IMHE OpenIR  > 山地灾害与地表过程重点实验室
Assessing Susceptibility of Debris Flow in Southwest China Using Gradient Boosting Machine
Di Baofeng1,2; Zhang Hanyue2; Liu Yongyao2; Li Jierui; Chen Ningsheng3; Stamatopoulos Constantine A.4; Luo Yuzhou5; Zhan Yu2,6,7
2019
Source PublicationSCIENTIFIC REPORTS
ISSN2045-2322
Volume9Pages:12532
SubtypeArticle
Contribution Rank3
AbstractA gradient boosting machine (GBM) was developed to model the susceptibility of debris flow in Sichuan, Southwest China for risk management. A total of 3839 events of debris flow during 1949-2017 were compiled from the Sichuan Geo-Environment Monitoring program, field surveys, and satellite imagery interpretation. In the cross-validation, the GBM showed better performance, with the prediction accuracy of 82.0% and area under curve of 0.88, than the benchmark models, including the Logistic Regression, the K-Nearest Neighbor, the Support Vector Machine, and the Artificial Neural Network. The elevation range, precipitation, and aridity index played the most important role in determining the susceptibility. In addition, the water erosion intensity, road construction, channel gradient, and human settlement sites also largely contributed to the formation of debris flow. The susceptibility map produced by the GBM shows that the spatial distributions of high-susceptibility watersheds were highly coupled with the locations of the topographical extreme belt, fault zone, seismic belt, and dry valleys. This study provides critical information for risk mitigating and prevention of debris flow.
DOI10.1038/s41598-019-48986-5
Indexed BySCI
Language英语
WOS IDWOS:000483017100011
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/26960
Collection山地灾害与地表过程重点实验室
Corresponding AuthorZhan Yu
Affiliation1.Institute for Disaster Management and Reconstruction, Sichuan University-Hongkong Polytechnic University, Chengdu, Sichuan, 610200, China;
2.Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China;
3.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China;
4.Stamatopoulos and Associates Co. and Hellenic Open University, Athens, 11471, Greece;
5.Department of Land, Air, and Water Resources, University of California, Davis, California, 95616, United States;
6.Sino-German Centre for Water and Health Research, Sichuan University, Chengdu, Sichuan, 610065, China;
7.Medical Big Data Center, Sichuan University, Chengdu, Sichuan, 610041, China
Recommended Citation
GB/T 7714
Di Baofeng,Zhang Hanyue,Liu Yongyao,et al. Assessing Susceptibility of Debris Flow in Southwest China Using Gradient Boosting Machine[J]. SCIENTIFIC REPORTS,2019,9:12532.
APA Di Baofeng.,Zhang Hanyue.,Liu Yongyao.,Li Jierui.,Chen Ningsheng.,...&Zhan Yu.(2019).Assessing Susceptibility of Debris Flow in Southwest China Using Gradient Boosting Machine.SCIENTIFIC REPORTS,9,12532.
MLA Di Baofeng,et al."Assessing Susceptibility of Debris Flow in Southwest China Using Gradient Boosting Machine".SCIENTIFIC REPORTS 9(2019):12532.
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