Summary
A variety of slow slip events at subduction zones have been observed. They can be stress meters for monitoring the stress state of megathrust faults during their earthquake cycles. In this study, we focus on long-term slow slip events (LSSEs) recurring at downdip portions of megathrust faults among such slow earthquakes. Data analyses and simulation studies of LSSEs have so far been executed independently. In atmosphere and ocean sciences, data assimilations that optimally combine data analyses and simulation studies have been developed. We develop a method for estimating frictional properties and monitoring slip evolution on an LSSE fault, with a sequential data assimilation method, the ensemble Kalman filter (EnKF). We executed numerical twin experiments for the Bungo Channel LSSE fault in southwest Japan to validate the method. First, based on a rate- and state-dependent friction law, we set a rate-weakening circular LSSE patch on the rate-strengthening flat plate interface, whose critical nucleation size is larger than that of the patch, and reproduced the observed Bungo Channel LSSEs with recurrence times of approximately 7 yr and slip durations of 1 yr. Then, we synthesized the observed data of surface displacement rates at uniformly distributed stations with noises from the simulated slip model. Using our EnKF method, we successfully estimated the frictional parameters and the slip rate evolution after a few cycles. Secondly, we considered the effect of the megathrust fault existing in the updip portion of the LSSE fault, as revealed by kinematic inversion studies of Global Navigation Satellite System (GNSS) data and added this locked region with a slip deficit rate in the model. We estimated the slip rate on the locked region only kinematically, but the quasi-dynamic equation of motion in each LSSE fault cell includes the stress term arising from the locked region. Based on this model, we synthesized the observed surface displacement rate data for the actual distribution of GNSS stations and executed EnKF estimations including the slip rate on the locked region. The slip rate on the locked region could be quickly retrieved. Even for the actual distribution of GNSS stations, we could successfully estimate frictional parameters and slip evolution on the LSSE fault. Thus, our twin numerical experiments showed the validity of our EnKF method, although we need further studies for actual GNSS data analyses.
Bayesian multi-model estimation for fault slip distribution: the effect of prior constraints in the estimation for slow slip events beneath the Bungo Channel, southwest Japan
