Ground motion models for the new seismic hazard model of Italy (MPS19): selection for active shallow crustal regions and subduction zones

Lanzano, Giovanni; Luzi, Lucia; Marzocchi, Warner; Pacor, Francesca; Meletti, Carlo; Marzocchi, Warner; Rotondi, R.; Varini, Elisa

doi:10.1007/s10518-020-00850-y

Cited by 37 publications

(30 citation statements)

References 64 publications

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“…This section summarizes the activity of the selection and weight of GMMs for MPS19, that has been exhaustively treated in Lanzano et al [2020]. The candidate GMMs potentially suitable for Italy have to satisfy the following general conditions: i) representation of the characteristics of ground motion for whole Italian territory; ii) calibration for the engineering bedrock (i.e.…”

Section: The Gmmsmentioning

confidence: 99%

“…A preliminary selection of candidate GMMs is performed over nearly one thousand models published in scientific literature, which are listed in Douglas [2019]. In order to reduce the number of available models, we adopt the rejecting criteria by Cotton et al [2006] and Bommer et al [2010], and then add further projectspecific criteria to fulfil the requirements of MPS19 listed above [see Lanzano et al, 2020 1 The GMMs coefficients up to 4 s by ITA10 and BND14 have been provided by the Authors, even if they are not published.…”

Section: The Gmmsmentioning

confidence: 99%

“…Luzi et al, 2016]. The testing datasets for ASCRs and SZ are provided and described in Lanzano et al [2020]. We verify the stability of the hindcasting skill of candidate GMMs, and examine their behavior on the basis of the requirements of MPS19, using 4 different subsets: i) the whole dataset (named All); ii) a subset of records with stations classified as EC8 site class A (named EC8-A); iii) a subset of events with M w ≥ 5 and stations located at R JB < 50 km (named MR), since these magnitude and distance ranges are those mostly affecting the hazard in Italy; iv) a validation subset without the Italian records preceding 2009 (named After 2009), to obtain a dataset independent of that used to calibrate the ITA10 [Bindi et al, 2011] model.…”

Section: The Gmmsmentioning

confidence: 99%

“…the quantile score [Gneiting and Raftery, 2007], to check the consistency of the results. The details of the scoring procedure and the scoring values for each GMM are reported and discussed in Lanzano et al [2020]; here in Table 5 we show the average values of the scores, and the un-normalized weight for each GMM using the EC8-A subset; the un-normalized weight is the ordinal number of the score. Summing up the total un-normalized scores of EC8-A and MR subsets, the grand-total 3 The AB10 predictions at 4 s (not provided by the Authors) are linearly extrapolated from those at 2 and 3 s.…”

Section: The Gmmsmentioning

confidence: 99%

“…Rank of candidate GMMs for the ASCR dataset EC8-A. UNW: un-normalized weight.For the Italian subduction zone, which corresponds to the Calabrian Arc in the southern Tyrrhenian sea, we select two GMMs after the pre-selection and scoring procedures: i)Skarlatoudis et al [2013], HEL13, and ii)Abrahamson et al [2016], HYD15 [for details, seeLanzano et al, 2020]. For volcanic zones (i.e., Etna, Aeolian islands, and Campanian volcanoes) we use a single GMM that is the model calibrated on purpose by, since no GMM available in the previous literature [e.g Faccioli et al 2010;Tusa and Langer, 2016].…”

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confidence: 99%

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The new Italian seismic hazard model (MPS19)

Meletti¹,

Marzocchi²,

Lanzano³

et al. 2021

Annals of Geophysics

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We describe the main structure and outcomes of the new probabilistic seismic hazard model for Italy, MPS19 [Modello di Pericolosità Sismica, 2019]. Besides to outline the probabilistic framework adopted, the multitude of new data that have been made available after the preparation of the previous MPS04, and the set of earthquake rate and ground motion models used, we give particular emphasis to the main novelties of the modeling and the MPS19 outcomes. Specifically, we (i) introduce a novel approach to estimate and to visualize the epistemic uncertainty over the whole country; (ii) assign weights to each model components (earthquake rate and ground motion models) according to a quantitative testing phase and structured experts’ elicitation sessions; (iii) test (retrospectively) the MPS19 outcomes with the horizontal peak ground acceleration observed in the last decades, and the macroseismic intensities of the last centuries; (iv) introduce a pioneering approach to build MPS19_cluster, which accounts for the effect of earthquakes that have been removed by declustering. Finally, to make the interpretation of MPS19 outcomes easier for a wide range of possible stakeholders, we represent the final result also in terms of probability to exceed 0.15 g in 50 years.

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Section: The Gmmsmentioning

confidence: 99%

Section: The Gmmsmentioning

confidence: 99%

Section: The Gmmsmentioning

confidence: 99%

Section: The Gmmsmentioning

confidence: 99%

mentioning

confidence: 99%

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The new Italian seismic hazard model (MPS19)

Meletti¹,

Marzocchi²,

Lanzano³

et al. 2021

Annals of Geophysics

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Macroseismic intensity hazard maps for Italy based on a recent grid source model

Cito

Chioccarelli

Iervolino

2022

Bull Earthquake Eng

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Seismic hazard maps from probabilistic seismic hazard analysis or PSHA collect, at different sites, the values of the (site-specific) ground motion intensity measures of interest that, taken individually, have the same exceedance return period. For large-scale analyses, a widely used intensity measure is the macroseismic (MS) intensity, that provides an assessment of the earthquake effect based on the observed consequences in the hit area. Hazard maps can be developed in terms of MS intensity, and some examples exist in this respect. In the case of Italy, the last MS hazard map is based on the same seismic source model (known as MPS04) adopted to derive the design seismic actions of the current building code, a study dating more than ten years ago. It provides results in terms of countrywide Mercalli–Cancani–Sieberg (MCS) intensity level with 475 years return period. This short paper presents and discusses MCS probabilistic seismic hazard maps for Italy based on a recent grid-seismicity source model, herein named MPS19, synthetizing the large effort of a wide scientific community. The results, which are obtained by means of classical PSHA, are given in the form of maps referring to the 475 years return period, and also others of earthquake engineering interest. Moreover, it is discussed that the return period does not univocally identifies the MS intensity because, although MS is, by definition, a discrete random variable, it is modelled, in a given earthquake, by means of a normal distribution, that is, treated as continuous. Thus, the maps of the minimum return period causing the occurrence or exceedance of different MCS intensities are also provided. Finally, the comparison between the 475 years return period hazard map presented and the one which is currently the point of reference in Italy, that is, computed using MPS04, is briefly discussed. All the computed maps are made available to the reader as supplemental material.

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Exploring the impact of spatial correlations of earthquake ground motions in the catastrophe modelling process: a case study for Italy

Schiappapietra

Stripajova

Pažák

et al. 2022

Bull Earthquake Eng

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Catastrophe models are important tools to provide proper assessment and financial management of earthquake-related emergencies, which still create the largest protection gap across all perils. Earthquake catastrophe models include three main components, namely: (1) the earthquake hazard model, (2) the exposure model and, (3) the vulnerability model. Simulating spatially distributed ground-motion fields within either deterministic or probabilistic seismic hazard assessments poses a major challenge when site-related financial protection products are required. In this framework, we develop ad hoc correlation models for different Italian regions (specifically northern, central and southern Italy) and thereafter we perform both deterministic scenario-based and probabilistic event-based hazard and risk assessments in order to advance the understanding of spatial correlations within the catastrophe modelling process. We employ the OpenQuake engine for our calculations. This is an open-source tool suitable for accounting for the spatial correlation of earthquake ground-motion residuals. Our outcomes, albeit preliminary, demonstrate the importance of considering not only the spatial correlation of ground motions, but also its associated uncertainty in risk analyses. Although loss exceedance probability curves for the return periods of interest for the (re)insurance industry show similar trends, both hazard and risk footprints in terms of average annual losses feature less noisy and more realistic patterns if spatial correlation is taken into account. Such results will have implications for (re)insurance companies evaluating the risk to high-value civil engineering infrastructures.

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Ground motion models for the new seismic hazard model of Italy (MPS19): selection for active shallow crustal regions and subduction zones

Cited by 37 publications

References 64 publications

The new Italian seismic hazard model (MPS19)

The new Italian seismic hazard model (MPS19)

Macroseismic intensity hazard maps for Italy based on a recent grid source model

Exploring the impact of spatial correlations of earthquake ground motions in the catastrophe modelling process: a case study for Italy

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