Geomorphic signatures of reservoir–slope hazards triggered by the Baihetan Reservoir impoundment, lower Jinsha River, China
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摘要: 蓄水位变化触发的坡体失稳是高山峡谷区大规模水电开发情景下普遍存在的灾害形式。21世纪以来，由于水电开发加剧，对这种特定类型灾害隐患的识别提出了更高要求。近些年，InSAR观测在很大程度上解决了在大尺度空间开展多目标变形体识别的难题，但由于观测的即时性，无法识别尚未发生变形的隐伏灾患，迫切需要归纳蓄水触发岸坡灾变的地貌标志，以利灾患判别。自2021年白鹤滩库区大规模蓄水以来，连续触发一系列库岸坡体失稳，为总结蓄水灾变地貌标志提供了良好时机。文章通过将InSAR观测、一系列地貌参数及光学影像进行有机结合，即利用2020—2023年期间升轨228景、降轨234景的Sentinel-1A数据，借助DS-InSAR技术对蓄水触发变形坡体进行识别，对其拔河高度、坡度、坡向和起伏度等一系列地貌参数的灾变触发解释力进行了排序，又结合岩层结构、岩性差异、降水与蓄水位变化记录进行了相关性分析，得出了白鹤滩库区蓄水位触发失稳坡体的岩性强弱、岸坡结构和地貌参数及其数值区间，形成的组合形式可作为地貌标志用于实现对该类型灾害隐患的早期识别。在进一步的分析过程中发现，除了蓄水作用之外，降水事件也是库岸坡体失稳不可忽视的驱动因素。该认识对于水电开发背景下的防灾减灾工作具有积极意义，有利于水电站选址与运营，并为其他类型坡体失稳评估提供参考。Abstract:
Objective Slope instability triggered by reservoir water-level fluctuations represents a prevalent geohazard in mountainous regions and canyons undergoing large-scale hydropower development. Since the 21st century, accelerated hydropower development has necessitated enhanced methodologies for identifying such specific-type geohazard potentials. In recent years, InSAR observations have largely addressed the challenge of identifying large-scale, multi-target deformation; however, due to limitations in real-time monitoring capabilities, this technique cannot detect latent hazards that have not yet manifested as deformations. Therefore, there is an urgent need to establish geomorphic signatures of reservoir-induced slope failures to improve hazard identification specificity. The large-scale impoundment of the Baihetan Reservoir since 2021 has triggered a series of slope instabilities, providing an exceptional opportunity to define the geomorphic signatures. Methods We integrated InSAR observations, geomorphic parameters, and optical imagery. Specifically, we utilize 228 ascending and 234 descending Sentinel-1A datasets (2020–2023) processed with DS-InSAR to identify deformed slopes triggered by reservoir water-level fluctuations. Results The results demonstrate the explanatory power of geomorphic parameters such as toe height, slope, aspect, and roughness in relation to disaster triggers. Furthermore, the analysis reveals correlations between lithological variations, slope structures, precipitation, and reservoir water-level fluctuations. Conclusion The strength of lithology, slope structure, and geomorphometric parameters in the Baihetan Reservoir area, along with their corresponding numerical ranges, form composite geomorphic signatures that can be used to identify hazards associated with reservoir water-level-induced slope instability early on. Additionally, we discovered that, beyond the effects of water-level fluctuations , precipitation events also play a significant role in triggering slope instability in the reservoir area, highlighting the importance of this factor as a driving force. Significance These insights significantly advance risk mitigation strategies for hydropower projects, facilitating optimal site selection and operation of hydropower stations, while providing a reference framework for assessing other slope instability mechanisms. -
Key words:
- Baihetan /
- reservoir /
- landslide /
- InSAR /
- geomorphic signatures /
- geodetector /
- geohazard
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图 1 研究区概况图
基于国家地理信息公共服务平台GS(2024)0650号标准地图制作，底图边界无修改a—白鹤滩水电站地理位置；b—研究区范围及海拔；c—不稳定区域1实景照片；d—不稳定区域2实景照片；e—不稳定区域3实景照片；f—不稳定区域4实景照片
Figure 1. Overview map of the study area
(a) Location of the Baihetan Hydropower Station; (b) Extent and elevation of the study area; (c) Photo of unstable area 1; (d) Photo of unstable area 2; (e) Photo of unstable area 3; (f) Photo of unstable area 4 Fig. 1a is produced based on the standard map (No. GS(2024)0650) from the National Geographic Information Public Service Platform, without modification of the base map boundaries.
图 3 斜坡单元划分结果及特征
涉水坡体为与825m水位线存在相交情况的斜坡单元a—斜坡单元；b—斜坡单元面积−数列特征；c—坡向标准差特征
Figure 3. Slope unit delineation and characteristics
(a) Slope units; (b) Area–sequence characteristics of slope units; (c) Aspect standard deviation characteristics Water-influenced slopes refer to those intersecting with the 825 m water level contour.
图 4 地貌参数数值分布情况
a—拔河高度数值分布；b—坡度数值分布；c—地形起伏度数值分布；d—地表粗糙度数值分布；e—平面曲率数值分布；f—剖面曲率数值分布；g—高程变异系数数值分布；h—面积−高程积分值数值分布；i—地表指数数值分布；j—地形湿度指数数值分布；k—输沙能力指数数值分布；l—坡向数值分布
Figure 4. Numerical distribution of geomorphic parameters
(a) Numerical distribution of toe height; (b) Numerical distribution of slope gradient; (c) Numerical distribution of terrain relief; (d) Numerical distribution of surface roughness; (e) Numerical distribution of plan curvature; (f) Numerical distribution of profile curvature; (g) Numerical distribution of elevation coefficient of variation; (h) Numerical distribution of area–elevation integral value; (i) Numerical distribution of surface index; (j) Numerical distribution of topographic wetness index; (k) Numerical distribution of sediment transport capacity index; (l) Numerical distribution of aspect
图 5 DS-InSAR监测地表形变速率
a—基于升轨数据；b—基于降轨数据
Figure 5. Surface deformation rates monitored by DS-InSAR
(a) Based on ascending orbit datasets; (b) Based on descending orbit datasets
图 6 典型变形坡体的InSAR观测特征
a—典型变形坡体1形变特征；b—典型变形坡体2形变特征；c—典型变形坡体3形变特征；d—典型变形坡体4形变特征；e—典型变形坡体5形变特征
Figure 6. InSAR-monitored characteristics of typical deformed slopes
(a) Deformation characteristics of deformed slope 1; (b) Deformation characteristics of deformed slope 2; (c) Deformation characteristics of deformed slope 3; (d) Deformation characteristics of deformed slope 4; (e) Deformation characteristics of deformed slope 5
图 7 变形坡体空间分布
a—基于升轨数据识别的变形坡体所在斜坡单元；b—基于降轨数据识别的变形坡体所在斜坡单元
Figure 7. Spatial distribution of deformed slopes
(a) Slope units with deformed slopes identified from ascending orbit datasets; (b) Slope units with deformed slopes identified from descending orbit datasets
图 8 蓄水与非蓄水触发型变形坡体地貌参数特征
Figure 8. Characteristics of geomorphic parameters for slopes with impoundment-triggered and non-impoundment-triggered deformation
图 9 地貌参数因子解释力（q值）排序
Figure 9. Ranking of the explanatory power (q value) of geomorphic parameters for slopes
(a) Ranking of the explanatory power of geomorphic parameters for water-influenced slopes; (b) Ranking of explanatory power of geomorphic parameters for non-water-influenced slopes
图 10 地貌参数交互作用探测结果
Figure 10. Interaction detection results of geomorphic parameters for slopes
(a) Interaction of geomorphic parameters for water-influenced slopes; (b) Interaction of geomorphic parameters for non-water-influenced slopes
图 11 坡体形变速率及与降水量相关性
a—涉水坡体形变；b—非涉水坡体形变；c—涉水坡体形变与降水相关性；d—非涉水坡体形变与降水相关性
Figure 11. Slope deformation rate and its correlation with precipitation
(a) Deformation rate of water-influenced slopes; (b) Deformation rateof non-water-influenced slopes; (c) Correlation of water-influenced slopes and precipitation; (d) Correlation of non-water-influenced slopes and precipitation
图 12 坡体形变速率及与蓄水位相关性
a—涉水坡体形变；b—非涉水坡体形变；c—涉水坡体形变与蓄水位相关性；d—非涉水坡体形变与蓄水位相关性
Figure 12. Slope deformation rate and its correlation with reservoir level
(a) Deformation rate of water-influenced slopes; (b) Deformation rate of non-water-influenced slopes; (c) Correlation of water-influenced slopes and reservoir level; (d) Correlation of non-water-influenced slopes and reservoir level
图 13 变形坡体的数量分布
岸坡结构划分依据（覃怡等，2015）为岩层倾向与坡向间的夹角，即顺向坡（0°~20°）、斜向坡（20°~70°）、横向坡（70°~100°）、正交坡（接近90°）和反向坡（> 100°）a—在不同岩组；b—在不同岸坡结构
Figure 13. Distribution of deformed slope counts
(a) In different rock formations; (b) In different slope structures The classification of bank–slope structures is based on the angle betweenthe dip direction of the rock layers and the slope direction, i.e., cis-bank slope (0°–20°), diagonal bank–slope (20°–70°), transverse bank–slope (70°–100°), orthogonal bank–slope (close to 90°), and reverse bank–slope (> 100°) （Qin et al.，2015）
图 14 地貌参数间的相关性
Figure 14. Correlation of geomorphic parameters for slopes
(a) Correlation of geomorphic parameters for water-influenced slopes; (b) Correlation of geomorphic parameters for non-water-influenced slopes
表 1 SAR影像及具体参数
Table 1. Basic parameters of SAR datasets
属性 参数 卫星 Sentinel-1A 波段 C 波长/cm 5.6 成像模式 IW 极化方式 VV 入射角/（°） 43.34（升轨） 39.06（降轨） 方位角/（°） 12.54（升轨） 167.46（降轨） 轨道号 升轨（26） 降轨（62） 距离向及方位向分辨率/m×m 5 × 20 最短时间基线/d 12 影像数量/景 228（升轨） 234（降轨） 时间范围 2020-01-09−2023-12-31（升轨） 2020-01-11−2023-12-21（降轨） 多视参数（方位向∶距离向） 2∶8 
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表 2 因子探测结果显著性检验
Table 2. Significance tests for factor detection results
编号 涉水坡体 非涉水坡体 地貌参数 P值 地貌参数 P值 1 坡向 5.80 × 10−11 坡度 5.10 × 10−11 2 输沙能力指数 2.13 × 10−9 拔河高度 1.02 × 10−10 3 坡度 1.11 × 10−8 坡向 3.08 × 10−10 4 地表粗糙度 9.21 × 10−8 输沙能力指数 3.78 × 10−10 5 地形起伏度 3.91 × 10−7 地表指数 4.71 × 10−10 6 拔河高度 1.22 × 10−5 地形起伏度 5.31 × 10−10 7 地形湿度指数 1.71 × 10−5 地表粗糙度 6.84 × 10−10 8 剖面曲率 1.09 × 10−4 平面曲率 6.35 × 10−5 9 平面曲率 5.51 × 10−4 剖面曲率 5.98 × 10−3 10 面积−高程积分值 1.70 × 10−3 高程变异系数 6.66 × 10−3 11 地表指数 8.84 × 10−3 地形湿度指数 8.49 × 10−3 12 高程变异系数 3.97 × 10−2 面积−高程积分值 9.05 × 10−1 注：编号为按显著性检验P值从小到大排序
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表 3 白鹤滩库区蓄水触发岸坡灾变的地貌识别标志
Table 3. Geomorphic signatures of bank–slope disasters triggered by reservoir in the Baihetan Reservoir area
岩性 岸坡结构 地貌参数 较软岩组 反向坡 坡向（西北）、剖面曲率（−2，1）、拔河高度（200 m，500 m） 较软岩组 正交坡 坡向（西北）、地形湿度指数（2.5，6.3）、平面曲率（−1，2） 较软岩组 顺向坡 坡向（西北）、平面曲率（−1，2）、坡度（30°，40°） 较硬岩组 反向坡 坡向（西北）、拔河高度（200 m，500 m）、面积−高程积分值（0.42，0.58） 注：较软岩组包括：凝灰岩、千枚岩、砂质泥岩、泥灰岩、泥质砂岩、粉砂岩、碎屑岩、南方的碳酸盐岩（岩溶发育）等；较硬岩组包括：熔结凝灰岩、大理岩、板岩、白云岩、石灰岩、钙质胶结的砂岩、北部和西部的碳酸盐岩（岩溶不发育）等；标志应用要求：采用30m分辨率DEM时地貌参数提取须基于3×3像元大小的窗口
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