# A numerical approach for estimating the probability of earthquake surface rupture

Lisa Mammarella, Francesco Visini, Paolo Boncio, Stéphane Baize, Oona

Scotti, Céline Beauval, Bruno Pace, Stephen Thompson

► To cite this version:

Lisa Mammarella, Francesco Visini, Paolo Boncio, Stéphane Baize, Oona Scotti, et al.. A numerical approach for estimating the probability of earthquake surface rupture. EGU General Assembly 2025, European Geosciences Union (EGU), Apr 2025, Vienne, Austria. pp.EGU25-5092, 10.5194/egusphere-egu25-5092. hal-05450046

HAL Id: hal-05450046

https://hal.science/hal-05450046v1

Submitted on 9 Jan 2026

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# A numerical approach for estimating the probability of earthquake surface rupture

**Lisa Mammarella**<fnref n="1" />, **Francesco Visini**<fnref n="2" />, **Paolo Boncio**<fnref n="1" />, **Stéphane Baize**<fnref n="3" />, **Oona Scotti**<fnref n="3" />, **Céline Beauval**<fnref n="4" />, **Bruno Pace**<fnref n="1" />, and **Stephen Thompson**<fnref n="5" />

This study is part of the Probabilistic Fault Displacement Hazard Analysis (PFDHA) framework, which assesses the hazard posed by coseismic surface faulting to infrastructure systems (e.g., lifelines, nuclear power plants, and dams) located on or near an earthquake fault trace. The primary objective of this study is to estimate the probability of surface rupture on the principal fault—the main fault responsible for seismic moment release—based on faulting style, seismogenic thickness, fault geometry, and rupture size (i.e., earthquake magnitude). Current methods for estimating the probability of surface rupture on the principal fault are primarily based on empirical models. These models rely on observations of surface rupture occurrences versus non-occurrences, analyzed through logistic regressions using global or regional datasets of historical crustal earthquakes. However, empirical models have several limitations, including potential biases, catalog incompleteness (i.e., missing surface rupture data), and inconsistencies in fault geometry information and seismotectonic settings (e.g., seismogenic thickness). To overcome these limitations, we propose a numerical approach to compute the Conditional Probability of Surface Rupture (CPSR). This approach incorporates faulting style (normal, reverse, strike-slip), seismogenic thickness, fault dip, magnitude-dependent scaling relations for rupture shape and size, nucleation position within the rupture, and the statistical distribution of hypocenters within the seismogenic crust. These parameters are derived from statistical analyses of global fault rupture databases and earthquake distributions in various non-subduction seismotectonic settings. Our results indicate that CPSR probabilities are strongly influenced by seismogenic thickness and fault dip angle. Moreover, comparison between numerical results and empirical models suggests that CPSR depends on the specific characteristics of the study area. This model can be integrated into PFDHA as an epistemic alternative to purely empirical approaches. Additionally, the numerical code for CPSR computation has been developed and is openly available on GitHub.

<footnote n="1">¹University of Chieti-Pescara, INGEO, Pescara, Italy (lisa.mammarella@unich.it)</footnote>

<footnote n="2">²INGV, Istituto Nazionale di Geofisica e Vulcanologia, Chieti, Italy</footnote>

<footnote n="3">³IRSN, Institut de Radioprotection et de Sûreté Nucléaire, Paris, France</footnote>

<footnote n="4">⁴ISTerre, IRD, Grenoble, France</footnote>

<footnote n="5">⁵Lettis Consultants International, Inc., Concord, CA, USA</footnote>