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首页> 外文期刊>Engineering Geology >Landslide hazard spatial analysis and prediction using G1S in the Xiaojiang watershed, Yunnan, China
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Landslide hazard spatial analysis and prediction using G1S in the Xiaojiang watershed, Yunnan, China

机译:云南小江流域G1S滑坡灾害空间分析与预测

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摘要

The Xiaojiang watershed in Southwest China has high landslide hazard and has been given the title of "the Museum of Geohazards in China". However, the available information on landslides in the Xiaojiang watershed is still limited. We constructed the essential spatial database of landslides using the GIS techniques. The quantitative relationships between landslides and factors affecting landslides are established by the Certainty Factor model (CF). The affecting factors such as lithology, structure, slope angle, slope aspect, elevation and off-fault distance are recognized. By applying CF value integration and landslide zonation, the most significant affecting factors are selected. The widespread landslide activities in the Xiaojiang watershed are caused and triggered by heavy rain. A promising approach to modeling the spatial distribution of rainfall-triggered landslide is combining the mechanistic infinite slope stability model with a hydrological model. A model modified from Stability INdex Mapping (SINMAP) is used to prepare the landslide susceptibility maps for different rainfall conditions. Information on these maps could be useful for explaining the known existing landslide, making emergency decisions and relieving the efforts on the avoidance and mitigation of future landslide hazards.
机译:中国西南地区的小江流域具有很高的滑坡危险性,并被授予“中国地质灾害博物馆”的称号。但是,关于小江流域滑坡的可用信息仍然有限。我们使用GIS技术构建了重要的滑坡空间数据库。确定性因子模型(CF)建立了滑坡与影响滑坡的因素之间的定量关系。可以识别影响因素,例如岩性,结构,坡度角,坡度,高度和断层距离。通过应用CF值积分和滑坡分区,选择了最重要的影响因素。小江流域广泛的滑坡活动是由大雨引起的。一种将降雨触发的滑坡的空间分布建模的有前途的方法是将机械无限边坡稳定性模型与水文模型相结合。根据稳定性指数映射(SINMAP)修改的模型用于准备不同降雨条件下的滑坡敏感性图。这些地图上的信息对于解释已知的现有滑坡,做出紧急决策以及减轻避免和减轻未来滑坡灾害的工作可能是有用的。

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