EGU23-17044, updated on 26 Feb 2023
https://doi.org/10.5194/egusphere-egu23-17044
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A data-driven and process-based system for mountain torrent and debris flow early warning and risk forecasting

Peng Cui
Peng Cui
  • Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, China (pengcui@imde.ac.cn)

Mountain torrents and debris flows are widely distributed in the mountainous region, threatening the urban development and infrastructure in mountain areas. The adverse effects of these hazards may increase due to the continued socio-economic development and influence of climate change on the frequency and magnitude of the hazards. This lecture introduces an early warning system of mountain hazards based on hazards process simulation and associated risk forecasting. The system identifies the watershed with high susceptibility to mountain hazard occurrences by monitoring the hazard-fostering conditions and real-time meteorological data. Focusing on those watersheds, the formation and movement of the hazards were simulated while different characteristics were captured, such as debris flow scale amplification and flash flood erosion. The risk of the mountain hazards was assessed based on the whole process of disaster formation-movement-deposition/disaster-causing. Compared with traditional early warning systems, which largely rely on rainfall thresholds and expert judgment, this proposed system is fully data-driven and process-based, while little human intervention is required. This system provides more accurate early warning information, and risk forecasting can better support disaster response planning for the government agency. This system is currently under trial in Liangshan Prefecture, Sichuan Province of China. Just in 2022, 15 debris flow and 52 flash flood events were captured and the early warning information was delivered to the residents and government. The accuracy is more than 79% and significantly improved the disaster resilience of the mountainous region.

About the Presenter

 Prof. CUI Peng has long been engaged in research on the formation mechanism, risk assessment, monitoring and early warning, prevention and control technology of debris flows and other mountain hazards. He has given a strong pulse to several topics of major relevance for disaster risk reduction and management, including (1) deepening the understanding of debris flow formation, scale amplification, and disaster-causing mechanisms; (2) providing rigorous insights concerning the formation and evolution of earthquake-induced hazards and multi-hazard chaining effect; (3) development of multi-scale disaster risk assessment model; (4) building of risk-level-based monitoring and early system to support efficient disaster reduction; and (5) creating the mass control and energy-based disaster mitigation theory and technology. He has published more than 400 papers with over 12000 citations and is the world's most published scholar in the field of debris flow.

How to cite: Cui, P.: A data-driven and process-based system for mountain torrent and debris flow early warning and risk forecasting, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17044, https://doi.org/10.5194/egusphere-egu23-17044, 2023.