Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides

TL;DR

This study employs a geostatistical model with a latent spatial effect to effectively capture and analyze seismic shaking patterns from earthquake-induced landslides, outperforming models based solely on seismic parameters.

Contribution

The paper introduces a novel use of a latent spatial effect in geostatistical modeling to capture seismic shaking patterns without prior earthquake data.

Findings

LSE accurately reproduces seismic shaking patterns spatially.

Models with LSE outperform seismic parameter-only models.

LSE captures effects beyond seismic measurements, like topographic amplification.

Abstract

In this paper, we investigate earthquake-induced landslides using a geostatistical model that includes a latent spatial effect (LSE). The LSE represents the spatially structured residuals in the data, which are complementary to the information carried by the covariates. To determine whether the LSE can capture the residual signal from a given trigger, we test whether the LSE is able to capture the pattern of seismic shaking caused by an earthquake from the distribution of seismically induced landslides, without prior knowledge of the earthquake being included in the statistical model. We assess the landslide intensity, i.e., the expected number of landslide activations per mapping unit, for the area in which landslides triggered by the Wenchuan (M 7.9, May 12, 2008) and Lushan (M 6.6, April 20, 2013) earthquakes overlap. We chose an area of overlapping landslides in order to test our method on landslide inventories located in the near and far fields of the earthquake. We generated three different models for each earthquake-induced landslide scenario: i) seismic parameters only (as a proxy for the trigger); ii) the LSE only; and iii) both seismic parameters and the LSE. The three configurations share the same set of morphometric covariates. This allowed us to study the pattern in the LSE and assess whether it adequately approximated the effects of seismic wave propagation. Moreover, it allowed us to check whether the LSE captured effects that are not explained by the shaking levels, such as topographic amplification. Our results show that the LSE reproduced the shaking patterns in space for both earthquakes with a level of spatial detail even greater than the seismic parameters. In addition, the models including the LSE perform better than conventional models featuring seismic parameters only.