Abstract Monitoring and predicting fault slip behaviors in subduction zones is essential for understanding earthquake cycles and assessing future earthquake potential.We developed a data assimilation method for fault slip monitoring and the short-term prediction of slow slip events, and applied to the 2010 Bungo Channel slow slip event in southwest Japan.The observed geodetic data were quantitatively explained using a physics-based model Kids Bodysuit with data assimilation.We investigated short-term predictability by assimilating observation data within limited periods.Without prior constraints on fault slip style, observations solely during slip acceleration predicted the occurrence of a fast slip; however, the inclusion of slip deceleration data successfully predicted a slow transient slip.
With prior constraints to exclude unstable slip, the assimilation of data after slow slip event occurrence also predicted a slow transient slip.This N-Acetyl Cysteine (NAC) study provides a tool using data assimilation for fault slip monitoring and prediction based on real observation data.Graphical Abstract.