Quantitative Hazard Prediction of Rainfall-Induced Shallow Landslides Considering Triggering and Predisposing Factors: A Case of Natural Terrain Landslides in Hong Kong

In recent years, torrential rainfall has triggered numerous shallow landslides in southeastern China, especially in Hong Kong. Therefore, giving a spatial-temporal hazard prediction for rainfall-induced shallow landslides in Hong Kong on a fine-grained scale is imperative. Nowadays, most empirical hazard prediction methods are qualitative and consider only rainfall features. The generated prediction results lack sufficient spatial details, and the areas of high and very high hazard account for a large proportion. By improving the qualitative empirical hazard prediction method based on frequency statistics, this article proposes a quantitative natural terrain landslide hazard prediction model for Hong Kong based on antecedent rainfall intensity, maximum 24-h rolling rainfall intensity, and landslide susceptibility, which simultaneously considers landslide triggering and predisposing factors. The spatial accuracy and fineness of the prediction results generated by the proposed method are enhanced compared to those predicted by the qualitative method based on rainfall features, demonstrating its efficacy and benefits.