Preprints
https://doi.org/10.5194/nhess-2020-63
https://doi.org/10.5194/nhess-2020-63
16 Mar 2020
 | 16 Mar 2020
Status: this preprint was under review for the journal NHESS but the revision was not accepted.

The assessment of earthquake-triggered landslides susceptibility with considering coseismic ground deformation

Yu Zhao, Zeng Huang, Zhenlei Wei, Jun Zheng, and Kazuo Konagai

Abstract. The distance to the surface rupture zone has been commonly regarded as an important influencing factor in the evaluation of earthquake-triggered landslides susceptibility. However, the obvious surface rupture zones usually do not occur in some buried-fault earthquakes cases, which mean lacking of the information about the distance to the surface rupture. In this study, a new influencing factor named coseismic ground deformation was added to remedy this shortcoming. The Mid-Niigata prefecture earthquake was regareded as the study case. In order to select a more suitable model for generating the landslides susceptibility map, three commonly used models named Logistic Regression (LR), Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were also conducted to assess the landslides susceptibility. The performances of these three models were evaluated with the receiver operating characteristic (ROC) curve. The calculated results showed the ANN model has the highest AUC (area under the curve) value of 0.82. As the earthquake triggered more landslides in the epicenter area, which makes it more prone to landslides in further earthquakes, the landslides susceptibility in the epicenter area was also further evaluated.

Yu Zhao, Zeng Huang, Zhenlei Wei, Jun Zheng, and Kazuo Konagai
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Yu Zhao, Zeng Huang, Zhenlei Wei, Jun Zheng, and Kazuo Konagai
Yu Zhao, Zeng Huang, Zhenlei Wei, Jun Zheng, and Kazuo Konagai

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