中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

文献类型:期刊论文

作者Shaojie Zhang1; Luqiang Zhao2; Ricardo Delgado-Tellez3; Hongjun Bao4
刊名NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
出版日期2018
卷号18期号:3页码:969-982
关键词SOIL COUPLING MECHANISM TRIGGERED LANDSLIDES HYDROLOGICAL MODEL WARNING SYSTEM SLOPE PREDICTION UMBRIA AREA
ISSN号1561-8633
DOI10.5194/nhess-18-969-2018
产权排序1
通讯作者Luqiang Zhao
英文摘要Conventional 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.
语种英语
WOS记录号WOS:000428480900001
出版者COPERNICUS GESELLSCHAFT MBH
源URL[http://ir.imde.ac.cn/handle/131551/22956]  
专题成都山地灾害与环境研究所_山地灾害与地表过程重点实验室
作者单位1.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
推荐引用方式
GB/T 7714
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.

入库方式: OAI收割

来源:成都山地灾害与环境研究所

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