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The use of Artificial Neural Network (ANN) approaches has gained a significant role over the last decade in the field of predicting the distribution of effects triggered by natural forcing, this being particularly relevant for the development of adequate risk mitigation strategies. Among the most critical features of these approaches, there are the accurate geolocation of the available data as well as their numerosity and spatial distribution. The use of an ANN has never been tested at a national scale in Italy, especially in estimating earthquake-triggered landslides susceptibility. Based on the statistics deductible from the most up-to-date national inventory of earthquake-induced ground effects, i.e. the CEDIT catalogue, it results that over 56\% of the ground effects triggered by earthquakes in Italy are represented by landslides. Therefore, a landslide dataset with such high geolocation precision was suitable to evaluate the efficiency of an ANN to explain the distribution of landslides over the Italian territory. An ex-post evaluation of the ANN-based susceptibility model was also performed, using a sub-dataset of historical data with lower geolocation precision. The ANN training highly performed in terms of spatial prediction, by partitioning the Italian landscape into slope units. The obtained results returned a distribution of potentially unstable slope units with maximum concentrations primarily distributed in the central-northern Apennines and secondarily in the southern Apennines. Moreover, the Alpine sector clearly appeared to be divided into two areas, a western one with relatively low susceptibility to earthquake-triggered landslides and the eastern sector with a higher susceptibility. However, the scale of the analysis carried out to train the ANN does not allow it to be applied for planning purposes or for seismic microzonation studies, for which training on a smaller spatial scale will be required.

Landslides are among the most frequent secondary effects related to seismic events. The prediction of the expected displacements of landslides activated by seismic shaking (1st-time failures and reactivated landslides) is therefore a substantial feature for the hazard assessment in high seismicity regions. Several databases collecting geological and geometrical information on worldwide landslides events are available in literature. This study presents the result of statistical analyses on morphometric, topographic and geotechnical parameters extracted from existing landslide databases (Domej et al., 2020; Martino et al., 2019; Tanyas et al., 2019). The aim is to define a procedure to generate 2D step-like-slope landslide models representative of the most common landslides in terms of failure mechanism (divided into two main categories: purely rotational and translational landslides), volume, and geotechnical properties. Rock falls and toppling, flow-like landslides and deep-seated landslides were excluded from the initial dataset, because they are associated with peculiar physical processes during the failure and the propagation. The performed statistical analysis allowed to identify the most frequent values of depth/length ratios, volume and slope angle, from which other geometrical measurements were analytically derived. In addition, various landslide locations along the slope were considered to cover most of the real cases. This resulted in 36 different landslides/slopes shapes. Landslides dynamic/geotechnical parameters (shear wave velocity, density, strength) were selected to be consistent with those inferred for rocks, cohesive soils and granular soils by statistical analysis. The representativeness of the inferred models is assessed by comparing the theoretical geometries with the real ones detected in the Campotosto Basin (Central Apennines, Italy), a high seismicity area very close to the Amatrice village, which was strongly hit by the recent 2016-2017 (M 6.5) Central Italy seismic sequence as well as by the 2009 (M 5.9) L’Aquila earthquake. The simplified landslide models represent the first part of a major study on the prediction of seismically induced landslide displacements. The aim is to improve the existing Newmark’s approach–based PARSIFAL (Probabilistic Approach to pRovide Scenarios of earthquake-Induced slope FAiLures) method (Martino et al., 2019) to assess the earthquake-induced displacements at a regional scale, by introducing corrective factors derived from parametric dynamic numerical simulations on the simplified geometries; such factors should incorporate some aspects of the complex seismic waves/landslides slopes interaction. Such a procedure will allow to overcome the Newmark’s method limitations and to extend the advantages of the numerical analyses, the use of which is generally limited to studies at slope scale, over larger areas.

Hundreds of landslides were triggered by the mainshocks (up to Mw 6.5) that occurred in 2016 in Central Italy during the seismic sequence that originated in the Apennine and ended in January 2017. These landslides were studied via field-based investigation and remote sensing techniques during the weeks immediately after the mainshocks occurred. EarthQuake-triggered Landslides (EQtLs) mostly consisted of rockfalls and rockslides. The spatial distribution of the examined EQtLs with respect to the epicentres of the main shocks resulted in very good agreement with the available empirical curves of maximum distance vs. magnitude. Based on the collected dataset, approximately 70% of the landslides impacted transportation routes (national, provincial and secondary roads linking towns and mountain villages) since they principally detached from road cuts. The landslides caused traffic interruption, and some delayed rescue vehicles from reaching the zones most damaged by earthquakes; moreover, some landslides caused the temporary isolation of several localities in the epicentre area. Even if it seems obvious that road cuts favour slope failure under shaking conditions, the dataset reported here is the first one for Italy where such an effect is quantified. Moreover, a statistical analysis was conducted to explore the relationships between the spatial distribution of EQtLs and some selected causative factors, including both natural (i.e., earthquake and terrain) and anthropogenic factors (i.e., presence of roads and trackways). Among the considered combinations of causative factors (both natural and anthropogenic), this study demonstrates that the occurrence of the uphill road cuts at the bottom of deep incised V-shaped valleys strongly influenced the spatial clustering of the EQtL triggered in 2016 in Central Italy.

On August 16th, 2018, an Mw 5.1 earthquake struck the Molise region (central Italy), inducing 84 earthquake-triggered landslides that involved soil covers of clayey materials and flysch on gently-dip slopes predominantly. To quantify the spatio-temporal landslide activity in the months immediately after the earthquake, a Differential SAR Interferometry (DInSAR) analysis was carried out in a time span comprising two years before the earthquake and one followed, recognising both first-time and reactivated landslides. The results showed a clear increase in landslide activity following the low magnitude earthquake occurrence with respect to the one recorded in the same months of the previous years. Several coherent landslides (earth slides and earth flows) were observed following the seasonally recurrent rainfall events. Such an increase was observed for both reactivations and first-time landslides, showing a decrease of inactivity period as well as activity over wider periods. Furthermore, spatial density distribution of the landslides was investigated in the post-seismic time along transepts perpendicular and parallel to the direction of the tectonic element responsible for the seismic event, respectively. An asymmetrical distribution was deduced parallel to the fault strike with the higher number of landslides located inside the compressional sector according to a strike-slip faulting mechanism.

Rock mass damaging has become a topic of great interest in the engineering-geology research community during the last decades as it can significantly influence slopes stability. In this sense, the study of mechanics and dynamics of jointed rock masses represents a challenge because it will allow to better understand how external continuous and transient stressors can influence the short- to long-term stability controlling their pre-failure behavior. Consequently, the detection of permanent changes in physical and mechanical parameters, due to periodic or transient stressors, is an important target to mitigate the related geological risk as it can potentially lead rock masses to failure, especially when infrastructures and natural or cultural heritages are exposed elements. In this framework, the Acuto field laboratory (Central Italy) has been designed and implemented in 2016 within an abandoned quarry by employing an integrated geotechnical and geophysical monitoring system, with the aim of investigating how natural and anthropic conditioning factors could lead fractured rock masses to failure. The integrated monitoring system, which is installed on a potentially unstable 20-m3 jointed rock block, is composed of several strain devices (i.e., strain gauges -SG- and jointmeters -JM-), one fully equipped weather station, one rock thermometer, eight high-sensitivity microseismic uniaxial accelerometers and optical and InfraRed Thermal cameras. The acquisition of long-term monitoring time-series, coupling multimethodological approaches, allowed to establish cause-to-effect relationships among different environmental stressors and induced strain effects, highlighting the continuous action of thermal stresses on rock mass deformations both at the daily and seasonal timescales. In fact, while the analysis of thermal and strain monitoring data allowed to characterize the cyclic contraction and relaxation response of major rock fractures and microcracks to temperature fluctuations, the microseismic monitoring array was able to detect during thermal transient (i.e., freezing conditions) the occurrence of microseismic emissions potentially related to the genesis or progressive growth of pre-existing cracks.Starting from 2018, experimental activities at the Acuto field lab are supported by the “Dipartimento di Eccellenza” project of the Italian Ministry of Education Universities and Research funds attributed to the Department of Earth Sciences of the University of Rome “Sapienza”. In this framework, the Acuto filed laboratory will undergo a structural upgrade that will be aimed at the investigation of two new sectors of the abandoned quarry. These new sectors will be instrumented with innovative thermal profiles probe, fiber Brag grating sensors and traditional SG and JM for detailed stress-strain monitoring, acoustic emission sensors and high-frequency and low-frequency geophones for ambient seismic noise monitoring and microseismic events detection as well as accelerometers for evaluating the rock mass response in the case of seismic shaking. The main goal of such an improvement will be both technical and methodological, and will shed light on the application of integrated geophysical and geotechnical monitoring approaches in investigating the multiscale rock mass damaging process as well as the detection of rock mass failure precursors by using non-conventional combinations and configurations of geotechnical and broad-band geophysical devices.

Geothermal and volcanic systems are prone to gravity-induced slope instability at different scales. Endogenous magmatic, hydrothermal and seismic forcings can significantly modify rock mass rheology and perturb the local stress field and gravitational equilibrium, inducing shallow or slope-scale processes. The island of Ischia, which is part of the Phlegrean Volcanic District (Italy), is a remarkable example of this kind of complex interacting system. This study focuses on monitoring the hydrothermal system located beneath the ongoing slope-scale deformation, which involves Mt Nuovo (the western part of Mt Epomeo) and is a complementary effect of the resurgence of an ancient caldera. Debris and rock avalanches have affected the slopes of this volcanic island, in response to the renewal of volcanic activity and caldera resurgence. Large parts of the corresponding mass-wasting deposits overlay the most active areas of the Ischia hydrothermal system, where ongoing slope-scale gravity-driven deformation owing to a mass rock creep (MRC) process is still evolving. To investigate possible relations between the perturbing shallow hydrothermal system and the MRC process, thermal monitoring of selected groups of fumarolic emissions located in several portions of the deforming sector has been carried out since 2008 on a monthly basis by means of direct (thermal probes) and remote sensing (IR-thermography) techniques. Thermal monitoring of specific fumaroles reveals a peculiar seasonal trend characterized by a delayed inverse correlation with rainy periods and a short-term pulsating response to dry stages. The fumaroles also appear spatially correlated to the presence of MRC-related structures involving volcanic slopes. According to the measured thermal data, a conceptual model of the thermal interactions within the Mt Nuovo slope is provided, framing the potential role of thermal actions in accelerating the deformation process. In this view, possible chain effects, owing to magmatic or hydrothermal renovation, are depicted, delineating the most severe multihazard scenario consisting of an accelerating evolution of the MRC process towards paroxysmal collapse.

This study reports a comparative analysis of the environmental conditions and micro-seismicity recorded on a rock wall resulting from an intense meteorological event. The findings are focused on a quarry wall located in the Acuto Field Laboratory (Central Italy), where multi-parametric environmental monitoring is operating and an Artificial intelligence Camera Prototype has been placed to detect rock falls reaching a railway target. Six accelerometers were installed to detect micro-seismic events caused by the expected strong thermal transient caused by the Buran storm on February 2018. Within a few hours, a steep decrease in the average air and rock mass temperature down to 8 °C was recorded, and −4 °C and −8 °C were reached for the rock and air temperatures, respectively. A total of 103 micro-seismic events were analysed with respect to both rainfall and thermal forcing: while no correlation with rainfall was reported, the steep thermal transient was responsible for the strain effect that occurred during the heating phase of the rock mass following the Buran storm. An elastic deformation event with a maximum daily amplitude of 165 μ strain was recorded by the strain gages installed on the mm-joints due to the rock heating and cooling caused by the variation in temperature. The collected evidences show the relevance of short thermal transients in modifying stress conditions within rock masses and their relationship to a peculiar micro-seismic response. The main outcomes established the key role played by integrated monitoring systems to better understand the relationship between vibrational behaviour and environmental forcings in terms of understanding the precursors to rock failure.

During the last few years, several approaches have been proposed to improve early warning systems for managing geological risk due to landslides, where important infrastructures (such as railways, highways, pipelines, and aqueducts) are exposed elements. In this regard, an Artificial intelligence Camera Prototype (AiCP) for real-time monitoring has been integrated in a multisensor monitoring system devoted to rock fall detection. An abandoned limestone quarry was chosen at Acuto (central Italy) as test-site for verifying the reliability of the integrated monitoring system. A portion of jointed rock mass, with dimensions suitable for optical monitoring, was instrumented by extensometers. One meter of railway track was used as a target for fallen blocks and a weather station was installed nearby. Main goals of the test were (i) evaluating the reliability of the AiCP and (ii) detecting rock blocks that reach the railway track by the AiCP. At this aim, several experiments were carried out by throwing rock blocks over the railway track. During these experiments, the AiCP detected the blocks and automatically transmitted an alarm signal.

In the last few years, several approaches and methods have been proposed to improve early warning systems for managing risks due to rapid slope failures where important infrastructures are the main exposed elements. To this aim, a multi-sensor monitoring system has been installed in an abandoned quarry at Acuto (central Italy) to realise a natural-scale test site for detecting rock-falls from a cliff slope. The installed multi-sensor monitoring system consists of: i) two weather stations; ii) optical cam (Smart Camera) connected to an Artificial Intelligence (AI) system; iii) stress- strain geotechnical system; iv) seismic monitoring device and nano-seismic array for detecting microseismic events on the cliff slope. The main objective of the experiment at this test site is to investigate precursors of rock mass failures by coupling remote and local sensors. The integrated monitoring system is devoted to record strain rates of rock mass joints, capturing their variations as an effect of forcing actions, which are the temperature, the rainfalls and the wind velocity and direction. The preliminary tests demonstrate that the data analysis methods allowed the identification of external destabilizing actions responsible for strain effects on rock joints. More in particular, it was observed that the temperature variations play a significant role for detectable strains of rock mass joints. The preliminary results obtained so far encourage further experiments. © 2017 The Authors.

Mechanical response of rock masses to the periodical fluctuation of surface temperatures is a relevant topic to be focused on for the comprehension of short- to long-term stability of rock slopes continuously stressed by slight yet periodical actions. To better understand how preparatory factors can lead rock masses toward failure, thermal and strain monitoring activities are ongoing in a selected quarry wall, where an experimental test-site was implemented on a jointed rock block. The role of pervasive joints in perturbing the heating-cooling process of the rock mass and their related effects was already output by direct and remote monitoring. For these purposes, FDM numerical modelling was focused on the comprehension and simulation of induced mechanical effects due to cyclical thermal forcings over a simplified 2D half-space. Therefore, the role of rock mass joints on both heat propagation and resulting thermo-mechanical effects was analysed, basing on monitoring data, field experiments and numerical modelling. Numerical results output the role of periodic daily, annual and compound thermal input in inducing irreversible deformation along joints under different rock mass jointing configuration, as a function of the intrinsic period of thermal input and joint attitude. Temperature distribution across joints was also analysed as a possible constraining effect for time and space distribution of yielding. A sensitivity analysis of heat propagation conditions was performed in order to infer the role of joint sets on induced thermo-mechanical strains at the rock block scale. A non-negligible influence on surficial as well as deeper portions of the rock mass was observed, highlighting how near-surface temperature fluctuations can drive the long-term evolution of rock block conditions towards failure.

The use of Mt. Epomeo Green Tuff (MEGT) as a building stone is widespread on Ischia Island (Italy). We assess here the fire resistance of MEGT by thermally stressing samples to temperatures up to 1000 °C. Porosity and uniaxial compressive strength increase and decrease from 44% and 4.5 MPa at ambient temperature to 48% and 1.5 MPa following exposure to 1000 °C, respectively. Complementary thermogravimetric and X-ray powder diffraction analyses, experiments that monitor acoustic emissions during heating/cooling, and microstructural observations highlight that these changes are the result of thermal microcracks, formed due to the breakdown of zeolites and clays (MEGT contains 35 wt.% analcime, 15 wt.% smectite, and 3 wt.% illite) at high temperature. Although the stability of structures built from MEGT will be jeopardised at high temperature, a very low thermal diffusivity requires that fires must burn for many hours to compromise the strength of a typical dimension stone: tuffs are tough in the event of fire.

This paper illustrates the design of a multi-sensor monitoring system located in Acuto (Frosinone - Central Italy) where an abandoned quarry was devoted to experimental test-site. The test-site is managed by the Research Centre for the Geological Risks (CERI) and is focused on testing and comparing multi-sensing and multi-parametric remote techniques for early warning, applied to rock falls with strategic infrastructure targets. The final aim of this testing is to process the data collected by techniques integrated by a network of conventional and smart sensors, following observational-bases and statistical approaches. The installed multi-sensor monitoring system consists in 2 control units for weather monitoring, 1 thermometer for the rocky mass temperature, 10 strain-gauges for rock mass joints, 2 optical devices (Smart Cameras) and 1 nanoseismic monitoring network.

The Peschiera Springs slope (RI), which hosts the drainage plant of the Rome's aqueduct, is affected by a gravitational slope deformation process, that is responsible for a rock-mass lateral spreading, associated to several landforms including sinkholes, subvertical scarps and trenches. An experiment, based on an innovative method of monitoring, was carried out to record microseismic events generated by underground instabilities such as failures and collapses. At this aim a SNS (Seismic Navigation System) array was installed during the year 2013 inside a the tunnel of the drainage plant in order to carry out a continuous monitoring. The nanoseismic monitoring, allowed to record 37 microseismic events. The seismic records were managed by NanoseismicSuite software that allowed to identify and characterize two different typologies of events: 19 underground collapses and 18 underground failures. The locations of these events are in good agreement with the evolutionary geological model of the ongoing gravitational slope deformation, i.e. with the spatial distribution of the main trenches and scarps on the slope. © Società Geologica Italiana, Roma 2015.