IGSNRR OpenIR
Identification of the Debris Flow Process Types within Catchments of Beijing Mountainous Area
Wang, Nan1,2; Cheng, Weiming1,2,3,4; Zhao, Min1,4,5; Liu, Qiangyi1,2; Wang, Jing6
2019-04-01
Source PublicationWATER
ISSN2073-4441
Volume11Issue:4Pages:26
Corresponding AuthorCheng, Weiming(chengwm@lreis.ac.cn)
AbstractThe distinguishable sediment concentration, density, and transport mechanisms characterize the different magnitudes of destruction due to debris flow process (DFP). Identifying the dominating DFP type within a catchment is of paramount importance in determining the efficient delineation and mitigation strategies. However, few studies have focused on the identification of the DFP types (including water-flood, debris-flood, and debris-flow) based on machine learning methods. Therefore, while taking Beijing as the study area, this paper aims to establish an integrated framework for the identification of the DFP types, which consists of an indicator calculation system, imbalance dataset learning (borderline-Synthetic Minority Oversampling Technique (borderline-SMOTE)), and classification model selection (Random Forest (RF), AdaBoost, Gradient Boosting (GBDT)). The classification accuracies of the models were compared and the significance of parameters was then assessed. The results indicate that Random Forest has the highest accuracy (0.752), together with the highest area under the receiver operating characteristic curve (AUROC = 0.73), and the lowest root-mean-square error (RMSE = 0.544). This study confirms that the catchment shape and the relief gradient features benefit the identification of the DFP types. Whereby, the roughness index (RI) and the Relief ratio (Rr) can be used to effectively describe the DFP types. The spatial distribution of the DFP types is analyzed in this paper to provide a reference for diverse practical measures, which are suitable for the particularity of highly destructive catchments.
Keyworddebris flow process machinelearning catchment Beijing mountainous area
DOI10.3390/w11040638
WOS KeywordLOGISTIC-REGRESSION ; LANDSLIDE HAZARD ; RISK-ASSESSMENT ; ALLUVIAL FANS ; SUSCEPTIBILITY ; CLASSIFICATION ; PREDICTION ; FATALITIES ; EVOLUTION ; GRADIENT
Indexed BySCI
Language英语
Funding ProjectChina Institute of Water Resources and Hydropower Research (IWHR)[SHZH-IWHR-57] ; National Natural Science Foundation of China[41571388]
Funding OrganizationChina Institute of Water Resources and Hydropower Research (IWHR) ; National Natural Science Foundation of China
WOS Research AreaWater Resources
WOS SubjectWater Resources
WOS IDWOS:000473105700008
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/58460
Collection中国科学院地理科学与资源研究所
Corresponding AuthorCheng, Weiming
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
4.Collaborat Innovat Ctr South China Sea Studies, Nanjing 210093, Jiangsu, Peoples R China
5.Nanjing Univ, Sch Geog & Oceanog Sci, Nanjing 210023, Jiangsu, Peoples R China
6.Res Inst Explorat & Dev Dagang Oil Field, Tianjin 300280, Peoples R China
Recommended Citation
GB/T 7714
Wang, Nan,Cheng, Weiming,Zhao, Min,et al. Identification of the Debris Flow Process Types within Catchments of Beijing Mountainous Area[J]. WATER,2019,11(4):26.
APA Wang, Nan,Cheng, Weiming,Zhao, Min,Liu, Qiangyi,&Wang, Jing.(2019).Identification of the Debris Flow Process Types within Catchments of Beijing Mountainous Area.WATER,11(4),26.
MLA Wang, Nan,et al."Identification of the Debris Flow Process Types within Catchments of Beijing Mountainous Area".WATER 11.4(2019):26.
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