The Monteluco di Roio mountain (L’Aquila, Italy) presents a compelling case study of unexpected seismic amplification. Based on its geophysical and geotechnical features, characterized by stratigraphy primarily composed of carbonate bedrock, significant seismic amplification was unexpected. Nevertheless, during the April 6, 2009, earthquake, a reinforced concrete building within the Monteluco di Roio university complex sustained severe structural damage. To isolate the effects of topography, shallow stratigraphy, and internal bedrock geometry on seismic response, we conducted several numerical simulations across various scenarios. The results indicate that topographic amplification is negligible and stratigraphic amplification is limited to high frequencies. In contrast, the internal geometry of the carbonate substrate, characterized by tilted stratification intersected by sub-vertical faults, is responsible for significant amplification across a broad frequency range. Such geological configurations are common in Apennine chain or other orogenic belts worldwide. Given that broad-range frequency amplification can potentially impact a high number of buildings during a seismic event and considering that current seismic guidelines often lack requirements for detailed bedrock characterization, this study highlights critical warnings for seismic safety assessments and territorial planning.

Farming systems worldwide have exhibited climatic adaptation and improved crop outputs over the last century. Nevertheless, interannual yield fluctuations still drive volatility in food commodity prices, challenging food security. Predicting short-term yield variations from observed climatic patterns can thus provide significant benefits. This paper enhances a transparent, computational efficient and closed-form probabilistic short-term yield forecasting method introduced in our previous research. The case of wheat yield for an Italian province, where the Standardized Precipitation-Evapotranspiration Index (SPEI) was identified as a key predictor, is considered for illustrative purposes. Forecasting is defined as evaluating the conditional probability distribution of the next yield value, given the recorded SPEI in a selected month of the current year. As a main challenge is that the yield–SPEI relationship exhibits parameters varying over time, here we propose a least-squares method adapted for interpolating curves with time-varying parameters. Combined with resampling techniques, this enables robust probabilistic forecasts. Validation through Monte Carlo simulations and resampling confirmed the method’s effectiveness. The framework can be potentially tailored to different crops, regions, and spatial scales. Such predictive capacity may prove valuable in preparing stakeholders across the crop production–consumption chain, including financial markets, in managing risks linked to unexpected production outcomes.

A novel approach in monitoring the inner dynamics of mountains, massifs, and of the Earth crust in general, involves hydrogeological measurements, as well as new generation multi-component seismic stations. Several hydrogeological stations monitor the water parameters of the large Gran Sasso aquifer. This is especially important when the instrumentation used has a high sensitivity and is able to access frequencies below 1 mHz, opening the possibility of observing very slow signals of local origin. For several years, the ring laser gyroscope GINGERINO is operative inside the underground Gran Sasso laboratory (LNGS-INFN), and monitors the local Earth angular velocity around the vertical axis. Together with the co-located GIGS broadband seismometer (seismic stations of national network of INGV), it constitutes a 4C seismic station; the 4 degrees of freedom put together give insight into the inner movements of the Gran Sasso massif, that find correspondence in measurements conducted on the groundwater of the aquifer. In particular, the hydrogeological interpretation of the slow dynamics of the period since May to August 2023, and of the powerful mountain bang event of August 14 is consistent with data from GINGERINO. The final large bang event was also detected by the GIGS broadband seismic station and accelerometer station of RAN (National Accelerometer Network of Civil Protection Department). Furthermore, in the underground laboratories the bang event was recorded by an acoustic sensor and the groundwater hydraulic pressure monitor shows an anomaly exactly when the bang event occurred. Finally, the monitoring data of the groundwater at the boundary of the Gran Sasso aquifer also reveal anomalies linked to the bang event.

This research extends a previous investigation initiated by the authors focusing on the impact of geometric nonlinearity on the propagation of seismic waves in a two-dimensional model of the Aterno Valley, which includes the urban region of L'Aquila. Starting from a Cauchy continuum framework, this study undertakes a comparative analysis between a traditional linearized formulation, based on infinitesimal strain energy, and a nonlinear model that incorporates the Green-Lagrange strain tensor. The computational domain describes a detailed geological cross-section of the valley, comprising three primary stratigraphic layers. In addition, the upper layer incorporates mechanical segmentation. Furthermore, the excitation is represented as a spherical wavefront applied at the basal boundary, emulating a deep, high-energy source equivalent to an earthquake with a magnitude of Mw >= 6. Finite element simulations were performed in COMSOL using a generalized-alpha time integration scheme. An examination was conducted on two distinct configurations of Young's modulus distribution within the upper stratum. The first configuration comprised a homogeneous rigid top layer characterized by a unicum body, while the second configuration incorporated soft inclusions within the upper layer to emulate its fragmentation. A comparative analysis was conducted on nonlinear and linear simulations using normalized energy deviation parameters. This approach facilitated the quantification of the relative discrepancies between the deformation energy densities exhibited by the two models. The results indicate that, while the average deviations between the linear and nonlinear formulations are generally moderate, substantial local discrepancies are observed in regions near interfaces with pronounced stiffness contrasts. Specifically, energy deviations in these areas can exceed 100% in certain regions. The observed localized amplifications and redistributions of energy indicate that geometric nonlinearities might significantly affect the spatial distribution of wave energy propagation. This effect is particularly pronounced in scenarios where the shallow layers are mechanically segmented or incorporate compliant inclusions. The temporal evolution of energy at specific reference points within the urban area exhibits scenario-dependent variations, suggesting that linear assumptions may inaccurately characterize site response under conditions of high-intensity excitation. The results confirm the assumption that geometric nonlinearities are significant factors in strongly heterogeneous basins. This emphasizes the need for precise geometric representation and realistic modeling of stiffness distributions to improve predictive accuracy and reliability.

Effective adaptation planning for perennial crops, particularly in mountain contexts with climate-sensitive agroecosystems, requires a robust understanding of yield responses to climatic variability. Based on long-term data and a methodological framework covering both linear regression and machine learning techniques, the present study investigates the influence of interannual variability in agro-climatic indices on apple and grape yields in Trentino-Alto Adige, an alpine region in northern Italy. Results reveal that apple yields are more consistently influenced by climate variability than grape yields, with frost occurrence and heat-related indices emerging as key predictors. The machine learning approach, through variable importance metrics and individual conditional expectation plots, provides insights into nonlinear yield responses to critical climatic thresholds, such as sharp declines beyond a certain number of frost days or plateauing gains under sustained heat accumulation. Conversely, grape yields exhibit more heterogeneous and buffered responses, reflecting more complex interactions with climatic conditions. Overall, the study highlights the added value of data-driven approaches with physical interpretability for capturing intricate climate-yield relationships. In regions increasingly exposed to climate pressures, such as the alpine valleys, these tools can support the development of targeted strategies to sustain long-term crop productivity.

We present a detailed database and a 3D seismostratigraphic subsoil model for L'Aquila, severely affected by the April 6, 2009, Mw 6.3 earthquake, with the goal to provide the necessary input for evaluating local seismic effects in the city. The database was meticulously constructed using QGIS software, integrating a wide array of existing information, including geological, geophysical, geotechnical, and borehole data. The initial 3D geological-geophysical model was created using Petrel software by Schlumberger, applying a data-supported minimum convergent interpolation method. The compilation involved loading over 1300 shallow boreholes, approximately 50 deep boreholes, several seismic reflection profiles, and gravimetric data. This extensive dataset was crucial for constraining the geo-lithological setting of the studied area. To define the boundaries between the various Plio-Quaternary alluvial-slope units and the Meso-Cenozoic top-bedrock surface, we utilized an existing fine-scale geological map by Nocentini et al. (2017). Furthermore, the diverse geological units were reorganized into seven distinct classes based on their geophysical properties to facilitate the modeling process. The approach is highly integrative, combining various analyses to construct a realistic 3D subsoil model at a fine scale using the best available data. More precisely, we have continuously reconstructed the top surface of the seismic bedrock (Meso-Cenozoic carbonate rocks), and that of the overlying unit which is most widespread in the study area (Calabrian-age pelite and sand). The key novelty is that the resulting subsoil model is not simply an interpolation result but represents a data-supported reconstruction, significantly enhancing its reliability for seismic hazard assessment.

Globally, crop productive systems exhibit climatic adaptation, resulting in increased overall yields over the past century. Nevertheless, inter-annual fluctuations in production can lead to food price volatility, raising concerns about food security. Within this framework, short-term crop yield predictions informed by climate observations may significantly contribute to sustainable agricultural development. In this study, we discuss the criteria for historical monitoring and forecasting of the productive system response to climatic fluctuations, both ordinary and extreme. Here, forecasting is intended as an assessment of the conditional probability distribution of crop yield, given the observed value of a key climatic index in an appropriately chosen month of the year. Wheat production in the Teramo province (central Italy) is adopted as a case study to illustrate the approach. To characterize climatic conditions, this study utilizes the Standardized Precipitation Evapotranspiration Index (SPEI) as a key indicator impacting wheat yield. Validation has been carried out by means of Monte Carlo simulations, confirming the effectiveness of the method. The main findings of this study show that the model describing the yield–SPEI relationship has time-varying parameters and that the study of their variation trend allows for an estimate of their current values. These results are of interest from a methodological point of view, as these methods can be adapted to various crop products across different geographical regions, offering a tool to anticipate production figures. This offers effective tools for informed decision-making in support of both agricultural and economic sustainability, with the additional benefit of helping to mitigate price volatility.

Power-law distributions, with their interdisciplinary applications in fractals, non-linear systems, chaos theory, self-organized criticality, and scale-free systems, have garnered significant attention in recent decades. These theories find applications across various scientific disciplines, from physics to Earth sciences, social sciences, economics, and finance. Parameter estimation for such distributions can be effectively conducted by examining data at multiple scales of observation. This article illustrates practical multi-scale analysis methods through case studies from the statistical analysis of rock fractures and financial data, explaining their advantages and the underlying hypotheses and theories. Furthermore, a novel version of a maximum likelihood-based parameter estimation criterion, adapted for multi-scale samples, is presented, reassuring the audience about its applicability.

The use of hydroseimograms (i.e., high frequency pore pressure monitoring in wells in rock) emerges as a promising tool for a better understanding of the physics underlying earthquakes, as well as for seismic activity monitoring and/or prediction. This study investigates the earthquake detection capability of a hydraulic pressure device (HPD) installed in the Gran Sasso aquifer (GSA), Italy. The HPD, located in boreholes S13 and S14, near the INGV seismic station, GIGS, monitors hydraulic pressure changes within the aquifer. We compared data from the HPD and from GIGS to assess the HPD’s ability to detect earthquakes. The analysis covered the period from May 2015 to December 2023. The HPD successfully identified 148 out of 1068 analyzed earthquakes. Compared to previous studies, our HPD displayed significantly higher sensitivity, particularly for crustal earthquakes. These HPD devices show distinctive features, such as deep location, high frequency sampling (20 Hz), and hosting wells intercepting the main fault network. The unique location of the HPD, combined with its sensitivity to seismic events, makes it a valuable tool for continuous monitoring of earthquake activity, coupled with pore pressure trends and anomalies, in the region. These results confirm the potential of the HPD system for earthquake detection within the GSA. Future studies will continue to evaluate the HPD’s capabilities and its role in earthquake hazard assessment, as well as its potential use in other areas worldwide.

In active tectonic areas, fault systems represent one of the main structural elements in shaping landscapes. Thus, the study and dating of landforms and continental deposits affected by tectonic deformation, such as river profiles and knickpoints, paleosurfaces, strath and alluvial terraces, are crucial to assess the activity state of the faults and how they evolved over time. Some features may provide a time-averaged history of deformation (e.g., deformed geomorphic markers), while others have the potential to record a continuous history of deformation (e.g., rock-uplift histories from inversions of river profiles). In this work, we present three case studies where we reconstruct the history and characteristics of fault systems at different scales through a combination of geomorphological and morphostratigraphical analyses. At a regional scale, we present the case study of the North Anatolian Fault (NAF). We reconstructed a spatio-temporal history of rock-uplift by inverting river profiles from 19 different catchments draining the northern part of the Central Pontides, a mountain belt uplifted by the transpression produced by the NAF. We found that uplift migrated westward over time, and combining our results with other published data, we proposed a model describing the age and propagation rates of the NAF from the nucleation point in the Eastern Pontides to the Marmara Sea. The second case study investigates, at a meso-scale, the Quaternary evolution of the northwestern sector of the Apennine Chain (Italy). By combining the rock-uplift history inferred from the inversion of river profiles from 6 catchments draining the Apennine Belt and the morphostratigraphy of the youngest marine units uplifted during the Pliocene in the Po Plain, we inferred the main activity phases of the thrust-top/compressive arc system of the Alessandria Basin and Monferrato Arc, one of the outermost arcs of the northern Apennines. The third case study is a local investigation into identifying the master faults in the Aterno River Valley, one of the most active tectonic intramontane basins in the Central Apennines (Italy). Because the tectonic complexity of the area makes it unsuitable for reconstructing a continuous deformation history by the inversion of river profiles, we applied a different approach by combining the deformation of dated paleosurfaces and fluvial terraces with the present characteristics of the topography (slope, relief, present elevation of deformed paleosurfaces and terraces) and drainage system (channel steepness index, knickpoints). We identified two opposite fault segments (Monte Marine Fault in the Upper Aterno Valley and Bazzano-Monticchio-Fossa Fault in the Lower Aterno Valley), respectively dipping SW and NE, representing the master faults of two different half-grabens.

This study presents a comprehensive analysis of site effects in the highly seismic area of L’Aquila in central Italy, which has been conducted within the framework of a seismic microzonation project funded by the Abruzzo Region’s Department of Government of the Territory and Environmental Policies. The project was aimed at best practices on the management of urban and land territory for seismic risk mitigation. Through the integration of detailed geophysical and geotechnical data with numerical modeling, we provide an accurate assessment of local seismic amplification. Two-dimensional numerical simulations using the LSR 2D code were performed on many representative geological sections to compute amplification factors for various period ranges. This case study allowed us to outline some key considerations for best practices in local seismic response analysis and seismic microzonation studies in Italy. Given the prevalence of 2D basin edge, buried morphology, and topographic effects in Plio-Quaternary geologically complex intermontane basins in central Italy, as demonstrated in the L’Aquila case study, use of two-dimensional models is suggested. In order to validate the numerical models and their associated spectra and amplification factors, it is also suggested to compare transfer functions with HVSR microtremor measurements at control points along the studied sections.

Surface faulting and liquefaction are two earthquake-related effects to be considered in geological hazard assessment studies, particularly in application cases involving the construction or reconstruction of strategic buildings. The first effect is connected to the coseismic rupture on surface occurring along the active and capable fault, whereas the second relates to the ground seismic shaking and occurs mostly on sandy-silty grain sized deposits with shallow water table. Here, the results of investigations carried out in the Pagliare di Sassa village, nearby L’Aquila (central Italy), are presented, with the aim of shedding light on a potentially active and capable fault previously hypothesized at a site selected for the building of a school. The acquisition of paleoseismological, geophysical and geognostic data allowed to rule out the presence of the active and capable fault in the school area and to characterize several soft sediment deformation structures, interpreted as seismites related to two earthquake-induced paleoliquefaction events. Their occurrence has been linked through ceramic and radiocarbon dating. The seismites were used to determine the likely historical earthquakes (date, seismogenic source and magnitude), which in turn helped determine their occurrence contributing to the comprehension of the seismotectonic setting of central Italy. Lastly, the assessment of these local seismic instabilities, evidenced by the case study of Pagliare di Sassa, represents a key prerequisite for best practices in land and urban planning, devoted to the building of strategic edifice, such as a school. In such cases, the application of palaeoseismological technique proves to be invaluable for mitigating the seismic risk.

Radon is increasingly recognized as a geogas tracer for geodynamic processes and a potential earthquake precursor. The European ArtEmis project aims to investigate earthquake hydrogeology, utilizing a European network of advanced, low-cost sensors to explore radon concentration pre-, co- and post-seismic changes and anomalies, in groundwater of key seismogenic sites. In Italy, this project focuses on monitoring radon concentration in groundwater of Abruzzo region chosen for its high seismicity. The selection process of the hydrosensitive to seismicity sites in Abruzzo, where sensors will be installed, is outlined in this study. As radon concentrations in groundwater are believed to be less susceptible to the shallow phenomena than radon measurements in soil gas, radon monitoring will be carried out only within carefully selected high-discharge springs. Site selection prioritized hydrosensitive to seismicity locations, considering source rock properties, hydrogeological and seismotectonic settings and seismic activity, viewed as main factors influencing radon release. Potential sites, including carbonate aquifers, intermontane plains, and spa areas, were identified due to their interaction with main seismogenic faults, high-discharge springs, and potential geogas upwelling. These springs are representative of large rock volumes crossed by seismogenic faults, reflecting deep processes, such as the radon upwelling, minimally influenced by shallow or seasonal water cycle variations.

It is usually accepted in geophysics (and in civil engineering) that linear models can be used for describing an earthquake and the consequent seismic waves’ propagation. However, the large deformation experienced by the soil in these situations suggests that this paradigm requires more critical consideration. In fact, we claim that, in the vicinity of some discontinuities (that are common in all the geophysical applications of continuum models), the corresponding strain concentrations make the hypothesis of small deformation to be inadequate. In this paper, we verify the inappropriateness of the linear paradigm in a simple but reasonable case, with a view to a future application of this study to the effects of the 2009 L’Aquila earthquake. To this aim, we start with an analysis which is restricted to a two-dimensional body (i) with an inhomogeneity that resembles the Aterno River Valley, central Italy and (ii) with a non-linearity that is the most simple one, choosing the strain energy to be quadratic in the non-linear measures of deformation. More precisely, we consider a 2D piecewise homogeneous domain and a material that is viscoelastic isotropic and geometrically non-linear. We apply, to the bottom of such a domain, a seismic excitation and calculate the differences in the response between the linear and the geometrically non-linear cases. Using a suitably designed numerical model, we prove that, as conjectured, these differences not only originate near the pre-defined geometrical discontinuities but also propagate throughout the rest of the domain. Moreover, we find numerical predictions of the frequency ratios and ground acceleration time dependence and amplitude that produce, in the case of non-linear models, predictions which are closer to experimental evidence than those obtained using the corresponding linear model.

Earthquakes, as one of the most prominent natural disasters, pose a severe threat to societies in regions near active fault lines. Being able to forecast when, where and how strong an earthquake will be is beyond current scientific capabilities. At present, forecasting methods yield earthquake occurrence probabilities within a specific time frame spanning several years. Measurements of changes of radon concentrations in groundwater have shown pronounced changes preceding imminent earthquakes. The potential in using radon as a precursor for earthquakes has been explored by multiple groups over many years. Radon measurements in soil have shown large variations in activity, partly due to atmospheric influences. The ArtEmis project seeks to offer new insight into the correlation between imminent earthquakes and changes in radon emission from the upper crust by employing novel concepts for measurements and analysis. The paper presents system aspects of the ArtEmis project, a description of the ArtEmis sensor prototype and first results.

This paper illustrates the outcomes of a third-level Seismic Microzonation project carried out in pilot areas of the Municipality of L’Aquila, Italy, an area characterized by recent strong seismic activity (6 April 2009 Mw 6.3 earthquake and central Italy 2016 seismic sequence—Mw 6.0 and 6.5 events). The primary aim was to develop numerical maps for urban and land planning to mitigate seismic risk, in line with the guidelines of the Italian Civil Protection Department. The local amplification assessment was organized through various sequential and/or parallel activities, including geotechnical and geophysical investigations and characterization, seismic input and numerical code selection, acquisition of 2D microtremor arrays, and comparison between 1D and 2D numerical modeling of seismic site response. This case study introduces several innovations to the microzonation procedures outlined in current Italian and European regulations, such as the use of microtremor arrays to assess a reliable subsoil model and a new procedure for associating amplification factors to each microzone. The results obtained are significant both for the detailed seismic characterization of the territory and for providing methodological indications useful for similar future studies. The use of 2D models is integrated into the flowchart for producing third-level microzonation maps, offering valuable tools within the framework of urban and land management from a perspective of territorial sustainability.

The sensitivity of the agricultural production system to short- and long-term climate variations significantly affects the availability and prices of food resources, raising relevant issues of sustainability and food security. Globally, productive systems have adapted to climate change, leading to increased yields over the past century. However, the extent to which these adaptations mitigate the impacts of short-term climate fluctuations, both extreme and ordinary, remains poorly studied. To evaluate the vulnerability of crop yield to short-term climate fluctuations and to determine whether it changes over time, we conducted a statistical analysis focusing on one of the main crops in the Abruzzo region (central Italy) as a case study: grape. The study involves correlation analysis between opportune climatic indices (SPI and SPEI) and grape yield data over the sixty-year period from 1952 to 2014, aimed at evaluating the impact of short-term climatic fluctuations—both extreme and ordinary—on crop yield. Our findings reveal an increasing correlation, mainly in the summer–autumn season, which suggests a rising sensitivity of the productive system over time. The observed increase is indicative of the Abruzzo grape production system’s adaptation to climate change, resulting in higher overall yields but not enhancing the response to short-term climatic fluctuations.

The manuscript provides a comprehensive review of the results that have been obtained from radon concentrations in the ground, particularly their correlation with earthquakes, over the past fifty years in Greece. Data collection methods have evolved from solid-state nuclear track detectors to more advanced continuous monitoring devices. The influence of meteorological parameters was eliminated through time series analysis, revealing correlations between radon signals and earthquakes M3.5–6.5. Anomalies persisted for days to weeks, depending on the faulting type. The review concludes with a discussion and evaluation of the results, highlighting the potential for future research on this intriguing correlation between radon and earthquakes.

Short-term climate fluctuations can have a significant impact on the stability of food resource prices, thus threatening food security, even in cases where the crop production system shows good adaptation to climate change and/or increasing average yields over time. This paper illustrates, in detail, a statistical approach aimed at verifying whether the variation of the crop production system vulnerability to climate fluctuation exhibits a trend over time. These methods were applied to the case study of wheat grown in the Abruzzo region (Italy). The results show that, although the wheat crop yield still shows ongoing growth, the correlation between climate fluctuations and yield oscillations exhibits a systematic increase over the past sixty years. Such an increase in climate-related production fluctuations may represent a disturbing element for market equilibria and be potentially harmful for the various economic subjects involved at various scales, such as producers, distributors, investors/financial traders, and final consumers. The statistical approach illustrated provides a framework for monitoring climate impacts and also provides the basis for building up statistical forecasting models to support informed decision making in agricultural management and financial planning.

Statistical analyses of time series of A-DInSAR post-seismic data (April 6th 2009 L’Aquila earthquake), acquired in the time range 2010-2021 from the Cosmo-SkyMed (by ASI) and Sentinel-1 (by ESA) missions, have been carried out. These have allowed investigating the relationships between ground deformations and geological, hydrogeological, and geomorphological features of the study area, located in L’Aquila (Italy) historical centre (LAHC). The analysis of these data is still ongoing and offers promising research perspectives in the field of geomechanical/geotechnical subsoil characterization, based on satellite ground deformation data, also useful in seismic hazard characterization and mitigation. L’Aquila downtown is placed in the L'Aquila-Scoppito intermontane basin (Central Italy) which is a half-graben bordered by SW-dipping normal mostly active faults, filled with approximately maximum 600 meters of Plio-Quaternary continental slope, colluvial and alluvial deposits which overlie unconformably the carbonate bedrock. To assess the relationship between the geological-geomorphological and hydrogeological study area features and ground deformation in L’Aquila downtown, a correlation analysis has been carried out, between subsidence velocity and the following driving factors: water table depth, ground slope, shear wave velocity of outcropping lithologies and Red Soil thickness. Furthermore, cluster analysis and various filtering and time series treatment have been applied to these time series with the aim of analysing seasonal and deseasonalized trends. The correlation between subsidence velocity and the above-mentioned driving factors is statistically significant. It is presumable that the subsidence process is mainly controlled by the kind and thickness of lithologies involved. The above illustrated correlation analysis provides a first result, which may be improved by a multivariate approach. Let us consider a simple vertical strain model, made up of overlying layers (e.g., Red Soil, L’Aquila Breccia, etc.) in the consolidation phase. The integrated analysis of A-DInSAR and well data may allow determining the subsurface structure for the studied urban area, with particular attention to Red Soils, which, due to their high compressibility, have been recognized as lithology responsible for site-specific seismic amplifications. This may provide a promising powerful method of geotechnical characterization at urban scale and at a relatively low cost. The main achieved results can be summarized as follows: The A-DInSAR post-seismic data, recorded in the time range 2010-2021, revealed a post-seismic subsidence phenomenon, still ongoing. The correlation analysis allows us to conclude that subsidence velocities are mainly controlled by the properties and thicknesses of shallower rock layers. The subsidence velocity is positively correlated with the damage level of buildings. The cross-correlation analysis highlighted a significant correlation between seasonal fluctuations in subsidence rate and rainfall variations. The seasonally adjusted A-DInSAR time series highlighted an anomaly in the subsidence trend, observable during the Amatrice-Norcia seismic sequence of 2016. The study of this anomaly deserves attention and will be the subject of future research. Ground deformations detected by means of A-DInSAR technology may provide a promising inversion criterion, enabling us to perform a geotechnical characterization of shallow rock layers, over large areas, at relatively low costs.