Identification of temporal patterns in the seismicity of Sumatra using Poisson Hidden Markov models


Published: 16 May 2014
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On 26 December 2004 and 28 March 2005 two large earthquakes occurred between the Indo-Australian and the southeastern Eurasian plates with moment magnitudes Mw=9.1 and Mw=8.6, respectively. Complete data (mb≥4.2) of the post-1993 time interval have been used to apply Poisson Hidden Markov models (PHMMs) for identifying temporal patterns in the time series of the two earthquake sequences. Each time series consists of earthquake counts, in given and constant time units, in the regions determined by the aftershock zones of the two mainshocks. In PHMMs each count is generated by one of m different Poisson processes that are called states. The series of states is unobserved and is in fact a Markov chain. The model incorporates a varying seismicity rate, it assigns a different rate to each state and it detects the changes on the rate over time. In PHMMs unobserved factors, related to the local properties of the region are considered affecting the earthquake occurrence rate. Estimation and interpretation of the unobserved sequence of states that underlie the data contribute to better understanding of the geophysical processes that take place in the region. We applied PHMMs to the time series of the two mainshocks and we estimated the unobserved sequences of states that underlie the data. The results obtained showed that the region of the 26 December 2004 earthquake was in state of low seismicity during almost the entire observation period. On the contrary, in the region of the 28 March 2005 earthquake the seismic activity is attributed to triggered seismicity, due to stress transfer from the region of the 2004 mainshock.

Supporting Agencies


Orfanogiannaki, K., Karlis, D., & Papadopoulos, G. A. (2014). Identification of temporal patterns in the seismicity of Sumatra using Poisson Hidden Markov models. Research in Geophysics, 4(1). https://doi.org/10.4081/rg.2014.4969

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