Preprints
https://doi.org/10.5194/egusphere-2026-1608
https://doi.org/10.5194/egusphere-2026-1608
20 Apr 2026
 | 20 Apr 2026
Status: this preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).

ROC-optimized rainfall thresholds for typhoon-induced landslides: environmental and magnitude stratification in Zixing City, China

Weifeng Xiao, Ge Liu, Weimin Huang, Zhenghui Xiao, and Luguuang Luo

Abstract. Typhoon-induced landslides pose severe hazards in mountainous East and Southeast Asia, yet conventional intensity-duration thresholds inadequately capture complex rainfall structures and geoenvironmental heterogeneity. We developed environment- and magnitude-stratified rainfall thresholds using 705 landslides triggered by Typhoon Gaemi (July 2024) in Zixing City, China. Environmental stratification by slope, lithology, fault proximity, and vegetation yielded seven geomorphic domains. Receiver operating characteristic (ROC) analysis optimized dual-parameter thresholds combining 24-hour cumulative rainfall (AccR24h) with maximum hourly intensity (Imax). Stratified AccR24h+Imax models achieved AUC = 0.68–0.83, exceeding unstratified baselines (AUC = 0.70) by 13 %. Slope gradient exerted dominant control: steep terrain (>30°) required 37 % less AccR24h than gentle slopes. Discriminant weights revealed process hierarchies—high-susceptibility domains assigned 62 % weight to accumulation versus 38 % to intensity. Medium-scale landslides (500–5,000 m²) required 29 % higher AccR24h and exhibited 38 % longer time lags, indicating progressive deep-seated failure. Magnitude-specific thresholds reduced false alarms by 56 % while maintaining 89 % sensitivity. The methodological framework (environmental stratification + dual-parameter optimization) is applicable to other typhoon-affected regions, though threshold values and relative parameter weights require recalibration with local multi-event inventories. Integrating geoenvironmental controls with compound rainfall metrics substantially improves early warning precision for typhoon-induced landslides.

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Weifeng Xiao, Ge Liu, Weimin Huang, Zhenghui Xiao, and Luguuang Luo

Status: open (until 01 Jun 2026)

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Weifeng Xiao, Ge Liu, Weimin Huang, Zhenghui Xiao, and Luguuang Luo
Weifeng Xiao, Ge Liu, Weimin Huang, Zhenghui Xiao, and Luguuang Luo
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Short summary
To improve typhoon-induced landslide early warning systems, we used data from Typhoon Gaemi (705 landslides in Zixing City, China, 2024) to study how slope steepness, rock type, fault distance and vegetation affect landslides; we found steeper slopes and fault-adjacent areas need less rain, larger landslides need more prolonged heavy rain, and combining total and peak rainfall improved accuracy, helping build better systems to protect lives and property in typhoon-prone mountains.
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