Department of Civil Engineering, National Taiwan University, Taipei, Taiwan.
Sci Rep. 2022 May 11;12(1):7751. doi: 10.1038/s41598-022-10611-3.
Identifying cliffs that are prone to fall and providing a sufficient lead time for rockfall warning are crucial steps in disaster risk reduction and preventive maintenance work, especially that led by local governments. However, existing rockfall warning systems provide uncertain rockfall location forecasting and short warning times because the deformation and cracking of unstable slopes are not sufficiently detected by sensors before the rock collapses. Here, we introduce ground microtremor signals for early rockfall forecasting and demonstrate that microtremor characteristics can be used to detect unstable rock wedges on slopes, quantitatively describe the stability of slopes and lengthen the lead time for rockfall warning. We show that the change in the energy of ground microtremors can be an early precursor of rockfall and that the signal frequency decreases with slope instability. This finding indicates that ground microtremor signals are remarkably sensitive to slope stability. We conclude that microtremor characteristics can be used as an appropriate slope stability index for early rockfall warning systems and predicting the spatiotemporal characteristics of rockfall hazards. This early warning method has the advantages of providing a long lead time and on-demand monitoring, while increasing slope stability accessibility and prefailure location detectability.
识别易发生崩塌的悬崖，并为落石预警提供足够的提前时间，这是减少灾害风险和预防性维护工作的关键步骤，特别是由地方政府主导的工作。然而，现有的落石预警系统提供的落石位置预测结果不确定，预警时间较短，这是因为在传感器检测到不稳定边坡的变形和开裂之前，岩石已经崩塌。在这里，我们引入了地面微震信号，用于早期的落石预测，并证明微震特征可用于检测边坡上不稳定的楔形岩石，定量描述边坡的稳定性，并延长落石预警的提前时间。我们表明，地面微震能量的变化可能是落石的早期前兆，并且信号频率随边坡失稳而降低。这一发现表明，地面微震信号对边坡稳定性非常敏感。我们得出结论，微震特征可用作早期落石预警系统的适当边坡稳定性指标，并预测落石灾害的时空特征。这种预警方法具有提供长预警时间和按需监测的优点，同时增加了边坡稳定性的可及性和失效前位置的可探测性。
