Combining rainfall-induced shallow landslides and subsequent debris flows for hazard chain prediction

• Published in: Catena (Giessen) Vol. 213; p. 106199
• Main Authors: Zhou, Wenqi, Qiu, Haijun, Wang, Luyao, Pei, Yanqian, Tang, Bingzhe, Ma, Shuyue, Yang, Dongdong, Cao, Mingming
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2022
• Subjects: catenas; Coupled model; Debris flows; Hazard chain prediction; Landslides; meteorological data; mountains; prediction; rain; Landslides; Coupled model; Debris flows; Hazard chain prediction
• ISSN: 0341-8162; 1872-6887
• DOI: 10.1016/j.catena.2022.106199

•A coupled model for predicting landslide-debris flow hazard chains was proposed.•The coupled model is capable of predicting the hazard chain by the hour.•The input of landslide area influences the prediction of debris flow.•The rainfall threshold curve supports landslide prediction in areas lacking data. Landslides, debris flows, and other destructive natural hazards induced by heavy rainfall in mountainous regions are sometimes not independent but combined to form a disaster chain. Based on the integral link between the triggering of the landslide and the subsequent debris flow, we propose an approach that combines the Transient Rainfall Infiltration and Grid-Based Regional Slope Stability (TRIGRS) model and the Rapid Mass Movements Simulation (RAMMS) model to achieve hourly hazard prediction. The results indicate that the TRIGRS model performed well in predicting the spatial distribution of the shallow landslides, with a success rate of 81.86%. Thus, it is reasonable to use it as the initial input for debris flow simulations. The relationship between the landslide area and the accumulated rainfall obtained using the TRIGRS model is a power-law relationship, which provides a reference for regions that lack rainfall data to predict the material source of a debris flow. The coupled model was found to have a good accuracy of 76.77% in simulating the debris flow. This was close to the debris flow simulation based on the interpreted landslides, and it still produced reasonable results and a more practical value. Furthermore, the proposed coupled model can dynamically predict disasters by the hour based on actual rainfall events. Therefore, the results of this study help provide a more complete hazard prediction picture for rainfall-induced landslide-debris flow hazards in mountainous regions.