Abstract:

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. However, previous studies have primarily focused on the effects of key triggers such as earthquakes and rainfall, or have been limited to analyzing the evolution mechanisms before and after slope instability. In contrast, long-term continuous monitoring of typical rock slopes in southwest China remains scarce, particularly in terms of exploring the quantitative relationships between external factors such as air temperature, rainfall, and seismicity, and seismic velocity changes. This limits a better understanding of how seasonal external factor variations affect slope stability.

Therefore, in this study, we conducted a 2.5-year in situ monitoring campaign of daily seismic velocity variations on the slow-moving Pubugou rock slope in southwestern China, using continuous ambient noise data recorded by two seismic stations deployed from October 1, 2020, to February 26, 2023. To assess the impact of long-term environmental fluctuations on slope stability, collocated meteorological and rainfall sensors were installed to record air temperature and precipitation at a daily sampling rate. Furthermore, we cataloged 27 446 local earthquakes(M_L1.0-6.8) occurring within a 250-km radius of the slope during the study period. Based on these integrated observations, we systematically investigated the relationships between seasonal seismic velocity changes and external forcing factors—specifically, air temperature, rainfall, and regional seismicity. The results show that the seismic velocity changes exhibit seasonal and 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 seismic velocity decreases by -0.3%~-0.6% during the monsoon. We find that the M_L6.8 Luding earthquake that occurred on September 5, 2022 induced a seismic velocity decrease of ~-2.3%, followed by a 23-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 M_L5.6 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 optimal fitting coefficients for the temperature, rainfall-induced pore pressure, and earthquake-induced seismic intensity on the slope are 1.0×10^-3, -3.59×10^-5, and -6.68×10^-4, respectively. These coefficients suggest that the seasonal seismic velocity changes of the slope are positively correlated with the temperature and negatively correlated with the pore pressure and seismic intensity, as we expected. 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.

Key words: rock slope, ambient background noise, seismic velocity changes, multi-physics coupling model

摘要：

近年来, 利用环境地震学方法对岩质边坡等地质灾害体开展监测预警日益受到行业关注。其中, 利用环境背景噪声干涉技术测量边坡内部的速度变化, 对于深入了解外界因素作用下边坡内部的损伤演化过程及其规律具有重要的研究和应用价值。文中通过布设在中国西南地区大渡河流域典型岩质边坡-瀑布沟边坡上的2台长期运行的地震仪, 利用环境背景噪声干涉技术对该边坡开展了长达2年5个月的多重散射波波速变化监测。结果表明: 在年尺度内, 波速变化在-1.5%~2.0%的范围内表现出季节性的可逆型波动, 且与气温变化呈现出显著的线性正相关; 在季节性尺度内, 边坡对夏季降雨的响应表现为0.3%~0.6%的波速小幅下降, 同时周边区域的大地震事件也会导致边坡速度的短时下降。最后, 文中利用多元线性回归方法, 构建了该岩质边坡季节性波速变化的多物理场耦合模型, 对上述外界因素与波速变化之间的关系进行分析, 得到气温、降雨及地震活动对该岩质边坡波速变化的定量化响应。

关键词: 岩质边坡, 环境背景噪声, 波速变化, 多物理场耦合模型