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This study investigates the missing data problem in the Japan Meteorological Agency catalog of the Kumamoto aftershock sequence, which occurred since April 15, 2016, in Japan. Based on the assumption that earthquake magnitudes are independent of their occurrence times, we replenish the short-term missing data of small earthquakes by using a bi-scale transformation and study their influence on the maximum likelihood estimate (MLE) of the epidemic-type aftershock sequences (ETAS) parameters by comparing the analysis results from the original and the replenished datasets. The results show that the MLEs of the ETAS parameters vary when this model is fitted to the recorded catalog with different cutoff magnitudes, while those MLEs remain stable for the replenished dataset. Further analysis shows that the seismicity becomes quiescent after the occurrence of the second major shock, which can be regarded as a precursory phenomenon of the occurrence of the subsequent $$M_J7.3$$MJ7.3 mainshock. This relative quiescence is demonstrated more clearly by the analysis of the replenished dataset.Graphical abstract(Left 6 panels) Illustration of applying the replenishing algorithm to the short missing of aftershocks in the Kumamoto aftershock sequence. (Right 6 panels) ETAS parameters estimated from the Kumamoto aftershock sequence with different magnitude thresholds. See text for details.

Data completeness of the Kumamoto earthquake sequence in the JMA catalog and its influence on the estimation of the ETAS parameters