The creation of hazard maps relative to volcanic phenomena requires taking into account the intrinsic complexity and variability of eruptions. Here we present an example of how HPC can allow producing a high resolution multi-source probabilistic hazard assessment due to tephra fallout over a domain covering Southern Italy. The three active volcanoes in the Neapolitan area, Somma-Vesuvius, Campi Flegrei and Ischia, were considered as volcanic sources. For each one, we explored three explosive size classes (Small, Medium and Large) for Somma Vesuvius and Campi Flegrei, and one explosive size class (Large) for Ischia. For each size class, we performed 1500 numerical simulations of ash dispersion (total of 10500) using the Fall3D (V8.0) model over a computational domain covering Southern Italy with a 0.03° ? 0.03° (~3 km ? 3 km) resolution. Within each size class, the eruptive parameters have been randomly sampled from well-suited probability distributions and with different meteorological conditions, obtained by randomly sampling a day between 1990 and 2020 and retrieving the relative data from the ECMWF ERA5 database. This allowed exploring the intra-class variability and to quantify aleatoric uncertainty. The results of these simulations have been post-processed with a statistical approach by assigning a weight to each eruption (based on its eruption magnitude) and the annual eruption rate of each size class. For the case of Campi Flegrei, the variability in the eruptive vent position has also been explored by constructing a grid of possible vent locations with different spatial probability. By merging the results obtained for each source and size class we produced a portfolio of hazard maps showing the expected mean annual frequency of overcoming selected thresholds in ground tephra load. A disaggregation analysis has also been performed in order to understand which particular source and/or size class had the greater impact on a particular area. The completion of this work, considering both numerical simulations and the statistical elaboration of the results has required a total of more than 5000 core hours and the processing of more than 2TB of data, an effort that wouldn't have been possible without the access to high level HPC resources.

In recent decades, one of the most interesting innovations has undoubtedly been the application of resilience principles to the study and mitigation of seismic risk. However, although new rigorous mathematical models have become available in the context of seismic resilience assessment, their applications to real case studies focus on a local scale, or even single structures. Consequently, new models and procedures are absolutely necessary to adopt resilience measurements in the formulation of mitigation strategies on a national or subnational scale. Given the crucial role of residential buildings in the global resilience of Italian cities against major earthquakes, a new framework for large-scale applications is proposed to roughly measure the seismic resilience of communities through the integration of an empirical recovery function based on the reconstruction process of housing systems in the aftermath of the 2012 Northern Italy Earthquake. As a first attempt, the framework is applied to housing systems in the southern regions of Italy by modelling their physical damage with vulnerability curves defined on the basis of macroseismic approaches. The main results are presented and discussed in terms of average functionality levels over time in order to compare and understand the recovery capacity of the considered housing systems.

In 2009, after declaring a state of emergency for the Central Archaeological Area of Rome following the adverse weather conditions of November and December 2008, the Government Commissioner and the Italian Department of Civil Protection (DPC) assigned the Institute of Environmental Geology and Geoengineering (IGAG) of the Italian National Research Council (CNR) to evaluate the geohazard level affecting the Central Archaeological Area of Rome (i.e., Palatine Hill, Roman Forum, and Colosseum). Research activities started up in February 2009 and were concluded in February 2011, with the valued contribution of the Archaeological Superintendence.

Numerical simulations of seismic site response require the characterization of the nonlinear behaviour of shallow subsoil. When extensive evaluations are of concern, as in the case of seismic microzonation studies, funding problems prevent from the systematic use of laboratory tests to provide detailed evaluations. For this purpose, 485 shear modulus reduction, G\G0(?) and damping ratio, D(?) curves were collected from multiple literature sources available in Italy. Each curve was associated with the related engineering geological units considered in seismic microzonation studies. A statistical analysis of the data was carried out with the aim of shedding light on the significant difference between the laboratory classification of samples and the macroscopic/engineering geological one, provided during seismic microzonation studies. Since the engineering geological classification plays a prominent role in extensive site response evaluations, the outcomes of the present work may be of help at least when preliminary seismic response estimates are of concern. The dataset provides reference information that can serve as key data for large-scale hazard assessments worldwide.

Nowadays, modeling of tephra fallout hazard is coupled with probabilistic analysis that takes into account the natural variability of the volcanic phenomena in terms of eruption probability, eruption sizes, vent position, and meteorological conditions. In this framework, we present a prototypal methodology to carry out the long-term tephra fallout hazard assessment in southern Italy from the active Neapolitan volcanoes: Somma-Vesuvius, Campi Flegrei, and Ischia. The FALL3D model (v.8.0) has been used to run thousands of numerical simulations (1500 per eruption size class), considering the ECMWF ERA5 meteorological dataset over the last 30 years. The output in terms of tephra ground load has been processed within a new workflow for large-scale, high-resolution volcanic hazard assessment, relying on a Bayesian procedure, in order to provide the mean annual frequency with which the tephra load at the ground exceeds given critical thresholds at a target site within a 50-year exposure time. Our results are expressed in terms of absolute mean hazard maps considering different levels of aggregation, from the impact of each volcanic source and eruption size class to the quantification of the total hazard. This work provides, for the first time, a multi-volcano probabilistic hazard assessment posed by tephra fallout, comparable with those used for seismic phenomena and other natural disasters. This methodology can be applied to any other volcanic areas or over different exposure times, allowing researchers to account for the eruptive history of the target volcanoes that, when available, could include the occurrence of less frequent large eruptions, representing critical elements for risk evaluations.

In the last years, an increasing attention has been devoted to seismically induced site effects, particularly punctual and linear liquefaction ones. The large availability of geotechnical investigation publicly disclosed by institutional and scientific communities, combined with the evidence collected from previous seismic events, represents an opportunity for liquefaction probability prediction through machine learning approaches. In particular, the machine learning ML regression algorithm "Ensemble Bagged Tree" allows to predict the probability of liquefaction occurrence. The geotechnical investigations provided by Geyin et al., 2021 for Canterbury (New Zealand) has been used as learning site since it is one of the most comprehensive geotechnical datasets freely available. This model is based on the correlation of liquefaction occurrence with the main features controlling the phenomenon triggering. It proved to be capable to predict the occurrence of liquefaction with good accuracy in training phase. This trained model will be tested to predict liquefaction probability for national and international case studies.

Il presente documento contiene una proposta operativa di piattaforma attiva h24 in sala GIS della sede CNR IGAG di Montelibretti che produrrebbe in tempo quasi reale e in maniera totalmente automatizzata, mappe interattive da distribuire a DPC. L'attivazione della piattaforma avviene sulla base del sito RAN DPC (https://ran.protezionecivile.it/IT/index.php) per magnitudo locale superiore a 4.

In questo documento viene descritta una proposta di costituzione di un gruppo operativo CNR IGAG denominato RISE (Rapid Intervention for Seismic Emergencies) per l'intervento in emergenza in caso di evento sismico rilevante. Il gruppo opererà a supporto della Funzione Tecnica della Di.Coma.C. Nel report vengono inoltre descritti gli obiettivi che il gruppo dovrà perseguire e le risorse umane e strumentali messe a disposizione per affrontare le tematiche presenti in fase emergenziale.

Questo report presenta le metodologie per la valutazione della pericolosità sismica e vulcanica in prospettiva multi-hazard

Quest report presenta lo stato dell'arte, le criticità e le proposte per sviluppare metodologie di analisi multi-hazard (sismico e vulcanico), ai fini della valutazione dell'operatività del sistema strutturale per la gestione dell'emergenza in Ambiti Territoriali Ottimali.

L'obiettivo del WP2 è la realizzazione di mappe di scuotimento sismico ad alta risoluzione con metodologia machine learning utilizzando la banca dati nazionale degli studi di microzonazione sismica e la banca dati della rete accelerometrica. Attraverso questa metodologia si realizzano le mappe di scenario e di predizione delle misure di intensità sismica da utilizzare a seguito di evento sismico e quindi di supporto alle squadre che si attivano in emergenza. In questo report si descrive il modello machine learning per la predizione dello scuotimento sismico.

L'obiettivo del WP2 è la realizzazione di mappe di scuotimento sismico ad alta risoluzione con metodologia machine learning. I modelli di machine learning verranno alimentati da dati proveniente da i) la banca dati nazionale degli studi di microzonazione sismica; ii)la banca dati della rete accelerometrica. I dati di input, di seguito definiti predittori, saranno omogeneizzati secondo uno standard condiviso e costituiranno il dataset di allenamento dei modelli di predizione. Attraverso questa metodologia si realizzano le mappe di scenario e di predizione delle misure di intensità sismica da utilizzare nelle prime fasi successive ad un evento sismico. In questo report si descrive il dataset dei predittori che viene rilasciato al fine di realizzare il modello machine learning per la predizione dello scuotimento sismico.

L'obiettivo del presente report è: o Aggiornamento della mappa Vs30 nazionale necessaria per generare mappe predittive di scuotimento sismico; o Mappe nazionali dei Fattori di Amplificazione a scala nazionale.

The peak roof drift ratio is one of the most important engineering parameters to describe the expected seismic damage in a building. A predictive model of the drift ratio was developed using a machine learning approach (Gaussian process regression model) on a dataset of approximately 11,800 records from 34 monitored buildings in Japan. Four predictors for ground motion and three predictors for building vulnerability are used in the machinelearning modelling. The residual analysis shows a reduction of 50% compared to the state of the art. The Gaussian process regression model is applied in a second analysis on an original dataset of approximately 4,500 records for 127 monitored buildings in Italy. A satisfactory comparison emerges by comparing the drift ratio prediction map with the observed damage pattern produced by satellite imagery for a test site in central Italy after the 2009 earthquake. The drift ratio map plays an important role in the simulation of an earthquake scenario at regional scale, which is needed by Civil Protection for emergency planning and management activities.

The extensive evaluation of the impact of local seismo-stratigraphic configurations on seismic ground motion presents significant challenges due to the necessity of considering the combined effects of uncertainty and smallscale lateral variability of the relevant parameters. To effectively explore these sources of uncertainty, a new Python-based computer program is proposed for one-dimensional seismic site response simulations, adopting the equivalent linear viscoelastic approach in the frequency domain. With respect to existing software, the code introduces new pre- and post-processing features, which also meet the specific requirements of seismic microzonation studies. Within the code, the complete spectrum of uncertainties related to local seismo-stratigraphic configurations, including lithotype successions, layer thicknesses, and seismic and geotechnical properties for the considered lithotypes, is managed by considering user-defined constraints and statistical properties of the relevant parameters. Additionally, a batch approach is offered, enabling the application of the procedure to an unlimited number of different scenarios. To demonstrate the potentiality of the proposed code, a comprehensive set of 90,000 local seismic site response analyses was conducted, showing a clear correlation between the amplification factors, the mean shear wave velocity in the upper 30 m, the fundamental frequency of the deposit and the depth to the seismic bedrock.

In the aftermath of the 2009 L'Aquila earthquake, the Italian government issued significant measures to stimulate seismic prevention in its territories. To this end, billions of euros were distributed to the twenty Italian Regions in proportion to their seismic risk and according to the requests of public administrators and private taxpayers. However, the distribution of resources among the Regions took place without considering important aspects of resilience such as the emergency management and recovery, as well as the integration and social cohesion of populations. This article proposes a framework to identify a large-scale prioritisation of the Italian Territorial Contexts (TCs) recently defined for civil protection purposes in order to allocate economic resources among Regions in accordance with the resilience deficiencies of their communities. The proposal is based on known methods of multi-criteria analysis that are commonly used in the engineering field, and as a first application, it has been applied to all TCs of five Regions of southern Italy. The results of this study may be useful for policy makers to develop a national resilience policy.

Studio di microzonazione sismica di livello 3 e della Condizione Limite per l'Emergenza (CLE) del Comune di Terre del Reno

Rapporto finale delle attività svolte nell'ambito dell'ACCORDO DI COLLABORAZIONE TRA REGIONE EMILIA-ROMAGNA, AMMINISTRAZIONE COMUNALE DI TERRE DEL RENO, CONSIGLIO NAZIONALE DELLE RICERCHE - ISTITUTO DI GEOLOGIA AMBIENTALE E GEOINGEGNERIA, UNIVERSITÀ DEGLI STUDI DI CASSINO E DEL LAZIO MERIDIONALE - DIPARTIMENTO DI INGEGNERIA CIVILE E MECCANICA FINALIZZATO A DEFINIRE UNA STRATEGIA MULTILIVELLO PER VALUTARE IL RISCHIO DA LIQUEFAZIONE IN PRESENZA DI ARGINI E SITUAZIONI GEOLOGICHE E MORFOLOGICHE COMPLESSE (ATTUAZIONE DELL'ARTICOLO 11 DELLA LEGGE 24 GIUGNO 2099, N. 77. STUDIO REALIZZATO CON CONTRIBUTO OCPDC 675/2020 - DGR 1238/2020 (DD 21384/2020)).

The sequestration of sediment deposited on alluvial floodplains may release an identifiable fingerprint on sediment composition and texture. In this regard, soil micromorphology, can be used to better discriminate the role of autocyclic and long-term factors in controlling the environmental condition of soil formation when framed into Quaternary stratigraphic record. In this study, we report a high-resolution micromorphological characterization of the Tiber River floodplain soils for a better understanding of the soil processes related to changes in water table, biological activity, weathering, and accommodation space and integrate soil micromorphology with sequence stratigraphy. Petrographic and micromorphological features from a borehole advanced 60 m into the Tiber channel belt and floodplain, document incipient pedogenetic modifications across stratigraphic markers evidenced by faunal and plant activity, accumulation of peat, and typified by precipitation of heavy metals, iron oxides and secondary carbonates. All these features developed in correspondence of surfaces of stratigraphic significance and reveal depositional features and post-depositional modifications associated with different environmental changes. These observations tell us about a specific history case of incipient soils formation in the Tiber Depositional Sequence but may serve as a model to reconstruct the stratigraphic evolution of ancient relict soils in similar alluvial settings. This work demonstrates that a combination between sedimentological and stratigraphic observations and soil micromorphology can be critical to supplement field observations and determine the relative effect of pedogenic and depositional processes on the organization, composition and texture, and geotechnical properties of floodplain in urban areas.

The current configuration of the archeological area of Rome and the Palatin Hill, lends well to describing the relationship between a city and the natural hazards that threaten itself. The monuments, the built structures, and the archeological remains with the relative foundation soils, both man-made and natural, are here depicted on geological section based on the most recent geo-archeological studies to visualize the conditions such as: the morphology and the buried morpho-stratigraphic structure, wich expert acconditioning on the city development on natural risks factors (effects of amplification of seismic waves, flood phenomena, slope instability).