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

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• 作者：Eugenio Chioccarelli ; Iunio Iervolino
• 刊名：Bulletin of Earthquake Engineering
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：14
• 期：9
• 页码：2607-2626
• 全文大小：17,420 KB
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geotechnical Engineering
  Civil Engineering
  Geophysics and Geodesy
  Hydrogeology
  Structural Geology
  
• 出版者：Springer Netherlands
• ISSN：1573-1456
• 卷排序：14

文摘

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 operationalearthquakelossforecasting (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.KeywordsSeismic risk managementEmergency managementSeismic swarms