Seismic-based detection, location and identification of volcano-induced landslides: a feasibility study based on the 2018 Anak Krakatau volcano flank collapse

Abstract

The 22 December 2018 Anak Krakatau volcanic flank collapse triggered a devastating tsunami along the Sunda Strait, highlighting the need for an early warning system to detect both volcanic collapse and landslide-triggered tsunami from seismic data. Seismically, massive landslides exhibit a deficiency in high-frequency radiation compared to tectonic earthquakes, classifying them as long-period events. In order to use seismic signals for tsunami early warning, the analysis must rely heavily on stations at close distances, particularly because slower-traveling surface waves are required for a good location. In this study, we used spectral analysis to distinguish the 2018 flank collapse from typical tectonic earthquakes and utilized long-period back-projection (40–70 s) of surface wave envelopes to assess its location. Using the Indonesian seismic network, we conducted spectral analysis of the first 100 s of seismic data, with recordings from epicentral distances of 1.0°–2.5°. We confirmed a systematic deficiency of high frequencies in landslide events, enabling the use of a simple frequency ratio to discriminate between earthquakes and landslides. The location was then determined through back-projection within 3 minutes after the event initiation. Our results indicate that the Indonesian seismic network is viable for back-projection, with expected response times within 3–4 minutes at volcanoes with high tsunami potential due to subaerial flank collapse. We conclude by considering practicalities of implementing this approach in operational tsunami early warning systems.