Monitoring and Evaluation of Debris Flow Disaster in the Loess Plateau Area of China: A Case Study
Author:
Wan Baofeng1, An Ning1, Bai Gexue1
Affiliation:
1. Gansu Institute of Engineering Geology, Lanzhou 730000, China
Abstract
The Loess Plateau area, with complex geomorphological features and geological structure, is highly prone to geologic disasters such as landslides and debris flow, which cause great losses. To investigate the initiation mechanism of landslide and debris flow disasters and their spreading patterns, historical satellite images in the Laolang gully were collected and digitized to generate three-dimensional topographic and geomorphological maps. Typical landslides were selected for landslide thickness measurement using a standard penetrometer and high-density electrical method. Numerical models were established to simulate the occurrence and development of landslides under different working conditions and to evaluate the spreading range based on the propagation algorithm and friction law. The results show that the 10 m resolution DEM data are well matched with the potential hazard events observed in the field site. The smaller the critical slope threshold, the greater the extent and distance of landslide spreading. The larger the angle of arrival, the greater the energy loss, and therefore the smaller the landslide movement distance. The results can provide scientific theoretical guidance for the prevention and control of rainfall-induced landslide and debris flow disasters in the Loess Plateau area.
Funder
Special Fund for Geological Disaster Prevention and Control of Department of Natural Resources of Gansu Province 2021 Innovation Fund Project of Gansu Provincial Bureau of Geology and Mineral Resources
Reference42 articles.
1. Wahab, M.K.A., Zainol, M.R.R.M., Ikhsan, J., Zawawi, M.H., Abas, M.A., Noor, N.M., Razak, N.A., and Sholichin, M. (2023). Assessment of Debris Flow Impact Based on Experimental Analysis along a Deposition Area. Sustainability, 15. 2. Bai, G., Hou, Y., Wan, B., An, N., Yan, Y., Tang, Z., Yan, M., Zhang, Y., and Sun, D. (2022). Performance Evaluation and Engineering Verification of Machine Learning Based Prediction Models for Slope Stability. Appl. Sci., 12. 3. Zhou, Y., Yue, D., Liang, G., Li, S., Zhao, Y., Chao, Z., and Meng, X. (2022). Risk Assessment of Debris Flow in a Mountain-Basin Area, Western China. Remote Sens., 14. 4. Progress of debris flow in China;Cui;J. Nat. Disaster,2000 5. Mathematical modelling of debris flow-boulder-barrier interactions using the Coupled Eulerian Lagrangian method;Sha;Appl. Math. Model.,2023
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