Towards an Operational Earthquake Forecasting Model for Europe

The go-to models for developing time-dependent earthquake forecasts are Epidemic-Type Aftershock Sequence (ETAS) models. They model earthquake occurrence as a spatio-temporal self-exciting point process, using basic empirical laws such as the Omori-Utsu law for the temporal evolution of aftershock rate, the Gutenberg-Richter law to describe the size distribution of earthquakes, the exponential productivity law and so on. The main focus and core strength of ETAS lie in modelling aftershock occurrence. An important aspect which holds great potential for improvement is the modelling of background seismicity.

In this study, we focus on the data sets and expert solicitations acquired for building the European Seismic Hazard Model (ESHM) 2020. Since these data sets cover a wide range of space and time, the properties of the earthquake catalogs (completeness magnitude, magnitude resolution, time and space resolution, b-value) vary by region and time period. We address these issues using the model accounting for the time-varying completeness magnitude (Mizrahi et al., 2021) and other adjustments, then develop an ETAS model that allows the background seismicity rate to vary with space and be covariate-dependent. The expectation-maximisation-based algorithm allows for these rates to be given as an input, in our case based on fault locations, estimated long-term seismicity rates and area sources, or estimated during inversion for expert-defined zonations. We test the models retrospectively for self-consistency and pseudo-prospectively to identify the ones that lead to the best operational forecasting model for Europe.