Susceptibility modeling of hydro-morphological processes considered river topology
文献类型：期刊论文
| 作者 | Wang, Nan7; Li, Mingxiao5,6; Zhang, Hongyan7; Cheng, Weiming3,4; Du, Chao2; Lombardo, Luigi1 |
| 刊名 | GEO-SPATIAL INFORMATION SCIENCE
 |
| 出版日期 | 2024-12-26 |
| 页码 | 20 |
| 关键词 | Hydro-morphological processes (HMP) river topology deep learning susceptibility The Yangtze River Basin |
| ISSN号 | 1009-5020 |
| DOI | 10.1080/10095020.2024.2440614 |
| 通讯作者 | Li, Mingxiao(limx@szu.edu.cn) |
| 英文摘要 | Hydro-Morphological Processes (HMP, any natural phenomenon contained within the spectrum defined between debris flows and flash floods) are most likely to occur in small catchments, especially buffer zones along or near rivers. Rivers transfer matter and energy between hydrographic units, thus potentially affecting the occurrence of HMPs in nearby catchments. To date, previous HMP susceptibility studies based on data-driven modeling lacked taking into account these interactions between catchments. In this work, we fully considered the role played by river topology and developed a Topology-based HMP susceptibility model (Topo-HMPSM) to emulate the interactions between catchments and predict the susceptibility of HMPs for the Yangtze River Basin during 1985-2015. Results confirmed that our proposed model outperforms four selected baseline models with the best F1-score (mean = 0.744, best = 0.756) and relatively lower uncertainties. A graph-based deep neural network improves the predictive and interpretability of HMP susceptibility modeling using embedding learning techniques. This work attempts to set a standard for incorporating river topology into deep learning models. Our findings highlight the importance of river topology in predicting HMP and support better informed hazard mitigation strategies. |
| WOS关键词 | FLOOD SUSCEPTIBILITY ; BASIN ; CHINA ; EVOLUTION ; RAINFALL ; SYSTEMS ; SCALE |
| 资助项目 | National Natural Science Foundation of China[42201452] ; National Natural Science Foundation of China[42101463] ; Fundamental Research Funds for the Central Universities[2412022QD003] ; State Key Laboratory of Resources and Environmental Information System (LREIS) ; China Institute of Water Resources and Hydropower Research (IWHR) |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001399694000001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; State Key Laboratory of Resources and Environmental Information System (LREIS) ; China Institute of Water Resources and Hydropower Research (IWHR) |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/212687]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Li, Mingxiao |
| 作者单位 | 1.Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, Enschede, Netherlands 2.George Mason Univ, Geog & Geoinformat Sci, Fairfax, VA USA 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 5.Shenzhen Univ, Coll Civil & Transportat Engn, Guangdong Key Lab Urban Informat, Shenzhen, Peoples R China 6.Key Lab Geoenvironm Monitoring Great Bay Area MNR, Shenzhen, Peoples R China 7.Northeast Normal Univ, Sch Geog Sci, Key Lab Geog Proc & Ecol Secur Changbai Mt, Minist Educ, Changchun, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Nan,Li, Mingxiao,Zhang, Hongyan,et al. Susceptibility modeling of hydro-morphological processes considered river topology[J]. GEO-SPATIAL INFORMATION SCIENCE,2024:20. |
| APA | Wang, Nan,Li, Mingxiao,Zhang, Hongyan,Cheng, Weiming,Du, Chao,&Lombardo, Luigi.(2024).Susceptibility modeling of hydro-morphological processes considered river topology.GEO-SPATIAL INFORMATION SCIENCE,20. |
| MLA | Wang, Nan,et al."Susceptibility modeling of hydro-morphological processes considered river topology".GEO-SPATIAL INFORMATION SCIENCE (2024):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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