Get started
Work

Infrasound early warning model for debris flow in a typical drainage basin in Beijing mountainous area

Year: 2024
Type: article
Abstract: Objective Infrasound is an effective approach for debris flow warning. Traditional threshold-based warning methods focus solely on individual infrasound characteristics, which can lead to false alarms or missed detections. Thus, incorporating multiple time-frequency characteristics is essential to improve warning accuracy. Methods Infrasound data from Caodianshui Village, Beijing, were analyzed to differentiate the infrasound characteristics of debris flows from environmental background. A random forest algorithm was employed to establish an infrasound warning model for debris flows. Results The effective pressure of debris flow infrasound ranges from 0.4 to 1.0 Pa, while environmental infrasound typical remains below 0.1 Pa, though noise can raise it above 0.4 Pa.Noise infrasound energy is primarily concentrated below 6 Hz, whereas debris flow infrasound exhibits significantly higher energy in the 6-15 Hz. Therefore, comprehensive time-frequency characteristics, especially the energy in the range of 6-15 Hz, should be considered when identifying debris flow infrasound. Using effective infrasound pressure, infrasound pressure within 6-15 Hz, zero crossing rate, dominant frequency, and its amplitude as characteristic variables, a debris flow warning model was constructed based on a random forest algorithm. The model achieved an AUC of 0.99, with a 90% recognition accuracy for test data, a 15% improvement over threshold methods. Conclusion The random forest-based infrasound warning model substantially improves warning accuracy for debris flows and is applicable to typical basins in the Beijing mountainous areas. This approach offers a valuable reference for infrasound-based debris flow warning research in other areas.
DOI: 10.19509/j.cnki.dzkq.tb20240223
Authors: Jiashuo YU, Shuhua ZHAI, Shangzhi XU, Jian MAO, Menglun LI, Qiangqiang WANG, Huanhuan LIU, Yuntao WANG, Miao YU
Language: English
Open Access status: green
OpenAlex ID: W6888522792
FWCI:
Cites:
Cited by:
Related to: