Ensemble Predictions of Rainfall-Induced Landslide Risk under Climate Change in China Integrating Antecedent Soil-Wetness Factors

Abstract

Global warming has increased the occurrence of extreme weather events, causing significant economic losses and casualties from rainfall-induced landslides. China, being highly prone to landslides, requires comprehensive predictions of future rainfall-induced landslide risks. By developing a landslide-prediction model integrated with the CMIP6 GCMs ensemble, we predict the spatiotemporal distribution of future rainfall-induced landslides in China, incorporating antecedent soil-wetness factors. In this study, antecedent soil wetness is represented by the antecedent effective rainfall index (ARI), which accounts for cumulative rainfall, evaporation, and runoff losses. Firstly, we calculated landslide susceptibility using seven geographic factors, such as slope and geology. Then, we constructed landslide threshold models with two antecedent soil-wetness indicators. Compared to the traditional recent cumulative rainfall thresholds, the landslide threshold model based on ARI demonstrated higher hit rates and lower false alarm rates. Ensemble predictions indicate that in the early 21st century, the risk of landslides decreases in the Qinghai–Tibet Plateau, Southwest, and Southeast regions but increases in other regions. Mid-century projections show a 10% to 40% increase in landslide risk across most regions. By the end of the century, the risk is expected to rise by more than 15% nationwide, displaying a spatial distribution pattern that intensifies from east to west.

Keywords

• rainfall-induced landslides
• ensemble prediction
• antecedent soil-wetness factors
• climate change