【封面论文】基于高分辨率光纤传感神经的库区滑坡热水力响应机理研究

【研究背景】

滑坡滑动区/面的热-水-孔隙-力学特征是当前的研究热点,特别是考虑到近年来水库诱发滑坡对社会造成的巨大损失,这一问题的研究显得尤为迫切。关于关键的工程地质界面在滑坡渐进性破坏中的潜在作用还未得到足够的认识,这一缺口是当前研究的主要瓶颈。深入探索这些界面的作用不仅是基础理论发展的需要,也对防灾减灾工程实践具有重要的意义。 

【研究内容】

为了解决上述问题,我们选择我国三峡库区中游的新铺滑坡作为案例研究,通过使用超弱光纤布拉格光栅(UWFBG)技术,我们在滑坡脚部的一个31米深的钻孔中垂直埋设了特殊的传感光缆,将其称为“大地神经元”,用于收集土壤温度、含水量、孔隙水压力和应变等数据。我们分析了2021-2022年期间的现场监测结果,并在整个钻孔中生成了多参量的时空剖面。 研究结果表明,湿年份比干年份更容易引发滑坡运动。滑坡的年度热活跃层大约在9米的深度,可能在较暖的年份向下移动。动态地下水位位于9-15米深度,应变峰值对年度水文气象周期表现出周期性的跳跃和回退响应。这些界面行为有助于我们了解水库调节及气候变化如何影响库岸边坡的稳定性。此外,本文还提出了一种渐进性库区滑坡的评估新方法,可基于滑坡界面力学行为构建一个可靠的监测预警系统。

【研究意义】

创新:这项研究的创新之处在于我们采用了高分辨率光纤传感技术,成功监测获得了水库诱发滑坡的多物理响应。通过分析滑坡内重要的工程地质界面,我们能够更好地理解滑坡的渐进性破坏机制。此外,我们的研究结果对于解释滑坡的形成机制、预测滑坡风险以及制定相应的防灾措施具有重要的意义。

总结:高分辨率光纤传感技术的应用为我们提供了深入了解水库诱发滑坡的多物理响应的机会。通过研究滑坡滑动区/面之外的界面行为,我们能够更好地理解滑坡的形成机制,并为滑坡监测和预警系统的建立提供了基础。这项研究的成果对于减少滑坡灾害对社会造成的损失具有重要意义,也为相关领域的进一步研究提供了借鉴。

Thermo-hydro-poro-mechanical responses of a reservoir-induced landslide tracked by high-resolution fiber optic sensing nerves

来源:Journal of Rock Mechanics and Geotechnical Engineering

作者:Ye X.; Zhu H.-H.; Cheng G.; Pei H.-F.; Shi B.; Schenato L.; Pasuto A.

作者单位:南京大学, 华北科技学院, 大连理工大学, 意大利国家研究委员会, 意大利帕多瓦大学

出版时间:2024-03-01

DOI:10.1016/j.jrmge.2023.04.004

Abstract: Thermo-poro-mechanical responses along sliding zone/surface have been extensively studied. However, it has not been recognized that the potential contribution of other crucial engineering geological interfaces beyond the slip surface to progressive failure. Here, we aim to investigate the subsurface multiphysics of reservoir landslides under two extreme hydrologic conditions (i.e. wet and dry), particularly within sliding masses. Based on ultra-weak fiber Bragg grating (UWFBG) technology, we employ special-purpose fiber optic sensing cables that can be implanted into boreholes as “nerves of the Earth” to collect data on soil temperature, water content, pore water pressure, and strain. The Xinpu landslide in the middle reach of the Three Gorges Reservoir Area in China was selected as a case study to establish a paradigm for in situ thermo-hydro-poro-mechanical monitoring. These UWFBG-based sensing cables were vertically buried in a 31 m-deep borehole at the foot of the landslide, with a resolution of 1 m except for the pressure sensor. We reported field measurements covering the period 2021 and 2022 and produced the spatiotemporal profiles throughout the borehole. Results show that wet years are more likely to motivate landslide motions than dry years. The annual thermally active layer of the landslide has a critical depth of roughly 9 m and might move downward in warmer years. The dynamic groundwater table is located at depths of 9e15 m, where the peaked strain undergoes a periodical response of leap and withdrawal to annual hydrometeorological cycles. These interface behaviors may support the interpretation of the contribution of reservoir regulation to slope stability, allowing us to correlate them to local damage events and potential global destabilization. This paper also offers a natural framework for interpreting thermo-hydro-poro-mechanical signatures from creeping reservoir bank slopes, which may form the basis for a landslide monitoring and early warning system.

References

Alcántara-Ayala, I., Domínguez-Morales, L., 2008. The San Juan de Grijalva catastrophic landslide, Chiapas, Mexico: lessons learnt. Tokyo, Japan. In: Sassa, K., Canuti, P. (Eds.), Proceedings of the 1st World Landslide Forum, pp. 96-99 (Berlin, Germany).

Alonso, E.E., Zervos, A., Pinyol, N.M., 2016. Thermo-poro-mechanical analysis of landslides: from creeping behaviour to catastrophic failure. Geotechnique 66 (3), 202-219.

Askins, C.G., Tsai, T.E., Williams, G.M., Putnam, M.A., Friebele, E.J., 1992. Fiber Bragg reflectors prepared by a single excimer pulse. Opt. Lett. 17 (11), 833-835.

Baron, I., Cílek, V., Krejcí, O., Melichar, R., Hubatka, F., 2004. Structure and dynamics of deep-seated slope failures in the magura flysch nappe, outer western carpathians (Czech republic). Nat. Hazard Earth Sys 4 (4), 549-562.

Bennett, G.L., Roering, J.J., Mackey, B.H., Handwerger, A.L., Schmidt, D.A., Guillod, B.P., 2016. Historic drought puts the brakes on earthflows in Northern California. Geophys. Res. Lett. 43, 5725-5731.

Blight, G.E., 1997. Interactions between the atmosphere and the earth. Geotechnique 47 (4), 715-767.

Cascini, L., Cuomo, S., Pastor, M., Sorbino, G., 2010. Modeling of rainfall-induced shallow landslides of the flow-type. J. Geotech. Geoenviron. Eng. 1 (1), 85-98.

Cendrero, A., Forte, L.M., Remondo, J., Cuesta-Albertos, J.A., 2020. Anthropocene geomorphic change. Climate or human activities? Earth’s Future 8, e2019EF001305.

Chen, M.L., Yang, X.G., Zhou, J.W., 2022. Spatial distribution and failure mechanism of water-induced landslides in the reservoir areas of Southwest China. J. Rock Mech. Geotech. Eng. 15 (2), 442-456.

Cohen-Waeber, J., Bürgmann, R., Chaussard, E., Giannico, C., Ferretti, A., 2018. Spatiotemporal patterns of precipitation-modulated landslide deformation from independent component analysis of InSAR time series. Geophys. Res. Lett. 45, 1878-1887.

Costa, J.E., Schuster, R.L., 1988. The formation and failure of natural dams. Geol. Soc. Am. Bull. 100 (7), 1054-1068.

De Luca, P., Messori, G., Wilby, R.L., Mazzoleni, M., Di Baldassarre, G., 2020. Concurrent wet and dry hydrological extremes at the global scale. Earth Syst. Dynam. 11, 251-266.

Di Maio, R., De Paola, C., Forte, G., Piegari, E., Pirone, M., Santo, A., Urciuoli, G., 2020. An integrated geological, geotechnical and geophysical approach to identify predisposing factors for flowslide occurrence. Eng. Geol. 267, 105473.

Fan, L.F., Lehmann, P., Zheng, C.M., Or, D., 2020. Rainfall intensity temporal patterns affect shallow landslide triggering and hazard evolution. Geophys. Res. Lett. 47, e2019GL085994.

Ferrari, A., Ledesma, A., González, D.A., Corominas, J., 2011. Effects of the foot evolution on the behaviour of slow-moving landslides. Eng. Geol. 117, 217-218.

Finnegan, N.J., Perkins, J.P., Nereson, A.L., Handwerger, A.L., 2021. Unsaturated flow processes and the onset of seasonal deformation in slow-moving landslides. J. Geophys. Res.: Earth Surf. 126, e2020JF005758.

Freifeld, B.M., Finsterle, S., Onstott, T.C., Toole, P., Pratt, L.M., 2008. Ground surface temperature reconstructions: using in situ estimates for thermal conductivity acquired with a fiber-optic distributed thermal perturbation sensor. Geophys. Res. Lett. 35, L14309.

Froude, M.J., Petley, D.N., 2018. Global fatal landslide occurrence from 2004 to 2016. Nat. Hazards Earth Syst. Sci. 18, 2161-2181.

Hasler, C., 2022. Reaching new levels in groundwater monitoring. Eos 103. https://doi.org/10.1029/2022EO220517.

Ho, Y.T., Huang, A.B., Lee, J.T., 2006. Development of a fibre Bragg grating sensored ground movement monitoring system. Meas. Sci. Technol. 17 (7), 1733-1740.

Hu, X., Bürgmann, R., Schulz, W.H., Fielding, E.J., 2020. Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing. Nat. Commun. 11, 2792.

Hugentobler, M., Loew, S., Aaron, J., Roques, C., Oestreicher, N., 2020. Borehole monitoring of thermo-hydro-mechanical rock slope processes adjacent to an actively retreating glacier. Geomorphology 362, 107190.

Hungr, O., Leroueil, S., Picarelli, L., 2014. The Varnes classification of landslide types, an update. Landslides 11 (2), 167-194.

Iqbal, J., Tu, X.B., Xu, L., 2017. Landslide hazards in reservoir areas: case study of Xiangjiaba reservoir, southwest China. Nat. Hazards Rev. 18 (4), 04017009.

Iverson, R.M., Reid, M.E., Lahusen, R.G., 1997. Debris-flow mobilization from landslides. Annu. Rev. Earth Planet Sci. 25, 85-138.

Jiang, H.W., Li, Y.Y., Zhou, C., Hong, H.Y., Glade, T., Yin, K.L., 2020. Landslide displacement prediction combining LSTM and SVR algorithms: a case study of Shengjibao Landslide from the Three Gorges Reservoir area. Appl. Sci. 10, 7830.

Jones, J.N., Boulton, S.J., Bennett, G.L., Stokes, M., Whitworth, M.R.Z., 2021. Temporal variations in landslide distributions following extreme events: implications for landslide susceptibility modeling. J. Geophys. Res.: Earth Surf. 126, e2021JF006067.

Kafle, L., Xu, W.J., Zeng, S.Y., Nagel, T., 2022. A numerical investigation of slope stability influenced by the combined effects of reservoir water level fluctuations and precipitation: a case study of the Bianjiazhai landslide in China. Eng. Geol. 297, 106508.

Kelam, A.A., Akgün, H., Koçkar, M.K., 2022. Application of an optical fiber-based system for mass movement monitoring. Environ. Earth Sci. 81 (5), 1-18.

Kelam, A.A., Koçkar, M.K., Akgün, H., 2016. Utilization of optical fiber system for mass movement monitoring. Disaster Science and Engineering 2 (1), 19-24.

Lehmann, P., Or, D., 2012. Hydromechanical triggering of landslides: from progressive local failures to mass release. Water Resour. Res. 48, W03535.

Lindner, E., Hartung, A., Chojetzki, D.H.C., Chojetzki, C., Schuster, K., Bierlich, J., Rothhardtal, M., 2014. Trends and future of fiber Bragg grating sensing technologies: tailored draw tower gratings (DTGs). Proc. SPIE 9141, 91410X.

Liu, S.P., Shi, B., Gu, K., Zhang, C.C., He, J.H., Wu, J.H., Wei, G.Q., 2021. Fiber-optic wireless sensor network using ultra-weak fiber Bragg gratings for vertical subsurface deformation monitoring. Nat. Hazards 109, 2557-2573.

Luo, M., Lau, N.C., Liu, Z., Wu, S., Wang, X., 2022. An observational investigation of spatiotemporally contiguous heatwaves in China from a 3D perspective. Geophys. Res. Lett. 49, e2022GL097714.

Ma, F., Yuan, X., 2023. When will the unprecedented 2022 summer heat waves in Yangtze River basin become normal in a warming climate? Geophys. Res. Lett. 50, e2022GL101946.

Moyo, P., Brownjohn, J.M.W., Suresh, R., Tjin, S.C., 2005. Development of fiber Bragg grating sensors for monitoring civil infrastructure. Eng. Struct. 27 (12), 1828-1834.

Müller, L., 1964. The rock slide in the Vajont Valley. Rock Mech. Eng. Geol. 2 (3-4), 148-212.

Ozturk, U., Bozzolan, E., Holcombe, E.A., Shukla, R., Pianosi, F., Wagener, T., 2022. How climate change and unplanned urban sprawl bring more landslides. Nature 608, 262-265.

Palmer, J., 2017. Creeping earth could hold secret to deadly landslides. Nature 548, 384-386.

Paronuzzi, P., Rigo, E., Bolla, A., 2013. Influence of filling-drawdown cycles of the Vajont reservoir on Mt. Toc slope stability. Geomorphology 191 (1e2), 75-93.

Prokesová, R., Medvedová, A., Táborík, P., Snopková, Z., 2013. Towards hydrological triggering mechanisms of large deep-seated landslides. Landslides 10, 239-254.

Read, T., Bour, O., Bense, V., Le Borgne, T., Goderniaux, P., Klepikova, M.V., Hochreutener, R., Lavenant, N., Boschero, V., 2013. Characterizing groundwater flow and heat transport in fractured rock using fiber-optic distributed temperature sensing. Geophys. Res. Lett. 40, 2055-2059.

Rybach, L., Pfister, M., 1994. Temperature predictions and predictive temperatures in deep tunnels. Rock Mech. Rock Eng. 27 (2), 77-88.

Sayde, C., Gregory, C., Gil-Rodriguez, M., Tufillaro, N., Tyler, S., van de Giesen, N., Hochreutener, R., Lavenant, N., Boschero, V., 2010. Feasibility of soil moisture monitoring with heated fiber optics. Water Resour. Res. 46, W06201.

Scaringi, G., Loche, M., 2022. A thermo-hydro-mechanical approach to soil slope stability under climate change. Geomorphology 401, 108108.

Schulz, W.H., Smith, J.B., Wang, G., Jiang, Y., Roering, J.J., 2018. Clayey landslide initiation and acceleration strongly modulated by soil swelling. Geophys. Res. Lett. 45 (4), 1888-1896.

Schuster, R.L., 1979. Reservoir-induced landslides. Bull. Int. Assoc. Eng. Geol. 20, 8-15.

Seguí, C., Veveakis, M., 2021. Continuous assessment of landslides by measuring their basal temperature. Landslides 18, 3953-3961.

Selker, J., van de Giesen, N.,Westhoff, M., Luxemburg,W., Parlange, M.B., 2006. Fiber optics opens window on stream dynamics. Geophys. Res. Lett. 33 (24), L24401.

Shi, B., Zhang, D., Zhu, H.H., Zhang, C.C., Gu, K., Sang, H.W., Han, H.M., Sun, M.Y., Liu, J., 2021. DFOS applications to geo-engineering monitoring. Photonic Sens 11, 158-186.

Sidder, A., 2022. Fiber optics open new frontier for landslide monitoring. Eos 103. https://doi.org/10.1029/2022EO220373.

Soga, K., Luo, L., 2018. Distributed fiber optics sensors for civil engineering infrastructure sensing. J Struct. Integr. Main. 3 (1), 1-21.

Song, K., Wang, F.W., Yi, Q.L., Lu, S.Q., 2018. Landslide deformation behavior influenced by water level fluctuations of the Three Gorges Reservoir (China). Eng. Geol. 247, 58-68.

Sun, M.Y., Shi, B., Zhang, C.C., Liu, J., Guo, J.Y., Zheng, X., Wang, Y.Q., Wei, G.Q., 2022. Quantifying the spatio-temporal variability of total water content in seasonally frozen soil using actively heated fiber Bragg grating sensing. J. Hydrol. 606, 127386.

Sun, M.Y., Shi, B., Zhang, C.C., Zheng, X., Guo, J.Y., Wang, Y.Q., He, M.N., Liu, J., 2021. Quasi-distributed fiber-optic in-situ monitoring technology for large-scale measurement of soil water content and its application. Eng. Geol. 294, 106373.

Tang, H.M., Wasowski, J., Juang, C.H., 2019. Geohazards in the Three Gorges Reservoir area, China-Lessons learned from decades of research. Eng. Geol. 261, 105267.

Tichavský, R., Ballesteros-Cánovas, J.A., Silhán, K., Tolasz, R., Stoffel, M., 2019. Dry spells and extreme precipitation are the main trigger of landslides in Central Europe. Sci. Rep. 9, 14560.

Veveakis, E., Vardoulakis, I., Di Toro, G., 2007. Thermoporomechanics of creeping landslides: the 1963 Vaiont slide, northern Italy. J. Geophys. Res. 112, F03026.

Wang, F.W., Zhang, Y.M., Huo, Z.T., Matsumoto, T., Huang, B.L., 2004. The July 14, 2003 qianjiangping landslide, three Gorges reservoir, China. Landslides 1, 157-162.

Westra, S., Fowler, H.J., Evans, J.P., Alexander, L.V., Berg, P., Johnson, F., Kendon, E.J., Lenderink, G., Roberts, N.M., 2014. Future changes to the intensity and frequency of short-duration extreme rainfall. Rev. Geophys. 52, 522-555.

Xu, J.J., Tang, C.S., Cheng, Q., Vahedifard, F., Liu, B., Shi, B., 2022a. Monitoring and early detection of soil desiccation cracking using distributed fibre optical sensing. Geotechnique. https://doi.org/10.1680/jgeot.21.00397.

Xu, Y.K., Lu, Z., Leshchinsky, B., 2022b. Kinematics of irrigation-induced landslides in a Washington desert: impacts of basal geometry. Geophys. Res. Lett. 127 (2), e2021JF006355.

Yang, M.H., Bai, W., Guo, H.Y., Wen, H.Q., Yu, H.H., Jiang, D.S., 2016. Huge capacity fiber-optic sensing network based on ultra-weak draw tower gratings. Photonic Sens 6 (1), 26-41.

Ye, X., Zhu, H.H.,Wang, J., Zhang, Q., Shi, B., Schenato, L., Pasuto, A., 2022. Subsurface multi-physical monitoring of a reservoir landslide with the fiber-optic nerve system. Geophys. Res. Lett. 49 (11), e2022GL098211.

Yin, Y.P., Huang, B.L., Wang, W.P., Wei, Y.J., Ma, X.H., Ma, F., Zhao, C., 2016. Reservoir induced landslides and risk control in three Gorges project on Yangtze River, China. J. Rock Mech. Geotech. Eng. 8, 577-595.

Zeni, L., Picarelli, L., Avolio, B., Coscetta, A., Papa, R., Zeni, G., Di Maio, C., Vassallo, R., Minardo, A., 2015. Brillouin optical time-domain analysis for geotechnical monitoring. J. Rock Mech. Geotech. Eng. 7 (4), 458-462.

Zhang, C.C., Shi, B., Zhang, S., Gu, K., Liu, S.P., Gong, X.L., Wei, G.Q., 2021a. Microanchored borehole fiber optics allows strain profiling of the shallow subsurface. Sci. Rep. 11, 9173.

Zhang, C.Y., Yin, Y.P., Yan, H., Li, H.X., Dai, Z.W., Zhang, N., 2021b. Reactivation characteristics and hydrological inducing factors of a massive ancient landslide in the three Gorges Reservoir, China. Eng. Geol. 292, 106273.