Mechanistic analysis of loess landslide reactivation in northern Shaanxi based on coupled numerical modeling of hydrological processes and stress strain evolution: A case study of the Erzhuangkelandslide in Yan’an
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摘要:
二庄科滑坡是典型受降雨影响的滑坡,降雨改变了老滑坡的渗流场,削弱基质吸力和土体抗剪强度,导致内部产生张拉裂缝,引发整体滑动和局部大变形,但现有研究很少考虑二庄科滑坡的渗流场与应力场的相互作用。文章基于实际工程地质灾害背景,在现场监测数据和地形物理参数的基础上,建立了几何计算模型,并进行水力耦合数值模拟。通过研究滑坡内部饱和度和孔压的变化规律来探讨降雨入渗规律,从应力位移的角度探讨降雨强度对滑坡复活的影响规律。此外,为了验证方法的准确性和可行性,选取了滑坡实测点位并找到了数值模型对应位置,对位移、土压力和饱和度三个方面进行了对比分析,得出数值模型能较好地反映实际情况的结论。通过数值模拟耦合计算和降雨条件下老滑坡复活机制的研究,对实测数据进行解释并分析滑坡复活过程,为后续工程预警和减灾工作提供理论基础和技术指导。
Abstract:The Erzhuangke landslide is a typical landslide affected by the rainy season. Rainfall changes the seepage pattern with the pre-existing landslide, weakening matric suction and soil shear strength, leading to the formation of tension cracks internally. This triggers overall sliding and localized extensive deformations. Existing studies seldom considers the interaction between the seepage field and stress field of the Erzhuangke landslide. Therefore, based on the actual engineering geological disaster scenarios, supported by on-site monitoring data and terrain physical parameters, a geometric computational model is established, and hydraulic coupled numerical simulations are conducted. By investigating variations in saturation and pore pressure within the landslide, the paper explores the rainfall infiltration patterns. It examines the impact of rainfall intensity on landslide reactivation from the perspective of stress displacement. In addition, in order to validate the accuracy and feasibility of the method, selected measurement points from the landslide are matched with corresponding positions in the numerical model. Comparative analysis is performed on displacement, soil pressure, and saturation aspects, confirming that the numerical model effectively reflects the actual situation. Through coupling numerical simulations and the study of the reactivation mechanism of the old landslide under rainfall conditions, the paper interprets field data, analyzes the reactivation process, and provides theoretical foundations and technical guidance for subsequent engineering early warning and disaster mitigation works.
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图 2 工程地质灾害监测点分布图[10]
Figure 2.
表 1 模型参数设置
Table 1. Table of model parameter settings
土体类型 密度/(kg∙m−3) 体积模量/Pa 孔隙率 饱和渗透系数/(m∙s−1) 内摩擦角/(°) 黏聚力/Pa 剪切模量/Pa 初始孔隙压力/Pa Qh 1900 2×108 0.40 3.9×10−4 18 3×104 — 21977 Qp 1900 2×108 0.40 3.9×10−4 18 3×104 — 21977 砂岩 2800 1×109 0.15 1×10−12 36 1.2×106 3×108 0 表 2 G6点竖向位移实际模拟数据对比
Table 2. Comparison of actual and simulated vertical displacements for monitoring point G6
日期 2021-10-28 2021-10-29 2021-10-30 2021-10-31 实际数据/mm 239.01 241.03 242.00 243.04 模拟数据/mm 202.98 209.76 214.31 219.05 误差/% 15.07 12.97 11.44 9.87 表 3 G7点竖向位移实际模拟数据对比
Table 3. Comparison of actual and simulated vertical displacements for monitoring point G7
日期 2021-10-10 2021-10-11 2021-10-12 2021-10-13 实际数据/mm −2.014 −2.991 −4.028 −4.028 模拟数据/mm 1.630 2.370 2.610 2.780 误差/% 180.93 179.24 164.80 169.02 表 4 G6点水平位移实际模拟数据对比
Table 4. Comparison of actual and simulated horizontal displacements for monitoring point G6
日期 2021-10-15 2021-10-16 2021-10-17 2021-10-18 实际数据/mm 109.50 111.35 113.32 117.00 模拟数据/mm 102.85 106.15 107.12 107.97 误差/% 6.07 4.67 5.47 7.72 表 5 G7点水平位移实际模拟数据对比
Table 5. Comparison of actual and simulated horizontal displacements for monitoring point G7
日期 2021-10-12 2021-10-13 2021-10-14 2021-10-15 实际数据/mm 9.249 14.798 20.348 24.093 模拟数据/mm 4.090 4.170 4.400 5.670 误差/% 55.7 71.82 78.38 76.47 -
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