1 - International Seismic Safety Organization, ISSO, Arsita. Italy
2 - Accademia Nazionale dei Lincei, Rome. Italy
3 - Institute of Geophysics, China Earthquake Administration, Beijing. China
4 - Accademia Nazionale delle Scienze detta dei XL, Rome. Italy
Most of the fatal drawbacks of PSHA (Probabilistic Seismic Hazard Assessment) have been discussed by many authors and call for a new paradigm (different from PSHA) to evaluate seismic hazard (for a recent review see Panza and Peresan, 2016; Jia, 2018; and references therein). The Neo-Deterministic Seismic Hazard Assessment (NDSHA) method, proposed some twenty year ago, is found to reliably and realistically simulate the wide suite of earthquake ground motions that may impact civil populations as well as their heritage buildings. The scenario based NDSHA’s modeling technique is developed from fundamental physical knowledge of: (i) the seismic source process; (ii) the propagation of earthquake waves; and (iii) their combined interactions with site effects. Thus, NDSHA effectively accounts for the tensor nature of earthquake ground motions: (a) formally described as the tensor product of the earthquake source functions and the Green’s Functions of the transmitting (pathway) medium: and (b) more informally described as mathematical arrays of numbers or functions (indices) “that transform according to certain rules under a change of coordinates.”
Importantly, NDSHA uses all available information about the space distribution of large magnitude earthquake phenomena, including: (a) Maximum Credible Earthquake (MCE) – which is based on seismic history and seismotectonics; and (b) geological and geophysical data. Moreover it does not rely on scalar empirical ground motion attenuation models, as these are often both: (a) weakly constrained by available observations; and (b) fundamentally unable to account for the tensor nature of earthquake ground motion.
Standard NDSHA is estimated as the envelope ground shaking from the largest observed or credible earthquakes, and does not consider temporal features of earthquakes occurrence. Hence it provides robust and safely conservative hazard estimates for engineering design and mitigation decision strategies; but without requiring (often faulty) assumptions about the probabilistic model of earthquake occurrence. No need to invoke the chimeric, physically rootless “return period”. If specific applications may benefit from temporal information, including a gross estimate of the average occurrence time, the definition of the Gutenberg-Richter (GR) relation is performed according to the multi-scale seismicity model and occurrence rate is associated to each NDSHA modeled source.
Observations from recent destructive earthquakes in Italy, e.g. Emilia 2012, Central Italy 2009 and 2016-2017 seismic crises, and Nepal 2015, have confirmed the validity of NDSHA’s approach and application (Fasan et al., 2016). Recently, NDSHA has been applied to schools and to tangible cultural heritage. The widespread application of NDSHA may enhance earthquake safety and resilience of civil populations in all earthquake-prone regions. This is especially relevant in those tectonically active areas where the historic earthquake record is too short to have yet experienced (due to a relatively prolonged quiescence) the full range of large, major and great earthquake events, which may potentially occur (Panza et al., 2001, 2012; Magrin et al., 2016, 2017; Panza et al., 2013 and references therein; Panza, 2017).
Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle-range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns, like CN and M8 (Keilis- Borok and Soloviev, 2003; Peresan et al., 2005, 2012). Accordingly with Panza et al. (2017), the proper integration of seismological and geodetic information, clearly supplies a reliable contribution to the reduction of the space extent of predictions of earthquakes (e.g. the 2016-2017 seismic crisis in Central Italy and the 2012 Emilia sequence) and defines a new paradigm for time dependent hazard scenarios. In this framework, GPS data are not used to estimate the standard 2D velocity and strain field in the area, but to reconstruct the station's velocity and strain pattern along transects, which are properly oriented according to the a priori information about the known tectonic setting. Overall, the analysis of the available geodetic data indicates that it is possible to highlight the velocity variation and the related strain accumulation within the area alarmed by CN.
The integrated routine monitoring, CN and GPS, could be more widely applied in the near future, since dense permanent GNSS networks could be established using low-cost GNSS receivers. An example of the possible significant reduction of the size of the CN alarmed areas, by the integrated monitoring, CN and GPS, is given in the figure. The map shows the NDSHA ground motion scenario at bedrock for alarmed Central Italy CN region, expressed here in terms of PGV (Peak Ground Velocity), and the rectangular area covered by the GPS stations, where large anomalies in the velocity and strain pattern are observed. Remarkably, the seismic hazard scenario, which refers to the area simultaneously defined/alerted based on CN and GPS data, extends for about only 5000 km2. By the way, the PGV values observed by Rete Accelerometrica Nazionale–Dipartimento Protezione Civile (RAN–DPC) at Amatrice (up to 31 cm/s) and Norcia (up to 56 cm/s) fit very nicely the values predicted by NDSHA ground motion scenarios (30–60 cm/s).
Fasan, M., Magrin, M., Amadio, C., Romanelli, F., Vaccari, F., and Panza, G.F. (2016) A seismological and engineering perspective on the 2016 Central Italy earthquakes, Int. J. Earthquake and Impact Engineering, 1, 395-420, ISSN online: 2397-9380, https://doi.org/10.1504/IJEIE.2016.083253.
Jia, J. (2018) Soil Dynamics and Foundation Modeling, Springer, Cham, Switzerland, pp.741, SBN 978-3-319-40357-1, https://doi.org/10.1007/978-3-319-40358-8.
Keilis-Borok, V.I., Soloviev, A.A. (eds) (2003) Non-linear dynamics of the lithosphere and earthquake prediction. Springer, Heidelberg, Germany, pp. 337.
Magrin, A., Gusev, A.A., Romanelli, F., Vaccari, F. and Panza, G.F. (2016) Broadband NDSHA computations and earthquake ground motion observations for the Italian territory, Int. J. Earthquake and Impact Engineering, 1, 159-173, ISSN online: 2397-9380, doi: 10.1504/IJEIE.2016.10000979.
Magrin, A., Peresan, A., Kronrod, T., Vaccari, F. and Panza, G.F. (2017) Neo-deterministic seismic hazard assessment and earthquake occurrence rate, Eng. Geol., 229, 95-109.
Panza, G.F. (2017) NDSHA: Robust and reliable seismic hazard assessment, Proceedings, International Conference on Disaster Risk Mitigation, Dhaka, Bangladesh, September 23 - 24, 2017, arXiv:1709.02945
Panza, G.F., La Mura, C., Peresan, A., Romanelli, F. and Vaccari, F. (2012) Seismic Hazard Scenarios as Preventive Tools for a Disaster Resilient Society, Advances in Geophysics, 53, 93-165.
Panza, G.F. and Peresan, A. (2016). Difendersi dal terremoto si può - L’approccio neodeterministico . ISBN: 978-88-6310-738-8, EPC Editore, https://www.epc.it/Prodotto/Editoria/Libri/Difendersi-dal-terremoto-si-puo%27/3342.
Panza, G.F., Peresan, A. and La Mura, C. (2013) Seismic hazard and strong motion: an operational neo- deterministic approach from national to local scale, in Geophysics and Geochemistry, Eds. UNESCO-EOLSS Joint Committee, in Encyclopedia of Life Support Systems (EOLSS), Developed under the Auspices of the UNESCO, Eolss Publishers, Oxford, UK, [http://www.eolss.net].
Panza, G.F., Peresan, A., Sansò, F., Crespi, M., Mazzoni, A. and Mascetti, A. (2017) How geodesy can contribute to the understanding and prediction of earthquakes. Rend. Fis. Acc. Lincei, DOI 10.1007/s12210-017-0626-y
Panza, G.F., Romanelli, F. and Vaccari, F. (2001) Seismic wave propagation in laterally heterogeneous anelastic media: theory and applications to seismic zonation, Advances in Geophysics, 43, 1-95.
Peresan, A., Kossobokov,V. G. and Panza, G.F. (2012). Operational earthquake forecast/prediction. Rend. Fis. Acc. Lincei, 23, 131-138, DOI:10.1007/s12210-012-0171-7.
Peresan, A., Kossobokov V. G., Romashkova, L., Panza, G.F. (2005) Intermediate-term middle-range earthquake predictions in Italy: a review. Earth Sci. Rev., 69, 97–132.