Preprints
https://doi.org/10.5194/egusphere-2023-2015
https://doi.org/10.5194/egusphere-2023-2015
26 Sep 2023
 | 26 Sep 2023

Real-time Monitoring and Analysis of Debris Flow Events: Insight from seismic signal features and dynamic flow characteristics

Yan Yan, Cheng Zeng, Yifei Cui, Sheng Hu, Xinglu Wang, and Hui Tang

Abstract. Debris flows are among the most dangerous natural hazards worldwide because they start abruptly, move quickly, and transport large boulders, causing great loss of life and infrastructure. The most important approach to preventing and mitigating debris flows is through monitoring and early warning. In recent years, environmental seismology has emerged as a powerful method for monitoring debris flows because it allows non-contact observation over large areas and can provide extensive information on debris flow dynamics. However, further research is required on combining debris flow imagery with seismic signal analysis, incorporating information from post-disaster surveys, and the inversion of seismic signals into dynamic parameters of debris flows. Here, we aim to explore the basic parameters, development process, and magnitude of debris flows based on seismic signal analysis combined with other information recorded in real time during the formation and development of three debris flows in Wenchuan, China. The analysis involves three stages. First, we compensate for the energy loss of the seismic signal due to the absorption attenuation effect and restore the signal to an unchanged state as far as possible. Second, we identify the start and end time of the debris flow from the seismic signal, analyze the rainfall data to determine that the debris flow was triggered by the test rain, and determine that changes in the energy and frequency ranges of the seismic signal are highly consistent with the development of the debris flow. Third, a comprehensive analysis of debris flow images, the power spectral density (PSD) of the seismic signal, and forward modeling of the PSD of the seismic signal of the debris flow are used to reveal the relationship between the seismic signal and the development process of the debris flow and clarify the feasibility of debris flow analysis from the time-frequency characteristics of the seismic signal. Debris flow exhibits the characteristics of fast excitation and slow recession. Using the cross-correlation algorithm and verifying Manning's formula, a maximum velocity of 7.027 m/s was calculated for the second debris flow. A comparison of the frequency characteristics of the seismic signal allowed the relative magnitude of the three debris flows to be assessed. The study provides a theoretical basis and a case study exemplar for the reconstruction of the debris flow process and peak velocity estimation using debris flow seismology, offering a framework for upscaling debris flow monitoring networks and the determination of early warning thresholds.

Yan Yan, Cheng Zeng, Yifei Cui, Sheng Hu, Xinglu Wang, and Hui Tang

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2015', Anonymous Referee #1, 09 Nov 2023
    • AC1: 'Reply on RC1', Yan Yan, 26 Jan 2024
  • RC2: 'Comment on egusphere-2023-2015', Anonymous Referee #2, 27 Nov 2023
    • AC2: 'Reply on RC2', Yan Yan, 26 Jan 2024
  • AC3: 'Comment on egusphere-2023-2015', Yan Yan, 26 Jan 2024
Yan Yan, Cheng Zeng, Yifei Cui, Sheng Hu, Xinglu Wang, and Hui Tang
Yan Yan, Cheng Zeng, Yifei Cui, Sheng Hu, Xinglu Wang, and Hui Tang

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Short summary
We aim to explore the basic parameters, development process, and magnitude of debris flows based on seismic signal analysis combined with other information recorded in real time during the formation and development of three debris flows in Wenchuan, China. The study provides a theoretical basis and a case study exemplar for the reconstruction of the debris flow process and peak velocity estimation using debris flow seismology.