首页|Debris Flow Susceptibility Evaluation in Meizoseismal Region: A Case Study in Jiuzhaigou, China

Debris Flow Susceptibility Evaluation in Meizoseismal Region: A Case Study in Jiuzhaigou, China

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Jiuzhaigou is situated on a mountain-canyon region and is famous for frequent tectonic activities. An abundance of loose co-seismic landslides and collapses were produced on gullies after the Jiuzhaigou Earthquake on August 8, 2017, which was served as material source for debris flow in later years. Debris flow appears frequently which are seriously endangering the safety of people's lives and properties. Even the earliest debris flow appeared in areas where no case ever reported before. The debris flow susceptibility evaluation (DFSE) is used for predicting the areas prone to debris flow, which is urgently required to avoid hazards and help to guide the strategy of preventive measures. Therefore, this work employs debris flow in Jiuzhaigou to reveal the characteristics of disaster-pregnant environment and to explore the application of machine learning in DFSE. Some new viewpoints are suggested: (i) Material density factor of debris flow is first adopted in this work, and it is proved to be a critical factor for triggering debris flows by sensitivity analysis method. (ii) Deep neural network and convolutional neural network (CNN) achieve relatively good area under the curve (AUC) values and are 0.021-0.024 higher than traditional machine learning methods. (iii) Watershed units combined with CNN-based model can achieve more accurate, reliable and practical susceptibility map. This work provides an idea for prevention of debris flow in mountainous lands.

machine learningearthquakesdebris flow susceptibilityconvolutional neural networkdeep neural networkwatershed unit

Yongwei Li、Linrong Xu、Yonghui Shang、Shuyang Chen

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School of Civil Engineering,Central South University,Changsha 410075,China

National Engineering Research Center of High-Speed Railway Construction Technology,Central South University,Changsha 410075,China

School of Civil Engineering,Central South University of Forestry and Technology,Changsha 410004,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Key Research and Development Program of ChinaNatural Sciences Funding Project of Hunan ProvinceExcellent Youth Fund Project of Hunan Provincial Education DepartmentFundamental Research Funds for the Central Universities of Central South University

42172322U2268213420074192018YFC15054032020JJ598121B02262022ZZTS0646

2024

10.1007/s12583-022-1803-1

地球科学学刊(英文版)
中国地质大学

地球科学学刊(英文版)

CSTPCD
影响因子：0.724
ISSN：1674-487X
年,卷(期)：2024.35(1)
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