## 4 Experimental Results and Model Interpretability Analysis
### Hazard Assessment  
Based on the landslide susceptibility assessment results from the Inception model, a landslide hazard assessment was conducted for the \"25 April 2010, heavy rainfall in Zayu, Tibet.\" The rainfall dataset used was the \"1961-2022 national daily precipitation grid dataset.\" Rainfall data for the corresponding dates were extracted and converted into a unified resolution of 30 m, aligned with the row and column sizes of the model training factor dataset. The maximum, minimum, and average daily rainfall within the study area is shown in Table 8. The daily rainfall data were accumulated to obtain the cumulative rainfall from 22 to 25 April. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Index** & **Dataset** & **Inception** & **BPNN** & **ResNet** & **CNN** & **VGG-16** \\ \hline \multirow{2}{*}{OA/\%} & Training set & 80.213 & 72.326 & 68.568 & 80.014 & 70.431 \\  & Validation set & 78.951 & 71.610 & 66.427 & 78.277 & 68.869 \\ \hline \multirow{2}{*}{Sensitivity/\%} & Training set & 85.017 & 80.752 & 80.634 & 83.626 & 75.341 \\  & Validation set & 82.667 & 78.233 & 78.933 & 81.233 & 73.250 \\ \hline \multirow{2}{*}{\(1/\)MAE} & Training set & 2.324 & 2.745 & 1.806 & 2.268 & 1.907 \\  & Validation set & 2.199 & 1.931 & 1.753 & 2.170 & 1.802 \\ \hline \multirow{2}{*}{\(1/\)RMSE} & Training set & 5.023 & 3.812 & 3.107 & 4.862 & 3.598 \\  & Validation set & 4.751 & 3.522 & 2.979 & 4.603 & 3.212 \\ \hline \end{tabular}
\end{table} 
Table 7: Accuracy evaluation of five models. The threshold for rainfall-induced landslides was divided into five levels: does not occur, beginning to occur, sporadic occurrence, group occurrence, and massive occurrence, corresponding to cumulative rainfall thresholds of 100 mm, 140 mm, 170 mm, and 200 mm [39]. The reclassified results of the cumulative rainfall grid are shown in Figure 12.  
Based on the landslide susceptibility results predicted by the Inception model, a landslide hazard classification table (Table 9) was established, categorizing landslide risk into five levels: low, moderately low, moderate, moderately high, and high. These are abbreviated as L, ML, M, MH, and H in the table. Landslide susceptibility was scored from top to bottom as 5-1; the cumulative rainfall was scored in the same way, and the two scores add up to 8-10 as high (H), 7 as moderately high (MH), 5-6 as medium (M), 4 as moderately low (ML), and 2-3 as low (L). \begin{table}
\begin{tabular}{c c c c} \hline
**Date** & **Minimum Value/mm** & **Maximum Value/mm** & **Average Value/mm** \\ \hline
22 April & 3.09 & 26.41 & 8.21 \\
23 April & 5.08 & 118.60 & 80.74 \\
24 April & 5.26 & 94.78 & 46.33 \\
25 April & 4.65 & 50.49 & 18.75 \\ \hline \end{tabular}
\end{table} 
Table 8: Details of rainfall from 22 to 25 April. Figure 12: Classification map of cumulative rainfall: (**a**) 22 April; (**b**) 23 April; (**c**) 24 April; (**d**) 25 April. Figure 13 shows that as the cumulative rainfall increases daily, the areas with moderate, moderately high, and high landslide hazard levels in Zayu County also increase. The areas with higher landslide hazard levels are mainly distributed in the southern part, where the cumulative rainfall is highest, and there are many areas with high and moderately high landslide susceptibility levels. Overall, the risk of landslides in Zayu County began to increase on 22 April, with a maximum rainfall of 26.41 mm in the area. The maximum rainfall on 23 April was 118.60 mm, an increase of 92.19 mm compared to the 22 April. The maximum rainfall on April 24 was 94.78 mm, when the cumulative rainfall reached 239.79 mm, making the risk of landslides extremely high. After 25 April, the maximum rainfall showed a clear downward trend; the maximum rainfall on 25 April was 50.49 mm, a decrease of 44.78 mm