Insight into data-driven model for the formation mechanism and causative factors of landslides induced by the 2013 Tianshui extreme rainfall event

The 2013 extreme rainfall-induced landslide in the Tianshui area was the most severe geological disaster since 1984. This study aims to improve the understanding of landslide formation mechanisms by using a data-driven model to predict landslide probabilities under various rainfall scenarios. A probability evaluation model was constructed based on total rainfall and landslide data, with uncertainty quantified through 20 model runs. The results show consistent trends in predicted landslide probability across five rainfall scenarios, with high probability areas primarily located on valley sides. As rainfall accumulates, the areas with low probability (<0.005) decrease, while the areas with moderate probability (0.01–0.02) increase. Further analysis of various influencing factors on landslides shows that the hillslope gradient has the highest regression coefficient, followed by the topographic wetness index (TWI), indicating that steeper slopes and higher TWI values are linked to a higher likelihood of landslides. Conversely, elevation and relief show negative coefficients, suggesting that areas with lower elevation and relief are more susceptible to landslides. Due to the unique terrain and lithological characteristics of the region, it is highly prone to landslides, with rainfall as a triggering factor contributing only marginally to their occurrence.

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Publication Details

Journal
Geomatics Natural Hazards and Risk
Published
2025-04-08
DOI
https://doi.org/10.1080/19475705.2025.2487826
Citations
1
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
2.42

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article

Insight into data-driven model for the formation mechanism and causative factors of landslides induced by the 2013 Tianshui extreme rainfall event

Chong Bang Xu, Siyuan Ma, Xiaoyi Shao
1 citations
Geomatics Natural Hazards and Risk
Landslides and related hazards
2.42
article

Insight into data-driven model for the formation mechanism and causative factors of landslides induced by the 2013 Tianshui extreme rainfall event

Chong Bang Xu, Siyuan Ma, Xiaoyi Shao
article en
1 citations

Abstract

The 2013 extreme rainfall-induced landslide in the Tianshui area was the most severe geological disaster since 1984. This study aims to improve the understanding of landslide formation mechanisms by using a data-driven model to predict landslide probabilities under various rainfall scenarios. A probability evaluation model was constructed based on total rainfall and landslide data, with uncertainty quantified through 20 model runs. The results show consistent trends in predicted landslide probability across five rainfall scenarios, with high probability areas primarily located on valley sides. As rainfall accumulates, the areas with low probability (<0.005) decrease, while the areas with moderate probability (0.01–0.02) increase. Further analysis of various influencing factors on landslides shows that the hillslope gradient has the highest regression coefficient, followed by the topographic wetness index (TWI), indicating that steeper slopes and higher TWI values are linked to a higher likelihood of landslides. Conversely, elevation and relief show negative coefficients, suggesting that areas with lower elevation and relief are more susceptible to landslides. Due to the unique terrain and lithological characteristics of the region, it is highly prone to landslides, with rainfall as a triggering factor contributing only marginally to their occurrence.

Geomatics Natural Hazards and RiskVol. 16(1)
Institute of Geology, China Earthquake Administration, China Earthquake Administration (CN)
National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 13%
Landslides and related hazards
2.42
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