## 1 Introduction  
China has many mountainous areas, complex terrain, and structural development, and the frequent occurrence of severe weather, such as heavy rainfall, makes the number of casualties and economic losses caused by geological disasters, such as landslides, collapses, debris flows, and ground subsidence, higher in the world [1; 2; 3]. According to the National Geological Hazard Bulletin issued by the Ministry of Natural Resources of the People's Republic of China, the number of landslide disasters (54,257) accounted for nearly 71% of the total number of geological disasters (76,845) between 2012 and 2019 [4; 5]. Rainfall is one of the main factors inducing landslides; influenced by the southeast monsoon and southwest monsoon climate, rainfall in most areas of China is mainly concentrated in May-September, and the number of geological disasters occurring in August-September is higher. Due to the influence of geographical conditions, landslides occur mainly in the central and southern and southwest and east of China [6; 7; 8]. The number and scope of landslides are large, and it is almost impossible to rely on protective measures, such as retaining walls and antislip piles, to prevent and control all slopes with potential landslide threats. Therefore,it is of great significance to understand the occurrence mechanism of rainfall landslides and make effective early warning models and forecasting techniques [9; 10]. Landslide model experiments are one of the important tools to study the evolutionary mechanism of landslides [11; 12]. As early as the 1870s, researchers in the United States and Japan conducted research on rainfall-type landslide model experiments. Three sets of indoor physical model experiments were designed with selected landslide site materials, and the induced mechanism of loess landslides was revealed by combining experimental phenomena with data recorded by three sensors: a volumetric water content sensor, matrix suction sensor, and pore water pressure sensor [13]. [PERSON] et al. concluded from the field model experiments that the main basis of deformation and damage of granite fully weathered soil slopes is the steep increase of water content and pore water pressure fluctuation; the instability is caused by the decrease of soil matrix suction due to rainfall infiltration, and thus the strength is reduced; itsdamage mode is local slope slip followed by cracks, and finally, large-scale collapse [14]. [PERSON] et al. conducted experiments on landslide models under the coupling effect of earthquakes and rainfall and found that after an earthquake, the superposition of adverse rainfall factors belonged to the typical disaster chain effect with an obvious crack development in the middle and rear of the model and a large deformation at the leading edge of the slope [15]. The study on the landslide mechanism provides a theoretical basis for landslide early warning forecasting. Based on the negative correlation between the deformation velocity time-series curve and slope stability, [PERSON] et al. established a landslide damage time prediction model with rapid convergence of slope stability [16]. Currently, landslide early warning and forecasting methods still mainly rely on slope surface displacement detection. By conducting indoor model experiments on specific research areas and summarizing and analyzing the results of indoor model experiments as well as field displacement detection data, the relationship between displacement rate and duration in the accelerated deformation stage of slopes was established, and finally, the prediction method of landslide damage time was proposed. [PERSON]'s team conducted a detailed study on the formation mechanism of the Hefangtai loess landslide in Gansu, constructed an early warning model to cope with sudden-type loess landslides based on its damage characteristics, and successfully predicted the time of landslide occurrence [17; 18; 19].