Risk Assessment of An Earthquake-Collapse-Landslide Disaster Chain by Bayesian Network and Newmark Models

Lina Han, Qing Ma, Feng Zhang, Yichen Zhang, Jiquan Zhang, Yongbin Bao and Jing Zhao
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Lina Han: School of Environment, Northeast Normal University, Changchun 130024, China
Qing Ma: School of Environment, Northeast Normal University, Changchun 130024, China
Feng Zhang: College of Resources and Environment, Jilin Agricultural University, Changchun 130118, China
Yichen Zhang: Jilin Institute of Geological Environment Monitoring, Changchun 130061, China
Jiquan Zhang: School of Environment, Northeast Normal University, Changchun 130024, China
Yongbin Bao: School of Environment, Northeast Normal University, Changchun 130024, China
Jing Zhao: School of Environment, Northeast Normal University, Changchun 130024, China

IJERPH, 2019, vol. 16, issue 18, 1-17

Abstract: Severe natural disasters and related secondary disasters are a huge menace to society. Currently, it is difficult to identify risk formation mechanisms and quantitatively evaluate the risks associated with disaster chains; thus, there is a need to further develop relevant risk assessment methods. In this research, we propose an earthquake disaster chain risk evaluation method that couples Bayesian network and Newmark models that are based on natural hazard risk formation theory with the aim of identifying the influence of earthquake disaster chains. This new method effectively considers two risk elements: hazard and vulnerability, and hazard analysis, which includes chain probability analysis and hazard intensity analysis. The chain probability of adjacent disasters was obtained from the Bayesian network model, and the permanent displacement that was applied to represent the potential hazard intensity was calculated by the Newmark model. To validate the method, the Changbai Mountain volcano earthquake–collapse–landslide disaster chain was selected as a case study. The risk assessment results showed that the high-and medium-risk zones were predominantly located within a 10 km radius of Tianchi, and that other regions within the study area were mainly associated with very low-to low-risk values. The verified results of the reported method showed that the area of the receiver operating characteristic (ROC) curve was 0.817, which indicates that the method is very effective for earthquake disaster chain risk recognition and assessment.

Keywords: risk assessment; earthquake disaster chain; Bayesian Network model; Newmark model; Changbai Mountain volcano (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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