EGU25-128, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-128
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 30 Apr, 16:15–16:25 (CEST)
 
Room N2
Long-term field observation dataset and key findings of the dynamic characteristics of debris flows in Jiangjia Ravine, China
Dongri Song, Li Wei, Wei Zhong, and Xiaoyu Li
Dongri Song et al.
  • Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, China (drsong@imde.ac.cn)

Due to the unpredictable nature of debris flows, it is difficult to systematically establish a long-term debris-flow observation dataset. Since the 1960s, the Dongchuan Debris Flow Observation and Research Station (DDFORS) at Jiangjia Ravine was established. Field observation and research on the initiation, transportation, and accumulation of debris flow have been carried out, and a debris-flow database has been established. These sixty years of observations provide a solid foundation for exploring the dynamics and mechanisms of debris flows. Based on the observation data of debris flows, the sources of flow resistance during the natural debris-flow process were investigated. A visco-collisional resistance model was developed. The model indicates that, for surge flows, fluid viscous effects play a more significant role than solid particle interactions. However, for continuous flows, inertial collisions between particles dominate over fluid viscous effects. In addition, based on simple hydraulic jump equations, the eroded deposition depth of surge flows is quantified. For surge flows with erosion-deposition propagation, significant downward erosion potential is confirmed. The total momentum of surge flow not only originates from the apparent surge front, but also includes the momentum within the eroded deposition layer. The revealed erosion pattern and hidden momentum in debris-flow surges may improve the reliability of debris-flow risk assessment. This long-term field observation dataset will be open to the public by early 2025.

How to cite: Song, D., Wei, L., Zhong, W., and Li, X.: Long-term field observation dataset and key findings of the dynamic characteristics of debris flows in Jiangjia Ravine, China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-128, https://doi.org/10.5194/egusphere-egu25-128, 2025.