Study on the Dynamic Evolution Patterns of Landslides in Northwestern Sichuan Based on Dynamic Influencing Factors

Yu Zhu, Huajin Li (), Ran Tang and Shenghua Cui
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Yu Zhu: Chengdu University, School of Architecture and Civil Engineering
Huajin Li: Chengdu University, School of Architecture and Civil Engineering
Ran Tang: Chengdu University, School of Architecture and Civil Engineering
Shenghua Cui: Chengdu University of Technology, State Key Laboratory of Geohazard Prevention and Geoenvironment Protection

A chapter in Proceedings of the 11th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2024), 2025, pp 188-195 from Springer

Abstract: Abstract Clarifying the dynamic evolution patterns of landslides is crucial for landslide disaster prevention. Focusing on the northwestern region of Sichuan, analyzing 240 typical cases of actively deforming landslides over the past twenty years, examining the impact of various environmental factors such as vegetation, and rainfall on the dynamic development of landslides. Research indicates that vegetation coverage is a crucial factor influencing the development of landslides. Areas with high vegetation coverage tend to contribute more significantly to landslide activity. This phenomenon may be attributed to the excessive weight of root systems and increased rainfall interception, which negatively impact slope stability. In contrast, regions with high rainfall experience a more considerable increase in both the area and frequency of landslides. However, the annual average rainfall over a 20-year period shows minimal correlation with the frequency of landslide activity. This suggests that short-term intense rainfall events may play a more critical role in triggering landslide occurrences. By integrating the dynamic evolution patterns of landslides, targeted disaster prevention measures formulated can effectively enhance the region’s proactive disaster prevention capabilities.

Keywords: Active Landslides; Dynamic Evolution Patterns; Environmental Factors; Disaster Prevention (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-946-9_24

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