Preventive Planning Model for Rescue Priority Management in Seismic Emergency

Preventive Planning Model for Rescue Priority Management in Seismic Emergency

Monica Cardarilli Mara Lombardi Massimo Guarascio 

Department of Chemical Materials Environmental Engineering, Sapienza University of Rome, Italy

1 February 2018
| Citation



This study stems from the detection analysis of damaged buildings in Nocera Umbra (Central Italy), which has been affected by the earthquake sequence during 1997–1998, causing serious damages to material goods and human casualties. This natural disaster highlighted the need to achieve a strategic planning during the emergency phase based not only on effective actions but also on the efficient management of rescue and relief operations.

The application of Quantitative Risk Analysis (QRA) has led to the seismic risk assessment for estimating the potential level of the expected damage, on heritage buildings and human lives.

Data and information have been gathered during the surveys carried out after the major seismic event. A deep analysis has highlighted the existence of a correlation ratio between the critical structural features and the propensity of buildings to collapse. Considering either the exposed population, this information represents the crucial element for a relief management plan.

All risk indicators associated to each damage scenario have allowed to assign a scale of priorities at every relief operations for an effective risk mitigation based on damage level and expected casualties.

The ex-post emergency organization would be able to make more efficient both allocation and management of resources, equipment and technical teams during rescue activities. This is strongly connected to the ex-ante priority planning of the operations related to magnitude and distribution of expected collapses and casualties thank to the simulation performed to the potential risk scenarios. 


building collapse, Quantitative Risk Analysis, seismic emergency, vulnerability index


[1] Ariki, F., Shima, S. & Midorikawa, S., Earthquake disaster prevention of Yokohama City. Journal of Japan Association for Earthquake Engineering, 4(3), pp. 148–153, 2004.

[2] Bal, I.E., Crowley, H. & Pinho, R., Displacement-based earthquake loss assessment for an earthquake scenario in Istanbul. Journal of Earthquake Engineering, 11(2), pp. 12–22, 2008.

[3] Erdik, M., Sesetyan, K., Demircioglu, M.B., Hancılar, U. & Zulfikar, C., Rapid earthquake loss assessment after damaging earthquakes. Soil Dynamics and Earthquake Engineering, 31(2), pp. 247–266, 2011.

[4] GNDT/SNN Ratio Seismic Microzonation Project Umbria-Marche Nocera Umbra: Seismic Microzonation Elements, Milan, 1999.

[5] Spence, R.J.S., Coburn, A.W., Sakai, S. & Pomonis, A., A parameterless scale of seismic intensity for use in seismic risk analysis and vulnerability assessment. In: Society for References Earthquake and Civil Engineering Dynamics (ed.), Earthquake Blast AND Impact: Measurement and Effects of Vibration. Elsevier Applied Science, Amsterdam, 1991.

[6] OPCM (2006) n. 3519

[7] Ambraseys, N.N., Simpson K.A. & Bommer, J.J., Prediction of horizontal response spectra in Europe. Earthquake Engineering & Structural Dynamics, 25, pp. 371–400, 1996.<371::aid-eqe550>;2-1

[8] Calvi, G.M., Pinho, R., Magenes, G., Bommer, J.J., Restrepo-Velez, L.F. & Crowley, H., The development of seismic vulnerability assessment methodologies over the past 30 years. ISET Journal of Earthquake Technology, 43(4), pp. 75–104, 2006.

[9] Lagomarsino, S. & Giovinazzi, S., Macroseismic and mechanical models for the fragility and damage assessment of current buildings. Bull Earthquake Engineering, 4, pp. 445–463, 2006.

[10] Larionov, V., Frolova, N. & Ugarov, A., Approaches to fragility evaluation and their application for operative forecast of earthquake consequences. All-Russian conference “Risk- 2000”, ed. A. Ragozin, ANKIL, Moscow, pp. 132–135, 2000.

[11] Yeh, C.H., Jean, W.Y. & Loh, C.H., Damage building assessment for earthquake loss estimation in Taiwan. In: Proceedings of the 12th world conference on earthquake engineering, Auckland, New Zealand, Paper No. 1500, 2000.

[12] Italian Regio Decreto (1937) n. 2105, 22nd November.

[13] Italian Ministerial Decree (1987) n. 141, 9th January.

[14] Bommer, J., Pinho, R. & Crowley, H., Using a displacement-based approach for earthquake loss estimation. Advances in earthquake engineering for urban risk reduction, eds. S.T. Wasti & G. Ozcebe, Springer, Dordrecht, 2006.

[15] Crowley, H., Pinho, R. & Bommer, J.J., A probabilistic displacement-based fragility assessment procedure for earthquake loss estimation. Bulletin of Earthquake Engineering, 2(2), pp. 173–219, 2004.

[16] Eguchi, R.T., Goltz, J.D., Seligson, H.A., Flores, P.J., Blais, N.C., Heaton, T.H. & Bortugno, E., Real-time loss estimation as an emergency response decision support system: the EPEDAT. Earthquake Spectra, 13(4), pp. 815–832, 1997.

[17] Coburn, A. & Spence, R., Earthquake Protection, 2nd edn. Wiley, Chichester, 2002. 

[18] Spence, R.J.S., Earthquake disaster scenario prediction and loss modeling for urban areas: LESSLOSS report. IUSS Press, Pavia, 2007.

[19] Di Pasquale, G., Ferlito, R., Orsini, G., Papa, F., Pizza, A.G., Van Dyck, J. & Veneziano, D., Seismic scenarios tools for emergency planning and management. In: Proceedings of the XXIX GAESC, Potsdam, Germany, 2004.

[20] Jaiswal, K. & Wald, D., An empirical model for global earthquake fatality estimation. Earthquake Spectra, 26(4), pp. 1017–1037, 2010.

[21] Samardjieva, E. & Badal, J., Estimation of the expected number of casualties caused by strong earthquakes. Bulletin of the Seismological Society of America, 92(6), pp. 2310–2322, 2002.

[22] Italian M.D. Infrastructures and Transport (2005), Annex 3, Table 4.3.1.

[23] Markus, M., Fiedrich, F., Leebmann, J., Schweier, C. & Steinle, E., Concept for an integrated disaster management tool. In: Proceedings of the 13th WCEE, Vancouver, BC, Canada, 2004.