17:15 〜 19:15
[SSS07-P08] Study on seasonal variations of wave velocity and its influence factors on rock slope: application to the Pubugou rock slope in Southwest China
キーワード：Ambient seismic noise interferometry, Rock slope stability, Seismic velocity variation, Damage evolution of landslides
Ambient seismic noise interferometry has been recently used to monitor the damage evolution of landslides. The measured velocity changes of slopes at shallow depth play a crucial role in better understanding the mechanical changes of slopes under different external loadings.
In this work, by using the continuous ambient noise data recorded by two seismic seismometers deployed on the slow-moving Pubugou rock slope in southwest China, we conduct a 2.5-year in-situ monitoring of the daily seismic velocity changes of the slope. The results show that the seismic velocity changes exhibit seasonal reversible fluctuations in the range of -1.5% to 2.0% on an annual scale which is well linearly correlated with the changes in the air temperature, while the precipitation induced seimic velocity decreases by -0.3%~-0.6% during the monsoon.
We find that the ML6.8 Luding earthquake that occurred on September 5, 2022 induced a seismic velocity decrease of ~-2.3%, followed by a 20-day recovery phase to the pre-earthquake state by removing the influence of the seasonal air temperature fluctuation using a linear regression model. While, the ML5.6 aftershock occurred on January 26, 2023 induced a velocity decrease of ~-0.4% in the temperature corrected time series of seismic velocity changes. Furthermore, we propose a seismic velocity-based coupling model on the slope by using the multiple linear regression method to quantify the external loadings, such as the air temperature, rainfall, and seismic activities. The model-fitted parameters suggest that the seasonal seismic velocity changes of the slope are mainly driven by the air temperature.
Finally, our results highlight the strong potential of the method to assess the risk of the slope instability by proposing an empirical warning index based on the analysis of a short-term decrease in the seismic velocity changes observed through long-term monitoring.
In this work, by using the continuous ambient noise data recorded by two seismic seismometers deployed on the slow-moving Pubugou rock slope in southwest China, we conduct a 2.5-year in-situ monitoring of the daily seismic velocity changes of the slope. The results show that the seismic velocity changes exhibit seasonal reversible fluctuations in the range of -1.5% to 2.0% on an annual scale which is well linearly correlated with the changes in the air temperature, while the precipitation induced seimic velocity decreases by -0.3%~-0.6% during the monsoon.
We find that the ML6.8 Luding earthquake that occurred on September 5, 2022 induced a seismic velocity decrease of ~-2.3%, followed by a 20-day recovery phase to the pre-earthquake state by removing the influence of the seasonal air temperature fluctuation using a linear regression model. While, the ML5.6 aftershock occurred on January 26, 2023 induced a velocity decrease of ~-0.4% in the temperature corrected time series of seismic velocity changes. Furthermore, we propose a seismic velocity-based coupling model on the slope by using the multiple linear regression method to quantify the external loadings, such as the air temperature, rainfall, and seismic activities. The model-fitted parameters suggest that the seasonal seismic velocity changes of the slope are mainly driven by the air temperature.
Finally, our results highlight the strong potential of the method to assess the risk of the slope instability by proposing an empirical warning index based on the analysis of a short-term decrease in the seismic velocity changes observed through long-term monitoring.