The Mt. Morrone seismotectonic source: analysis of fault model uncertainty for Ground Motion Prediction

In the past decade, seismic hazard assessment has increasingly relied on innovative approaches based on seismotectonic models for accurate physics-based short-term and long-term forecasts. Ensuring consistency and homogenization is essential when assembling data for a scientifically robust seismotectonic model. Additionally, a rigorous probabilistic framework is necessary to properly explore the uncertainties related to the seismotectonic model components, including geometric and kinematic characteristics (e.g., length, strike, dip, depth, and rake), and seismotectonic potential (e.g., long-term slip rate, and Mw).

In this contribution, we focus on the Mt. Morrone active fault in the central Apennines, which has a seismotectonic potential Mw+6.7 but has been silent for the past 1.8 kyr. We modeled the fault and used smoothed boxcar functions as probability density functions (PDFs) for the source parameters (Mw, Hypocenter coordinates, Strike, Dip, Rake). We then generated an ensemble of source scenarios by randomly sampling from these PDFs. This approach allowed us to encompass the uncertainty associated with the Mt. Morrone fault model by defining a set of plausible rupture scenarios, all compatible with the modeled fault. In order to assess the impact of source uncertainty on ground-motion predictions, we implemented ProbShakemap [Stallone et al., 2024], a Python toolbox designed for rapid earthquake source uncertainty propagation to ground-shaking estimates. Our test case includes all municipalities within the region as Point of Interest (POI) highlighting the importance of understanding ground shaking impact for effective land-use planning and risk mitigation.