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The kinematic source rupture process of the 2016 Meinong earthquake (Mw = 6.4) in Taiwan was derived from apparent source time functions retrieved from teleseismic S-waves by using a refined homomorphic deconvolution method. The total duration of the rupture process was approximately 15 s, and one slip-concentrated area can be represented as the source model based on images representing static slip distribution. The rupture process began in a down-dip direction from the fault toward Tainan City, strongly suggesting that the rupture had a unilateral northwestern direction. The asperity with an area of approximately 15 × 15 km2 and the maximum slip of approximately 2 m were centered 12.8 km northwest of the hypocenter. Coseismic vertical deformation was calculated based on the source model. Compared with the results derived from InSAR (Interferometric Synthetic Aperture Radar) data, our results demonstrated that the location with maximum uplift was accurately well detected, but our maximum value was just approximately 0.4 times of the InSAR-derived value. It reveals that there are the other mechanisms to affect the vertical deformation, rather than only depending on the source model. At different depths, areas west, east, and north of the hypocenter maintained high values of Coulomb stress changes. This explains the mechanism behind aftershocks being triggered and provides a reference for predicting aftershock locations after a large earthquake. The estimated seismic spectral intensities, including spectral acceleration and velocity intensity (SIa and SIv), were derived. Source directivity effects caused damage to buildings, and we concluded that all damaged buildings were located within a SIa value of 400 gal. Destroyed buildings taller than seven floors were located in an area with a SIv value of 30 cm/s. These observations agree with those on damages caused by the 2010 Jiasian earthquake (ML 6.4) in Tainan, Taiwan.

The Source Characteristics of the Mw6.4, 2016 Meinong Taiwan Earthquake from Teleseismic Data Using the Hybrid Homomorphic Deconvolution Method