A hybrid ETAS-coulomb approach to forecast spatiotemporal aftershock rates

Abstract

Aftershock sequences are an ideal testing ground for operational earthquake forecasting models as they contain relatively large numbers of earthquakes clustered in time and space. To date, most successful forecast models have been statistical, building on empirical observations of aftershock decay with time and earthquake size frequency distributions. Another approach is to include Coulomb stress changes from the mainshock which influence the spatial location of the aftershocks although these models have generally not performed as well as the statistical ones. Here we develop a new hybrid Epidemic‐Type Aftershock Sequence (ETAS)/Coulomb model which attempts to overcome the limitations of its predecessors by redistributing forecast rate from negatively to positively stressed regions based on observations in the model learning period of the percentage of events occurring in those positively stressed regions. We test this model against the 1992 Landers aftershock sequence using three different ETAS kernels and five different models for slip in the Landers earthquake. We also consider two variations of rate redistribution, one based on a fixed value and the other variable depending on the percentage of aftershocks observed in positively stressed Coulomb regions during the learning period. We find that the latter model performs at least as well as ETAS on its own in all tests and better than ETAS in 14 of 15 tests in which we forecast successive 24‐hr periods. Our results suggest that including Coulomb stress changes can improve operational earthquake forecasting models.