Lessons learned from two case histories of seismic microzonation in Italy

The prediction of the variability of the seismic ground motion in a given built-up area is considered an effective tool to plan appropriate urban development, to undertake actions on seismic risk mitigation and to understand the damage pattern caused by a strong-motion event. The procedures for stud...

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Bibliographic Details
Published in:Natural hazards (Dordrecht) 2014-12, Vol.74 (3), p.2005-2035
Main Authors: Santucci de Magistris, Filippo, d’Onofrio, Anna, Penna, Augusto, Puglia, Rodolfo, Silvestri, Francesco
Format: Article
Language:English
Subjects:
Case histories
Case studies
Civil Engineering
Damage
Earth and Environmental Science
Earth Sciences
Earth, ocean, space
Engineering and environment geology. Geothermics
Environmental Management
Exact sciences and technology
Geophysics/Geodesy
Geotechnical Engineering & Applied Earth Sciences
Ground motion
Hydrogeology
Mathematical models
Natural Hazards
Natural hazards: prediction, damages, etc
Original Paper
Risk reduction
Seismic response
Seismology
Subsoils
Urban areas
Urban development
Villages
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Summary:The prediction of the variability of the seismic ground motion in a given built-up area is considered an effective tool to plan appropriate urban development, to undertake actions on seismic risk mitigation and to understand the damage pattern caused by a strong-motion event. The procedures for studying the seismic response and the seismic microzonation of an urban area are well established; nevertheless, some controversial points still exists and are discussed here. In this paper, the selection of a reference input motion, the construction of a subsoil model and the seismic response analysis procedures are discussed in detail, based on the authors’ experience in two Italian case histories: the seismic microzonation of the city of Benevento, which was a predictive study, and the simulation of seismic response and damage distribution in the village of San Giuliano di Puglia, which was a retrospective analysis.
ISSN:0921-030X
1573-0840
DOI:10.1007/s11069-014-1281-6