An updated comprehension of landslide kinematics is a prerequisite for developing effective risk assessment and emergency management in the context of climate variability and anthropogenic disturbances. This study employs a multidisciplinary approach, taking the Outang landslide in China's Three Gorges Reservoir area as a case study. We examined the spatiotemporal surface processes and time- and subzone-dependent hydrometeorological factors from 2007 to 2021, particularly identifying rainfall regimes and reservoir water levels that trigger landslide movements. Given the uneven distribution of GNSS surface markers, we introduced weighted monthly mean displacement (D) and weighted marker frequency (f), enhancing the accuracy of our insights into distinct active subzones of the landslide. Preliminary results revealed July, September and June as months of higher susceptibility, as well as months with low water levels. The early-stage deformation control by reservoir water levels is being increasingly overshadowed by rainfall, due to extreme weather events and localized anti-slip measures. Long-term surface processes have also highlighted the transformation of landslide failure modes towards a compound pattern, from a predominantly retrogressive to a thrust-dominated pattern, and even overall translation coupled with localized rotation. Furthermore, the comparative analysis of normalized displacement/ strain demonstrates the power and potential of integrating multi-source monitoring data. By revisiting the evolution processes and potential deformation mechanisms of the Outang landslide, we are getting closer to understanding more about the dynamics of giant landslides in reservoir areas, and illuminate the pathway towards enhanced risk management and emergency response strategies.

Revisiting spatiotemporal evolution process and mechanism of a giant reservoir landslide during weather extremes

Catani, Filippo
Methodology
2024

Abstract

An updated comprehension of landslide kinematics is a prerequisite for developing effective risk assessment and emergency management in the context of climate variability and anthropogenic disturbances. This study employs a multidisciplinary approach, taking the Outang landslide in China's Three Gorges Reservoir area as a case study. We examined the spatiotemporal surface processes and time- and subzone-dependent hydrometeorological factors from 2007 to 2021, particularly identifying rainfall regimes and reservoir water levels that trigger landslide movements. Given the uneven distribution of GNSS surface markers, we introduced weighted monthly mean displacement (D) and weighted marker frequency (f), enhancing the accuracy of our insights into distinct active subzones of the landslide. Preliminary results revealed July, September and June as months of higher susceptibility, as well as months with low water levels. The early-stage deformation control by reservoir water levels is being increasingly overshadowed by rainfall, due to extreme weather events and localized anti-slip measures. Long-term surface processes have also highlighted the transformation of landslide failure modes towards a compound pattern, from a predominantly retrogressive to a thrust-dominated pattern, and even overall translation coupled with localized rotation. Furthermore, the comparative analysis of normalized displacement/ strain demonstrates the power and potential of integrating multi-source monitoring data. By revisiting the evolution processes and potential deformation mechanisms of the Outang landslide, we are getting closer to understanding more about the dynamics of giant landslides in reservoir areas, and illuminate the pathway towards enhanced risk management and emergency response strategies.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3521589
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