At the 2016 Kumamoto earthquake, surface ruptures were observed not only along the Futagawa fault, where main ruptures occurred, but also along the Hinagu fault. To estimate the slip distribution on these faults, we extend a method of nonlinear inversion analysis (Fukahata and Wright in Geophys J Int 173:353-364, 2008 ) to a two-fault system. With the method of Fukahata and Wright ( 2008 ), we can simultaneously determine the optimal dip angle of a fault and the slip distribution on it, based on Akaike’s Bayesian information criterion by regarding the dip angle as an hyperparameter. By inverting the InSAR data with the developed method, we obtain the dip angles of the Futagawa and Hinagu faults as 61° ± 6° and 74° ± 12°, respectively. The slip on the Futagawa fault is mainly strike slip. The largest slip on it is over 5 m around the center of the model fault (130.9° in longitude) with a significant normal slip component. The slip on the Futagawa fault quickly decreases to zero beyond the intersection with the Hinagu fault. On the other hand, the slip has a local peak just inside Aso caldera, which would be a cause of severe damage in this area. A relatively larger reverse fault slip component on a deeper part around the intersection with Aso caldera suggests that something complicated happened there. The slip on the Hinagu fault is almost a pure strike slip with a peak of about 2.4 m. The developed method is useful in clarifying the slip distribution, when a complicated rupture like the Kumamoto earthquake happens in a remote area. Slip distribution of the Kumamoto earthquake. Slip on the Futagawa fault ( left ) and the Hinagu fault ( right ) projected onto a vertical plane is shown. The standard deviation of each fault slip is also shown at the bottom left (strike-slip component) and right (dip-slip component) diagrams. The contour interval for both the slip and standard deviation is 0.5 m. Vertical broken lines show the location of intersection with the other fault. NE and SW denote northeast and southwest, respectively
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