Permutation entropy variations in seismic noise before and after eruptive activity at Shinmoedake volcano, Kirishima complex, Japan

Abstract

Permutation entropy (PE) is a complexity metric that encodes a time series into sequences of symbols and can be used to decipher between deterministic and stochastic behavior. This study investigates PE variations in seismic noise during three eruption cycles in 2011, 2017, and 2018 at Shinmoedake volcano, Japan. The volcano is monitored by a dedicated seismic network and by infrasound microphones that recorded continuously during the aforementioned eruptions. The frequency range 1–7 Hz was used in order to infer temporal changes of PE in seismic noise and minimize any human contributions. The results showed that PE values decreased before the occurrence of each eruption. By combining these results with other observations we can attribute this decrease in PE to two reasons: first, to the occurrence of volcanic tremor that is a deterministic signal, and second, to magma migration at shallower depth beneath Shinmoedake which can attenuate high-frequency seismic waves and thus result in a less stochastic signal. PE also exhibited a spike-like increase just before the onset of the three eruptions. In 2011 and 2017, this feature was probably associated with bubble growth and collapse due to the interaction between the aquifer and high temperature magma. In 2018 the aquifer had mostly evaporated; hence, the spike in PE values was likely generated by fracturing of solidified magma within the conduit as fresh magma was pushing its way upwards. These results show that PE is a potentially useful tool for monitoring seismic noise at volcanoes and can contribute toward forecasting volcanic eruptions in conjunction with other widely used methodologies. Graphical Abstract

Dynamical changes of seismic properties prior to, during, and after 2014–2015 Holuhraun Eruption, Iceland

“…Therefore, not only Sudibyo et al (2022) can observe a high correlation between PE and the hypocentral distance between seismic event's source and the seismic station, they can also use PE to accurately predict the geyser's eruptions. Konstantinou et al (2022) reported a consistently decreasing PE prior and during 3 eruptions in Shinmoedake, a stratovolcano in Japan, which is associated to the dominant occurrence of the pre-and eruptive tremor. In Shinmoedake, as magma moves to the shallower depth and the higher frequency of the seismic events get attenuated, PE drops before the eruption starts.…”

“…After the main eruption starts, the eruptive tremor dominates the 6 months of eruption, and we observed decreasing values of PE and mean IF, while PPE increases. Volcanic tremors have been reported to have a low PE due to their low dominant frequency and narrow spectral distribution (Konstantinou et al, 2022). The eruptive tremor in Holuhraun has most energy in a low and narrow frequency band ranging from 0.8 to 2.5 Hz (Eibl et al, 2017b).…”

“…As magma reaches the surface, magma interaction with the shallow subsurface can generate tremor and/or long period signal. When a pre-eruptive tremor and/or long period signal is present, they exhibit a more regular oscillation and are narrow banded in frequency, and hence PE is reported to drop (Konstantinou et al, 2022).…”

Seismic background level growth can reveal slowly developing long-term eruption precursors

“…Analyzing non-volcanic persistent noise using seismic interferometry 24,25 or permutation entropy 26,27 could extract subtle underground changes prior to eruptions. These studies raised a hope that we may observe seismological precursors for any eruption with adequate monitoring systems and analytical techniques.…”

Seismic background level (SBL) growth can reveal slowly developing long-term eruption precursors

“…Vila et al 25 , 26 proposed to monitor the base level noise seismic spectrum (BLNSS) to detect early signals of volcanic unrest and found that BLNSS gradually increased over 10 months before ash eruptive episodes at Llaima volcano, Chile, in April, 2003 25 . Analyzing non-volcanic persistent noise using seismic interferometry 27 , 28 or permutation entropy 29 , 30 could extract subtle underground changes prior to eruptions. These studies raised a hope that we may observe seismological precursors for any eruption with adequate monitoring systems and analytical techniques.…”