Abstract
Analyzing and quantifying the deformation process of landslides is of paramount importance in facilitating landslide early warning. As such, this study is committed to proposing a universal phenomenological model for deformation stages division and early warning of landslides based on the kinematic features. First, five landslide deformation patterns were classified based on the creep theory, and suggestions for stage division of each deformation pattern are presented. Then, the statistical characteristics of landslide velocity were analyzed, and a probability-based deformation stage division method was proposed. Finally, the Comprehensive Standardized Deformation Index (CSDI) model, which includes the calculation of the \({CSDI}^{M-M}\) (Min-Max normalization) and \({CSDI}^{M}\) (Mean normalization) was proposed and verified in 24 landslides worldwide. The results show that, except for the oscillating pattern, the \({CSDI}^{M-M}\) is feasible in the stages division of all deformation patterns with a strong correspondence with the actual state of the landslides. The \({CSDI}^{M}\) is a reliable landslide warning criterion and threshold determination method, as it is effective in the early warning of imminent landslides with a low false alarm rate. The CSDI model provides new insight into the division of landslide deformation stages and landslide risk assessment.
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Funding
Major Program of the National Natural Science Foundation of China, No. 42090055, Huiming Tang, National Key Scientific Instrument and Equipment Development Projects of China, No. 41827808 Huiming Tang, the National Natural Sciences Foundation of China, 42207212, Junrong Zhang, Postdoctoral Research Foundation of China, 2021M703002, Junrong Zhang, the Open Fund of Badong National Observation and Research Station of Geohazards (No. BNORSG-202314).
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JZ: methodology, writing—original draft, writing—review and editing. HT: funding acquisition, supervision. CL: writing—review and editing. WG: supervision. BZ: software, visualization. YZ: visualization.
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Zhang, J., Tang, H., Li, C. et al. Deformation stage division and early warning of landslides based on the statistical characteristics of landslide kinematic features. Landslides 21, 717–735 (2024). https://doi.org/10.1007/s10346-023-02192-7
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DOI: https://doi.org/10.1007/s10346-023-02192-7