Adding strain rate information into a short-term seismicity model improves forecasting performances: the case of Campi Flegrei, Italy

Campi Flegrei is a large active volcanic caldera in southern Italy, currently undergoing a prolonged phase of unrest that began in 2005, characterized by ground uplift and an increase in seismicity. Classical short-term seismicity models, such as the temporal Epidemic Type Aftershock Sequence (ETAS) model, rely exclusively on earthquake catalog data and do not incorporate external forcing mechanisms like crustal deformation. In this study, we extend the ETAS model by integrating strain rate information derived from GNSS measurements, allowing the background rate to vary in time through a data-driven convolution with an empirically estimated response kernel. Using eleven years of observations (2013-2024), we compare the forecasting performance of the classical and deformation-driven ETAS models. Our results show that including strain rate significantly improves forecasting ability, as evidenced by a lower Akaike Information Criterion (AIC). This finding suggests that incorporating geodetic signals into seismicity models enhances their physical realism and predictive skill, providing a promising path toward Operational Earthquake Forecasting in active volcanic regions.