Susceptibility Assessment of Debris Flows Coupled with Ecohydrological Activation in the Eastern Qinghai-Tibet Plateau | |
Jiang, Hu4,5; Zou, Qiang3,4,5; Zhou, Bin4,5; Hu, Zhenru2,5; Li, Cong4,5; Yao, Shunyu1,4; Yao, Hongkun4,5 | |
刊名 | REMOTE SENSING |
2022-03-01 | |
卷号 | 14期号:6页码:24 |
关键词 | debris flow susceptibility prediction machine learning the eastern margin of Qinghai-Tibet Plateau ecohydrological activation |
ISSN号 | 无 |
DOI | 10.3390/rs14061444 |
英文摘要 | The eastern margin of the Qinghai-Tibet Plateau is an extreme topography transition zone, and characterized by significant vegetation zonation, in addition to geographic features (such as enormous topographic relief and active tectonics) that control the occurrence of debris flows, which are rapid, surging flows of water-charged clastic sediments moving along a steep channel and are one of the most dangerous mountain hazards in this region. There is thus an urgent need in this region to conduct a regional-scale debris flow susceptibility assessment to determine the spatial likelihood of a debris flow occurrence and guarantee the safety of people and property, in addition to the smooth operation of the Sichuan-Tibet transport corridor. It is, however, a challenging task to estimate the region's debris flow susceptibility while taking into consideration the comprehensive impacts of vegetation on the occurrence of debris flows, such as the positive effect of root anchoring and the negative effect of vegetation weight loads. In this study, a novel regional-scale susceptibility assessment method was constructed by integrating state-of-the-art machine learning algorithms (such as support vector classification (SVC), random forest (RF), and eXtreme Gradient Boosting (XGB)) with the removing outliers (RO) algorithm and particle swarm optimization (PSO), allowing the impacts of vegetation on debris flow initiation to be integrated with the topographical conditions, hydrological conditions, and geotechnical conditions. This method is finally applied to assess the regional-scale susceptibility of debris flows in the Dadu River basin on the eastern margin of the Qinghai-Tibet Plateau. The study results show that (i) all hybrid machine learning techniques can effectively predict the occurrence of debris flows in the extreme topography transition zone; (ii) the hybrid machine learning technique RO-PSO-SVC has the best performance, and its accuracy (ACC) is 0.946 and the area under the ROC curve (AUC) is 0.981; (iii) the RO-PSO algorithm improves SVC, RF, and XGB performance (according to the ACC value) by 3.84%, 2.59%, and 5.94%, respectively; and (iv) the contribution rate of ecology-related variables is almost only one-tenth that of topography- and hydrology-related factors, according to the factor important analysis for RO-PSO-SVC. Furthermore, debris flow susceptibility maps for the Dadu River basin were created, which can be used to assess and mitigate debris flow hazards. |
资助项目 | National Nature Science Foundation of China[41790432] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23090303] ; Second Tibetan Plateau Scientific Expedition and Research Program (STEP)[2019QZKK0902] ; Sichuan Science and Technology Planning Program[2019YJ0006] |
WOS关键词 | LANDSLIDES ; VEGETATION ; RAINFALL ; MACHINE ; HAZARDS ; SOIL ; GIS ; REINFORCEMENT ; CATCHMENTS ; PROVINCE |
WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
语种 | 英语 |
出版者 | MDPI |
WOS记录号 | WOS:000774625700001 |
资助机构 | National Nature Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Second Tibetan Plateau Scientific Expedition and Research Program (STEP) ; Sichuan Science and Technology Planning Program |
内容类型 | 期刊论文 |
源URL | [http://ir.imde.ac.cn/handle/131551/56512] |
专题 | 中国科学院水利部成都山地灾害与环境研究所 |
通讯作者 | Zou, Qiang |
作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Peoples R China 3.CAS HEC, China Pakistan Joint Res Ctr Earth Sci, Islamabad 45320, Pakistan 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Inst Mt Hazards & Environm IMHE, Key Lab Mt Hazards & Earth Surface Proc, Chengdu 610041, Peoples R China |
推荐引用方式 GB/T 7714 | Jiang, Hu,Zou, Qiang,Zhou, Bin,et al. Susceptibility Assessment of Debris Flows Coupled with Ecohydrological Activation in the Eastern Qinghai-Tibet Plateau[J]. REMOTE SENSING,2022,14(6):24. |
APA | Jiang, Hu.,Zou, Qiang.,Zhou, Bin.,Hu, Zhenru.,Li, Cong.,...&Yao, Hongkun.(2022).Susceptibility Assessment of Debris Flows Coupled with Ecohydrological Activation in the Eastern Qinghai-Tibet Plateau.REMOTE SENSING,14(6),24. |
MLA | Jiang, Hu,et al."Susceptibility Assessment of Debris Flows Coupled with Ecohydrological Activation in the Eastern Qinghai-Tibet Plateau".REMOTE SENSING 14.6(2022):24. |
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