基于时序InSAR技术的木鱼包滑坡时空变形特征分析

刘艺梁; 樊西丰; 申高伟; 左清军; 唐玄; 李永奕; 朱前

doi:10.19509/j.cnki.dzkq.tb20240489

基于时序InSAR技术的木鱼包滑坡时空变形特征分析

doi: 10.19509/j.cnki.dzkq.tb20240489

刘艺梁^{a, b, c,},
樊西丰^{a, b, c, ,},
申高伟^{a, b, c},
左清军^{a, b, c},
唐玄^{a, b, c},
李永奕^{a, b, c},
朱前^{a, b, c}

a.
三峡大学三峡库区地质灾害教育部重点实验室
b.
三峡大学防灾减灾湖北省重点实验室
c.
三峡大学土木与建筑学院，湖北宜昌 443002

基金项目: 国家自然科学基金项目（41807294）；湖北省自然科学基金项目（2018CFB400）

详细信息

作者简介:
刘艺梁：E-mail：lyl@ctgu.edu.cn

通讯作者:
E-mail：1518226868@qq.com

中图分类号: P237; P642.22
计量
- 文章访问数: 126
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2024-08-28
- 录用日期: 2024-10-21
- 修回日期: 2024-10-10
- 网络出版日期: 2024-11-18

Analysis of spatio-temporal deformation characteristics of the Muyubao landslide via time series InSAR technology

LIU Yiliang^{a, b, c
,},
FAN Xifeng^{a, b, c
, ,},
SHEN Gaowei^{a, b, c},
ZUO Qingjun^{a, b, c},
TANG Xuan^{a, b, c},
LI Yongyi^{a, b, c},
ZHU Qian^{a, b, c}

a.
China Three Gorges University Key Laboratory of Geological Hazards on Three Gorges Reservoir Area, Ministry of Education
b.
China Three Gorges University Hubei Key Laboratory of Disaster Prevention and Mitigation
c.
China Three Gorges University College of Civil Engineering & Architecture, China Three Gorges University, Yichang Hubei 443002, China

More Information

Author Bio:
E-mail：lyl@ctgu.edu.cn

Corresponding author: E-mail：1518226868@qq.com

摘要

摘要:
自2003年三峡库区蓄水以来，木鱼包滑坡持续变形，严重威胁长江航运和库区人民生命财产安全。为全面精准地分析滑坡地表变形信息，采用斯坦福永久散射体−多时相InSAR（StaMPS-MTI）技术和短基线集时序InSAR（SBAS-InSAR）技术结合哨兵一号数据反演木鱼包滑坡2017−2022年的地表形变，并与全球导航卫星系统（GNSS）监测数据进行对比分析，结合2种技术的优点，点面结合对滑坡的时空变形特征进行了分区研究。研究结果表明：InSAR技术得到的形变信息可靠，2种时序InSAR技术各有优劣；对比各个分区的形变速率区间值，滑坡东侧坡面（−30.6～−46.2 mm/a）>主滑面东侧（−25.2～−37.8 mm/a）>主滑面西侧（−21.5～−31.5 mm/a）。在InSAR形变结果和前人研究基础上，对木鱼包滑坡变形模式进行了总结：木鱼包滑坡变形受降雨和库水影响，分为整体变形和局部变形2种。在高水位运行期，滑坡受浮托减重作用发生整体变形，库水阈值约为168 m。强降雨入渗岩体使地下水位升高，促使整体变形的同时，影响浅层土体和破碎岩体导致局部变形。在库水位下降期，滑坡受浮托减重和动水压力共同影响，其中浮托减重作用占主导地位，动水压力存在约36 d的滞后时间。在低水位运行期和库水位上升期，整体变形停止，强降雨使局部变形区发生变形。研究结果证明时序InSAR技术可以有效识别和监测滑坡，可以为地质灾害防治、风险评价提供技术支撑。
- 木鱼包滑坡 /
- 形变监测 /
- SBAS-InSAR /
- StaMPS-MTI /
- 三峡库区 /
- 库水位 /
- 降雨
Abstract: <p>Since the impoundment of the Three Gorges Reservoir Area in 2003, the Muyubao landslide has continuously deformed, posing significant risks to Yangtze River navigation and the safety of people's lives and property in the reservoir area. </p></sec><sec><title>Objective
To more comprehensively and accurately analyze the surface deformation information of the landslide,
Methods
this study employs the Stanford method for persistent scatterers-multi-temporal InSAR (StaMPS-MTI) and small baseline subset InSAR (SBAS-InSAR) technology, combined with Sentinel-1 data, to invert the deformation information of the Muyubao landslide from 2017 to 2022. The deformation information is compared with GNSS monitoring data, and a regional analysis of the spatio-temporal deformation characteristics of the landslide is conducted by integrating the advantages of both technologies through a combination of point and surface measurements.
Results
The results confirm that the deformation information obtained by InSAR technology is reliable, and each time-series InSAR technology has its own strengths and limitations. Specifically, the deformation rate intervals are as follows: the eastern slope of the landslide (−30.6 to −46.2 mm/year) > the eastern side of the major slipping plane (−25.2 to −37.8 mm/year) > the western side of the major slipping plane (−21.5 to −31.5 mm/year).
Conclusion
Based on the InSAR deformation results and previous studies, the deformation mode of the Muyubao landslide can be summarized as follows: the landslide undergoes overall and local deformation influenced by rainfall and reservoir water levels. During high water level periods, buoyancy-induced weight loss causes overall deformation, with a critical water level threshold of approximately 168 m. Heavy rainfall infiltrates the rock mass, raising the groundwater level, which promotes overall deformation and triggers local deformation in shallow soil and fractured rock masses. During the reservoir water decline period, the landslide is influenced by both buoyancy-induced weight loss and hydrodynamic pressure, with buoyancy effects being dominant; the hydrodynamic pressure effect lags by about 36 days. During low water level and rising water periods, overall deformation ceases, and heavy rainfall primarily causes localized deformation. The results indicate that time-series InSAR technology can effectively identify and monitor landslides, providing technical support for geological disaster prevention and risk assessment.
- Muyubao landslide /
- deformation monitoring /
- SBAS-InSAR /
- StaMPS-MTI /
- Three Gorges Reservoir area /
- reservoir water level /
- rainfall

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图 1 木鱼包滑坡地理位置及概况

A区. 东侧坡面；B区. 主滑面东部；C区. 主滑面西部；下同

Figure 1. Geographical location and overview of the Muyubao landslide

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图 2 木鱼包滑坡工程地质剖面图

Figure 2. Engineering geological profile of the Muyubao landslide

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图 3 时空基线图

Figure 3. Space-time baseline

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图 4 木鱼包滑坡2017年3月−2022年12月时序InSAR结果图

a.基于StaMPS-MTI的形变速率分布图；b. 基于SBAS-InSAR的形变速率分布图；c. GNSS监测方向图；d. 基于SBAS-InSAR的不同分区形变速率分布箱线图

Figure 4. Time-series InSAR results map of the Muyubao landslide from March 2017 to Decemeber 2022

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图 5 木鱼包滑坡时序曲线结果对比图

Figure 5. Time series curve results comparison diagram of the Muyubao landslide

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图 6 木鱼包滑坡累计位移增量图

Figure 6. Cumulative displacement increment diagram of the Muyubao landslide

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图 7 蠕滑变形阶段中位数累计天数−平均累计位移增量 (a) 及月峰值降雨量−位移增量差值 (b) 图

Figure 7. Accumulated days-displacement increment (a) and monthly peak rainfall-displacement increment difference (b) in creep deformation stage

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图 8 木鱼包滑坡控制点分布 (a) 及其时序曲线 (b～d)

Figure 8. Control point distribution (a) and time-series curve (b-d) of the Muyubao landslide

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图 9 控制点位移−库水位−降雨曲线

Ⅰ～Ⅵ为库水位运动曲线划分的6个阶段

Figure 9. Control point displacement-reservoir water level-rainfall curve

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图 10 木鱼包滑坡剖面线位置 (a) 及累计形变速率 (b～d) 图

Figure 10. Profile line position (a) and cumulative deformation rate diagram (b-d) of the Muyubao landslide

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图 11 木鱼包滑坡局部变形现象图

a. A区中部局部坍塌；b. A区中部公路拉裂；c. B区前缘块崩落；d. C区后部建筑错动

Figure 11. Local deformation phenomenon diagram of the Muyubao landslide

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表 1 木鱼包滑坡时序曲线结果对比表

Table 1. Time series curve results comparison table of the Muyubao landslide

监测站点	RMSE/mm		MAE/mm		余弦相似度		累计位移差/mm
监测站点	StaMPS	SBAS	StaMPS	SBAS	StaMPS	SBAS	StaMPS	SBAS
ZGX295	11.9315	14.6127	10.0547	12.2512	0.9973	0.9947	13.2312	16.4967
ZGX296	16.0125	34.8575	13.2624	33.243	0.9973	0.9951	24.7207	30.2178
ZGX297	23.0645	60.3476	21.7981	56.6074	0.9959	0.9886	20.3274	64.2438
ZGX298	7.3346	43.1930	5.8499	40.2692	0.9960	0.9318	7.0869	26.9161

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表 2 StaMPS曲线与GNSS曲线拟合优度表

Table 2. Goodness of fit table of StaMPS curve and GNSS curve

监测站点	ZGX295	ZGX296	ZGX297	ZGX298
拟合优度R²	0.9644	0.9360	0.8666	0.9558

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表 3 整体变形阶段统计表

Table 3. Statistical table of overall deformation stage

时段序号	时间	中高水位 (≥165 m) 累计天数/d	高水位 (≥170 m) 累计天数/d	月峰值降雨量/ mm	平均累计位移增量/ mm
②	2017/09/08-2018/03/07	159	131	208.6	−29.9
④	2018/09/03-2019/03/02	155	130	138.2	−22.1
⑥	2019/09/10-2020/03/08	148	96	163.2	−18.0
⑧	2020/09/04-2021/03/03	152	124	161.6	−19.3
⑩	2021/09/11-2022/03/10	175	124	51.4	−29.1

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表 4 蠕滑变形阶段统计表

Table 4. Statistical table of creep deformation stage

时段序号	时间	库水下降期中水位(≥160 m) 累计天数/d	月峰值降雨量/ mm	平均累计位移增量/ mm	累计位移增量峰值/ mm
①	2017/03/12-2018/09/08	53	数据缺失	−5.9	−28.9
③	2018/03/07-2018/09/03	60	233.0	−12.8	−29.4
⑤	2019/03/02-2019/09/10	38	183.6	−0.8	−15.5
⑦	2020/03/08-2020/09/04	49	256.6	−6.0	−23.5
⑨	2021/03/03-2021/09/11	55	146.6	−8.5	−33.3
⑪	2022/03/10-2022/09/06	71	177.6	−16.8	−41.4

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