Valerio Poggi

Understanding how fault strength evolves through time remains a central challenge in seismology, particularly in complex plate-boundary regions characterized by structural segmentation and heterogeneous coupling. We investigate whether ground-motion variability from small earthquakes can track mechanical evolution of active faults in the southeastern Alps (northeast Italy—W Slovenia)—a region that hosted destructive earthquakes such as the 1511 (∼Mw 6.8) and the 1976 Mw 6.5 Friuli events. We analyze ∼115,000 near-fault peak ground acceleration (PGA) recordings from 6,219 earthquakes (0.5≤Mw≤4.2; 2016–2025) using a mixed-effects ground-motion model that isolates the between-event term (δBe), representing source-related variability independent of magnitude, distance, and site effects. δBe exhibits clear spatial clustering and correlates positively with independently estimated stress-drop residuals, confirming that ground-motion variability reflects rupture efficiency and relative fault strength. Mapping the temporal evolution of a normalized cumulative stress index derived from δBe reveals persistent east–west mechanical segmentation and multi-year trends. Notably, the epicentral area of the 1976 Friuli earthquake exhibits a progressive post-2022 increase in relative stress drop. Our results demonstrate that small-earthquake ground-motion variability provides a model-independent proxy for tracking spatial and temporal changes in fault mechanics. In the southeastern Alps, mechanically distinct fault domains evolve differently through time, suggesting heterogeneous stress loading and redistribution across adjacent segments of the plate boundary.

Distributed acoustic sensing (DAS) is rapidly emerging as a powerful complement to conventional seismic monitoring, enabling dense spatial sampling over tens of kilometers using existing fiber-optic telecommunication infrastructures. In this study, we present the design, implementation, and initial performance of a regional-scale DAS seismic monitoring network integrated within the operational framework of the Seismological Research Center of OGS in north-eastern Italy. The system is built upon dark fiber segments of a public telecommunication network and interrogated by multiple DAS units, covering several hundred kilometers of optical fiber and producing tens of thousands of virtual sensing channels. We describe the end-to-end workflow developed to support continuous DAS acquisition in an operational environment, including data conversion from proprietary formats to standard seismological archives, channel aggregation strategies, metadata handling, and real-time streaming through SeedLink and International Federation of Digital Seismograph Networks services. Attention is given to practical constraints related to data volume, latency, channel naming, and integration with existing seismic monitoring infrastructures. Using representative examples, we illustrate the capability of the network to record teleseismic and local seismic signals, to characterize spatially variable seismic noise conditions along fiber routes, and to contribute to earthquake location when combined with conventional seismic stations. These case studies highlight both the opportunities and current limitations of distributed acoustic sensing (DAS) for regional seismic monitoring, including issues related to channel localization, directional sensitivity, and effective sensing range. The presented network represents one of the most extensive operational DAS deployments for seismic monitoring in Europe to date. Our results demonstrate the feasibility of integrating large-scale DAS systems into routine monitoring activities and provide a reference framework for future developments toward multisensor, fiber-optic-based seismic observatories.

The rapid response system currently in operation in northeastern Italy is based on the U.S. Geological Survey ShakeMap tool, which integrates ground-motion observations with selected ground-motion models (GMMs), similar to the systems used worldwide. To overcome the well-known limitations of conventional GMMs, a complementary system called UrgentShake, which uses physics-based ground-motion simulations, is currently being developed. The system integrates a kinematic description of an extended seismic source and captures the complex propagation of seismic waves through the heterogeneous subsurface of the region, considering its geological characteristics and topography. The development of UrgentShake is enabled by the use of high-performance computing facilities, which allow expediting the process, ensuring timely generation of seismic scenarios. The capability of generating near-real-time earthquake scenarios under strict time constraints following a seismic event is currently under investigation. In this initial phase, the system has been established as a prototype to showcase its potential, with planned refinements aimed at enhancing both the accuracy of ground-shaking predictions and its practical applicability in real-world scenarios. These advancements will enable regional civil protection authorities to make informed, timely decisions for managing seismic emergencies and coordinating response efforts effectively.

Shallow shear-wave velocities (VS) sometimes are estimated from joint inversions of horizontal-to-vertical (H/V) spectral ratios and surface-wave dispersion curves derived from ambient noise or small active sources. Here, we evaluate carrying out these inversions using Rayleigh-wave dispersion curves computed from crustal-scale P-wave seismic refraction data. We use data from the 2014–2015 Eastern North American Margin (ENAM) experiment in Virginia and North Carolina, but similar seismic refraction data sets have been acquired over sedimentary basins of interest for seismic hazard studies, including in major urban areas. The ENAM project deployed a pair of ∼215 km long, northwest–southeast linear arrays with ∼300 m receiver spacing to record 11 dynamite shots, and 80 continuously recording seismometers with 5–6 km spacing along the same arrays to record offshore airguns. The arrays crossed the onland portion of the Atlantic Coastal Plain sediments, which are a seaward-thickening wedge of Cretaceous and younger sediments deposited mostly on crystalline bedrock. We compute Rayleigh-wave dispersion curves from 3 to 9 km long portions of the receiver arrays on each side of the dynamite shots, and we compute ambient-noise H/V ratios from the continuously recording seismometers. We use a genetic inversion algorithm in which forward velocity models in each “generation” are evaluated for misfits compared to the observed data, with subsequent generations constructed from the models with the smallest misfits. Velocities to depths of 500 m are defined well, as shown by a narrow range of velocities in the best-fit models, by the consistency between multiple inversion runs at a site, and by forward modeling of site responses. The resulting velocity cross-section of the Coastal Plain strata has seaward-dipping contours in the thinner portions of the Coastal Plain but smaller dips in the deeper portions. We interpret these results as showing that velocity contours in the ACP strata are influenced by a combination of lithology and overburden pressure. Results demonstrate that existing seismic refraction data have the potential for determining detailed shallow shear-wave velocity profiles.

Understanding the potential socioeconomic losses due to natural hazards, such as earthquakes, is of foremost importance in the field of catastrophe risk management. The construction of a probabilistic seismic risk model is complex and requires the tuning of several parameters essential to represent the seismic hazard of the region, the definition of the exposed inventory characteristics, and its vulnerability to ground motion. Because significant uncertainties could be associated with each model component, the loss estimates are often highly volatile. Nevertheless, to reduce the conceptual complexity and the computational burden, in many real‐life applications these uncertainties are either not adequately treated or neglected altogether. The false high fidelity of the ensuing loss estimates can mislead decision‐making strategies. Hence, it is useful to assess the influence that the variability in the estimated values of the model input parameters may exert on the final risk results and their relevant contributions. To this purpose, we have performed a sensitivity analysis of the results of an urban seismic risk assessment for Isfahan (Iran). Systematic variations have been applied to the values of the parameters that control the earthquake occurrence in the probabilistic seismic hazard model. Curves of input–output relative variations were built for different risk metrics with the goal of identifying the parameters most sensitive to input uncertainty. Our findings can be useful to support risk managers and practitioners in the process of building seismic hazard and risk models. We found that the Gutenberg–Richter a and b values, the maximum magnitude, and the threshold magnitude are large contributors to the variability of important risk measures, such as the 475 yr and the average annual loss, with the more frequent losses being, in general, most sensitive.