Computational Tools for Relaxing the Fault Segmentation in Probabilistic Seismic Hazard Modelling in Complex Fault Systems

  • F. VisiniEmail author
  • A. Valentini
  • T. Chartier
  • O. Scotti
  • B. Pace


Use of faults in seismic hazard models allows us to capture the recurrence of large-magnitude events and therefore improve the reliability of probabilistic seismic hazard assessment (PSHA). In the past decades, fault segmentation provided an important framework for quantifying fault-based PSHA. Recent complex coseismic ruptures (e.g., 2010 Mw 7.1 Canterbury, 2012 Mw 8.6 Sumatra, 2016 Mw 7.8 Kaikōura, 2016 Mw 6.5 central Italy) have shown the need to consider different possible combinations of rupture scenarios in PSHA. Here we present two new methodologies that model rates of ruptures along complex fault systems, one based on a floating rupture approach (FRESH) and another one based on assumed rupture scenarios (SUNFISH). They represent alternatives to a recently proposed approach (SHERIFS), and further step to overcome the segmented and un-segmented approaches commonly used in PSHA in Europe. Differences among SHERIFS, SUNFiSH and FRESH are related to the way slip rate, rupture geometries and magnitude–frequency distributions are modelled. To quantify the differences between these three methodologies, we compared PSHA results based on geometries and slip rates of a fault system located in northeastern Italy, assuming a given maximum magnitude and the same seismic moment rate target. Differences up to 20–30% in the peak ground acceleration at 2% and 10% in 50 years are observed. Finally, we show that the three methodologies are able to solve for the long-term rate of ruptures with resulting PSHA that reflect the fault system geometry and slip rates, without any assumption on segment boundaries. Using fault-based approaches in PSHA requires collecting as much local geological information as possible. Now that multi-fault rupture approaches are available, simplifying assumptions often made to model complex fault systems (uniform slip rate, segmentation hypothesis) are no longer necessary. On the other hand, local data collection should be strongly encouraged to better characterize the actual fault slip rate variability and the complex 3D geometries.


Fault system fault segmentation slip rates variability long-term rate of ruptures PSHA 



We acknowledge the helpful comments of the Associate Editor, Dr. Faure Walker and two anonymous reviewers. We warmly thank the FAULT2SHA members group for fruitful discussion and suggestions on the overall complex fault topics. We also thank Graeme Weatherill for the help with the OpenQuake python tool to build ruptures for FRESH, and Pierfrancesco Burrato for the detailed information on the slip rate calculation and derivation. FV is supported by FIRS 2016-Visini F.-0865.054 and CPS funds. A.V. is supported by Department INGeo funds (I. Raffi, responsible for “fondi dottorato” funds). T.C. is supported by AXA Research Fund. O.S is supported by IRSN funds. B.P. is supported by Department DiSPUTer funds (B. Pace, responsible for “ex 60%” funds).


  1. Basili, R., Valensise, G., Vannoli, P., Burrato, P., Fracassi, U., Mariano, S., et al. (2008). The database of individual seismogenic sources (DISS), version 3: Summarizing 20 years of research on Italy’s earthquake geology. Tectonophysics, 453(1–4), 20–43. Scholar
  2. Bull, J. M., Barnes, P. M., Lamarche, G., Sanderson, D. J., Cowie, P. A., Taylor, S. K., et al. (2006). High-resolution record of displacement accumulation on an active normal fault: Implications for models of slip accumulation during repeated earthquakes. Journal of Structural Geology, 28(7), 1146–1166. Scholar
  3. Burrato, P., Poli, M. E., Vannoli, P., Zanferrari, A., Basili, R., & Galadini, F. (2008). Sources of Mw 5+ earthquakes in northeastern Italy and western Slovenia: An updated view based on geological and seismological evidence. Tectonophysics, 453(1–4), 157–176. Scholar
  4. Carafa, M. M. C., & Bird, P. (2016). Improving deformation models by discounting transient signals in geodetic data: 2. Geodetic data, stress directions, and long-term strain rates in Italy. Journal of Geophysical Research Solid Earth, 121, 5557–5575. Scholar
  5. Castellarin, A., Cantelli, L., Fesce, A. M., Mercier, J. L., Picotti, V., Pini, G. A., et al. (1992). Alpine compressional tectonics in the Southern Alps. Relationships with the N-Apennines. Annales Tectonicae, 6, 62.Google Scholar
  6. Cauzzi, C., & Faccioli, E. (2008). Broadband (0.05 to 20 s) prediction of displacement response spectra based on worldwide digital records. Journal of Seismology, 12, 453–475.CrossRefGoogle Scholar
  7. Chartier, T., Scotti, O., Lyon-Caen, H., & Boiselet, A. (2017). Methodology for earthquake rupture rate estimates of fault networks: Example for the western Corinth rift, Greece. Natural Hazards and Earth System Sciences, 17(10), 1857–1869. Scholar
  8. Cheloni, D., D’Agostino, N., D’Anastasio, E., & Selvaggi, G. (2012). Reassessment of the source of the 1976 Friuli, NE Italy, earthquake sequence from the joint inversion of high-precision levelling and triangulation data. Geophysical Journal International, 190(2), 1279–1294. Scholar
  9. Cowie, P. A., Roberts, G. P., Bull, J. M., & Visini, F. (2012). Relationships between fault geometry, slip rate variability and earthquake recurrence in extensional settings. Geophysical Journal International, 189(1), 143–160. Scholar
  10. D’amato, D., Pace, B., Di Nicola, L., Stuart, F. M., Visini, F., Azzaro, R., et al. (2017). Holocene slip rate variability along the Pernicana fault system (Mt. Etna, Italy): Evidence from offset lava flows. Bulletin of the Geological Society of America, 129(3–4), 304–317. Scholar
  11. Danciu, L., Şeşetyan, K., Demircioglu, M., Gülen, L., Zare, M., Basili, R., et al. (2017). The 2014 Earthquake Model of the Middle East: Seismogenic sources. Bulletin of Earthquake Engineering. Scholar
  12. DISS Working Group. (2018). Database of Individual Seismogenic Sources (DISS), Version 3.2.1: A compilation of potential sources for earthquakes larger than M 5.5 in Italy and surrounding areas. Istituto Nazionale di Geofisica e Vulcanologia;
  13. Doglioni, C., & Bosellini, A. (1987). Eoalpine and mesoalpine tectonics in the Southern Alps. Geologische Rundschau, 76(3), 735–754. Scholar
  14. Faccioli, E., Bianchini A., & Villani, M. (2010). New ground motion prediction equations for T > 1 s and their influence on seismic hazard assessment. Proceedings of the University of Tokyo Symposium on Long-Period Ground Motion and Urban Disaster Mitigation, March 17–18, 2010.Google Scholar
  15. Field, E. H., Arrowsmith, R. J., Biasi, G. P., Bird, P., Dawson, T. E., Felzer, K. R., et al. (2014). Uniform California Earthquake Rupture Forecast, version 3 (UCERF3)—The time-independent model. Bulletin of the Seismological Society of America, 104(3), 1122–1180. Scholar
  16. Field, E. H., Dawson, T. E., Felzer, K. R., Frankel, A. D., Gupta, V., Jordan, T. H., et al. (2009). Uniform California earthquake rupture forecast, version 2 (UCERF 2). Bulletin of the Seismological Society of America, 99(4), 2053–2107. Scholar
  17. Galadini, F., Poli, M. E., & Zanferrari, A. (2005). Seismogenic sources potentially responsible for earthquakes with M ≥ 6 in the eastern Southern Alps (Thiene-Udine sector, NE Italy. Geophysical Journal International. Scholar
  18. Gutenberg, B., & Richter, C. F. (1954). Seismicity of the earth and associated phenomena. Princeton: Princeton University Press.Google Scholar
  19. Hanks, T. C., & Kanamori, H. (1979). A moment magnitude scale. Journal of Geophysical Research B Solid Earth, 84, 2348–2350. Scholar
  20. King, G., & Nabelek, J. (1985). Role of fault bends in the initiation and termination of earthquake rupture. Science, 228(4702), 984–987.CrossRefGoogle Scholar
  21. Molnar, P. (1979). Earthquake recurrence intervals and plate tectonics. Bullettin of the Seismological Society of America, 69, 115–133.Google Scholar
  22. Pace, B., Peruzza, L., Lavecchia, G., & Boncio, P. (2006). Layered seismogenic source model and probabilistic seismic-hazard analyses in central Italy. Bullettin of the Seismological Society of America, 96, 107–132.CrossRefGoogle Scholar
  23. Pace, B., Visini, F., & Peruzza, L. (2016). FiSH: MATLAB tools to turn fault data into seismic-hazard models. Seismological Research Letters, 87(2A), 374–386. Scholar
  24. Pagani, M., Monelli, D., Weatherill, G., Danciu, L., Crowley, H., Silva, V., et al. (2014a). OpenQuake engine: An open hazard (and risk) software for the global earthquake model. Seismological Research Letters, 85(3), 692–702. Scholar
  25. Pagani, M., Monelli, D., Weatherill, G. A. & Garcia, J. (2014b). The OpenQuake-engine Book: Hazard. Global Earthquake Model (GEM) Technical Report 2014-08, p. 67.
  26. Page, M. T., Field, E. H., Milner, K. R., & Powers, P. M. (2014). The UCERF3 grand inversion: Solving for the long-term rate of ruptures in a fault system. Bulletin of the Seismological Society of America, 104(3), 1181–1204. Scholar
  27. Peruzza, L., & Pace, B. (2002). Sensitivity analysis for seismic source characteristics to probabilistic seismic hazard assessment in central Apennines (Abruzzo area). Bollettino di Geofisica Teorica ed Applicata, 43(1–2), 79–100.Google Scholar
  28. Peruzza, L., Pace, B., & Visini, F. (2011). Fault-based earthquake rupture forecast in Central Italy: Remarks after the L’Aquila Mw 6.3 Event. Bulletin of the Seismological Society of America. Scholar
  29. Poli, M. E., Burrato, P., Galadini, F., & Zanferrari, A. (2008). Seismogenic sources responsible for destructive earthquakes in NE Italy. Bollettino di Geofisica Teorica e Applicata, 49, 301–313.Google Scholar
  30. Poli, M. E., Peruzza, L., Rebez, A., Renner, G., Slejko, D., & Zanferrari, A. (2002). New seismotectonic evidence from the analysis of the 1976–1977 and 1977–1999 seismicity in Friuli (NE Italy). Bollettino di Geofisica Teorica ed Applicata, 43(1–2), 53–78.Google Scholar
  31. Robinson, R., Nicol, A., Walsh, J. J., & Villamor, P. (2009). Features of earthquake occurrence in a complex normal fault network: Results from a synthetic seismicity model of the Taupo Rift, New Zealand. Journal of Geophysical Research Solid Earth, 114, 12. Scholar
  32. Rovida, A., Locati, M., Camassi, R., Lolli, B., & Gasperini, P. (2016). CPTI15, the 2015 version of the Parametric Catalogue of Italian Earthquakes. Istituto Nazionale di Geofisica e Vulcanologia. Scholar
  33. Schwartz, D. P., & Coppersmith, K. J. (1984). Fault behavior and characteristic earthquakes: Examples from the Wasatch and San Andreas Fault Zones. Journal of Geophysical Research Solid Earth, 89(B7), 5681–5698. Scholar
  34. Serpelloni, E., Anzidei, M., Baldi, P., Casula, G., & Galvani, A. (2005). Crustal velocity and strain-rate fields in Italy and surrounding regions: New results from the analysis of permanent and non-permanent GPS networks. Geophysical Journal International. Scholar
  35. Slejko, D., Carulli, G. B., Nicolich, R., Rebez, A., Zanferrari, A., Cavallin, A., et al. (1989). Seismotectonics of the eastern Southern-Alps: A rieview. Bollettino di Geofisica Teorica e Applicata, 31, 109–136.Google Scholar
  36. Stirling, M., Mcverry, G., Gerstenberger, M., Litchfield, N. Van, Dissen, R., et al. (2012). National seismic hazard model for New Zealand: 2010 update. Bulletin of the Seismological Society of America, 102, 1514–1542. Scholar
  37. Stucchi, M., Meletti, C., Montaldo, V., Crowley, H., Calvi, G. M., & Boschi, E. (2011). Seismic hazard assessment (2003–2009) for the Italian building code. Bulletin of the Seismological Society of America, 101(4), 1885–1911. Scholar
  38. Swan, F. H., Schwartz, D. P., & Cluff, L. S. (1980). Recurrence of moderate to large magnitude earthquakes produced by surface faulting on the Wasatch Fault Zone, Utah. Bulletin of the Seismological Society of America, 70(5), 1431–1462.Google Scholar
  39. Valentini, A., Visini, F., & Pace, B. (2017). Integrating faults and past earthquakes into a probabilistic seismic hazard model for peninsular Italy. Natural Hazards and Earth System Sciences, 17(11), 2017–2039. Scholar
  40. Visini, F., & Pace, B. (2014). Insights on a key parameter of earthquake forecasting, the coefficient of variation of the recurrence time, using a simple earthquake simulator. Seismological Research Letters, 86, 703–713. Scholar
  41. Weichert, D. H. (1980). Estimation of the earthquake recurrence parameters for unequal observation periods for different magnitudes. Bulletin of the Seismological Society of America, 70(4), 1337–1346. Scholar
  42. Wells, D. L., & Coppersmith, K. J. (1994). New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement. Bulletin of the Seismological Society of America, 84(4), 974–1002.Google Scholar
  43. Woessner, J., Laurentiu, D., Giardini, D., Crowley, H., Cotton, F., Grünthal, G., et al. (2015). The 2013 European seismic hazard model: Key components and results. Bulletin of Earthquake Engineering, 13(12), 3553–3596. Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Istituto Nazionale di Geofisica e VulcanologiaL’AquilaItaly
  2. 2.CRUST-DiSPUTer DepartmentUniversità degli Studi di Chieti-PescaraChietiItaly
  3. 3.InGeo DepartmentUniversità degli Studi di Chieti-PescaraChietiItaly
  4. 4.Geosciences DepartmentEcole Normale Supérieure de ParisParisFrance
  5. 5.Institut de Radioprotection et Sûretét NucléaireParisFrance

Personalised recommendations