Deformation history analysis and movement process simulation of glacier debris flow in Sanggu Valley in southern Tibet
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摘要:
藏东南雅鲁藏布江流域冰川型泥石流规模大、持续时间长、冲击力强，由于传统方法难以定量描述大尺度泥石流形成机理问题，根据桑谷沟流域泥石流现场实地调研、无人机航拍、卫星影像信息以及地质气象数据，揭示桑谷沟泥石流的暴发与物源、降雨量等因素之间关系，提出了一种联合InSAR与RAMMS技术全面分析泥石流爆发前物源形变过程与爆发期间泥石流运动特征的方法。基于SBAS-InSAR技术，针对桑谷沟泥石流2次爆发期间的形变进行分析，结合卫星影像图、无人机影像以及现场勘察，实现了桑谷沟泥石流灾害爆发前形变过程反演和灾变趋势预测；采用RAMMS泥石流数值模拟软件对桑谷沟泥石流爆发期间运动过程进行了模拟。研究表明：①通过InSAR技术解算桑谷沟泥石流LOS向形变，坡体长期处于蠕滑状态；物源区内最大形变速率为139 mm/a，流通区内速率最大为46 mm/a，堆积区速率最大为20 mm/a；降雨作用为泥石流发育提供了大量的松散来源。②根据不同步时状态下泥石流堆积深度和流速状态，将研究区演进过程划分为初始运动、加速运动、减速−最终3个阶段。该方法联合冰川泥石流形变历史分析和运动过程模拟，对泥石流发展趋势及预测提供科学依据，并为工程防治设计提供参考。
Abstract:Glacial debris flows in the Yarlung Zangbo River basin of southeastern Tibet are characterized by their large scale, prolonged duration, and significant societal and environmental impacts. Investigating the deformation characteristics and influencing factors of Sanggu Valley debris flow offers critical scientific insights for predicting, early warning, and mitigating glacial debris flow disasters in this region. Traditional methods often fall short in quantitatively describing the formation mechanisms of large-scale debris flows. To address this limitation, this study integrates field investigations, unmanned aerial vehicle (UAV) aerial photography, satellite imagery, and geological and meteorological data.
Objective This study aims to elucidate the relationship between debris flow outbreaks in Sanggu Valley and key influencing factors, including material sources and rainfall patterns.
Methods A novel method combining interferometric synthetic aperture radar (InSAR) and random-access mass spectrometry (RAMMS) techniques is developed to analyze the deformation process of debris flows before and during their initiation. SBAS-InSAR technology is employed to quantify the deformation of Sanggu Valley debris flow during two outbreaks, complemented by satellite images, UAV images, and field investigations. This approach enables the inversion of deformation processes and the prediction of disaster trends prior to the Sanggu Valley debris flow event. Additionally, RAMMS debris flow numerical simulation software is utilized to model the movement dynamics of the Sanggu Valley debris flow during its eruption.
Results This study yields the following key findings: ① InSAR-derived LOS deformation analysis of the Sanggu Valley debris flow reveals the prolonged slope creep, with maximum deformation rates of 139 mm/a in the source area, 46 mm/a in the flow area, and 20 mm/a in the accumulation area. Rainfall is identified as a critical factor in supplying loose materials for debris flow development. ②The evolution process of the debris flow is categorized into three stages: initial motion, accelerated motion, and deceleration.
Conclusion The proposed methodology, which integrates historical deformation analysis and numerical simulation of glacial debris flow dynamics, provides a scientific foundation for predicting debris flow development trends and designing effective engineering control measures.
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Key words:
- glacier debris flow /
- SBAS-InSAR /
- RAMMS /
- drone aerial photography /
- causes of debris flow /
- Sanggu Valley /
- southern Tibet
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图 1 研究区概况及SAR影像覆盖情况
a. 研究区地理位置及SAR覆盖情况；b. 桑谷沟泥石流全貌。LOS. 雷达视线方向
Figure 1. Overview of SAR image coverage in the study area
图 3 桑谷沟冰川分布（a）及现场调查冰川情况（b，c）
Figure 3. Glacier distribution (a) and field investigation (b, c) in Sanggu Valley
图 4 SBAS-InSAR技术流程图
SLC. 单视复数（single look complex）；GCP. 地面控制点（ground control point）；DEM. 数字高程模型（digital elevation model）
Figure 4. SBAS-InSAR technical flow chart
图 5 升降轨时空基线分布
图中数字为每个时间节点，且节点个数即为SAR影响数量
Figure 5. Space-time baseline distributions of the ascending and descending orbits
图 6 桑谷沟泥石流升降轨LOS向位移速率图
a. 升轨数据解译结果；b. 降轨数据解译结果
Figure 6. LOS displacement velocity map of the sangu valley debris flow in ascending and descending orbits
图 7 2020/10/02−2021/06/11升轨累计形变
Figure 7. Cumulative deformation in ascending orbit from october 2, 2020 to June 11, 2021
图 8 2020/10−2021/06坡体累计形变剖面（剖面A−A'位置见图7）
Figure 8. Slope cumulative deformation profile from October 2020 to June 2021
图 9 泥石流形成区时序形变与降雨数据相关性对比（降雨量数据来源于美国国家海洋和大气管理局，源格式为csv；特征监测点位置见图7）
Figure 9. Formation zone time-series deformation of debris flow in relation rainfall data
图 10 InSAR精度评估与验证
a. 非显著形变区监测统计直方图；b. 2018 年 Google Earth 影像（桑谷沟泥石流爆发前）；c. 2021 年 Google Earth 影像（桑谷沟泥石流爆发后）；d，e. 无人机拍摄资料。2020年9月26日桑谷沟爆发泥石流
Figure 10. Accuracy evaluation and verification of InSAR
图 11 桑谷沟泥石流不同步时堆积深度状态图
Figure 11. Map of accumulation depth of Sanggu Valley debris flow when it is not synchronized
图 12 桑谷沟泥石流不同步时流速状态图
Figure 12. Flow velocity state diagram of Sanggu Valley debris flow when it is not synchronized
图 13 桑谷沟泥石流最大堆积深度(a)与最大流速(b)图
Figure 13. Maximum accumulation depth (a) and maximum velocity (b) of debris flow in Sanggu Valley
表 1 Sentinel-1A升降轨SAR影像参数
Table 1. Sentinel-1A ascending and descending orbit SAR image parameters
参数类别 SAR传感器Sentinel-1A 轨道方向 升轨 降轨 空间分辨率/m 5×20 5×20 重访周期/d 12 12 入射角/(°) 40.92 37.03 飞行角/(°) 347.30 192.70 影像数量/个 18 24 监测时间 2020-10-02−2021-06-11 2020-09-27−2021-06-30 
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