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<p>Landslides are a recurring hazard in the Western Ghats of India, where steep terrain, intense monsoon rainfall, and anthropogenic activities frequently trigger slope failures. This study analyses the July 2024 Shirur landslide in Karnataka and its surrounding region using an integrated multi-scale framework that combines Finite Element Method (FEM) simulation, Random Forest Classifier (RFC)-based Landslide Susceptibility Mapping (LSM), and Limit Equilibrium Method (LEM) assessment. The FEM analysis identified rainfall-induced pore pressure rise and slope toe cutting as key triggers of instability, highlighting the need for a regional-scale evaluation. To overcome the limitations of region-wide FEM application, a multi-scale approach (Macro to Nano scale) was proposed, enabling the identification of potentially hazardous zones where detailed FEM analyses are required to prevent recurrence of similar landslides. The macro-scale RFC-based susceptibility map delineated Shirur and nearby areas as highly prone to landslides, while micro-scale LEM evaluations confirmed critical instabilities with Factors of Safety below 1.0 in several slopes. The proposed approach effectively bridges the gap between data-driven and deterministic techniques, thereby enhancing the reliability of slope failure prediction. The findings support the development of improved site-specific risk assessment and mitigation planning for landslide-prone corridors in the Western Ghats.</p>

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Macro to nano-scale landslide susceptibility zonation and analysis: insights from the 2024 Shirur landslide

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • Priyajit Kundu,
  • Varun Menon,
  • Sreevalsa Kolathayar,
  • Pruthviraj Umesh

摘要

Landslides are a recurring hazard in the Western Ghats of India, where steep terrain, intense monsoon rainfall, and anthropogenic activities frequently trigger slope failures. This study analyses the July 2024 Shirur landslide in Karnataka and its surrounding region using an integrated multi-scale framework that combines Finite Element Method (FEM) simulation, Random Forest Classifier (RFC)-based Landslide Susceptibility Mapping (LSM), and Limit Equilibrium Method (LEM) assessment. The FEM analysis identified rainfall-induced pore pressure rise and slope toe cutting as key triggers of instability, highlighting the need for a regional-scale evaluation. To overcome the limitations of region-wide FEM application, a multi-scale approach (Macro to Nano scale) was proposed, enabling the identification of potentially hazardous zones where detailed FEM analyses are required to prevent recurrence of similar landslides. The macro-scale RFC-based susceptibility map delineated Shirur and nearby areas as highly prone to landslides, while micro-scale LEM evaluations confirmed critical instabilities with Factors of Safety below 1.0 in several slopes. The proposed approach effectively bridges the gap between data-driven and deterministic techniques, thereby enhancing the reliability of slope failure prediction. The findings support the development of improved site-specific risk assessment and mitigation planning for landslide-prone corridors in the Western Ghats.