Shannon Entropy as an eruptive precursor: a practical study on Hawai‘i Island from 2017 to 2025

The search for reliable eruptive precursors is a central challenge in volcano monitoring, essential for optimizing volcanic early-warning systems. Recent studies have shown that the Shannon entropy of seismic signals is a promising precursor, capable of forecasting imminent eruptions with high reliability. In addition, cross entropy computed between pairs of seismic stations can help pinpoint the location of an impending eruptive vent.

In this study, we analyse the behaviour of these two entropy measures for the Island of Hawai‘i from 2017 to 2025. We examine eruptions from both Mauna Loa and Kīlauea, yielding forecast lead times of 30 minutes to 24 hours. Differences in these lead times may reflect the complexity of the volcano-structural setting of the island and its underlying volcanic plumbing systems. Highly fractured areas may favour rapid magma ascent, leading to a short eruption warning. Heat maps of cross-entropy across all station pairs in the network enabled precise forecasting of the locations of forthcoming eruptive sources, except when the new vent formed outside the seismic network.