A Method for Estimating the Coefficient of Variation of Large Earthquake Recurrence Interval Based on Paleoseismic Sequences
2025
Xing Guo | Zhijun Dai
The coefficient of variation &alpha: is a critical parameter in the Brownian Passage Time (BPT) model, used to quantify the variability of large earthquake recurrence intervals. In this paper, a new estimation method is proposed for &alpha: based on paleoseismic sequences across multiple faults within a given tectonic region. By integrating Monte Carlo simulations with a Bayesian framework, the method assesses the probability distribution of &alpha: without assuming that the sample average recurrence interval equals the true mean &mu:, thereby avoiding epistemic bias. To validate the method, 1,000,000 simulations were conducted in two study areas of differing spatial scales. In the Western Qilian Mountains-Hexi Corridor, the posterior mean of &alpha: is 0.36 (without dating uncertainty) and 0.34 (with uncertainty). Expanding the analysis to 29 faults across western China, the estimated &alpha: increases to 0.39 (without dating uncertainty) and 0.36 (with uncertainty), with substantially reduced uncertainty bounds. The results reveal that increasing the number of paleoseismic sequences significantly reduces the uncertainty in estimating &alpha:, while considering dating uncertainty has only a minor impact. The methodology provides a robust framework for deriving region-specific recurrence variability parameters and proves particularly valuable for tectonically active regions where individual fault records are sparse but collectively form comprehensive datasets across multiple fault systems.
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