Ambient Seismic Noise Analysis Associated with the 2010 Eruption of Merapi Volcano Using Temporal Variations of Randomness and Background Noise

Abstract

<jats:p>We present the combination of permutation entropy (PE) and power spectral density (PSD) analysis on continuous seismic data recorded by short-period seismic stations during the 2010 Merapi volcano eruption. The calculation of PE aims at characterizing the randomness level in seismic noise, while the PSD parameters use to detect the background noise level in various frequency bands. It was previously observed that a significant reduction of randomness before the volcano eruption could be indicated as one of the short-term precursors due to the lack of high frequencies (&gt;1 Hz) in the noise wave-field caused by high absorption losses as the hot magma uprises to the upper crust. The results show no significant reduction in signal randomness before the eruption series. The characteristic of events during the preeruptive period and the crisis tends to be chaotic (PE in the range 0.9 to 1). Further calculations show that the standard deviation in PE decreased in four days before the first eruption onset on 26 October. PE was stable at the highest values (very close to 1) and gradually returned to the previous fluctuation after the eruption onset. The level of background noise in the low- and high-frequency bands appeared to have the same tendency. The two main eruptions correspond to the two highest peaks of noise levels.</jats:p>

SEISMONOISY: A Quasi-Real-Time Seismic Noise Network Monitoring System

“…Vila et al [ 85 ] used the PSD level in the near-real-time monitoring applications of several active volcanoes, including Villarrica volcano (Chile), Tungurahua volcano (Ecuador), and Teide volcano (Spain). Rakhman et al [ 86 ] observed how the temporal variation in the PSD level for different frequencies can describe the intensity of the event prior of the eruption. Therefore, continuous noise level monitoring can be a useful tool for understanding noise variation in terms of both intensity level and frequency contribution over time.…”

Permutation entropy variation for 2007 effusive dome-forming eruption period of Kelud Volcano, Indonesia

“…in 2013 summarized several studies of PE on various fields showing that most of them used 𝑚𝑚 = 3-8, 𝐿𝐿 from tens to hundreds for time series from measurements of dynamical processes being observed at a fixed rate per unit time, 𝐿𝐿 = 1-5 for time series from measurements of processes that possess an inherent cycle represented by triggering events [10]. Previous studies such as [6] used 𝑚𝑚 = 5 and 𝐿𝐿 = 5 for monitor the 1996 Gjálp eruption; the same values for m and L were adapted by [11] to study the 2010 Merapi eruption; [5] applied 𝑚𝑚 = 5,6 and 𝐿𝐿 = 1,2,3,4,5 for monitor the January 2011 Shinmoedake eruptions sequence; [12] utilized 𝑚𝑚 = 3,4,5 and 𝐿𝐿 = 4,5,6 for study the 2014 Kelud eruption. Thus, we used variation of 𝑚𝑚 = 3,5 and 𝐿𝐿 = 2,3,4,5 to perform permutation entropy in this study.…”

VEVCC program for concatenation of volcanic events based on cross-correlation analysis

“…These events can have major implications for the safety and well-being of nearby populations, as they can trigger volcanic eruptions and other harmful phenomena. To effectively mitigate the risks associated with volcano-tectonic events, it is crucial to develop robust and reliable methods for detecting and predicting these events [1][2]. One widely used method for monitoring and detecting volcano-tectonic events is through the analysis of seismic signals [3].…”