Identification of the Debris Flow Process Types within Catchments of Beijing Mountainous Area
文献类型：期刊论文
| 作者 | Wang, Nan1,2; Cheng, Weiming1,2,3,4 ; Zhao, Min1,4,5; Liu, Qiangyi1,2; Wang, Jing6
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| 刊名 | WATER
 |
| 出版日期 | 2019-04-01 |
| 卷号 | 11期号:4页码:26 |
| ISSN号 | 2073-4441 |
| 关键词 | debris flow process machinelearning catchment Beijing mountainous area |
| DOI | 10.3390/w11040638 |
| 通讯作者 | Cheng, Weiming(chengwm@lreis.ac.cn) |
| 英文摘要 | The 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. |
| WOS关键词 | LOGISTIC-REGRESSION ; LANDSLIDE HAZARD ; RISK-ASSESSMENT ; ALLUVIAL FANS ; SUSCEPTIBILITY ; CLASSIFICATION ; PREDICTION ; FATALITIES ; EVOLUTION ; GRADIENT |
| 资助项目 | China Institute of Water Resources and Hydropower Research (IWHR)[SHZH-IWHR-57] ; National Natural Science Foundation of China[41571388] |
| WOS研究方向 | Water Resources |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000473105700008 |
| 资助机构 | China Institute of Water Resources and Hydropower Research (IWHR) ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/58459]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Cheng, Weiming |
| 作者单位 | 1.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 |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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