Large rockfall detection, location and characterization using broadband seismic records: A case study of Hongya rockfall

Large rockfalls often cause huge economic losses and casualties in densely populated mountain areas. Timely acquiring information on a large rockfall can help promptly assess the damage and residual risks and guide the emergency response. Recent works suggest that the seismic signals generated by large rockfalls can provide these key information, but most of them focused on exploring seismic signatures to understand rockfall dynamics, lacking a rapid disaster assessing scheme. Here, we establish a seismic signal-based assessment scheme and demonstrate its capability by taking a large event – the 5 April 2021 Hongya rockfall (Sichuan, China) – as a case study. This scheme consists of three components, which are rockfall identification, detection and location, and characterization. In the rockfall identification module, we show how a rockfall can be distinguished from an earthquake and a rockslide by analyzing its seismic signatures. In the detection and location module, we demonstrate how the kurtosis-based method can be used to rapidly detect the initiation of a rockfall and determine the seismic wave velocity accordingly, and how the arrival-time-based location method can be used to locate a rockfall event. In the rockfall characterization module, we show how rockfall volume can be estimated from the magnitude of radiated seismic energy and how to characterize the dynamic process of a rockfall by the signatures of seismogram, spectrum and recorded seismic energy. Our results show that the seismic signal-based scheme presented here is suitable to characterize large rockfalls and has certain potential for rapid and effective emergency management.