Accurate, readily available shaking estimates can improve situational awareness and rapid response efforts following a major earthquake. The spatial distribution of shaking relative to population and infrastructure has major implications for expected fatalities, damage, and disruptions. For large earthquakes, the location, size, and orientation of the causal fault plane (i.e., fault finiteness) play primary roles in determining the distribution of shaking. However, such a description of the causal fault is difficult to establish in the immediate aftermath of a major event, when observations are typically sparse and uncertain. However, during the time window between an event’s detection and the completion of quantitative constraints on the source, tectonic context can provide evidence for the rupture’s likely spatial orientation, thereby improving shaking estimates prior to formal finite-fault inversion results. Here, we propose a new method using tectonic context to describe a constrained, but still uncertain, source to improve early shaking estimates for large earthquakes. We demonstrate its implementation in the U.S. Geological Survey ShakeMap software by applying the proposed method to a catalog of 40 large (Mw>7), impactful global events from 2018 to 2026 and present an analysis of the results. We find that for 18 of the catalog events, the ShakeMap could be automatically constrained based on the seismotectonic context, whereas 14 events would require expert user input to determine whether a constrained approach is appropriate, and 8 events would not benefit from a constrained approach (but could be automatically identified). The results show that using seismotectonic context to constrain the source can substantially improve shaking estimates in the immediate minutes to hours following a major earthquake. We show a detailed comparison of the proposed (constrained) approach to the existing (unconstrained) approach for four earthquakes, each occurring in a distinct tectonic environment, to highlight the advantages and limitations of the method’s application.
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Yin et al. (2026) studied this question.
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