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  • 1
    Publication Date: 2020-02-05
    Description: In this paper, we present a method for handling uncertainties in the determination of the source parameters of earthquakes from spectral data. We propose a robust framework for estimating earthquake source parameters and relative uncertainties, which are propagated down to the estimation of basic seismic parameters of interest such as the seismic moment, the moment magnitude, the source size and the static stress drop. In practice, we put together a Bayesian approach for model parameter estimation and a weighted statistical mixing of multiple solutions obtained from a network of instruments, providing a useful framework for extracting meaningful data from intrinsically uncertain data sets. The Bayesian approach used to estimate the source spectra parameters is a simple but powerful mechanism for non-linear model fitting, providing also the opportunity to naturally propagate uncertainties and to assess the quality and uniqueness of the solution. Another important added value of such an approach is the possibility of integrating information from the expertise of seismologists. Such data can be encoded in a prior state of information that is then updated with the information provided by seismological data. The performance of the proposed approach is demonstrated analysing data from the 1909 April 23 earthquake occurred near Benavente (Portugal).
    Description: Published
    Description: 691-701
    Description: 2T. Tettonica attiva
    Description: JCR Journal
    Description: open
    Keywords: Fourier analysis ; Probability distributions ; Earthquake source observations ; Seismicity and tectonics ; 04. Solid Earth::04.02. Exploration geophysics::04.02.06. Seismic methods
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2020-02-05
    Description: Eruption forecasting refers, in general, to the assessment of the occurrence probability of a given erup- tive event, whereas volcanic hazards are normally associated with the analysis of superficial and evident phenomena that usually accompany eruptions (e.g., lava, pyroclastic flows, tephra fall, lahars, etc.). Nevertheless, several hazards of volcanic origin may occur in noneruptive phases dur- ing unrest episodes. Among others, remarkable examples are gas emissions, phreatic explosions, ground deforma- tion, and seismic swarms. Many of such events may lead to significant damages, and for this reason, the “risk” associ- ated to unrest episodes could not be negligible with respect to eruption-related phenomena. Our main objective in this paper is to provide a quantitative framework to calculate probabilities of volcanic unrest. The mathematical frame- work proposed is based on the integration of stochastic mod- els based on the analysis of eruption occurrence catalogs into a Bayesian event tree scheme for eruption forecast- ing and volcanic hazard assessment. Indeed, such models are based on long-term eruption catalogs and in many cases allow a more consistent analysis of long-term tem- poral modulations of volcanic activity. The main result of this approach is twofold: first, it allows to make inferences about the probability of volcanic unrest; second, it allows to project the results of stochastic modeling of the eruptive history of a volcano toward the probabilistic assessment of volcanic hazards. To illustrate the performance of the pro- posed approach, we apply it to determine probabilities of unrest at Miyakejima volcano, Japan.
    Description: Published
    Description: 689
    Description: 4.3. TTC - Scenari di pericolosità vulcanica
    Description: JCR Journal
    Description: open
    Keywords: Volcanic unrest ; Eruption forecasting ; Bayesian event tree ; Stochastic models ; Miyakejima volcano ; 04. Solid Earth::04.08. Volcanology::04.08.08. Volcanic risk
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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