## 4 Discussion  
### Importance of Effective Antecedent Precipitation in Landslide Disaster Prediction  
According to the literature review in Section 1, previous research on landslide susceptibility assessments identified that precipitation and particularly its complex spatiotemporal distribution are an important triggering factor of landslide disasters [71]. Most previous  
Figure 10: Amplification and validation of the 20-year landslide susceptibility map based on XGB modeling. studies have incorporated annual average precipitation into landslide susceptibility assessments [72; 73]. While this approach captures the spatial distribution of precipitation, it fails to reveal the impact of specific landslide events. Other studies have considered daily and hourly precipitation as influencing factors [74] to analyze individual landslide events, but they do not account for large-scale landslide hazards. In contrast, EAP, combined with different return periods, reflects the cumulative impact of precipitation on landslides across various temporal scales. Specifically, it accounts for the temporal decay of rainfall, providing a more accurate assessment of its effect on slope stability. EAP is a precipitation gauging measure, which considers its cumulative effects and measures the degree of soil moisture saturation. According to [PERSON] [75], there is a strong exponential relationship between soil moisture and antecedent precipitation during the early stages of landslides. This further emphasizes that EAP is indispensable for landslide prediction. [PERSON] [76] improved landslide early warning performance by including antecedent soil moisture. In particular, it was shown that, in cases where the soil moisture has a very low initial value, intense precipitation is able to trigger a landslide, while less intense precipitation can trigger landslides once the soil is already wet. In this study, the RF analysis identified EAP as the most influential factor in landslide susceptibility, surpassing all other variables. This finding supports the hypothesis that EAP is a crucial component in landslide susceptibility mapping. The present study further adds innovation to the field of landslide susceptibility mapping by introducing return periods and making susceptibility assessments for the 5-year, 10-year, 20-year, and 50-year intervals. This is an approach that accounts for the local geographic conditions and the spatial distribution characteristics of landslide events for different precipitation intensities. In particular, by developing multitemporal susceptibility maps, we gain insight into the dynamic evolution of landslide risk, which helps identify potential high-risk areas under different precipitation scenarios. The approach used in this paper is particularly well suited to hilly and mountainous regions with lush vegetation and abundant rainfall. In such environments, intense and frequent precipitation events gradually saturate the soil, and EAP indicators help effectively capture this process [77; 78]. As a result, the landslide susceptibility model incorporating EAP performs optimally in these humid, vegetated, and hilly terrains, where the cumulative antecedent rainfall plays a decisive role in slope stability [79; 80]. The selection of the EAP time window also plays a critical role in landslide prediction. Although there is currently no universally accepted standard for determining the optimal window length, existing studies suggest that a 10-day window performs well in humid subtropical regions. For instance, [PERSON] [81] adopted a 10-day EAP window in a study on landslide disasters in Sichuan Province and achieved favorable results. Similarly, [PERSON] [82], using data from Zhejiang Province, proposed a method based on a power-law relationship between precipitation and landslide occurrence, confirming the applicability and accuracy of the 10-day window for landslide prediction.