field and major deep slip patches. The overall rupture trace is generally straight and narrow with significant geometric complexities at a local scale. This results in transtensional and transpressional secondary structures, as multi-strand positive and negative tectonic flowers, hosting different patterns of the mole-tracks at the outcrop scale. The comprehensive and detailed field survey allowed characterizing the structural framework and geometric complexity of the surface faulting, ensuring accurate offset measurements and the reliable interpretation of both morphological and geometric features.

Earthquakes pose a significant threat worldwide, requiring rapid and accurate damage assessments to guide emergency response efforts. While empirical ground motion models are commonly used for their speed and simplicity, they often fail to account for critical factors such as site effects and the spatial variability of ground shaking. Physics-based ground shaking simulations can provide a more accurate alternative by modelling fault rupture, wave propagation and local site effects. However, their application in the near real-time has been limited due to computational complexity and long processing times. To overcome these limitations, we have developed UrgentShake, an HPC-based system designed to generate physics-based ground shaking scenarios under strict time constraints. A key focus of UrgentShake is the implementation of efficient strategies to reduce the computational time required to produce reliable solutions without compromising accuracy. Preliminary evaluations on two reference seismic events demonstrate UrgentShake's capability to significantly reduce time-to-solution, ensuring its potential to meet the critical timing demands of seismic emergency responses.

It is widely acknowledged that the majority of regions worldwide are susceptible to a range of potentially catastrophic natural hazards. Achieving a comprehensive estimation of the aggregate losses incurred by these diverse hazards necessitates the implementation of a multifaceted, tiered risk assessment approach, underpinned by harmonised methodologies, in accordance with the provisions outlined in the Sendai Framework for Disaster Risk Reduction (SFDRR). This methodological framework facilitates the direct comparability of risk estimates, thereby providing a foundational basis for the formulation of decisions concerning balanced and cost-effective mitigation and preparedness strategies that adequately address risk prioritisation. The Central Asian region, which has a documented history of seismic activity, fluvial flooding and landslides, is a pertinent case study. In an effort to support the process of risk mitigation in this region, the European Union, in collaboration with the World Bank Group (WBG) and the Global Facility for Disaster Reduction and Recovery (GFDRR), launched the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) programme, targeting the countries of Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan and Uzbekistan.In this context, the present work delineates the methodological framework and presents the results of the multi-hazard risk assessment carried out in the Central Asian region. These results are expressed in the form of probabilistic metrics pertaining to earthquake and flood loss estimates, including annual average losses, loss exceedance curves and return period specific losses. These metrics represent the basis for further technical recommendations, which are designed to support future disaster risk management (DRM) and disaster risk financing and insurance (DRFI) strategies in the region.