Improving empirical aftershock modeling based on additional source information

Several mechanisms are proposed to underlie earthquake triggering including static stress interactions and dynamic stress transfer. Significant differences of these mechanisms are particularly expected in the spatial distribution of aftershocks. However, testing the different hypotheses is challenging because it requires the consideration of the large uncertainties involved in stress calculations as well as the appropriate consideration of secondary aftershock triggering which is related to stress changes induced by smaller pre- and aftershocks. In order to evaluate the forecast capability of different mechanisms, we take the effect of smaller-magnitude earthquakes into account by using the epidemic type aftershock sequence (ETAS) model where the spatial probability distribution of direct aftershocks, if available, is correlated to alternative source information and mechanisms. We test surface shaking, rupture geometry, and slip distributions. As an approximation of the shaking level, we use ShakeMap data which are available in near real-time after a main shock and thus could be used for first-order forecasts of the spatial aftershock distribution. Alternatively, we test the use of empirical decay laws related to minimum fault distance and Coulomb stress change calculations based on published and random slip models. For comparison, we analyze the likelihood values of the different model combinations in the case of several well-known aftershock sequences (1992 Landers, 1999 Hector Mine, 2004 Parkfield). Our test shows that the fault geometry is the most valuable information for improving aftershock forecasts. Furthermore, we find that static stress maps can additionally improve the forecasts of off-fault aftershock locations, while the integration of ground shaking data could not upgrade the results significantly.