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Assessment of potential sediment disasters and resilience management of mountain roads using environmental indicators

Author

Listed:
  • Chao-Yuan Lin

    (National Chung Hsing University)

  • Yuan-Chung Lai

    (National Chung Hsing University)

  • Shao-Wei Wu

    (National Chung Hsing University)

  • Fan-Chung Mo

    (National Chung Hsing University)

  • Cheng-Yu Lin

    (Environmental Greening Association)

Abstract

In recent years, extreme rainfall events occur frequently, causing serious watershed sediment disasters, destroying mountain roads, and endangering the safety of residents' lives and property. This study aims to deal with the spatial change of potential sediment movement on the road slope pre-disaster and to screen disaster hot spots for early warning and control system. The conceptual model is used to simulate the distribution of primary and/or derived disasters on a watershed scale to assess the impact of sediment disasters caused by heavy rain event. Correlation analysis shows that the models in assessment of primary disaster and derived disaster are significantly correlated with the collapse ratio and disaster ratio, respectively. Since the primary disaster has been considered when calculating the derived disaster risk, the terrain subdivision along Provincial Highway 21 (Tai-21) is extracted to understand the derived sediment disaster on the road slope. The model can effectively evaluate the road sections prone to disasters. According to the risk level, the hot spot of road slope disasters and the management of disaster resilience are determined and can be the reference for disaster prevention and control.

Suggested Citation

  • Chao-Yuan Lin & Yuan-Chung Lai & Shao-Wei Wu & Fan-Chung Mo & Cheng-Yu Lin, 2022. "Assessment of potential sediment disasters and resilience management of mountain roads using environmental indicators," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1951-1975, March.
    • Handle: RePEc:spr:nathaz:v:111:y:2022:i:2:d:10.1007_s11069-021-05126-5
    DOI: 10.1007/s11069-021-05126-5
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    References listed on IDEAS

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    Cited by:

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    2. Changhong Zhou & Mu Chen & Jiangtao Chen & Yu Chen & Wenwu Chen, 2024. "A Multi-Hazard Risk Assessment Model for a Road Network Based on Neural Networks and Fuzzy Comprehensive Evaluation," Sustainability, MDPI, vol. 16(6), pages 1-16, March.

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