Objectives  Geological hazards not only cause serious economic losses and ecological damage, but also threaten the survival of mankind. The evaluation of geological hazard susceptibility is the basis of risk assessment of geological hazards. Previous studies focused on the selection of susceptibility assessment methods, but less on how to classify the susceptibility index of geological hazards. However, there is no good quantitative classification standard for the susceptibility of geological hazards in the current research results.

  Methods  Taking Wenchuan County of Sichuan Province as an example, twelve widely used factors affecting geological hazard susceptibility was selected, and the susceptibility assessment was carried out by using the information quantity model. The evaluation accuracy of the model was tested by the success rate curve. We proposed a quantitative classification standard for susceptibility. The susceptibility index is a cumulative curve of the proportion of geological hazards in descending order, and the susceptibility index is divided into five intervals: 5% of historical disaster points (low-prone), the remaining 10% (medium-prone), the remaining 20% (high-prone), and the remaining 65% (very-high).

  Results  The method of cumulative proportion subsection of historical geological hazards was compared with other eight methods and the accuracy of classification is verified. The results showed that the evaluation accuracy of the model was checked by two methods of validating the sample success rate curve and the non-disaster point sample success rate curve, and the rationality of the prediction results of the evaluation model was determined. The cumulative proportion subsection method of historical geological hazards showed good reasonableness in three ways: The proportion accuracy verification of vulnerable classification area, the frequency ratio accuracy verification of geological hazards and the location classification accuracy verification of geological hazards. It was the best classification standard in nine classification methods.

  Conclusions  The quantitative classification standard for the susceptibility of geological hazards established in this article has a good application effect, but this standard needs more examples to verify. Geological hazard susceptibility evaluation is based on a good factor classification. Research work needs not only to focus on scientific and advanced evaluation methods, but also basic research on how to select factors and rational classification of factors.