Modeling Slow slip events on the Hikurangi subduction zone using Independent Component Analysis

Abstract

In this study, we model Slow Slip Events (SSEs) occurring on the Hikurangi subduction zone, New Zealand, during the 2009-2022 time period based on the horizontal and vertical position time series of 130 GNSS stations. To do so, we divide the time series into two periods, one before and one after the 2016 Kaikoura earthquake. In both cases, the time series are corrected from instrumental and co-seismic offsets, and from a linear trend. The signal decomposition technique variational Bayesian Independent Component Analysis is then applied to the time series in order to separate the surface deformation signal due to SSEs from other sources of deformation. The independent components related to SSEs are linearly inverted for slip on the fault before being recombined. The method allows to model the slip history due to SSEs but relative to a secular slip trend which is dependent on the time period used to initially detrend the GNSS position time series and on the number of potential SSE within this period. The secular trend as well as the SSEs detection threshold vary thus spatially. To minimize the impact of the heterogeneous detection threshold, we use an iterative process which combines a SSE detection procedure based on slip rate with an inter-SSE linear trend correction determined from the previous iteration of SSEs’ detection. This allows to extract a catalog of transient events as well as to estimate the inter-SSE loading rate which is used to evaluate, with a Bayesian approach, the coupling map of the Hikurangi subduction zone. We then characterize those transient events (e.g. magnitude and duration), taking care to separate short-term SSEs occurring in the shallow part of the subduction (<20 km depth) from the long-term ones occurring in the deeper portions of the fault (>20 km depth). Lastly, we discuss about the slip budget and the impact of the Kaikoura earthquake on the slip-dynamics of the fault.