Volcanic Eruption Forecasting Using Shannon Entropy: Multiple Cases of Study

Abstract

The search for pre-eruptive observables that can be used for short-term volcanic early warning remains a scientific challenge. Pre-eruptive patterns in seismic data are usually identified by analyzing seismic catalogues (e.g., the number and types of recorded seismic events), the evolution of seismic energy, or changes in the tensional state of the volcanic medium as a consequence of changes in the volume of the volcano. However, although successful volcanic predictions have been achieved, there is still no generally valid model suitable for a large range of eruptive scenarios. In this study, we evaluate the potential successful use of Shannon entropy as short-term volcanic eruption forecasting extracted from seismic signals at five well studied volcanoes (Etna, Mount St. Helens, Kilauea, Augustine, and Bezymianny). We identified temporal patterns that can be used as short-term eruptive precursors. We quantified how the Shannon entropy drops several hours before the eruptions analyzed, between 4 days and 12 h before. When Shannon entropy is combined with the temporal evolution of other features (i.e., energy, kurtosis, and the frequency index) and complementary information on types of seismic sources, the meaning of physical changes in the volcanic system could be obtained. Our results show that pre-eruptive variation in Shannon entropy offers is a confident short-term volcanic eruption forecasting tool.