[S-SS08] Statistical seismology and underlying physical processes

[SSS08-P14] Estimating effective normal stress during SSE in Bungo channel from slip velocities and shear stress variations

*Yojiro Sasagawa¹, Toshinori Sato² (1.Graduate School of Science and Engineering, Chiba University, 2.Graduate School of Science, Chiba University)

Slow slip events (SSEs) are quasistatic phenomena which slip very slowly along the plate surface and which do not radiate seismic energy. They have been reported since Global Network Satellite System (GNSS) observations began in the 1990s. It is important to investigate stress state when SSEs occur because they are newly tectonic mechanism along plate boundary. Theoretical analysis using Rate- and state-dependent friction law have shown quasistatic slip behaviors following velocity weakening (e.g. Rice and Tse, JGR, 1986). Kobayashi and Sato (GRL, 2021, https://doi.org/10.1029/2021GL095690) estimated spatiotemporal slip distributions of the BOSO SSEs using GNSS data and plotted their shear stress change vs. slip velocity. Most trajectories are similar to theoretical stable trajectories whose gradients are equal to the product of the friction coefficients of the slipping plate (a-b) and the effective normal stress (σ_n). In this study, we estimated effective normal stress from SSEs in Bungo Channel, Japan. This region was detected four SSEs until now. We used daily F5 data by the Geospatial Information Authority of Japan (GSI). First, GNSS data was removed liner trends and seasonal variations. Next, we smoothed the detrended data and divided displacements into every-month. From every-month displacements, we estimated the spatiotemporal slip distributions for the SSE. To calculate shear stress change, we used the Coulomb 3.3 program by the U. S. Geological Survey (USGS). We plotted shear stress change vs. slip velocity and estimated effective normal stress from gradient of the trajectories during slip acceleration. As a result, the value of σ_n was 20-30 MPa for 2018 event. We analyze other three events now and will compare properties of each events. Acknowledgment. We used daily F5 data by GSI, and the Coulomb 3.3 program by the USGS. This work was supported by JSPS (23K03541).