Probabilistic evaluation of loess landslide impact using multivariate model
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Ling Xu I Dongdong Yan I Tengyuan Zhao
Probabilistic evaluation of loess landslide impact using multivariate model
Abstract The Loess Plateau is the largest loess accumulation area around the world, onto which loess landslides have been occurring frequently each year, thus bringing significant threats to communities there. To mitigate or manage the risk brought by loess landslides, many methods have been developed to gain insights into mechanisms that trigger loess landslides, or to identify regions that are susceptible to landslides through landslide susceptibility mapping. However, none of these methods can be used to quantitatively evaluate possible impact of potentially unstable slopes, which offers important information for risk management, especially for regions with high susceptibility to landslides. This study aims to fill this gap by constructing a loess landslide database first from field investigation. Then, a multivariate model for loess landslide data, including its height, width, area, and length, is developed considering correlation among these parameters. Subsequently, the multivariate model is used to predict statistically and quantitatively impact of a potentially unstable loess slope, in terms of slide width, length, and area, given height of the potentially unstable loess slope. The proposed method is applied to loess landslides occurred in Baoji City for illustration. Results show that the proposed method works reasonably well. In addition, some key equations are provided using results from the multivariate model. With these equations, geotechnical engineers or decisionmakers can evaluate possible impact of a potentially unstable loess slope with minimal effort. Keywords Non-Gaussian distribution modelling . Correlated data . Risk evaluation . Geo-hazards management Introduction The Loess Plateau, located in the northwestern part of China, is the largest loess accumulation area around the world. It has an area of about 631,000 km2 and covers around 6.6% of China’s land area (Liu 1985). Because of complex geomorphology of Loess Plateau, highly developed vertical joints, loose texture, and high sensitivity to suction stress of loess, the Loess Plateau has been suffering many geo-hazards each year, particularly loess landslides, which pose great threats to human beings, properties, and constructed infrastructures (Qiu et al. 2016; Zhuang et al. 2018). In addition, in the past few decades, there seems to be an increasing number of loess landslides in the Loess Plateau with involvement of human activities, such as construction of roads, railways, and agricultural irrigation (Malamud et al. 2004). Numerous studies have been carried out to study in depth the mechanisms that trigger loess landslides. Zhang et al. (2009) and Xu et al. (2012, 2014) proposed that agricultural irrigation is one of the most influential factors that trigger loess landslide; Wang et al. (2014), Peng et al. (2015), and others observed and demonstrated that loess landslide can be triggered by excavation and rainfall. Simulatio
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