Research on landslide displacement prediction method considering pore water pressure

QIAN Yu; WANG Li; SHU Bao; XU Hao; CHEN Bin; GENG Tianyu; WU Hanwen

doi:10.16031/j.cnki.issn.1003-8035.202412026

2025 Vol. 36, No. 5

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Article navigation > The Chinese Journal of Geological Hazard and Control > 2025 > 36(5): 56-63

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QIAN Yu, WANG Li, SHU Bao, XU Hao, CHEN Bin, GENG Tianyu, WU Hanwen. Research on landslide displacement prediction method considering pore water pressure[J]. The Chinese Journal of Geological Hazard and Control, 2025, 36(5): 56-63. doi: 10.16031/j.cnki.issn.1003-8035.202412026

Citation:

QIAN Yu, WANG Li, SHU Bao, XU Hao, CHEN Bin, GENG Tianyu, WU Hanwen. Research on landslide displacement prediction method considering pore water pressure[J]. The Chinese Journal of Geological Hazard and Control, 2025, 36(5): 56-63. doi: 10.16031/j.cnki.issn.1003-8035.202412026

Research on landslide displacement prediction method considering pore water pressure

School of Geological Engineering and Geodesy, Chang’an University, Xi’an, Shaanxi　710054, China

More Information

Corresponding author: SHU Bao, baos613@163.com

Received Date: 16 December 2024

Revised Date: 20 March 2025

Accepted Date: 28 July 2025

Publish Date: 25 October 2025

Abstract

Abstract

Landslide displacement prediction is a critical component of disaster prevention and mitigation. Rainfall infiltration directly affects the distribution of pore water pressure within the landslide mass, and the dynamic variation of pore water pressure significantly influences the shear strength of slip zone soils, making it a key factor in landslide initiation. To address the limitations of traditional landslide displacement prediction models that inadequately consider the coupling effects of pore water pressure, this paper proposes a novel displacement prediction method that incorporates pore water pressure. A one-dimensional diffusion model is used to simulate the changes in pore water pressure. Pore water pressure is introduced as a new influencing factor, and the optimal set of the influencing factors is determined using the maximum mutual information coefficient method. The selected influencing factors served as inputs to the displacement prediction model, while cumulative landslide displacement is used as the output. The method is validated using GNSS monitoring data from the Dangchuan landslide in Heifangtai, Yanguoxia Town, Yongjing County, Gansu Province, China. Results show a strong correlation between pore water pressure and landslide displacement. Incorporating normalized pore water pressure into the model significantly improves prediction accuracy, especially during periods of intense rainfall. The model achieves an RMSE of 2.9 mm, an MAE of 2.5 mm, and a coefficient of determination (R²) of 0.995, providing a promising approach for the accurate early warning of rainfall-induced landslides.
- displacement prediction /
- pore water pressure /
- impact factors /
- rainfall-induced landslide

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References

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