Search for a command to run...
This work aims to perform ground motion simulations using a simplified approach that allows fast yet accurate estimation of intensity measures (PGA, PGV, SA). The approach presented can be applied a few minutes after a strong earthquake, when knowledge of source parameters is still limited, or during the pre-emergency phase, contributing to more effective territorial planning. A similar goal can be achieved using physics-based models that account for source uncertainty. However, due to the limited time and data available immediately after an earthquake, physics-based models are not suitable for urgent computing (Stallone et al., 2025). The proposed method is based on two Python codes: HypoSmoothFaultSimulation (Di Naccio et al., 2025), a soon-to-be-released open-access software, which generates an ensemble of rupture scenarios starting from geometric and kinematic properties of the fault (length, strike, dip, depth, rake), and seismotectonic potential (magnitude). The second software, ProbShakemap (Stallone et al., 2025) computes ground shaking at different points of interest (POIs) by implementing one or more Ground Motion Models (GMMs), starting from the plausible hypocenters generated by HypoSmoothFaultSimulation. The latter code accounts for source parameter uncertainty by defining smoothed boxcar probability density functions (PDFs), which are subsequently sampled to generate the rupture scenarios. ProbShakemap accounts for both source-related and GMM-related uncertainties, producing multiple ground-shaking estimates for each POI. As a case study, the method was applied to the central Apennines, focusing on a representative sample of faults, by computing PGA maps on a regular grid, or at the location of RSN and RAN seismic stations. For the same sample of faults, the stochastic code EXSIM (Motazedian and Atkinson, 2005), which requires more detailed knowledge of source parameters and wave propagation effects, was also applied. These comparisons aim to highlight the differences between the proposed method and more complex physics-based models. It should be noted that the proposed method cannot provide reliable ground motion estimates in the near field, due to source-related effects such as velocity pulses, large peak accelerations and the effect of the vertical component, which strongly influence ground shaking close to the fault. However, the method is applicable in the intermediate field, which is still characterized by significant ground shaking during large earthquakes. Overall, this approach allows ground motion estimates to be obtained from a limited number of initial parameters while accounting for their associated uncertainty, enabling fast and simplified computation suitable for application before or immediately after a strong earthquake.BibliographyDI NACCIO, Deborah; STALLONE, Angela; MC CARAFA, Michele. The Mt. Morrone seismotectonic source: analysis of fault model uncertainty for Ground Motion Prediction. In: EGU General Assembly Conference Abstracts. 2025. p. EGU25-12632.Motazedian, D., Atkinson, 2005. Stochastic Finite-Fault Modeling Based on a Dynamic Corner Frequency. Bull. Seismol. Soc. Am. 95, 995–1010. https://doi.org/10.1785/0120030207STALLONE, Angela, et al. ProbShakemap: A Python toolbox propagating source uncertainty to ground motion prediction for urgent computing applications. Computers & Geosciences, 2025, 195: 105748.