Seismic Hazard and Public Safety

Marzocchi, Warner

doi:10.1002/2013eo270005

Cited by 14 publications

(7 citation statements)

References 11 publications

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“…The choice of the relevant ground-motion parameter, the exceedance probability threshold and the exposure time, is based on the balancing of safety and feasibility, because too stringent regulations may lead to prohibitive costs for the new buildings and for retrofitting. Because these thresholds do not have any specific physical meaning, they have to be chosen by regulators and decision makers, not by scientists (e.g., Marzocchi, 2013). Once these thresholds have been decided, however, seismologists can use them to test the reliability of hazard models using future observations (e.g., Stirling and Gerstenberger, 2010).…”

Section: Discussionmentioning

confidence: 99%

Some Thoughts on Declustering in Probabilistic Seismic-Hazard Analysis

Marzocchi¹,

Taroni²

2014

Bulletin of the Seismological Society of America

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In this paper, we discuss in depth, one of the basic procedures that stands behind probabilistic seismic-hazard analysis (PSHA), that is, the declustering of the seismicity rates. First, we explore the technical, scientific, and practical motivations that led to introducing the declustering of seismicity rates. Then, we show that for PSHA, declustering is essential only to minimize a spatial distortion of the earthquake occurrence process, but, conversely, it may lead to significant underestimation of the true seismic hazard. This underestimation precludes the possibility to test meaningfully PSHA against real observations, and it may lead to underestimate the seismic risk, whenever seismic-hazard maps are used for risk assessment. Finally, we propose a methodology that can be used in PSHA to avoid this potential bias.

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Section: Discussionmentioning

confidence: 99%

Some Thoughts on Declustering in Probabilistic Seismic-Hazard Analysis

Marzocchi¹,

Taroni²

2014

Bulletin of the Seismological Society of America

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“…This comparison demonstrates that the increased complication of selecting thresholds to produce hazard maps is only apparent. Indeed, the choice of one (or a few) subjective scenarios implicitly roughly correspond (more or less consciously) to set a probability threshold to the maps conditioned to the occurrence of one eruption [ Allen , ; Marzocchi et al , ; Marzocchi , ]. Conversely, BET_VH_ ST (as any short‐term PVHA) allows the choice of such critical probability level to be made by decision makers, not by volcanologists.…”

Section: Resultsmentioning

confidence: 99%

“…Yet short-term volcanic hazard models are still lacking, and during volcanic unrest, volcanologists usually assist decision makers producing maps of the deterministic outcome, or at best the probabilistic impact, of one or a few selected scenarios Scollo et al, 2009]. These maps are undoubtedly important for decision makers, but only a fully probabilistic volcanic hazard analysis (PVHA) can provide a quantitative solid basis for a rationale decision making [Cornell and Krawinkle, 2000;Der Kiureghian, 2005;Marzocchi andWoo, 2007, 2009;Sandri et al, 2012]. PVHA accounts properly for the intrinsic variability of the system and all known uncertainties [Senior Seismic Hazard Analysis Committee (SSHAC), 1997;Marzocchi and Jordan, 2014], and it offers a more complete view of the real volcanic hazard than any single scenario could do .…”

Section: Introductionmentioning

confidence: 99%

Probabilistic short‐term volcanic hazard in phases of unrest: A case study for tephra fallout

et al. 2014

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During volcanic crises, volcanologists estimate the impact of possible imminent eruptions usually through deterministic modeling of the effects of one or a few preestablished scenarios. Despite such an approach may bring an important information to the decision makers, the sole use of deterministic scenarios does not allow scientists to properly take into consideration all uncertainties, and it cannot be used to assess quantitatively the risk because the latter unavoidably requires a probabilistic approach. We present a model based on the concept of Bayesian event tree (hereinafter named BET_VH_ST, standing for Bayesian event tree for short‐term volcanic hazard), for short‐term near‐real‐time probabilistic volcanic hazard analysis formulated for any potential hazardous phenomenon accompanying an eruption. The specific goal of BET_VH_ST is to produce a quantitative assessment of the probability of exceedance of any potential level of intensity for a given volcanic hazard due to eruptions within restricted time windows (hours to days) in any area surrounding the volcano, accounting for all natural and epistemic uncertainties. BET_VH_ST properly assesses the conditional probability at each level of the event tree accounting for any relevant information derived from the monitoring system, theoretical models, and the past history of the volcano, propagating any relevant epistemic uncertainty underlying these assessments. As an application example of the model, we apply BET_VH_ST to assess short‐term volcanic hazard related to tephra loading during Major Emergency Simulation Exercise, a major exercise at Mount Vesuvius that took place from 19 to 23 October 2006, consisting in a blind simulation of Vesuvius reactivation, from the early warning phase up to the final eruption, including the evacuation of a sample of about 2000 people from the area at risk. The results show that BET_VH_ST is able to produce short‐term forecasts of the impact of tephra fall during a rapidly evolving crisis, accurately accounting for and propagating all uncertainties and enabling rational decision making under uncertainty.

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“…When dealing with the decision-making process, according to a widely accepted scheme, two categories of participants are usually identified: scientists and decision-makers (e.g., Marzocchi, 2013). They are often considered as two counterparts, which dynamically interact, representing two different points of view that have to be reconciled.…”

Section: Scientists and Decision-makersmentioning

confidence: 99%