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Assessing rainfall-induced shallow landslides under climate change: A slope-specific probabilistic framework in Lishui, Southeast China
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DOI：10.1016/j.jrmge.2026.05.036.png)
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Abstract
En 中文
Climate change is driving nonstationary changes in rainfall frequency and intensity, thereby increasing the frequency and severity of rainfall-induced shallow landslides in humid mountainous regions. Despite extensive research, most probabilistic landslide assessments incorporate global climate model projections into slope analyses without explicitly accounting for site-specific nonstationary rainfall evolution and its impacts on landslide probability. This study develops a novel probabilistic framework that integrates site-specific nonstationary rainfall hazard with physically based slope fragility to quantify shallow landslide probability in a changing climate. Site-specific nonstationary rainfall hazard is modeled using an alternating stochastic renewal process, where rainfall frequency and intensity characteristics are derived from bias-corrected and downscaled climate projections using the quantile delta mapping method. Shallow slope fragility is evaluated by coupling infiltration-induced pore pressure response with infinite slope stability analysis, while propagating uncertainties in soil properties. The probability of shallow landslides is estimated through the probabilistic integration of site-specific nonstationary rainfall hazard and slope fragility based on the total probability theorem. An illustrative example is provided, focusing on a granite weathering crust slope in Lishui, Southeast China, prone to rainfall-induced shallow landslides. Results indicate a significant increase in shallow landslide probability when site-specific, climate-driven nonstationary rainfall is incorporated.
Keywords:
Rainfall-induced shallow landslide
Climate change
Probabilistic assessment
Statistical downscaling
granite weathering crust slope
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