降雨作用下鄂西山区麻池村1号滑坡变形破坏过程试验

王赟; 陈菲菲; 沈颜参; 杨涛; 陈梦源; 李喜; 章广成

doi:10.19509/j.cnki.dzkq.tb20250271

降雨作用下鄂西山区麻池村1号滑坡变形破坏过程试验

doi: 10.19509/j.cnki.dzkq.tb20250271

王赟^1,,
陈菲菲²,
沈颜参¹,
杨涛³,
陈梦源³,
李喜³,
章广成^1, ,

中国地质大学（武汉）工程学院，武汉 430074
湖北省地质局第七地质大队，武汉 443111
湖北省地质环境总站资源与生态环境地质湖北省重点实验室，武汉 430034

基金项目: 国家自然科学基金项目（U2340230）；湖北省重点研发计划项目（2023BCB117）

详细信息

作者简介:
王赟：E-mail：wangyun1@cug.edu.cn

通讯作者:
E-mail：zhangguangc@cug.edu.cn

中图分类号: P642.22；TU457
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- 文章访问数: 266
- PDF下载量: 23
- 被引次数: 0
出版历程
- 收稿日期: 2025-06-14
- 录用日期: 2025-10-14
- 修回日期: 2025-09-24
- 网络出版日期: 2025-10-16

Experimental study on deformation and failure process of No. 1 landslide in Machi Village under rainfall conditions in mountainous area of western Hubei

Faculty of Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China
The Seventh Geological Brigade of Hubei Geological Bureau, Wuhan 443111, China
Hubei Key Laboratory of Resources and Eco-Environment Geology, Geological Environmental Center of Hubei Province, Wuhan 430034, China

More Information

Author Bio:
E-mail：wangyun1@cug.edu.cn

Corresponding author: E-mail：zhangguangc@cug.edu.cn

摘要

摘要:
鄂西山区广泛发育大规模堆积层滑坡，坡体变形演化与降雨时空分布高度关联。为揭示堆积层滑坡变形特征及其演化过程对降雨模式的响应规律，确定滑坡稳定性对各因素的敏感程度，选取十堰市典型堆积层滑坡——麻池村1号滑坡为例，采用物理模型试验探究前锋、中锋、平锋和后锋4种降雨雨型作用下滑坡的演化过程；采用正交试验和方差分析辨识影响滑坡稳定性的主控因素。研究结果表明：①4种降雨雨型对滑体土孔隙水压力的影响主要体现在孔隙水压力峰值出现时间随雨峰位置的变化，雨峰越靠前，峰值出现的时间越早。其次，后峰型降雨所导致的滑坡破坏区域相对较大，致灾效应较强。②在各种类型降雨条件下，边坡模型主要从中部开始变形，先发生蠕变，再到阶跃式变形直至边坡完全破坏。③正交试验方差分析表明，影响麻池村1号滑坡整体稳定性的敏感因素由大到小依次为：内摩擦角φ >黏聚力c >累计降雨量T >渗透系数K_s >滑带土容重γ >降雨雨型Q。滑带土的黏聚力c与内摩擦角φ是评估滑坡稳定性的关键抗剪强度参数。④对于滑坡前缘局部来说，渗透系数K_s是影响稳定性的重要因素，而对滑坡整体而言，累计降雨量T更为关键。麻池村1号滑坡属降雨诱发前缘牵引式滑坡，其中后峰型降雨致灾效应最强，本研究基于现象观测、变形破坏探究、关键参数分析的完整分析方法可信度高，所得的结果具有较高可靠性与适用性，研究成果可为鄂西山区同类滑坡监测与灾害应急处置提供理论支撑。
- 堆积层滑坡 /
- 降雨雨型 /
- 物理模型试验 /
- 变形演化 /
- 多因素敏感性分析 /
- 牵引式失稳
Abstract:
Objective
Large-scale colluvial landslides are widely distributed in mountainous areas of western Hubei, and slope deformation evolution is closely coupled with the spatiotemporal distribution of rainfall. Existing related studies mostly focus on single rainfall intensity or short-term monitoring data, lacking systematic comparative research on different rainfall peak patterns and quantitative sensitivity differentiation of multi-geomechanical parameters. This study aims to reveal the response patterns of colluvial slope deformation and evolutionary process under four typical rainfall patterns, and quantitatively identify the sensitivity ranking of various influencing factors to landslide stability.
Methods
Taking No.1 colluvial landslide in Machi Village of Shiyan City as the research prototype, a geometrically scaled indoor physical model was established based on similarity theory. Four rainfall scenarios (early-peak, mid-peak, flat-peak, and late-peak rainfall) were set up to reproduce the full deformation and failure process of the landslide. On the basis of model test data, orthogonal design combined with analysis of variance (ANOVA) was adopted to distinguish the dominant controlling factors of slope stability.
Results
The results showed that: ① The influence of the four rainfall patterns on pore water pressure in the landslide soil was mainly reflected in the timing of the peak pore water pressure, which varied with the position of the rainfall peak. The earlier the rainfall peak occurred, the earlier the peak pore water pressure appeared. Moreover, the late-peak rainfall pattern induced a relatively larger failure zone and exhibited a stronger disaster-causing effect. ② Under different rainfall patterns, the slope model began to deform primarily from the middle section, first undergoing creep deformation, followed by step-like deformation, and eventually complete failure. ③ ANOVA based on orthogonal tests indicated that the sensitivity of factors affecting the overall stability of the No.1 landslide in Machi Village decreased in the following order: Internal friction angle (φ) > cohesion (c) > cumulative rainfall (T) > permeability coefficient (K_s) > unit weight of slip zone soil (γ) > rainfall pattern (Q). The cohesion (c) and internal friction angle (φ) of the slip zone soil are the key shear strength parameters for evaluating landslide stability. ④ For the local front edge of the landslide, the permeability coefficient (K_s) was an important factor affecting stability, whereas for the overall landslide, cumulative rainfall (T) played a more critical role.
Conclusion
The No.1 landslide in Machi Village is a typical rainfall-induced retrogressive landslide, and late-peak rainfall has the strongest disaster-causing effect. The integrated research framework combining physical model observation, deformation evolution analysis, and multi-factor ANOVA sensitivity quantification proposed in this study has high accuracy and practicability. The research findings can provide theoretical support for deformation monitoring and emergency response of similar colluvial landslides in the mountainous areas of western Hubei.
- colluvial landslide /
- rainfall pattern /
- physical model test /
- deformation evolution /
- multi-factor sensitivity analysis /
- retrogressive failure

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图 1 麻池村1号滑坡地理位置

Figure 1. Geographic location of No. 1 landslide in Machi Village

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图 2 麻池村1号滑坡工程地质平面图(a)及剖面图 (b)

Figure 2. Engineering geology plan iew (a) and cross-sectional view (b) of No. 1 landslide in Machi Village

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图 3 麻池村1号滑坡变形情况

Figure 3. Deformation status of No. 1 landslide in Machi Village

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图 4 麻池村1号滑坡降雨量与累计位移量变化

Figure 4. Variation of rainfall and cumulative displacement of No. 1 landslide in Machi Village

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图 5 降雨雨型设计方案

Figure 5. Design scheme of rainfall patterns

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图 6 模型试验设计布置

Figure 6. Layout design of physical model test

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图 7 主要试验设备

Figure 7. Experimental setup

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图 8 不同降雨雨型物理模型试验的坡体变形破坏情况

Figure 8. Slope deformation and failure under physical model tests with different rainfall patterns

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图 9 物理模型试验监测点位移变形

Figure 9. Displacement deformation at monitoring points of physical model test

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图 10 滑坡体孔隙水压力监测曲线

Figure 10. Monitoring curve of pore water pressure in landslide mass

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图 11 滑坡体土压力监测曲线

Figure 11. Monitoring curve of earth pressure in landslide mass

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图 12 滑坡整体和前缘工程地质剖面

Figure 12. Engineering geological profiles of entire landslide and its front edge

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图 13 不同降雨强度下滑坡区域稳定性系数变化

Figure 13. Variation of stability coefficient of landslide area with different rainfall intensities

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图 14 不同降雨历时下滑坡区域稳定性系数变化

Figure 14. Variation of stability coefficient of landslide area with different rainfall durations

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图 15 不同降雨雨型下滑坡区域稳定性系数变化

Figure 15. Variation of stability coefficient of landslide area under different rainfall patterns

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表 1 麻池村1号滑坡位移变形区间

Table 1. Displacement deformation intervals of No. 1 landslide in Machi Village

时期		G4监测点		G5监测点		G6监测点
时间段	变形阶段	位移增量/mm	变形速率/(mm·d⁻¹)	位移增量/mm	变形速率/(mm·d⁻¹)	位移增量/mm	变形速率/(mm·d⁻¹)
2019年6月1日—2020年7月1日	初始变形	12.08	0.03	8.08	0.02	3.78	0.01
2020年7月1日—2020年9月1日	第1次变形	15.90	0.26	32.78	0.55	68.95	1.15
2020年9月1日—2020年10月1日	缓慢匀速变形	0.99	0.03	1.99	0.07	7.56	0.25
2020年10月1日—2020年11月1日	第2次变形	3.84	0.13	7.07	0.24	26.81	0.89
2020年11月1日—2021年7月1日	缓慢匀速变形	18.99	0.08	19.53	0.08	32.21	0.13
2021年7月1日—2021年9月1日	第3次变形	14.70	0.24	14.37	0.24	82.06	1.37
2021年9月1日—2021年11月1日	第4次变形	864.30	14.40	926.90	15.45	858.80	14.31
2021年11月1日—2023年10月1日	缓慢匀速变形	75.40	0.11	95.07	0.14	91.88	0.13
2023年10月1日—2023年11月1日	第5次变形	52.06	1.74	46.89	1.56	234.50	7.81
2023年11月1日—2024年5月1日	缓慢匀速变形	28.12	0.16	37.40	0.21	42.54	0.24

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表 2 物理模型试验主要相似系数

Table 2. Key similarity coefficients of physical model test

参量	相似常数	比例因子	参量	相似常数	比例因子
长度	C_l	400	内摩擦角	C_φ	1
重度	C_γ	1	降雨强度	C_q	1
黏聚力	C_c	400

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表 3 原状土体物理力学性质测试

Table 3. Physical and mechanical properties of undisturbed soil

样品编号	取样深度/m	物理力学性质指标
		含水率w/%	天然密度ρ₀/(g·cm⁻³)	干密度ρ_d/(g·cm⁻³)	抗剪强度		土体类型
		含水率w/%	天然密度ρ₀/(g·cm⁻³)	干密度ρ_d/(g·cm⁻³)	黏聚力c/kPa	内摩擦角φ/(°)	土体类型
1	2.4～2.6	19.9	2.04	1.70	29.0	18.6	粉质黏土
2	2.8～3.0	22.9	1.99	1.62	27.0	17.7	粉质黏土
3	5.2～5.4	20.3	2.04	1.70	28.0	18.5	黏土
4	3.4～3.6	25.5	1.98	1.58	22.5	16.1	粉质黏土
5	6.1～6.3	22.3	1.97	1.61	23.3	16.2	粉质黏土
6	9.5～9.7	20.1	2.90	1.58	26.5	17.7	粉质黏土
7	1.6～1.8	19.7	1.91	1.60	29.0	18.2	黏土
8	4.5～4.7	21.9	2.01	1.65	59.0	18.6	黏土
9	7.4～7.6	23.5	1.87	1.51	22.0	16.5	粉质黏土
10	2.5～2.7	19.7	1.93	1.61	27.5	18.9	含砾粉质黏土
11	4.2～4.4	18.9	1.98	1.67	30.2	17.9	粉质黏土
平均值		21.3	2.09	1.6	26.4	17.7

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表 4 滑坡岩土体力学参数

Table 4. Geomechanical parameters of landslide soil and rock mass

	饱和含水率/%	残余含水率/%	饱和渗透系数/(m·s⁻¹)	弹性模量/MPa	泊松比	重度/(kN·m⁻³)	黏聚力/kPa	摩擦角/(°)
含碎石粉质黏土	25	8	0.00001	30	0.30	20.8	25	26
粉质黏土软弱夹层	35	10	0.000001	24	0.40	20.8	15	16
强风化片岩	10	3	5.5×10⁻⁶	1000	0.25	26.8	100	30
中风化片岩	5	1	2.5×10⁻⁷	5000	0.15	—	—	—

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表 5 中国降雨等级划分表

Table 5. Rainfall intensity classification in China

降雨等级	日降雨量/(mm·d⁻¹)	降雨等级	日降雨量/(mm·d⁻¹)
小雨	<10	暴雨	[50, 100)
中雨	[10, 25)	大暴雨	[100, 250)
大雨	[25, 50)	特大暴雨	>250

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表 6 降雨工况分类

Table 6. Classification of rainfall conditions

工况	降雨历时/d	降雨量/mm	备注
工况1（降雨强度）	3	75	25 mm/d（中雨）
		150	50 mm/d（大雨）
		225	75 mm/d（暴雨）
		300	100 mm/d（暴雨）
		450	150 mm/d（大暴雨）
工况2（降雨历时）	5	300	60 mm/d
	7		43 mm/d
	9		34 mm/d
	10		30 mm/d
工况3（降雨雨型）	3	300	150∶100∶50
			50∶150∶100
			50∶100∶150
			100∶100∶100

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表 7 影响因素水平

Table 7. Levels of influencing factors

参数水平	外部因素		内部因素
	降雨条件		滑体土		滑带土
	降雨雨型Q	累计降雨量T/mm	容重γ/ (kN·m⁻³)	渗透系数 K_s/(m·s⁻¹)	黏聚力 c/kPa	内摩擦角φ/(°)
1	5∶3∶1	90	17	5×10^-6	12	13
2	1∶5∶3	135	19	1×10^-5	15	16
3	1∶3∶5	180	21	5×10^-5	18	19
4	1∶1∶1	225	23	1×10^-4	21	22

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表 8 正交设计方案及稳定性系数计算结果

Table 8. Orthogonal test design and stability coefficient calculation results

试验序号	各因素及其参数水平值						稳定性系数
试验序号	Q	T	γ	K_s	c	φ	F_s	F_s1
1	1	1	1	1	1	1	0.684	0.580
2	1	2	2	2	2	2	0.851	0.724
3	1	3	3	3	3	3	1.062	0.887
4	1	4	4	4	4	4	1.280	1.047
5	2	1	2	3	4	4	1.274	1.035
6	2	2	1	4	3	3	1.066	0.894
7	2	3	4	1	2	1	0.751	0.642
8	2	4	3	2	1	2	0.800	0.671
9	3	1	3	4	2	4	1.216	0.959
10	3	2	4	3	1	3	0.991	0.794
11	3	3	1	2	4	2	0.944	0.845
12	3	4	2	1	3	1	0.786	0.701
13	4	1	4	2	3	2	0.960	0.788
14	4	2	3	1	4	1	0.858	0.752
15	4	3	2	4	1	4	1.070	0.872
16	4	4	1	3	2	3	0.930	0.808
17	1	1	2	4	3	4	1.253	1.009
18	1	2	1	3	4	3	1.103	0.946
19	1	3	4	2	1	2	0.830	0.684
20	1	4	3	1	2	1	0.739	0.642
21	2	1	4	1	2	2	0.904	0.733
22	2	2	3	2	1	1	0.696	0.592
23	2	3	2	3	4	4	1.213	1.023
24	2	4	1	4	3	3	1.022	0.885
25	3	1	1	3	4	1	0.913	0.804
26	3	2	2	4	3	2	0.959	0.813
27	3	3	3	1	2	3	0.968	0.799
28	3	4	4	2	1	4	1.076	0.861
29	4	1	3	2	1	3	0.963	0.766
30	4	2	4	1	2	4	1.138	0.915
31	4	3	1	4	3	1	0.830	0.692
32	4	4	2	3	4	2	0.979	0.857
注：Q. 降雨雨型；T. 累计降雨量；γ. 容重；K_s. 渗透系数；C. 黏聚力；φ. 内摩擦角；F_s. 滑坡整体稳定性系数；F_s1. 滑坡前缘稳定性系数；下同

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表 9 滑坡整体及前缘稳定性系数方差分析结果

Table 9. ANOVA results for stability coefficient of entire landslide and its front edge

滑坡部位	统计量	影响因子
滑坡部位	统计量	Q	T	γ	K_s	c	φ
整体	平方和	0.001	0.012	0.009	0.007	0.079	0.313
	自由度	3	3	3	3	3	3
	F	2.69	23.07	16.51	13.91	148.47	590.24
	P	0.089	0	0	0	0	0
	显著性		极显著	极显著	极显著	极显著	极显著
	整体敏感性分析	φ > c > T > K_s > γ > Q
前缘局部	平方和	0.001	0.001	0	0.002	0.076	0.167
	自由度	3	3	3	3	3	3
	F	1.45	3.51	3.12	6.71	207.07	455.07
	P	0.063	0.046	0.275	0.006	0	0
	显著性		显著		极显著	极显著	极显著
	敏感性分析	φ > c > K_s > T > Q > γ

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