A multi-parameter monitoring system and early warning model for rainfall-induced landslides

Landslides are one of the most devastating natural disasters, with most being triggered by rainfall. Efficient monitoring and effective prevention of such slope failures are of paramount importance. This study focuses on the K3278 slope of the Daqing-Guangzhou Expressway and examines the characteristics of disasters that occurred during the course of its construction and operation. A multi-parameter monitoring system for rainfall-induced landslides is established, covering environment, displacement, and force monitoring. The early warning model comprises four distinct stages: long-term warning, mid-term warning, short-term warning, and imminent failure warning, with four levels of severity: attention, caution, alert, and alarm. The monitoring system and the warning model successfully predicted three slope hazards. Combining slope monitoring data and landslide field investigation, the destructive features and spatiotemporal evolution patterns of these hazards are analyzed. Taking the landslide event that occurred on June 20th, 2022, as a case study, the accuracy, timeliness, and effectiveness of the warning are discussed, further confirming the efficiency of the multi-parameter warning model.