Recorded displacements in a landslide slope due to regional and teleseismic earthquakes

Regional and teleseismic earthquakes can induce displacements along joints in a landslideinvolved rocky slope in Central Italy. The rarity of these effects is due to specific physical properties of the seismic signals associated with: (i) the energy content, (ii) the distribution of relative energy and peak of ground acceleration related to the ground motion components and (iii) the spectral amplitude distribution in the frequency domain; these properties allow the triggering earthquakes to be distinguished from the others. The observed effects are relevant when compared to the direction of the landslide movement and the dimensions of the involved rock mass volume. The landslide movement is less constrained in the direction parallel to the dip of the slope and the landslide dimensions are associated with characteristic periods that control the landslide deformational response in relation to the spectral content of the ground motion. The earthquake-induced displacements are significant because they have the same order of magnitude as the average annual cumulative displacement based on a decade of strain measurements within the slope

Earthquake-induced ground failures in Italy from a reviewed database

Abstract. A database (Italian acronym CEDIT) of earthquake-induced ground failures in Italy is presented, and the related content is analysed. The catalogue collects data regarding landslides, liquefaction, ground cracks, surface faulting and ground changes triggered by earthquakes of Mercalli epicentral intensity 8 or greater that occurred in the last millennium in Italy. As of January 2013, the CEDIT database has been available online for public use (http://www.ceri.uniroma1.it/cn/gis.jsp ) and is presently hosted by the website of the Research Centre for Geological Risks (CERI) of the Sapienza University of Rome. Summary statistics of the database content indicate that 14% of the Italian municipalities have experienced at least one earthquake-induced ground failure and that landslides are the most common ground effects (approximately 45%), followed by ground cracks (32%) and liquefaction (18%). The relationships between ground effects and earthquake parameters such as seismic source energy (earthquake magnitude and epicentral intensity), local conditions (site intensity) and source-to-site distances are also analysed. The analysis indicates that liquefaction, surface faulting and ground changes are much more dependent on the earthquake source energy (i.e. magnitude) than landslides and ground cracks. In contrast, the latter effects are triggered at lower site intensities and greater epicentral distances than the other environmental effects

New statistical RI index allow to better track the dynamics of COVID-19 outbreak in Italy

COVID-19 pandemic in Italy displayed a spatial distribution that made the tracking of its time course quite difficult. The most relevant anomaly was the marked spatial heterogeneity of COVID-19 diffusion. Lombardia region accounted for around 60% of fatal cases (while hosting 15% of Italian population). Moreover, 86% of fatalities concentrated in four Northern Italy regions. The ‘explosive’ outbreak of COVID-19 in Lombardia at the very beginning of pandemic fatally biased the R-like statistics routinely used to control the disease dynamics. To (at least partially) overcome this bias, we propose a new index RI = dH/dI (daily derivative ratio of H and I, given H = Healed and I = Infected), corresponding to the ratio between healed and infected patients relative daily changes. The proposed index is less flawed than R by the uncertainty related to the estimated number of infected persons and allows to follow (and possibly forecast) epidemic dynamics in a largely model-independent way. To analyze the dynamics of the epidemic, starting from the beginning of the virus spreading—when data are insufficient to make an estimate by adopting SIR model—a "sigmoidal family with delay" logistic model was introduced. That approach allowed in estimating the epidemic peak using the few data gathered even before mid-March. Based on this analysis, the peak was correctly predicted to occur by end of April. Analytical methodology of the dynamics of the epidemic we are proposing herein aims to forecast the time and intensity of the epidemic peak (forward prediction), while allowing identifying the (more likely) beginning of the epidemic (backward prediction). In addition, we established a relationship between hospitalization in intensive care units (ICU) versus deaths daily rates by avoiding the necessity to rely on precise estimates of the infected fraction of the population The joint evolution of the above parameters over time allows for a trustworthy and unbiased estimation of the dynamics of the epidemic, allowing us to clearly detect the qualitatively different character of the ‘so-called’ second wave with respect to the previous epidemic peak

Earthquake-reactivated landslide scenarios in Southern Italy based on spectral-matching input analysis

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