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Journal of Earth Science  > 2026  > Accepted Manuscript
Yan Yan, Renhe Wang, Cheng Zeng, Yifei Cui, Sheng Hu, Xinglu Wang, Hui Tang. Reconstruction of the Wenchuan debris flow process in August, 2022 by in-situ monitoring and analysis of seismic signals. Journal of Earth Science. doi: 10.1007/s12583-026-0002-x
Citation: Yan Yan, Renhe Wang, Cheng Zeng, Yifei Cui, Sheng Hu, Xinglu Wang, Hui Tang. Reconstruction of the Wenchuan debris flow process in August, 2022 by in-situ monitoring and analysis of seismic signals. Journal of Earth Science. doi: 10.1007/s12583-026-0002-x
shu

Reconstruction of the Wenchuan debris flow process in August, 2022 by in-situ monitoring and analysis of seismic signals

doi: 10.1007/s12583-026-0002-x

  • 1. Key Laboratory of High-Speed Railway Engineering, MOE/School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China

  • 2. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China

  • 3. Section 4.6: Geomorphology, German Research Centre for Geosciences (GFZ), Potsdam 14473, Germany

  • 4. College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China

  • 5. Section 4.7: Earth Surface Process Modelling, German Research Centre for Geosciences (GFZ), Potsdam 14473, Germany

Funds:

This study was financially supported by the National Natural Science Foundation of China (grant nos. 42271075，42120104002, and U21A2008), the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (grant no. 2019QZKK0906).

  • Available Online: 11 Mar 2026
    Abstract
  • Rainfall-induced debris flows are highly destructive due to their abrupt onset, rapid movement, and high sediment transport capacity, all of which can lead to significant loss of life and damage to infrastructure. However, a comprehensive analysis of their dynamic evolution remains limited by the scarcity of in-situ monitoring data. In this study, we utilized near-field seismic data recorded by acquisition instruments deployed in Wenchuan, China, combined with images and post-event field investigations to reconstruct the second debris flow event in Fotangba Gully. Seismic signal attenuation was compensated, and time-frequency analysis and power spectral density (PSD) calculations were conducted. The results reveal pronounced differences in signal amplitude and frequency content across stations, reflecting spatial heterogeneity in flow dynamics. We identified flow velocity and grain concentration as the dominant factors affecting the PSD curves. This research provides a framework for extracting debris flow kinematic characteristics from seismic signals and offers new insights for hazard evaluation and the design of mitigation strategies.

     

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  • Aaron, J., Spielmann, R., McArdell, B. W., et al., 2023. High‐Frequency 3D LiDAR Measurements of a Debris Flow: A Novel Method to Investigate the Dynamics of Full‐Scale Events in the Field. Geophysical Research Letters, 50(5): e2022GL102373. https://doi.org/10.1029/2022GL102373
    Andrade, S. D., Almeida, S., Saltos, E., et al., 2022. A simple and general methodology to calibrate seismic instruments for debris flow quantification: application to Cotopaxi and Tungurahua volcanoes (Ecuador). Landslides 19(3): 747-759. https://doi.org/10.1007/s10346-021-01784-5
    Arattano, M., 1999. On the use of seismic detectors as monitoring and warning systems for debris flows. Natural Hazards, 20(2): 197-213. https://doi.org/10.1023/A:1008061916445
    Arattano, M., Marchi, L., 2005. Measurements of debris flow velocity through cross-correlation of instrumentation data. Natural Hazards and Earth System Sciences, 5(1): 137-142. https://doi.org/10.5194/nhess-5-137-2005
    Arattano, M., Marchi, L., 2008. Systems and sensors for debris flow monitoring and warning. Sensors, 8(4): 2436-2452. https://doi.org/10.3390/s8042436
    Beason, S. R., Legg, N. T., Kenyon, T. R., et al., 2021. Forecasting and seismic detection of proglacial debris flows at Mount Rainier National Park, Washington, USA. Environmental & Engineering Geoscience, 27(1): 57-72. https://doi.org/10.2113/EEG-D-20-00014
    Belli, G., Marchetti, E., Walter, F., et al., 2025. Infrasound unmasks flow turbulence as an additional seismic source in debris flows. Geophysical Research Letters, 52(8): e2025GL116107. https://doi.org/10.1029/2025GL116107
    Belli, G., Walter, F., McArdell, B., et al., 2022. Infrasonic and seismic analysis of debris‐flow events at Illgraben (Switzerland): Relating signal features to flow parameters and to the seismo‐acoustic source mechanism. Journal of Geophysical Research: Earth Surface, 127(6): e2021JF006576. https://doi.org/10.1029/2021JF006576
    Burtin, A., Hovius, N., McArdell, B. W., et al., 2014. Seismic constraints on dynamic links between geomorphic processes and routing of sediment in a steep mountain catchment. Earth Surface Dynamics, 2(1): 21-33. https://doi.org/10.5194/esurf-2-21-2014
    Cao, C., Yu, B., Ma, E. L., et al., 2019. Study on debris flow in Fongtuba Gully after the earthquake at Wenchuan County of Sichuan Province. Journal of Sediment Research, 44(1): 38-43 (in Chinese).
    Chang, J. M., Kuo, Y. T., Chao, W. A., et al., 2024. Landslide warning area delineation through seismic signals and landslide characteristics: Insights from the Silabaku landslide in southern Taiwan. Seismological Research Letters, 95(5): 2986-2996. https://doi.org/10.1785/0220230071
    Chang, M., Liu, Y., Zhou, C., et al., 2020. Hazard assessment of a catastrophic mine waste debris flow of Hou Gully, Shimian, China. Engineering Geology, 275: 105733. https://doi.org/10.1016/j.enggeo.2020.105733
    Chen, T., Xu, G., Hiraishi, T., 2025. New Understandings of the Shaziba Landslide-Debris Flow in Hubei Province, China. Journal of Earth Science, 36(4): 1632-1649. https://doi.org/10.1007/s12583-023-1833-3
    Chen, X., Cui, P., You, Y., et al., 2015. Engineering measures for debris flow hazard mitigation in the Wenchuan earthquake area. Engineering Geology, 194: 73-85. https://doi.org/10.1016/j.enggeo.2015.04.027
    Comiti, F., Marchi, L., Macconi, P., et al., 2014. A new observation station for debris flows in the European Alps: First observations in the Gadria basin. Natural Hazards, 73: 1175-1198. https://doi.org/10.1007/s11069-014-1128-8
    Coviello, V., Arattano, M., Turconi, L., 2015. Detecting torrential processes from a distance with a seismic monitoring network. Natural Hazards, 78: 2055-2080. https://doi.org/10.1007/s11069-015-1799-5
    Crowley, J. K., Hubbard, B. E., Mars, J. C., 2003. Analysis of potential debris flow source areas on Mount Shasta, California, by using airborne and satellite remote sensing data. Remote Sensing of Environment, 87(2-3): 345-358. https://doi.org/10.1016/j.rse.2003.08.005
    Cui, P., Guo, X., Yan, Y., et al., 2018. Real-time observation of an active debris flow watershed in the Wenchuan Earthquake area. Geomorphology, 321: 153-166. https://doi.org/10.1016/j.geomorph.2018.09.005
    Cui, P., Zhou, G. G., Zhu, X. H., et al., 2013. Scale amplification of natural debris flows caused by cascading landslide dam failures. Geomorphology, 182: 173-189. https://doi.org/10.1016/j.geomorph.2012.11.013
    Deng, Y., Gao, Q., Wang, X., et al., 2025. A large-scale rock avalanche-debris flow cascading hazard in the Sedongpu catchment, southeastern Tibetan Plateau. Landslides, 22(1): 109-120. https://doi.org/10.1007/s10346-024-02156-2
    Dou, J., Xing, K., Wang, L., et al., 2025. Air-Space-Ground Synergistic Observations for Rapid Post-Seismic Disaster Assessment of 2025 Ms6. 8 Xigazê Earthquake, Xizang. Journal of Earth Science, 36(4): 1605-1622. https://doi.org/10.1007/s12583-025-0160-2
    Farin, M., Tsai, V. C., Lamb, M. P., et al., 2019. A physical model of the high-frequency seismic signal generated by debris flows. Earth Surface Processes and Landforms, 44(13): 2529-2543. https://doi.org/10.1002/esp.4660
    Fu, J., Wang, X., Li, Z., et al., 2020. Automatic phase-picking method for detecting earthquakes based on the signal-to-noise ratio concept. Seismological Research Letters, 91(1): 334-342. https://doi.org/10.1785/0220190067
    Futterman, W. I., 1962. Dispersive body waves. Journal of Geophysical Research, 67(13): 5279-5291. https://doi.org/10.1029/JZ067i013p05279
    Guo, N., Zhou, X., Xu, K., et al., 2023. Near-surface Q-value survey method based on uphole with hammer excitation and receiving using multi-stage geophones on wells. Oil Geophysical Prospecting, 58(2): 295-304 (in Chinese).
    Guo, X., Cui, P., Li, Y., et al., 2016. The formation and development of debris flows in large watersheds after the 2008 Wenchuan Earthquake. Landslides, 13: 25-37. https://doi.org/10.1007/s10346-015-0564-8
    Hibert, C., Noël, F., Toe, D., et al., 2022. Machine learning prediction of the mass and the velocity of controlled single-block rockfalls from the seismic waves they generate. Engineering Geology, 309: 106820. https://doi.org/10.1016/j.enggeo.2022.106820
    Huang, Z., Yang, Z., Pang, B., et al., 2025. Characterizing and clustering debris-flow and environmental-noise seismic signals using unsupervised deep learning. Geophysical Journal International, 243(2): ggaf353. https://doi.org/10.1093/gji/ggaf353
    . https://doi.org/10.2495/SAFE-V3-N2-105-115
    Hürlimann, M., Coviello, V., Bel, C., et al., 2019. Debris-flow monitoring and warning: Review and examples. Earth-Science Reviews, 199: 102981. https://doi.org/10.1016/j.earscirev.2019.102981
    Iverson, R. M., 1997. The physics of debris flows. Reviews of Geophysics, 35(3): 245-296. https://doi.org/10.1029/97RG00426
    Iverson, R. M., 2015. Scaling and design of landslide and debris flow experiments. Geomorphology, 244: 9-20. https://doi.org/10.1016/j.geomorph.2015.03.003
    Kean, J. W., Coe, J. A., Coviello, V., et al., 2015. Estimating rates of debris flow entrainment from ground vibrations. Geophysical Research Letters, 42(15): 6365-6372. https://doi.org/10.1002/2015GL064811
    Kean, J. W., Staley, D. M., Lancaster, J. T., et al., 2019. Inundation, flow dynamics, and damage in the 9 January 2018 Montecito debris flow event, California, USA: Opportunities and challenges for post-wildfire risk assessment. Geosphere, 15(4): 1140-1163. https://doi.org/10.1130/GES02048.1
    Kean, J. W., Staley, D. M., Leeper, R. J., et al., 2012. A low-cost method to measure the timing of postfire flash floods and debris flows relative to rainfall. Water Resources Research, 48(5): W05516. https://doi.org/10.1029/2011WR011460
    Kjartansson, E., 1979. Constant Q-wave propagation and attenuation. Journal of Geophysical Research: Solid Earth, 84(B9): 4737-4748. https://doi.org/10.1029/JB084iB09p04737
    Kleine, F., Bruland, C., Wuestefeld, A., et al., 2025. Seismic signal characterization of snow avalanches using distributed acoustic sensing in Grasdalen, western Norway. Natural Hazards and Earth System Sciences, 25(8): 2771-2782. https://doi.org/10.5194/nhess-25-2771-2025
    Koushik, S. S. S. D., Kumar, A., Kapil, J. C., 2024. Development of seismic signal-based snow-avalanche spectral utility. Journal of Earth System Science, 133(1): 25. https://doi.org/10.1007/s12040-024-02047-w
    Lai, V. H., Tsai, V. C., Lamb, M. P., et al., 2018. The seismic signature of debris flows: Flow mechanics and early warning at Montecito, California. Geophysical Research Letters, 45(11): 5528-5535. https://doi.org/10.1029/2018GL078030
    Li, X., Zhao, J., Kwan, J. S., 2020. Assessing debris flow impact on flexible ring net barrier: A coupled CFD-DEM study. Computers and Geotechnics, 128: 103850. https://doi.org/10.1016/j.compgeo.2020.103850
    Li, Z., Huang, X., Xu, Q., et al., 2017. Dynamics of the Wulong landslide revealed by broadband seismic records. Earth, Planets and Space, 69: 140. https://doi.org/10.1186/s40623-017-0714-5
    Liang, F., Zhang, Z., 2024. Seismic monitoring in rockfall: A literature review. Journal of Engineering Geology, 32(2): 545-564. https://doi.org/10.13544/j.cnki.jeg.2022-0079
    Liang, X., Segoni, S., Yin, K., et al., 2022. Characteristics of landslides and debris flows triggered by extreme rainfall in Daoshi Town during the 2019 Typhoon Lekima, Zhejiang Province, China. Landslides, 19(7): 1735-1749. https://doi.org/10.1007/s10346-021-01775-2
    Liu, C., Feng, X., Zhang, J., 2013. A stable inverse Q filtering using the iterative filtering method. Oil Geophysical Prospecting, 48(6): 890-895 (in Chinese).
    Liu, C., Yu, Z., Zhao, S., 2021. A coupled SPH-DEM-FEM model for fluid-particle-structure interaction and a case study of Wenjia gully debris flow impact estimation. Landslides, 18(7): 2403-2425. https://doi.org/10.1007/s10346-021-01643-z
    Marchetti, E., Walter, F., Barfucci, G., et al., 2019. Infrasound array analysis of debris flow activity and implication for early warning. Journal of Geophysical Research: Earth Surface, 124(2): 567-587. https://doi.org/10.1029/2018JF004672
    Marchi, L., Arattano, M., Deganutti, A. M., 2002. Ten years of debris flow monitoring in the Moscardo Torrent (Italian Alps). Geomorphology, 46(1-2): 1-17. https://doi.org/10.1016/S0169-555X(02)00052-4
    Nagl, G., Hübl, J., 2017. A check-dam to measure debris flow-structure interactions in the Gadria torrent. In: Mikoš, M., Arbanas, Ž., Yin, Y., Sassa, K. (eds.), Advancing Culture of Living with Landslides - Volume 5: Landslides in Different Environments. Springer, Cham, pp. 465-471. https://doi.org/10.1007/978-3-319-53483-1_53
    Porter, R., Joyal, T., Beers, R., et al., 2023. Characterization of environmental seismic signals in a post-wildfire environment: Examples from the Museum Fire, AZ. Journal of Geophysical Research: Earth Surface, 128(7): e2022JF006962. https://doi.org/10.1029/2022JF006962
    Rickenmann, D., 1999. Empirical relationships for debris flows. Natural Hazards, 19: 47-77. https://doi.org/10.1023/A:1008064220727
    Schenato, L., Pasuto, A., 2021. On the use of optical fiber sensors for debris flow monitoring: A review of recent achievements. Belt and Road Webinar Series on Geotechnics, Energy and Environment, 60-70. https://doi.org/10.1007/978-981-16-9963-4_5
    Schimmel, A., Coviello, V., Comiti, F., 2022. Debris flow velocity and volume estimations based on seismic data. Natural Hazards and Earth System Sciences, 22(6): 1955-1968. https://doi.org/10.5194/nhess-22-1955-2022
    Shen, W., Zhao, T., Zhao, J., et al., 2018. Quantifying the impact of dry debris flow against a rigid barrier by DEM analyses. Engineering Geology, 241: 86-96. https://doi.org/10.1016/j.enggeo.2018.05.003
    Strick, E., 1967. The determination of Q, dynamic viscosity and transient creep curves from wave propagation measurements. Geophysical Journal International, 13(1-3): 197-218. https://doi.org/10.1111/j.1365-246X.1967.tb02163.x
    Suwa, H., Okano, K., Kanno, T., 2009. Behavior of debris flows monitored on test slopes of Kamikamihorizawa Creek, Mount Yakedake, Japan. International Journal of Erosion Control Engineering, 2(2): 33-45. https://doi.org/10.13101/ijece.2.33
    Tang, C., Rengers, N. V., Van Asch, T. W., et al., 2011. Triggering conditions and depositional characteristics of a disastrous debris flow event in Zhouqu city, Gansu Province, northwestern China. Natural Hazards and Earth System Sciences, 11(11): 2903-2912. https://doi.org/10.5194/nhess-11-2903-2011
    Tecca, P. R., Galgaro, A., Genevois, R., et al., 2003. Development of a remotely controlled debris flow observation system in the Dolomites (Acquabona, Italy). Hydrological Processes, 17(9): 1771-1784. https://doi.org/10.1002/hyp.1212
    Tsai, V. C., Minchew, B., Lamb, M. P., et al., 2012. A physical model for seismic noise generation from sediment transport in rivers. Geophysical Research Letters, 39(2): L02404. https://doi.org/10.1029/2011GL050255
    Turbessi, L., Taboni, B., Umili, G., et al., 2025. Modeling debris flow events in the Rio Inferno watershed (Italy) through UAV-based geomorphological survey and rainfall data analysis. Sensors, 25(7): 1980. https://doi.org/10.3390/s25071980
    Walter, F., Chmiel, M., Hovius, N., 2022. Debris flows at Illgraben, Switzerland - From seismic wiggles to machine learning. Geomechanics and Tunnelling, 15(5): 671-675. https://doi.org/10.1002/geot.202200039
    Wang, X., Yin, X., Liu, T., et al., 2025. Morphotectonic Analyses of LiDAR-Derived DEMs: Insights into Tectonic Activity of the Xinhua Fault within the Three Gorges Area (Central China). Journal of Earth Science, 36(2): 823-829. https://doi.org/10.1007/s12583-024-0150-9
    Wang, Y., 2002. A stable and efficient approach of inverse Q filtering. Geophysics, 67(2): 657-663. https://doi.org/10.1190/1.1468618
    Wei, L., Zhang, X., Zhang, H., et al., 2025. Debris flow risk assessment via numerical simulation: A case study in Northeast China. Landslides, 1-26. https://doi.org/10.1007/s10346-025-02111-9
    Xu, M. D., Feng, Q. H., 1979. Roughness of debris flows. Proceedings of the First Conference of Chinese Research of Debris Flows, 51-52 (in Chinese).
    Yan, Y., Cui, P., Chen, S., et al., 2017. Characteristics and interpretation of the seismic signal of a field-scale landslide dam failure experiment. Journal of Mountain Science, 14: 219-236. https://doi.org/10.1007/s11629-016-4103-3
    Yan, Y., Cui, Y., Huang, X., et al., 2022. Combining seismic signal dynamic inversion and numerical modeling improves landslide process reconstruction. Earth Surface Dynamics, 10: 1233-1252. https://doi.org/10.5194/esurf-10-1233-2022, 2022.
    Yan, Y., Cui, Y., Liu, D., et al., 2021. Seismic signal characteristics and interpretation of the 2020 “6.17” Danba landslide dam failure hazard chain process. Landslides, 18: 2175-2192. https://doi.org/10.1007/s10346-021-01657-x
    Yan, Y., Cui, Y., Tian, X., et al., 2020. Seismic signal recognition and interpretation of the 2019 “7.23” Shuicheng landslide by seismogram stations. Landslides, 17: 1191-1206. https://doi.org/10.1007/s10346-020-01358-x
    Yan, Y., Tang, H., Hu, K., et al., 2023. Deriving debris-flow dynamics from real-time impact-force measurements. Journal of Geophysical Research: Earth Surface, 128: e2022JF006715. https://doi.org/10.1029/2022JF006715
    Yan, Y., Tang, H., Zhou, K., et al., 2025. Statistical characteristics of basal forces generated by experimental debris flows. Journal of Geophysical Research: Solid Earth, 130(3): e2024JB030027. https://doi.org/10.1029/2024JB030027
    Yang, H., Haque, E., Song, K., 2021. Experimental study on the effects of physical conditions on the interaction between debris flow and baffles. Physics of Fluids, 33(5). https://doi.org/10.1063/5.0049787
    Yang, Y., Chen, G., Li, Y., et al., 2024. Characterization of stream, hyperconcentrated, and debris flows from seismic signals: Insights into sediment transport mechanisms and flow dynamics. Journal of Geophysical Research: Earth Surface, 129(4): e2023JF007527. https://doi.org/10.1029/2023JF007527
    Yu, G., Lim, S. Y., 2003. Modified Manning formula for flow in alluvial channels with sand-beds. Journal of Hydraulic Research, 41(6): 597-608. https://doi.org/10.1080/00221680309506892
    Zhang, W., Chen, J., Ma, J., et al., 2023. Evolution of sediment after a decade of the Wenchuan earthquake: A case study in a protected debris flow catchment in Wenchuan County, China. Acta Geotechnica, 18(7): 3905-3926. https://doi.org/10.1007/s11440-022-01789-x
    Zhang, X., Tang, C., Li, N., et al., 2022. Investigation of the 2019 Wenchuan County debris flow disaster suggests nonuniform spatial and temporal post-seismic debris flow evolution patterns. Landslides, 19(8): 1935-1956. https://doi.org/10.1007/s10346-022-01896-6
    Zhang, Z., 2021. Study on the inversion of dynamic parameters of landslides and debris flows based on seismic signals. University of Chinese Academy of Sciences (in Chinese).
    Zhang, Z., Walter, F., McArdell, B. W., et al., 2021a. Analyzing bulk flow characteristics of debris flows using their high-frequency seismic signature. Journal of Geophysical Research: Solid Earth, 126(12): e2021JB022755. https://doi.org/10.1029/2021JB022755
    . Geophysical Research Letters, 48(1): e2020GL088994. Insights from the particle impact model into the high-frequency seismic signature of debris flows
    Zhang, Z., Walter, F., McArdell, B. W., et al., 2025. Seismic signals monitor debris flow erosion and channel elevation. Geophysical Research Letters, 52(20): e2025GL118801. https://doi.org/10.1029/2025GL118801
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    Zhou, Q., Tang, H., Hibert, C., et al., 2025. Enhancing debris flow warning via machine learning feature reduction and model selection. Journal of Geophysical Research: Earth Surface, 130(4): e2024JF008094. https://doi.org/10.1029/2024JF008094
    Zhou, Q., Tang, H., Turowski, J. M., et al., 2024. Benford’s law as debris flow detector in seismic signals. Journal of Geophysical Research: Earth Surface, 129(9): e2024JF007691. https://doi.org/10.1029/2024JF007691
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