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A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale
Shaojie Zhang1; Luqiang Zhao2; Ricardo Delgado-Tellez3; Hongjun Bao4
Corresponding AuthorLuqiang Zhao
2018
Source PublicationNATURAL HAZARDS AND EARTH SYSTEM SCIENCES
ISSN1561-8633
Volume18Issue:3Pages:969-982
SubtypeArticle
Contribution Rank1
AbstractConventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (F-s) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of F-s. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality F-s < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rain-falls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high pre-diction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.
KeywordSOIL COUPLING MECHANISM TRIGGERED LANDSLIDES HYDROLOGICAL MODEL WARNING SYSTEM SLOPE PREDICTION UMBRIA AREA
DOI10.5194/nhess-18-969-2018
Indexed BySCI
WOS KeywordSOIL COUPLING MECHANISM ; TRIGGERED LANDSLIDES ; HYDROLOGICAL MODEL ; WARNING SYSTEM ; SLOPE ; PREDICTION ; UMBRIA ; AREA
Language英语
Quartile3区
Funding ProjectScience and Technology Service Network Initiative[KFJ-SW-STS-180] ; Science and Technology Support Project of Sichuan Province[2015SZ0214] ; Chongqing Municipal Bureau of Land, Resources and Housing Administration[KJ-2018005] ; National Natural Science Foundation of China[41775111]
TOP
WOS Research AreaGeology ; Meteorology & Atmospheric Sciences ; Water Resources
WOS SubjectGeosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS IDWOS:000428480900001
Funding OrganizationScience and Technology Service Network Initiative ; Science and Technology Support Project of Sichuan Province ; Chongqing Municipal Bureau of Land, Resources and Housing Administration ; National Natural Science Foundation of China
PublisherCOPERNICUS GESELLSCHAFT MBH
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/22957
Collection山地灾害与地表过程重点实验室
Affiliation1.Key Laboratory of Mountain Hazards and Earth Surface Process, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China;
2.Public Meteorological Service Center, China Meteorological Administration, Beijing 100081, China;
3.Nipe Sagua Baracoa Mountain Office, Ministry of Science, Technology and Environment of Cuba, Guantanamo, Cuba;
4.National Meteorological Center, China Meteorological Administration, Beijing 100081, China
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
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Shaojie Zhang,Luqiang Zhao,Ricardo Delgado-Tellez,et al. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale[J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES,2018,18(3):969-982.
APA Shaojie Zhang,Luqiang Zhao,Ricardo Delgado-Tellez,&Hongjun Bao.(2018).A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale.NATURAL HAZARDS AND EARTH SYSTEM SCIENCES,18(3),969-982.
MLA Shaojie Zhang,et al."A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale".NATURAL HAZARDS AND EARTH SYSTEM SCIENCES 18.3(2018):969-982.
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