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An hourly shallow landslide warning model developed by combining automatic landslide spatial susceptibility and temporal rainfall threshold predictions

文献类型：期刊论文

作者Cao, Yi-ming5,6; Guo, Wei4; Wu, Yu-ming6; Li, Lang-ping6; Zhang, Yi-xing1; Lan, Heng-xing2,3,6
刊名JOURNAL OF MOUNTAIN SCIENCE
出版日期2022-12-01
卷号19期号:12页码:3370-3387
关键词Landslide Hourly warning Temporal probability Spatial probability Rainfall threshold Susceptibility
ISSN号1672-6316
DOI10.1007/s11629-022-7370-1
通讯作者Li, Lang-ping(lilp@lreis.ac.cn) ; Lan, Heng-xing(lanhx@igsnrr.ac.cn)
英文摘要Landslide warning models are important for mitigating landslide risks. The rainfall threshold model is the most widely used early warning model for predicting rainfall-triggered landslides. Recently, the rainfall threshold model has been coupled with the landslide susceptibility (LS) model to improve the accuracy of early warnings in the spatial domain. Existing coupled models, designed based on a matrix including predefined rainfall thresholds and susceptibility levels, have been used to determine the warning level. These predefined classifications inevitably have subjective rainfall thresholds and susceptibility levels, thus affecting the probability distribution information and eventually influencing the reliability of the produced early warning. In this paper, we propose a novel landslide warning model in which the temporal and spatial probabilities of landslides are coupled without predefining the classified levels. The temporal probability of landslides is obtained from the probability distribution of rainfall intensities that triggered historical landslides. The spatial probability of landslides is then obtained from the susceptibility probability distribution. A case study shows that the proposed probability-coupled model can successfully provide hourly warning results before the occurrence of a landslide. Although all three models successfully predicted the landslide, the probability-coupled model produced a warning zone comprising the fewest grid cells. Quantitatively, the probability-coupled model produced only 39 grid cells in the warning zone, while the rainfall threshold model and the matrix-coupled model produced warning zones including 81 and 49 grid cells, respectively. The proposed model is also applicable to other regions affected by rainfall-induced landslides and is thus expected to be useful for practical landslide risk management.
WOS关键词ARTIFICIAL NEURAL-NETWORK ; FREQUENCY RATIO ; DEBRIS-FLOW ; LOGISTIC-REGRESSION ; DURATION CONTROL ; FUZZY-LOGIC ; INTENSITY ; SYSTEM ; MAPS ; GIS
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23090301] ; National Natural Science Foundation of China[42041006] ; National Natural Science Foundation of China[41927806] ; Fundamental Research Funds for the Central Universities, CHD[300102262901]
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000898090200003
出版者SCIENCE PRESS
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities, CHD
源URL[http://ir.igsnrr.ac.cn/handle/311030/189017]  
专题中国科学院地理科学与资源研究所
通讯作者Li, Lang-ping; Lan, Heng-xing
作者单位1.Tianjin Univ Commerce, Tianjin 300134, Peoples R China
2.Changan Univ, Key Lab Ecol Geol & Disaster Prevent, Minist Nat Resources, Xian 710064, Peoples R China
3.Changan Univ, Sch Geol Engn & Geomat, Xian 710064, Peoples R China
4.Fujian Meteorol Serv Ctr, Fuzhou 350025, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Cao, Yi-ming,Guo, Wei,Wu, Yu-ming,et al. An hourly shallow landslide warning model developed by combining automatic landslide spatial susceptibility and temporal rainfall threshold predictions[J]. JOURNAL OF MOUNTAIN SCIENCE,2022,19(12):3370-3387.
APA Cao, Yi-ming,Guo, Wei,Wu, Yu-ming,Li, Lang-ping,Zhang, Yi-xing,&Lan, Heng-xing.(2022).An hourly shallow landslide warning model developed by combining automatic landslide spatial susceptibility and temporal rainfall threshold predictions.JOURNAL OF MOUNTAIN SCIENCE,19(12),3370-3387.
MLA Cao, Yi-ming,et al."An hourly shallow landslide warning model developed by combining automatic landslide spatial susceptibility and temporal rainfall threshold predictions".JOURNAL OF MOUNTAIN SCIENCE 19.12(2022):3370-3387.

入库方式： OAI收割

来源：地理科学与资源研究所

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