ROC-optimized rainfall thresholds for typhoon-induced landslides: environmental and magnitude stratification in Zixing City, China
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.
General Comment:
The manuscript presents a well-designed and timely framework for establishing ROC-optimized rainfall thresholds for typhoon-induced landslides in complex mountainous terrain. By integrating environmental stratification and magnitude-dependent analyses based on a detailed inventory from Typhoon Gaemi, the study makes a solid contribution to landslide hazard assessment and early warning systems. The methodology is statistically rigorous, combining spatial block cross-validation, Youden index optimization, and DeLong tests.
Comments for the Authors:
In the introduction, when referencing the evolution of empirical rainfall thresholds, specifically around the sentence "Empirical rainfall thresholds, pioneered by Caine (1980) and refined over four decades (Peruccacci et al., 2017; Huang et al., 2022; Brunetti et al., 2025), remain a fundamental component of regional forecasting systems", the authors are encouraged to consider incorporating recent methodological advances on combined empirical thresholds. Specifically, the novel approach proposed by Silva et al. (2026) provides a highly relevant reference for combined threshold development in complex geographic environments:
Silva, R. F., Marques, R., & Zêzere, J. L. (2026). A New Approach for Developing Combined Empirical Rainfall-Triggered Landslide Thresholds: Application to São Miguel Island (Azores, Portugal). Water, 18(6), 673. https://doi.org/10.3390/w18060673
The study uses with 35 automatic rain gauges across 2,747km2. Given the steep topography of the Nanling Mountains, please briefly comment on how the interpolation error might affect threshold accuracy, especially in high-altitude zones with fewer stations.
The authors rightly note that subsets S6 (n=21) and S7 (n=24) exhibit high uncertainty due to small sample sizes. Please clarify in Section 4/5 whether these specific thresholds are recommended for operational use or if they should be flagged as preliminary pending further data collection.
The model was trained and validated using an impressive single-event dataset. While single-event datasets eliminate seasonal antecedent soil moisture bias, rainfall spatial patterns vary between typhoons (e.g. differing tracks or durations). Please add a short paragraph in the Discussion section addressing the transferability of these thresholds to future, non-Gaemi typhoon events.