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<p>Landslide occurrences are influenced by various spatial and climatic factors, some predictable to an extent, while others remain uncertain. Physically-based models like TRIGRS are crucial for assessing slope stability and rainfall thresholds. In this study, we evaluated rainfall intensity (RI) and duration (RD) for landslide prediction in Guangdong's northern region, focusing on areas with historical high-intensity rainfall and landslides.Zhou Our study encompassed four rainfall intensities (1&#xa0;mm to 50&#xa0;mm) and 32 durations (1 to 72&#xa0;h), considering diverse hillslope gradients and geological formations (sedimentary and igneous rocks). With increasing rainfall intensity, the time required for slope failure decreased until a critical threshold was reached, highlighting the importance of defining spatial thresholds across different rainfall simulations. Simulation results indicated that igneous rock failure occurred after 4.3&#xa0;h of 50&#xa0;mm/h rainfall, while sedimentary rock failure occurred in low-strength areas within 2 to 3&#xa0;h with the same rainfall intensity at different locations. Validation with landslide data yielded accuracies of 67.42% for sedimentary rock, 68.13% for both sedimentary and igneous rock, and 63.51% for igneous rock alone using TRIGRS. Furthermore, to evaluate the accuracy, the ROC and AUC validations were performed, showing sedimentary rocks as a highly accurate predictor of landslides with an AUC of 0.81. This analysis highlights the geological role in slope failure and aids in future rainfall-based threshold evaluations for early landslide warnings.</p>

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Rainfall threshold analysis for various geological formations in Northeastern Guangdong, China: a physically-based approach

  • 期刊论文

  • 发表日期：

    2026年1月16日

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  • Muhammad Zeeshan Ali,
  • Kejie Chen,
  • Wenfeng Cui,
  • Hai Zhu,
  • Zhiwen Zheng,
  • Wei Zhang,
  • Zhihua Zhou

摘要

Landslide occurrences are influenced by various spatial and climatic factors, some predictable to an extent, while others remain uncertain. Physically-based models like TRIGRS are crucial for assessing slope stability and rainfall thresholds. In this study, we evaluated rainfall intensity (RI) and duration (RD) for landslide prediction in Guangdong's northern region, focusing on areas with historical high-intensity rainfall and landslides.Zhou Our study encompassed four rainfall intensities (1 mm to 50 mm) and 32 durations (1 to 72 h), considering diverse hillslope gradients and geological formations (sedimentary and igneous rocks). With increasing rainfall intensity, the time required for slope failure decreased until a critical threshold was reached, highlighting the importance of defining spatial thresholds across different rainfall simulations. Simulation results indicated that igneous rock failure occurred after 4.3 h of 50 mm/h rainfall, while sedimentary rock failure occurred in low-strength areas within 2 to 3 h with the same rainfall intensity at different locations. Validation with landslide data yielded accuracies of 67.42% for sedimentary rock, 68.13% for both sedimentary and igneous rock, and 63.51% for igneous rock alone using TRIGRS. Furthermore, to evaluate the accuracy, the ROC and AUC validations were performed, showing sedimentary rocks as a highly accurate predictor of landslides with an AUC of 0.81. This analysis highlights the geological role in slope failure and aids in future rainfall-based threshold evaluations for early landslide warnings.