Method of landslide early warning and prediction based on deep displacement: A case study of a super large landslide in the reservoir area of a hydropower station in Yunnan
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摘要:
研究目的 水电站库区特大型滑坡形成机理极其复杂，现有预警预报方法很难准确预测滑坡变形阶段。
研究方法 为了更准确地对其进行预警预报研究，采用钻孔深部位移监测法，结合测斜仪监测原理，对现有的预警方法加以改进，提出针对测斜仪的动能、动能变化率预警指标。在此基础上，依据DH特大型滑坡的深部位移监测数据，对累积合位移-深度曲线、变形速率、变形加速度、动能及动能变化率的趋势和时间界限值进行分析，确立了辨识滑坡变形演化阶段的方法。
研究结果 研究结果表明，滑坡在不同的分区存在多个滑动面，滑动面以上呈现整体滑动趋势；滑坡由匀速变形阶段进入加速变形阶段，动能变化率有明显的增加且会大幅度波动。
结论 建立的基于深部位移动能和动能变化率预警指标的滑坡变形演化阶段辨识方法对每个阶段的划分和预警时间的辨识相较于速率和加速度曲线更加准确，能更好地识别出水电站库区特大型滑坡所处的变形阶段，为判断此类滑坡所处变形阶段提供参考依据。
Abstract:Objective The mechanism of super large landslides in hydropower station reservoir areas is extremely complex. It is difficult to accurately predict the deformation stage of landslides using existing early warning and prediction methods.
Methods In order to conduct more accurate early warning and prediction research on it, this article adopts the borehole deep displacement monitoring method. An improved early warning indicator of kinetic energy and kinetic energy change rate for inclinometers was proposed, which based on the monitoring principle of inclinometers. On the basis of deep displacement monitoring data of the DH super large landslide, the trend and time limit values of cumulated displacement depth curve, deformation rate, deformation acceleration, kinetic energy and its variation rate were analyzed. A method was established to identify the stages of landslide deformation evolution.
Results The research results indicate that landslides have multiple sliding surfaces in different zones, and there is an overall sliding trend above the landslide sliding surface. During the process of landslide from uniform deformation stage to accelerated deformation stage, the rate of kinetic energy change significantly increases and fluctuates significantly. The identification method for landslide deformation evolution stages based on deep displacement kinetic energy and kinetic energy change rate warning indicators is established.
Conclusions This method is more accurate in dividing each stage and identifying warning time compared to the rate and acceleration curves. Not only can it better identify the deformation stage of super lager landslides in hydropower station reservoir areas, but it can also provide a reference basis for determining the deformation stage of such landslides.
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[1] Acharya A, Kogure T. 2023. Application of novel distributed fibre−optic sensing for slope deformation monitoring: A comprehensive review[J]. Int. J. Environ. Sci. Technol., 20: 8217−8240. doi: 10.1007/s13762-022-04697-5
[2] Chung C C, Tran V, Azhar M. 2022. Guidelines from direct shear modeling in centrifuge for TDR landslide monitoring[J]. Engineering Geology, 310: 106870. doi: 10.1016/j.enggeo.2022.106870
[3] Chen H, Li Y J, Fang R, et al. 2015. A novel technique for monitoring deep displacement and early−warning of landslide[J]. Chinese Journal of Rock Mechanics and Engineering, 34(Supp.2): 4063−4070 (in Chinese with English abstract).
[4] Chen H, Tang H, Ge X R, et al. 2019. Research on early warning of creep landslide by early−warning indictors based on deep displacements[J]. Chinese Journal of Rock Mechanics and Engineering, 38(S1): 3015−3024 (in Chinese with English abstract).
[5] Chung C C, Wei S K, Tang H T. 2023. Optimal time domain reflectometry penetrometer design for soil water content and electrical conductivity profiling[J]. Geotechnical Testing Journal, 46(1): 168−189. doi: 10.1520/GTJ20220030
[6] Dai Y, Dai W J, Yu W K. 2022. A landslide multi−objective weighted displacement back analysis method synthesizing ground and underground displacement monitoring data[J]. Acta Geodaetica et Cartographica Sinica, 51(10): 2149−2159 (in Chinese with English abstract).
[7] Emanuele I, Giocanni G, Francesco M, et al. 2012. Design and implementation of a landslide early warning system[J]. Engineering Geology, 10(147/148): 124−136.
[8] Feng Z, Jin F X, Gong Y F. 2011. Monitoring and deformation failure analysis of red sandstone bedding slope[J]. Chinese Journal of Rock Mechanics and Engineering, 30(Suppl.2): 4078−4086 (in Chinese with English abstract).
[9] Guo Y X. 2014. Research on monitoring technology and application of high−steep slope and rockfall based on fiber bragg grating[D]. PhD Dissertation of Wuhan University of Technology (in Chinese with English abstract).
[10] He M C. 2009. Real−time remote monitoring and forecasting system for geological disasters of landslides and its engineering application[J]. Chinese Journal of Rock Mechanics and Engineering, 28(6): 1081−1090 (in Chinese with English abstract).
[11] Jin X G, Wang L S, Li X H. 2001. Determination and advanced forcasting on slide plane position for landslide[J]. The Chinese Journal of Geological Hazard and Control, (1): 14−16 (in Chinese with English abstract).
[12] Li C, Zhu J B, Wang B, et al. 2016. Critical deformation velocity of landslides in different deformation phases[J]. Chinese Journal of Rock Mechanics and Engineering, 35(7): 1407−1414 (in Chinese with English abstract).
[13] Liu J X, Guo C B, Wu R A, et al. 2024. Creeping deformation characteristics and stability analysis of Guili large deep−seated landslide in Jiangda, Xizang[J]. Geological Bulletin of China, 43(10): 1855−1868 (in Chinese with English abstract).
[14] Sun Z B, Yang X L. 2010. Sliding characteristics analysis of land slide based on the deep displacement[J]. Journal of Changsha University of Science & Technology(Natural Science), 7(2): 43−47 (in Chinese with English abstract).
[15] Tan H H, Fu H L. 2010. Testing study of application of time domain reflectometry to highway slope monitoring[J]. Rock and Soil Mechanics, 31(4): 1331−1336 (in Chinese with English abstract).
[16] Tang X S, Zheng Y R, Tang H M, et al. 2013. Numerical researches on deformation characteristics and prediction of reservoir landslides[J]. Chinese Journal of Geotechnical Engineering, 35(5): 940−947 (in Chinese with English abstract).
[17] Tan Q L, Bai M Z, Zhou P G, et al. 2021. Geological hazard risk assessment of line landslide based on remotely sensed data and GIS[J]. Measurement, 169: 108370. doi: 10.1016/j.measurement.2020.108370
[18] Thapa P S, Adhikari B R, Shaw R, et al. 2023. Geomorphological analysis and early warning systems for landslide risk mitigation in Nepalese mid−hills[J]. Nat Hazards, 117: 1793−1812. doi: 10.1007/s11069-023-05929-8
[19] Uwihirwe J, Hrachowitz M, Bogaard T, et al. 2022. Integration of observed and model−derived groundwater levels in landslide threshold models in Rwanda[J]. Nat. Hazards Earth Syst. Sci., 22: 1723−1742. doi: 10.5194/nhess-22-1723-2022
[20] Wang Z G, He W, Wang K. 2012. Geological hazard prevention and environment protection for water conservancy and hydropower engineering[J]. The Chinese Journal of Geological Hazard and Control, 23(2): 70−74 (in Chinese with English abstract).
[21] Wang K, Zhang W Y, Ma F, et al. 2015. Monitoring Methods of Landslide Deep Deformation and Discussion on Their Application[J]. Chinese Journal of Underground Space and Engineering, 11(1): 204−209 (in Chinese with English abstract).
[22] Wang M H, Li Y, Pei Y Q. 2023. Disaster characteristics and stability evaluation of the Hanjin Beishan landslide group in Linxia Basin, Gansu Province[J]. Geological Bulletin of China, 42(2/3): 460−468 (in Chinese with English abstract).
[23] Xu Q, Tang M G, Xu K X, et al. 2008. Research on space−time evolution laws and early warning−prediction of landslides[J]. Chinese Journal of Rock Mechanics and Engineering, 27(6): 1104−1112 (in Chinese with English abstract).
[24] Xu Q, Zeng Y P. 2009. Research on acceleration variation characteristics of creep landslide and early−warning prediction indicator of critical sliding[J]. Chinese Journal of Rock Mechanics and Engineering, 28(6): 1099−1106 (in Chinese with English abstract).
[25] Xu Q, Yuan Y, Zeng Y P, et al. 2011. Some new pre−warning criteria for creep slope failure[J]. Science China−Technological Sciences, 54(Supp.1): 210−220.
[26] Xu Q. 2012. Theoretical studies on prediction of landslides using slope deformation process data[J]. Journal of Engineering Geology, 20(2): 145−151 (in Chinese with English abstract).
[27] Zhang Z H, Feng X T, Zhou H, et al. 2009. Research on dynamic early warning method of slope deformation monitoring during excavation based on designed safety factor and failure mode[J]. Rock and Soil Mechanics, 30(3): 603−612 (in Chinese with English abstract).
[28] Zhang Y F, Fan J W, Yuan K. 2023. Disaster−induced mechanisms and prevention and control new technologies of major landslides[J]. Chinese Journal of Rock Mechanics and Engineering, 42(8): 1910−1927 (in Chinese with English abstract).
[29] 陈贺, 李亚军, 房锐, 等. 2015. 滑坡深部位移监测新技术及预警预报研究[J]. 岩石力学与工程学报, 34(增2): 4063−4070.
[30] 陈贺, 汤华, 葛修润, 等. 2019. 基于深部位移的蠕滑型滑坡预警指标及预警预报研究[J]. 岩石力学与工程学报, 38(S1): 3015−3024.
[31] 戴粤, 戴吾蛟, 余文坤. 2022. 综合地表与深部位移监测数据的滑坡多目标加权位移反分析方法[J]. 测绘学报, 51(10): 2149−2159. doi: 10.11947/j.AGCS.2022.20210163
[32] 冯振, 金福喜, 龚裔芳. 2011. 红砂岩顺层边坡监测及变形破坏分析[J]. 岩石力学与工程学报, 30(增2): 4078−4086.
[33] 郭永兴. 2014. 基于光纤光栅的高陡边坡及危岩落石监测技术与应用研究[D]. 武汉理工大学博士学位论文.
[34] 何满潮. 2009. 滑坡地质灾害远程监测预报系统及其工程应用[J]. 岩石力学与工程学报, 28(6): 1081−1090. doi: 10.3321/j.issn:1000-6915.2009.06.001
[35] 靳晓光, 王兰生, 李晓红. 2001. 滑坡滑动面位置的确定及超前预测[J]. 中国地质灾害与防治学报, 2001(1): 14−16.
[36] 李聪, 朱杰兵, 汪斌, 等. 2016. 滑坡不同变形阶段演化规律与变形速率预警判据研究[J]. 岩石力学与工程学报, 35(7): 1407−1414.
[37] 刘吉鑫, 郭长宝, 吴瑞安, 等. 2024. 西藏江达圭利大型深层滑坡蠕滑变形特征与稳定性分析[J]. 地质通报, 43(10): 1855−1868.
[38] 孙志彬, 杨小礼. 2010. 基于深部位移的边坡特征分析[J]. 长沙理工大学学报: 自然科学版, 7(2): 43−47.
[39] 谭捍华, 傅鹤林. 2010. TDR技术在公路边坡监测中的应用实验[J]. 岩土力学, 31(4): 1331−1336.
[40] 唐晓松, 郑颖人, 唐辉明, 等. 2013. 水库滑坡变形特征和预测预报的数值研究[J]. 岩土工程学报, 35(5): 940−947.
[41] 王自高, 何伟, 王昆. 2012. 水利水电工程中地质灾害预防与地质环境保护对策探讨[J]. 中国地质灾害与防治学报, 23(2): 70−74.
[42] 王凯, 张伟毅, 马飞, 等. 2015. 滑坡深部变形监测方法与应用探讨[J]. 地下空间与工程学报, 11(1): 204−209.
[43] 汪美华, 李勇, 裴叶青. 2023. 甘肃临夏盆地韩集北山滑坡群致灾特征与稳定性评价[J]. 地质通报, 42(2/3): 460−468.
[44] 许强, 汤明高, 徐开祥, 等. 2008. 滑坡时空演化规律及预警预报研究[J]. 岩石力学与工程学报, 27(6): 1104−1112. doi: 10.3321/j.issn:1000-6915.2008.06.003
[45] 许强, 曾裕平. 2009. 具有蠕变特点滑坡的加速度变化特征及临滑预警指标研究[J]. 岩石力学与工程学报, 28(6): 1099−1106. doi: 10.3321/j.issn:1000-6915.2009.06.003
[46] 许强. 2012. 滑坡的变形破坏行为与内在机理[J]. 工程地质学报, 20(2): 145−151. doi: 10.3969/j.issn.1004-9665.2012.02.001
[47] 张振华, 冯夏庭, 周辉, 等. 2009. 基于设计安全系数及破坏模式的边坡开挖过程动态变形监测预警方法研究[J]. 岩土力学, 30(3): 603−612.
[48] 张玉芳, 范家玮, 袁坤. 2023. 重大滑坡灾变机制与防治新技术研究[J]. 岩石力学与工程学报, 42(8): 1910−1927.
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