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Operational earthquake loss forecasting: a retrospective analysis of some recent Italian seismic sequences

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An Erratum to this article was published on 21 January 2016

Abstract

Operational earthquake forecasting (OEF) relies on real-time monitoring of seismic activity in an area of interest to provide constant (e.g., daily) updates of the expected number of events exceeding a certain magnitude threshold in a given time window (e.g., 1 week). It has been demonstrated that the rates from OEF can be used to estimate expected values of the seismic losses in the same time interval OEF refers to. This is a procedure recently defined as operational earthquake loss forecasting (OELF), which may be the basis for rational short-term seismic risk assessment and management. In Italy, an experimental OELF system, named MANTIS-K, is currently under testing. It is based on weekly rates of earthquakes exceeding magnitude (M) 4, which are updated once a day or right after the occurrence in the country of an M 3.5+ earthquake. It also relies on large-scale structural vulnerability and exposure data, which serve to the system to provide continuously the weekly expected number of: (1) collapsed buildings, (2) displaced residents, and (3) casualties. While the probabilistic basis of MANTIS-K was described in previous work, in this study OELF is critically discussed with respect to three recent Italian seismic sequences. The aim is threefold: (1) illustrating all the features of the OELF system in place; (2) providing insights to evaluate whether if it would have been a useful additional tool for short-term management; (3) recognizing common features, if any, among the losses computed for different sequences.

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Notes

  1. However, in the loss assessment, contributions from sources with epicentral distance larger than 150 km are neglected.

  2. Data from ISIDe, http://iside.rm.ingv.it/, last accessed 20/07/15. Because ISIDe does not provide measures in a unique magnitude scale for all the events, M without subscripts is used where necessary.

  3. It is to note that, the epicentre location of the mainshock of the sequence is known only afterwards. Conversely, in using MANTIS-K during a seismic sequence, some hypotheses on the location of the geographic area to be monitored would be required.

  4. Note that after a damaging earthquake, evacuation is likely to be expected, while at this stage the algorithm of MANTIS-K assumes stable exposure (and also vulnerability), despite the occurred earthquake.

  5. The values of PGA are available on the Italian Accelerometric Archive—ITACA—http://itaca.mi.ingv.it/, last accessed 20/07/15. However, note that for the second event ITACA does not specifies whether the PGA was recorded in free field conditions. In fact, Dolce and Di Bucci (2015) report a maximum horizontal PGA value for the second event of 289 cm/s2.

  6. See http://terremoti.ingv.it/it/ultimi-eventi/921-evento-sismico-tra-le-province-di-lucca-e-massa.html, last accessed 20/07/15.

  7. See Dolce and Di Bucci (2015) for a discussion, related to exposure, which may help in understanding this result.

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Acknowledgments

The study presented in this paper was developed in the framework of AMRA—Analisi e Monitoraggio dei Rischi Ambientali scarl (http://www.amracenter.com) for the strategies and tools for real-time earthquake risk reduction (REAKT; http://www.reaktproject.eu) funded by the European Commission via the Seventh Framework Program for Research, with Contract No. 282862. Professor Mauro Dolce and Dr. Warner Marzocchi are gratefully acknowledged for their comments, which improved quality and readability of this paper.

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  1. Analisi e Monitoraggio dei Rischi Ambientali (AMRA) scarl, via Nuova Agnano 11, 80125, Naples, Italy

    Eugenio Chioccarelli

  2. Dipartimento di Strutture per l’Ingegneria e l’Architettura, Università degli Studi di Napoli Federico II, via Claudio 21, 80125, Naples, Italy

    Iunio Iervolino

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  1. Eugenio Chioccarelli
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  2. Iunio Iervolino
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Correspondence to Iunio Iervolino.

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Chioccarelli, E., Iervolino, I. Operational earthquake loss forecasting: a retrospective analysis of some recent Italian seismic sequences. Bull Earthquake Eng 14, 2607–2626 (2016). https://doi.org/10.1007/s10518-015-9837-8

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