ZHANG Yingbin, YANG Zhiwei, LIU Jing, ZENG Ying, SUN Yu, TAN Jinyang. 2026: Vulnerability of mountain road networks to rainfall-induced landslide hazards. Journal of Mountain Science, 23(1): 188-202. DOI: 10.1007/s11629-025-9673-5
Citation: ZHANG Yingbin, YANG Zhiwei, LIU Jing, ZENG Ying, SUN Yu, TAN Jinyang. 2026: Vulnerability of mountain road networks to rainfall-induced landslide hazards. Journal of Mountain Science, 23(1): 188-202. DOI: 10.1007/s11629-025-9673-5

Vulnerability of mountain road networks to rainfall-induced landslide hazards

  • Global climate change is intensifying the impact of slope hazards, particularly rainfall-induced landslide hazards (RILH), on mountain road networks (MRNs). However, effective quantitative models for dynamically assessing MRNs vulnerability under RILH disturbances are still lacking. To bridge this gap, this study develops a Cascading Failure Model for Rainfall-Induced Landslide Hazard (CFM-RILH). Validation via a case study of the Garzê Tibetan Autonomous Prefecture Road Network (GTPRNs) reveals key characteristics of MRNs system vulnerability under RILH disturbances: (1) Under the disturbance effects of RILH, the vulnerability of the MRNs system follows a nonlinear phase transition law that intensifies with increasing disturbance intensity, exhibiting a distinct critical threshold. When the disturbance intensity exceeds this threshold, the system undergoes a global cascading failure phenomenon analogous to an "avalanche." (2) Under RILH disturbances, the robustness of the MRNs system possesses a distinct safety boundary. Exceeding this boundary not only fails to improve hazard resistance but instead substantially elevates the risk of large-scale cascading failure. (3) Increasing network redundancy may be considered one of the primary engineering measures for enhancing MRNs resilience against such disturbances. Based on these findings, we propose a "Two-Stage Emergency Response and Hierarchical Fortification" strategy specifically to improve the resilience of GTPRNs impacted by RILH. The CFM-RILH model provides an effective tool for assessing road network vulnerability under such hazards. Furthermore, its modeling framework can also inform vulnerability assessment and resilience strategy development for road networks affected by other types of slope hazards.
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