Testing various seismic potential models for hazard estimation against a historical earthquake catalog in Japan

Abstract

The classic zoning method and spatial smoothing of seismicity were used with seismicity, GPS, and late Quaternary fault data to develop time-invariant seismic potential models of shallow crustal earthquakes in the Japanese islands that were then tested against a 400-year Japanese historical earthquake catalog. The results demonstrated that the models so developed for seismic hazard estimation did not necessarily reproduce the observed seismicity. In some cases they were even worse than the Reference Model that assumes a uniform earthquake potential over all of the Japanese islands. A subsequent analysis of the original dataset once it had been divided into two subsets based on time indicated that the present-day spatial distribution of small earthquakes and surface horizontal strain are much affected by previous large earthquakes. Two sources of information were the most effective: regionalized seismicity of small earthquakes and the active fault data. Two models using each of them were not only successful, but also robust. A model combining the distributions of small and moderatesize earthquakes proposed by Frankel in 1995 was also effective for modeling the distributed sources, which are unrelated to the faults. In this study, we tested the spatial variation of the likelihood of large earthquakes with M ≥ 6.8.

Analysis of Changes in Seismicity Pattern for Probabilistic Seismic Hazard Analysis (PSHA) and Mitigation: Mapping Probability Difference before the Large Earthquake and Its Implementation in PSHA & Mitigation around Northern Sumatra

“…Following the previous study (Triyoso and Shimazaki, 2012, Triyoso et al, 2020a, 2020b, the PE of the annual peak ground motion of the horizontal component denotes by u at the position of a particular observation point due to the source event on the k-th grid which is assumed to have a Poisson distribution is given by: (u o , D k ) is the GMPE model selected and applies to a particular source model. The probability distribution of peak ground motion (PGA or PGV) at the observation point position is determined by calculating the total probability of all influence sources of a given radius and is estimated by the following equation.…”

“…One method that is often applied to extract clustering models is by applying seismicity smoothing using a Gaussian function to earthquake catalog data (Frankel, 1995). Some previous studies have implemented the above algorithm for example, (Frankel 1995, Petersen et al 2008, Triyoso & Shimazaki, 2012, Triyoso et al 2020a, Triyoso et al 2020b).…”

Correlation Dimension and Seismic Quiescence around Northern Sumatra 

“…Following the previous study, the seismicity smoothing algorithm using the Gaussian function approach, for example, (Frankel 1995, Petersen et al 2008, Triyoso & Shimazaki, 2012, Triyoso et al 2020a) is…”

Seismic Hazard Function (SHF) study of coastal sources of Sumatra Island: SHF evaluation of Padang and Bengkulu cities

“…Frankel (1995) proposed spatial smoothing of instrumentally recorded seismicity by combining small and moderate earthquakes with uniform background seismicity to avoid the subjective judgment necessary for drawing seismic source zones where causative structures of seismicity are largely unknown. Triyoso and Shimazaki (2012) proposed using a combination of the seismicity smoothing developed by Frankel (1995) and surface strain rate deduced from GPS data to estimate the potential seismic model for seismic hazard study and analysis. All proposed models are intended to improve the estimation of the seismic hazard in an area where the period of earthquake catalog observation is relatively short, GPS stations are rare, and the knowledge of Late Quaternary faults is even less.…”