## 4 Classification and Risk Assessment Results of Debris Flow in the Study Area
### Risk Assessment Based on Classification Results  
Based on the above clustering analysis results, debris flows are divided into four categories. However, the clustering analysis results only classify debris flows into different categories and which risk level corresponds to each of the four categories of debris flows. The clustering results are not provided, and another judgment is needed. Table 15 shows that, among Class I debris flows, Longcao Gully has the highest synthetic evaluation score of 0.8301, while Meizilin Gully has the lowest synthetic evaluation score of 0.6718. Among Class II debris flows, the synthetic evaluation score of Xiaoniuquan Gully debris flow is the highest at 0.5359, while the synthetic evaluation score of Henghe Gully is the lowest at 0.3963. Among Class III debris flows, Baiyan Gully has the highest synthetic evaluation score of 0.3064, while Shiliangzi Gully has the lowest synthetic evaluation score of 0.2716. Among Class IV debris flows, Feishui Rock Gully has the highest synthetic evaluation score of 0.2692, while Manban Gully has the lowest synthetic evaluation score of 0.2113. Therefore, based on the calculation results, the Class I debris flow in the study area is classified as extremely dangerous (0.6718 \(\leq D_{i}\leq\) 0.8301), the Class II debris flow is classified as highly dangerous (0.3963 \(\leq D_{i}\leq\) 0.5359), the Class III debris flow is classified as moderately dangerous (0.2716 \(\leq D_{i}\leq\) 0.3064), and the Class IV debris flow is classified as low-risk (0.2113 \(\leq D_{i}\leq\) 0.2692). This article compared and analyzed the debris flow risk assessment results with those obtained by the grey correlation and collaborative coupling methods (Table 16). Table 16 shows that the results obtained in this article are consistent with those obtained by the coupling synergy method, generally one level higher than the risk obtained by the grey correlation method. The results obtained by the grey correlation method are mainly medium to low, with a small amount being hazardous, and there is no extreme risk. Compared to the results obtained in this article, they tend to be conservative. The results of the grey correlation method indicate that the possibility of debris flow outbreaks in the study area is minimal. However, the results obtained by the grey correlation method do not match the actual situation of multiple debris flows that have already erupted in the research area. For example, in July 2009, a debris flow broke out in Yushi Gully, depositing some houses (Figures 10 and 11). In 2012, a significant debris flow disaster occurred on August 18 th in Longmenshan Town [64]. In August 2022, a debris flow disaster broke out in Longcao Gully, and on-site investigations also showed that there were multiple stages of debris flow accumulation in most debris flow channels (Figure 12). The evaluation criteria of the grey correlation method are significantly too low, so the evaluation results obtained in this article can better reflect the actual situation of debris flow outbreaks in the study area. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Classification** & **Number of Categories** & **Debris Flow** & _max (D\({}_{i}\))_ & _min (D\({}_{i}\))_ & **Debris Flow Risk Degree** \\ \hline I & 3 & Longcao, Meizilin, Yushi & 0.8301 & 0.6718 & extreme risk \\ II & 4 & Xiaoniuquan, Yanzidong, & 0.5359 & 0.3963 & high risk \\ III & 3 & Shiliangzi, Baiyan, Xujia & 0.2692 & 0.2113 & moderate risk \\ IV & 4 & Feishuiyan, Lianshan, & 0.3064 & 0.2716 & low risk \\ \hline \hline \end{tabular}
\end{table} 
Table 15: Debris flow risk assessment in study area. Figure 11: A Debris flow broke out in Yushi Gully, destroying houses (2009).