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Towards hydrometeorological thresholds of reservoir-induced landslide from subsurface strain observations

Science China(Technological Sciences) 2024年第6期67卷 1907-1922页

作者： YE Xiao ZHU HongHu WANG Jia ZHENG WanJi ZHANG Wei SCHENATO Luca PASUTO Alessandro CATANI Filippo School of Earth Sciences and Engineering Nanjing UniversityNanjing210023China Department of Geosciences University of PadovaPadova35131Italy School of Geosciences and Info-Physics Central South UniversityChangsha410083China Department of Information Engineering University of PadovaPadova35131Italy National Research Council-Research Institute for Geo-Hydrological Protection(CNR-IRPI) Padova35127Italy

Synergistic multi-factor early warning of large-scale landslides is a crucial component of geohazard prevention and mitigation efforts in reservoir *** forecasting and early warning based on surface displacements have been widely ***,the lack of direct subsurface real-time observations limits our ability to predict critical hydrometeorological conditions that trigger landslide *** this paper,we leverage subsurface strain data measured by high-resolution fiber optic sensing nerves that were installed in a giant reservoir landslide in the Three Gorges Reservoir(TGR)region,China,spanning a whole hydrologic year since February *** spatiotemporal strain profile has preliminarily identified the slip zones and potential drivers,indicating that high-intensity short-duration rainstorms controlled the landslide kinematics from an observation *** the time lag effect,we reexamined and quantified potential controls of accelerated movements using a data-driven approach,which reveals immediate response of landslide deformation to extreme rainfall with a zero-day *** identify critical hydrometeorological rules in accelerated movements,accounting for the dual effect of rainfall and reservoir water level variations,we thus construct a landslide prediction model that relies upon the boosting decision tree(BDT)algorithm using a dataset comprising daily rainfall,rainfall intensity,reservoir water level,water level fluctuations,and slip zone strain time *** results indicate that landslide acceleration is most likely to occur under the conditions of mid-low water levels(i.e.,57.9 mm and rainfall intensity>24.4 mm/h).Moreover,this prediction model allows us to update hydrometeorological thresholds by incorporating the latest monitoring *** on the shoulder of this landslide case,our study informs a practical and reliable path

关键词： slow-moving landslide fiber-optic monitoring subsurface strain hydrometeorological threshold extreme weather

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