Comparative evaluation of impact-based and hybrid approaches for real time earthquake shaking prediction

Earthquake Early Warning (EEW) systems can provide seconds to tens of seconds of advanced notice before the arrival of destructive seismic waves. Their effectiveness, however, depends on how quickly and accurately each system forecasts ground motion using real-time data. This study compares the performance of two distinct EEW algorithms (PLUM (Kodera et al. in Bull Seismol Soc Am 108:983–1003, 2018, https://doi.org/10.1785/0120170085 ; Kagawa in Front Earth Sci 9, 2021, https://doi.org/10.3389/feart.2021.672613 ) a pure impact-based approach, and a P-wave Shaking Forecast Based EEWS (QuakeUp (Zollo et al. in Earth Space Sci. 10(4), 2023, https://doi.org/10.1029/2022EA002657 ), which is a hybrid method) by simulating the 2016 Mjma 6.6 Central Tottori earthquake. Our offline "playback" of the event demonstrates that PLUM offers consistently high alert accuracy (≥ 90% stations Successfully Alerted) once threshold is exceeded but provides limited lead-times for sites near the epicenter. In some cases, stations up to 30 km from the source received effective warnings too late for significant protective actions. Conversely, QuakeUp could issue alerts as early as 3 s after the origin time, yielding up to 12 s of lead-time at 40 km. However, its accuracy briefly dropped to 64% before converging to 100% by around 12 s, reflecting the time required for magnitude and location estimates to mature. Despite these differences, both algorithms delivered reliable alerts across much of Tottori Prefecture. The results highlight how algorithmic design and station coverage influence warning performance, with PLUM excelling under dense station networks and QuakeUp offering broader, earlier coverage where real-time source parameters can be accurately constrained.