Abstract
The aim of this project was to produce an earthquake–landslide debris flow disaster chain susceptibility map for the Changbai Mountain region, China, by applying data-driven model series and parallel model and Bayesian Networks model. The accuracy of these two models was then compared. Parameters related to the occurrence of landslide and debris flow disasters, including earthquake intensity, rainfall, elevation, slope, slope aspect, lithology, distance to rivers, distance to faults, land use, and the normalized difference vegetation index (NDVI), were chosen and applied in these two models. Disaster chain susceptibility zones created using the two models were then contrasted and verified using the occurrence of past disasters obtained from remote sensing interpretations and field investigations. Both disaster chain susceptibility maps showed that the high susceptibility zones are situated within a 10 km radius around the Tianchi volcano, whereas the northern and southwestern sections of the study area comprise primarily very low or low susceptibility zones. The two models produced similar and compatible results as indicated by the outcomes of basic linear correlation and cross-correlation analyses. The verification results of the ROC curves were found to be 0.7727 and 0.8062 for the series and parallel model and BN model, respectively. These results indicate that the two models can be used as a preliminary base for further research activities aimed at providing hazard management tools, forecasting services, and early warning systems.
Highlights
In some countries of the world, earthquakes may constitute catastrophic natural disasters.Each earthquake may induce diverse secondary disasters and cause many deaths and injuries
Based on the above studies, this study aims to apply the data-driven model to evaluate and compare earthquake-landslide-debris flow disaster chain susceptibility zones in the Changbai Mountain area, China
Theearthquake-landslide earthquake-landslide and and earthquake-landslide-debris susceptibility maps obtained from the series and parallel model are shown in
Summary
Each earthquake may induce diverse secondary disasters and cause many deaths and injuries. In 2008, a catastrophic earthquake with Ms (surface wave magnitude) 7.9 occurred in Sichuan, China, triggering. On February 27, 2010, a disastrous earthquake with Ms 8.8 occurred in a coastal region of central Chile, resulting in 525 fatalities and approximately 20 billion dollars in economic losses, and is estimated to have influenced the lives of over 8 million people [3,4]. 19,000 fatalities and 200–300 billion dollars in economic losses [5,6]. The damages and losses caused by disaster chains are believed to often be much greater than those caused by the individual disasters themselves [11,12]. Disaster chain susceptibility assessment has, become increasingly important and urgent
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