Early Warning and Risk Assessment for Rainfall-Induced Shallow Loess Landslides

Rainfall-induced shallow loess landslides pose a significant threat to human life and property. Early warning and risk assessment of these landslides are critical prerequisites for engineering control and disaster loss reduction. The Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS)-Three-dimensional Slope Stability Analysis Tool (Scoops 3D) joint model can overcome the shortcomings of using a single TRIGRS model for hydrological analysis and a single Scoops 3D model for slope stability analysis. Landslide risk assessment based on expected economic loss, on the other hand, can overcome the issue of maintaining the risk level edge and sorting at the same level. In this paper, the TRIGRS model’s head pressures were put into the Scoops 3D model, with the southeast of Fangta, a town in Shaanxi province, China, as the study area. The relationship between the slope gradient and the number of grids in each stable grade was certified. The rainfall thresholds for landslides, based on both rainfall intensity and rainfall duration, were obtained by rerunning the TRIGRS-Scoops 3D joint model. The landslide range and land uses of each dangerous slope were determined by maximum likelihood classification, and then the expected economic loss was calculated. To verify the reliability of the TRIGRS-Scoops 3D joint model, the identified dangerous slopes were compared with the results from landslide susceptibility mapping. The results show that the unstable grids are concentrated within a slope gradient of 30° to 35°, and the landslide early warning levels are divided into Tier 3, Tier 2, and Tier 1 Warnings. The occurrence of shallow loess landslides is affected by both rainfall intensity and rainfall duration, and the combined effect should be considered in early warning. The distribution of both extreme susceptible grids and high susceptible grids across all 23 dangerous slopes demonstrates the reasonableness of the TRIGRS-Scoops 3D joint model. The landslide susceptible probability within some dangerous slopes exhibits spatial variability. The mapping relationship between the slope gradient and loess landslides is extremely complex. This paper can provide a theoretical basis for the early warning and risk management for rainfall-induced shallow loess landslides; the proposed method is also applicable to other regions with similar geological and meteorological conditions.