Italy Earthquake Research Articles

Comparative analysis between continuous and discontinuous methods for the assessment of a cultural heritage structure

AbstractIn an era marked by the urgent need to ensure the safety of existing buildings according to current standards, evaluating the stability of masonry structures against hazard events has become a significant challenge. Despite the versatility and durability of masonry, structural assessments are hampered by factors such as limited information on material properties, irregular geometries, and ageing. To address this issue, numerous modelling techniques have been developed, supported by extensive scientific literature. However, significant factors related to the case study replication, such as the geometric complexity, the mechanical behaviour of masonry, the loading applications, contribute to the challenges associated with modelling procedures, including computational time, discretization procedures, and step incrementation. This paper critically discusses the most innovative modelling approaches. Specifically, it aims to compare the efficiency of the Distinct Element (discontinuous) Methods and the Finite Element (continuous) Method, both applied to the numerical simulation of a case study structure severely damaged by the 2016 Central Italy earthquake under lateral loading conditions. The continuous method is analysed using Midas FEA NX©, while the discontinuous methods are studied using 3DEC© and LMGC90© software, each with different contact conditions. Finally, the investigation highlights the main advantages and disadvantages of each method. In particular, the discontinuous method demonstrates reliability in accurately replicating failure patterns, whereas the continuous method allows for a faster model setup, making it suitable for preliminary studies on structural dynamics.

Seismic Vulnerability Assessment of Historic Centers with Two Fast Methods Based on CARTIS Survey Methodology and Fragility Curves

After an earthquake, legislation tends to permit the rapid demolition of damaged buildings, including the built heritage, for safety reasons, as was the case for many small historic centers after the 2016 earthquake in central Italy. A balance should, of course, be struck between safety and preservation. There must be a willingness to engage in continuous interaction with the various bodies involved in post-earthquake management, particularly in the preventive phase of the complex activities regarding the issues of the seismic vulnerability of historic built. The widespread historical built heritage in Italy requires fast and reliable assessment procedures that allow a large-scale evaluation of the vulnerability of historical buildings before a seismic event. To this end, a proposal is presented here for the inverse use of the protocol for the seismic vulnerability survey of historic centers by means of a system called CARTIS form, coordinated since 2015 by the Italian consortium of Seismic and Structural Engineering Laboratories (ReLUIS). This rapid assessment is compared with an equally fast method for constructing fragility curves, based only on the information available in the ReLUIS–CARTIS database, defining the relationship between the probability of reaching a level of loss of structural safety or a vulnerability index as a function of the seismic acceleration PGA and the ground orography. The methodology outlined could be considered to be progress in cultural heritage diagnostics on a large scale, considering cultural heritage to be the diffuse historical residential masonry buildings that form the historic centers.

A contrastive topic-aware attentive framework with label encodings for post-disaster resource classification

Social media has emerged as a critical platform for disseminating real-time information during disasters. However, extracting actionable resource data, such as needs and availability, from this vast and unstructured content remains a significant challenge, leading to delays in identifying and allocating resources, with severe consequences for affected populations. This study addresses this challenge by investigating the potential of label and topic features, combined with text embeddings, to enhance the performance and efficiency of resource identification from social media data. We propose Crisis Resource Finder (CRFinder), a novel framework that leverages label encoding and topic features to extract richer contextual information, uncover hidden patterns, and reveal the true context of disaster resources. CRFinder incorporates novel techniques such as multi-level text-label attention and contrastive text-topic attention to capture semantic and thematic nuances within the textual data. Additionally, our approach employs topic injection and selective contextualization techniques to enhance thematic relevance and focus on critical information, which is pivotal for targeted relief efforts. Extensive experiments demonstrate the significant improvements achieved by CRFinder over existing state-of-the-art methods, with average weighted F1-score gains of 7.12%, 6.44%, and 7.89% on datasets from the Nepal earthquake, Italy earthquake, and Chennai floods, respectively. By providing timely and accurate insights into resource needs and availabilities, CRFinder has the potential to revolutionize disaster response efforts.

Studying Past Earthquakes with Modern Techniques: Ground-Motion Simulations for the 11 January 1693 Noto Earthquake in Italy

Abstract The 1693 Noto earthquake, which struck on 11 January, is one of the Italy’s largest and most devastating earthquakes. According to the Italian Parametric Earthquake Catalogue, it reached a maximum intensity of 11 on the Mercalli–Cancani–Sieberg scale and had an estimated magnitude of M 7.3. Nevertheless, its precise location and source definition remain subjects to debate due to the complexity of the seismic sequence and lack of geological evidence. A series of potential seismic sources differing in location, dimension, and kinematics have been proposed in the literature based on seismotectonic data and interpretations. The goal of this work is to perform a retrospective experiment to verify which of the proposed seismic sources have a better fit with the observed intensity data. To do so, novel simulation techniques are used to study this historical earthquake. We generated ground-motion scenarios for each proposed source model through a stochastic finite-fault simulation approach. Then, the simulated ground-motion parameters were converted to intensities using two different ground-motion intensity conversion equations for Italy. Finally, we compared these converted intensities with the observed intensity data in terms of normalized root mean square errors and converted intensities from ground-motion models. Our results generally show good consistency between converted intensities from the simulated and predicted ground motions, whereas the observed intensities fit better to converted ones from the peak ground velocity rather than peak ground acceleration. Our analysis reveals that the source model reproducing the best of the macroseismic data of the Noto earthquake is the Canicattì–Villasmundo fault system with a magnitude of 7.1.

Empirical seismic fragility of masonry buildings in historical centres accounting for structural interventions

Fragility models are widely employed to forecast seismic damage in built environments. However, the actual conditions of buildings, depending on their construction systems and transformations, are crucial for model reliability, especially in historical centres.In this paper, an empirical fragility model for residential masonry buildings from data collected within 19 historical centres struck by the 2016 Central Italy earthquake is proposed. The dataset includes both traditional unreinforced and hybrid buildings, where reinforced concrete elements were applied in the 1980s according to seismic reinforcement prescriptions for existing structures.This study acknowledges the impact of such structural modifications on the seismic performance of buildings, which can alter their vulnerability classification either improving or worsening it. The intensity measure for the fragility functions is the peak ground acceleration obtained from actual records through interpolation for each centre. Damage data and vulnerability assessment of 2134 traditional and hybrid structural units are conducted in the framework of the European Macroseismic Scale (EMS-98). The fragility functions are plotted for both structural types and EMS-98 vulnerability classes, also considering the contribution of structural interventions, and then compared to literature empirical models. Hybrid buildings achieve a behaviour similar to traditional buildings when floors are strengthened but walls are not. However, when both masonry walls and floors are strengthened, their performance significantly improved, approaching that of modern clay block buildings with rigid floors. Compared to literature models, the proposed one showed good compatibility for the most vulnerable buildings, whereas less vulnerable ones appeared even stronger thanks to interventions.

Labor market outcomes during opposite resource shocks: the 2009 and 2012 earthquakes in Italy

The 2009 and 2012 earthquakes in Italy occurred in a close-knit region and time horizon but differed substantially on both the initial shock to the stock and the subsequent flow of resources. This paper considers the short run impact on the dynamic response of labor market outcomes. Both earthquakes lowered employment and labor force participation by more than 0.5%. With its negative effect on the resources available, the 2009 shock led to a drop in real wages of 1.3% and a sharp—but short-lived—widening of the wage gap generated by the skill premium. The 2012 earthquake, which led firms to upgrade their technology, increased wages by 2.2% and led to a more balanced—but persistent—widening of the wage gap. The predictions of a model developed in this paper are consistent with these results.

The Preparation Phase of the 2022 ML 5.7 Offshore Fano (Italy) Earthquake: A Multiparametric–Multilayer Approach

This paper presents an analysis of anomalies detected during the preparatory phase of the 9 November 2022 ML = 5.7 earthquake, occurring approximately 30 km off the coast of the Marche region in the Adriatic Sea (Italy). It was the largest earthquake in Italy in the last 5 years. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models, such earthquake could induce anomalies in various observable variables, from the Earth’s surface to the ionosphere. Therefore, a multiparametric and multilayer approach based on ground and satellite data collected in each geolayer was adopted. This included the revised accelerated moment release method, the identification of anomalies in atmospheric parameters, such as Skin Temperature and Outgoing Longwave Radiation, and ionospheric signals, such as Es and F2 layer parameters from ionosonde measurements, magnetic field from Swarm satellites, and energetic electron precipitations from NOAA satellites. Several anomalies were detected in the days preceding the earthquake, revealing that their cumulative occurrence follows an exponential trend from the ground, progressing towards the upper atmosphere and the ionosphere. This progression of anomalies through different geolayers cannot simply be attributed to chance and is likely associated with the preparation phase of this earthquake, supporting the LAIC approach.

Behind the Italian catalogues: overlooked but far from negligible earthquakes

The Italian parametric earthquake catalogue is the result of several decades of historical seismological research, based in its turn on a centuries-long tradition of descriptive earthquake compilations. Thanks to historical seismological research undertaken since the mid-1980s, knowledge of the major historical earthquakes in Italy has hugely improved. These studies, however, focused mainly on earthquakes already recorded in Mario Baratta’s extensive compilation I terremoti d’Italia (a summary of earlier descriptive earthquake studies, published in 1901), rather than on the identification of earthquakes still ‘unknown’ to the Italian seismological tradition. As the results of a systematic perusal of ‘serial’ historical sources show, it is still possible to discover locally significant earthquakes (i.e. important for improving seismic history and hazard assessment of given localities or areas) that no previous studies had ever considered. Initiating new research projects specifically aimed at the identification of earthquakes unknown to the seismological tradition is therefore essential to improve hazard assessments on a subregional and local level.

Damage‐informed ground motion and semi‐empirical fragility assessment

AbstractCalibrating parametric fragility curves via empirical damage data is one of the standard approaches to derive seismic structural vulnerability models. Fragilities based on empirical data require the characterization of the ground motion (GM) intensity at the building sites in the area affected by the earthquake producing the observed damages. This is commonly conducted via ShakeMap, that is, a map of the expected values of a Gaussian random field (GRF) of the logarithms of a GM intensity measure conditional to magnitude, location, and possibly a set of recordings of the earthquake. Once that intensity and damage data at the same sites are available, the typical approach calibrates a two‐parameter fragility model. However, ShakeMap estimates are affected by uncertainty deriving from that of the GM model used to characterize it. Furthermore, such an uncertainty can be reduced by building damage data, which provide information on the shaking intensity at the sites where damage is observed. It is shown herein that if this uncertainty is not addressed, also considering the shaking information provided by damage, the estimates of the fragility parameters obtained using a median ShakeMap only can be biased, and a recommended maximum likelihood estimation procedure – which exploits the expectation maximization algorithm – is provided. These arguments are illustrated via an application considering damage data from the 2009 L'Aquila earthquake in central Italy.

Multicriteria decision tools for selection of sustainable integrated retrofits: application to the seismic and energy upgrade of a masonry building

The design of sustainable integrated retrofits is a new frontier in civil engineering that aims to minimize economic and environmental impacts of interventions on existing buildings. The enhanced methodology presented in this paper combines seismic and energy performance metrics with economic and environmental indicators associated with each integrated retrofit. The purpose is to identify the optimal retrofit through histograms, radar charts, proficiency ratios and iso-class plots, as the one corresponding to the higher seismic and energy performances and the minimum economic and environmental impacts. Such a methodology can be applied to either the installation phase of the retrofit or its entire life cycle, making it possible to compare these two scenarios in a long-term perspective. The methodology, generally valid for any building materials or structural typologies, is here applied to a two-story natural-stone masonry building, damaged by the 2016 Central Italy earthquake sequence.

Machine-learning-aided regional post-seismic usability prediction of buildings: 2016–2017 Central Italy earthquakes

This study addresses the development of machine learning models for predicting the post-seismic buildings usability within regions prone to frequent earthquakes. The analysis leverages on field data from 2016-2017 Central Italy earthquakes. Several machine learning techniques are employed for this task, namely K-nearest neighbors, linear support vector machine, radial basis function support vector machine, decision tree, random forest, neural network, adaptive boosting, naive Bayes, quadratic discriminant analysis, logistic regression, and linear discriminant analysis. The input variables include both building attributes and seismic intensity measures. Since the database turns out to be strongly imbalanced, the potential influence of two preprocessing techniques is examined, namely principal component analysis and synthetic minority oversampling technique. Several metrics are considered to evaluate the performance of the resulting predictive machine learning models. Moreover, this study investigates the optimal machine learning model’s robustness against uncertainties, quantifies the importance of its features, and investigates how usability classes clustering can impact its performance. Every step of the implemented procedure is deeply explained and discussed to provide useful guidelines for similar applications.

Renewable Energy Proliferation and the New Local Energy Community Paradigm: Analysis of a Case Study in Italy

Renewable energy communities (RECs) have been gaining momentum around the world, as a way to promote sustainable development and combat climate change. These communities are typically composed of individuals, businesses, and organizations that come together to invest in and promote the use of renewable energy sources, such as solar, wind, and hydraulic power. This article focuses on the benefits that renewable energy communities bring to a territory through the diffusion of renewable energy systems, tackling different issues like local depopulation, increasing energy prices, and a lack of jobs, while reducing greenhouse gas emissions and improving air quality. The novelty of this article lies in the results from the first-of-its-kind national call within the Next Appennino program, part of the National Complementary plan, aimed at the formation and proliferation of RECs in the area severed by the 2009 and 2016 earthquakes in Italy, as a way to add social, environmental, and sustainable value to the reconstruction of this territory. The data refer to the municipality of Castelraimondo and Unione Montana dei Monti Azzurri (a consortium of mountain municipalities), both located in the Marche region. Analysis of the consumer and prosumer energy needs, as well as the quantification of the exploitable production from the new renewable generators installed, showed that a total of 6.134 GWh/year can be shared by the community.

Effect of earthquake sequences on risk-based catastrophe bond pricing.

Catastrophe bonds (cat bond in short) are an alternative risk-transfer instrument used to transfer peril-specific financial risk from governments, financial institutions, or (re)insurers, to the capital market. Current approaches for cat bond pricing are calibrated on seismic mainshocks, and thus do not account for potential effects induced by earthquake sequences. This simplifying assumption implies that damage arises from mainshocks only, while aftershocks yield no damage. Postearthquake field surveys reveal that this assumption is inaccurate. For example, in the 2011 Christchurch Earthquake sequence and 2016-2017 Central Italy Earthquake sequence, aftershocks were responsible for higher economic losses when compared to those caused by mainshocks. This article proposes a time-dependent aggregate loss model that takes into account seismicity clustering and damage accumulation effects in the computation of damage. The model is calibrated on the seismic events recorded during the recent 2016-2017 Central Italy Earthquake sequence. Furthermore, the effects of earthquake sequence on cat bond pricing is explored by implementing the proposed model on five Italian municipalities. The investigation showed that neglecting time-dependency may lead to higher difference (up to 45%) in the cat bond price when compared to standardapproaches.

The effect of the earthquake in Central Italy on the depopulation of the affected territories

Peripheral and demographically fragile territories could be less resilient to the impact of large natural shocks such as earthquakes, but causal evidence is still limited, in particular for Western Europe. By leveraging data at municipal level, this paper studies the effects on the resident population of a large earthquake that affected a wide area in Central Italy in 2016. The demographic decline that the area was already experiencing before the event significantly worsened afterwards. In order to identify the earthquake’s impact a diff-in-diff event-study model is applied, thereby testing whether the control group (made up of similar municipalities in terms of geo-morphological and predetermined urbanization characteristics) provides a comparable population pattern before the event. The results show that the earthquake significantly exacerbated the population decrease, with the impact widening over time and corresponding to almost two fifths of the reduction actually observed. Although statistically significant for the whole area, the impact was more intense for the municipalities that suffered the most damage. An increasing effect on the share of elderly population was also detected. The overall impact was mostly driven by a worsening in net internal migration.

Preliminary findings on the experimental investigation of the small-strain behaviour of Pizzoli silty sand

The dynamic properties of soils play a crucial role in solving many geotechnical problems with special attention to earthquake engineering. In particular, the small-strain soil behavior should be accurately reproduced in geotechnical modelling to allow quantifying of the earthquake-induced site response. If the determination of the small-strain shear modulus can be easily inferred from in-situ measurements of shear wave velocity, the small-strain damping ratio of soils is rarely obtained from in-situ tests and it is commonly defined through cyclic or dynamic laboratory tests. This paper describes preliminary findings obtained from a laboratory investigation performed to measure the small-strain dynamic properties of the silty sand deposit of the Pizzoli site (L’Aquila, Italy). Due to the remarkable seismic hazard of the considered area, demonstrated by several seismic events, such as recently the 2009 L’Aquila and the 2016-2017 Central Italy earthquakes, and in the past, the 2 February 1703 earthquake, a specific investigation program including boreholes, geophysical and geotechnical in-situ tests was carried out. Resonant column tests have been also performed at the Geotechnical Laboratory of the University of L’Aquila in both forced and free vibration modes. The interpretation of the results has been used to identify the small-strain shear modulus and damping ratio. The shear modulus as obtained from the laboratory has been compared with that obtained via the existing in-situ shear wave velocity measurements. In contrast, the damping ratio has been compared with the value estimated with a literature relationship proposed for soil deposits of Central Italy.

Using mobile phone data to map evacuation and displacement: a case study of the central Italy earthquake

Population displacement is one of the most common consequences of disasters, and it can profoundly affect communities and territories. However, gaining an accurate measure of the size of displacement in the days and weeks following a major disaster can be extremely difficult. This study uses aggregated Call Detail Records as an inexpensive and efficient technique to measure post-disaster displacement in four Italian regions affected by repeated earthquakes in 2016–2017. By comparing post-disaster mobile phone count with a forecast computed before the earthquake hit, we can compute an index of change in the presence of mobile phones (MPE). This measure, obtained thanks to advanced analytical techniques, provides a reliable indication of the effect of the earthquake in terms of immediate and medium-term displacement. We test this measure against census data and in combination with other datasets. Looking into available data on economic activities and requests for financial support to rebuild damaged buildings, we can explain MPE and identify significant factors affecting population displacement. It is possible to apply this innovative methodology to other disaster scenarios and use it by policymakers who want to understand the determinants of population displacement.

Statistical Seismic Analysis by b-Value and Occurrence Time of the Latest Earthquakes in Italy

The study reported in this paper concerns the temporal variation in the b-value of the Gutenberg–Richter frequency–magnitude law, applied to the earthquakes that struck Italy from 2009 to 2016 in the geographical areas of L’Aquila, the Emilia Region, and Amatrice–Norcia. Generally, the b-value varies from one region to another dependent on earthquake incidences. Higher values of this parameter are correlated to the occurrence of low-magnitude events spread over a wide geographical area. Conversely, a lower b-value may lead to the prediction of a major earthquake localized along a fault. In addition, it is observed that each seismic event has a different “occurrence time”, which is a key point in the statistical study of earthquakes. In particular, its results are absolutely different for each specific event, and may vary from years to months or even just a few hours. Hence, both short- and long-term precursor phenomena have to be examined. Accordingly, the b-value analysis has to be performed by choosing the best time windows to study the foreshock and aftershock activities.

Explaining population variation after the 2016 Central Italy earthquake using Call Data Records and Twitter

Explaining population variation after the 2016 Central Italy earthquake using Call Data Records and Twitter

The ShakeMap Atlas of Historical Earthquakes in Italy: Configuration and Validation

Abstract Italy has a long tradition of studies on the seismic history of the country and the neighboring areas. Several archives and databases dealing with historical earthquake data—primarily intensity data points—have been published and are constantly updated. Macroseismic fields of significant events are of foremost importance in assessing earthquake effects and for the evaluation of seismic hazards. Here, we adopt the U.S. Geological Survey (USGS)-ShakeMap software to calculate the maps of strong ground shaking (shakemaps) of 79 historical earthquakes with magnitude ≥6 that have occurred in Italy between 1117 and 1968 C.E. We use the macroseismic data published in the Italian Macroseismic Database (DBMI15). The shakemaps have been determined using two different configurations. The first adopts the virtual intensity prediction equations approach (VIPE; i.e., a combination of ground-motion models [GMMs] and ground-motion intensity conversion equations [GMICEs]; Bindi, Pacor, et al., 2011; Oliveti et al., 2022b). The second exploits the intensity prediction equations (IPE; Pasolini, Albarello, et al., 2008; Lolli et al., 2019). The VIPE configuration has been found to provide more accurate results after appraisal through a cross-validation analysis and has been applied for the generation of the ShakeMap Atlas. The resulting maps are published in the Istituto Nazionale di Geofisica e Vulcanologia (INGV) ShakeMap (see Data and Resources; Oliveti et al., 2023), and in the Italian Archive of Historical Earthquake Data (ASMI; see Data and Resources; Rovida et al., 2017) platforms.

Ground motion simulations of historical earthquakes: the case study of the Fabriano (1741, Mw = 6.1) and Camerino (1799, Mw = 6.1) earthquakes in central Italy

Ground motion simulations of historical earthquakes: the case study of the Fabriano (1741, Mw = 6.1) and Camerino (1799, Mw = 6.1) earthquakes in central Italy