Abstract：To address the challenges of ambiguous physical meanings and the difficulty in quantitatively characterizing driving factors in existing slope displacement decomposition methods, a model- and data-driven displacement decomposition approach was proposed. This method first constructs a displacement model that considers the influencing factors of rainfall, blasting, excavation, and creep. It integrates numerical simulation results into the objective function, thereby establishing dual optimization objectives that ensure consistency between monitoring data and numerical simulations. The Adam optimization algorithm is utilized for parameter optimization, allowing for the quantitative separation of displacement contributions from various influencing factors by minimizing the objective function. The proposed method was applied to the slope of the material yard at the Yebatan Hydropower Station. Results indicate that the displacements induced by rainfall, blasting, excavation, and creep accounted for approximately 7.7%, 5.9%, 35.1%, and 51.3% of the total displacement, respectively. Initially, the early deformation of the slope was predominantly influenced by excavation. However, the contribution of creep gradually increased over time, ultimately becoming the dominant factor. In contrast, the effects of rainfall and blasting became significantly more pronounced during the later stages of excavation. The proposed method effectively reveals the temporal variation patterns of individual displacement components, contributing to a deeper understanding of the mechanisms of deformation evolution and the instability behavior of slopes.
刘族波1，刘加丽2，位 伟1*，姜清辉1. 模型与数据双驱动的边坡时序位移分解研究——以叶巴滩水电站料场边坡为例[J]. 岩石力学与工程学报, 2026, 45(10): 2942-2954.
LIU Zubo1, LIU Jiali2, WEI Wei1*, JIANG Qinghui1. Model- and data-driven research on time-series displacement decomposition for slope: A case study at the stockyard slope of Yebatan Hydropower Station. , 2026, 45(10): 2942-2954.
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2026, Vol. 45 
