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An Empirical Bayesian Kriging Approach for Site Period Mapping of Santiago Basin, Chile

Description: 

Seismic site classification plays an important role in the estimation of site amplification, which directly influences earthquake-induced damages. Site effects are strongly dependent on site-specific conditions as well as the spatial distribution of the geotechnical parameters in the region. Since the fundamental site period depends on the subsurface condition, surficial maps such as terrain or geology have a high probability of being well constrained only to shallow depths. At the same time, it is hard to find a consistent source of bedrock depth parameters around the globe. The use of geostatistical methods such as ordinary kriging or simple kriging can resolve this issue by relying on a spatial variogram for predictions at unsampled locations. However, uneven, or sparse data distribution usually creates unrealistic patterns. This study proposes the use of the Empirical Bayesian kriging interpolation method for site period mapping in Santiago basin, Chile. A low-precision model using depth to basement is used as prior information and ~200 fundamental site period measurements are considered as precision data within the basin. This study shows that the spatial prediction accuracy can be further improved over the ordinary kriging approach using the Empirical Bayesian kriging technique.

Session: Regional-Scale Hazard, Risk and Loss Assessments [Poster Session]

Type: Poster

Date: 5/3/2024

Presentation Time: 08:00 AM (local time)

Presenting Author: Devjyoti

Student Presenter: No

Invited Presentation: 

Authors