| Citation: | WANG Yingfan，YAO Xin，ZHANG Pusheng，et al. Characteristics of typhoon-induced heavy rainfall in Beiliu, Guangxi, and its impact on shallow landslide stability[J]. Bulletin of Geological Science and Technology，2026，45（4）：1-15 doi: 10.19509/j.cnki.dzkq.tb20250100
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To address the challenges in preventing and controlling mass landslides triggered by typhoon-induced heavy rainfall in granitic regions, this study focuses on Beiliu City, Guangxi Province as the study area, and systematically investigated the rainfall response mechanism and early warning technology of typhoon rainstorm-triggered landslides.
By analyzing the spatiotemporal distribution characteristics of rainfall and the mechanisms triggering landslides during typhoon-induced heavy rainfall events, the study quantified the rainfall kurtosis, skewness, peak location coefficient and classified typhoon-induced heavy rainfall into three types: post-peak, pre-peak, and concentrated. A regional slope stability evaluation method under heavy rainfall conditions was developed using the TRIGRS-Scoops3D coupled model. The method was validated using the "6・26" rainfall event in 2023 as an example.
The results indicated that over 50% of the study area experienced stability degradation under rainfall conditions, with extremely unstable zones accounting for 5.73%. High-risk areas were concentrated in the northern, eastern, and southwestern steep slope terrain units. All landslide points induced by heavy rainfall were located within the warning zones delineated based on stability evaluation results.
The results indicate that the typhoon-induced shallow landslide early warning method based on "rainfall pattern recognition-quantitative stability assessment-dynamic delineation of risk areas" possesses high reliability and applicability. The research findings provide scientific support for shallow landslide risk prevention and control, monitoring and early warning system development, and emergency management of geological disasters in typhoon-prone granitic regions.
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