Quantitative spatial distribution model of site-specific loess landslides on the Heifangtai terrace, China
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Qi Zhou I Qiang Xu I Dalei Peng I Xuanmei Fan I Chaojun Ouyang I Kuanyao Zhao I Huajin Li I Xing Zhu
Quantitative spatial distribution model of site-specific loess landslides on the Heifangtai terrace, China
Abstract Landslide disasters are associated with severe losses on the Loess Plateau of China. Although early warning systems and susceptibility mapping have mitigated this issue to some extent, most methods are qualitative or semi-quantitative in the sitespecific range. In this paper, a quantitative spatial distribution model is presented for site-specific loess landslide hazard assessment. Coupled with multi-temporal remote sensing images and high-precision UAV cloud point data, a total of 98 loess landslides that have occurred since 2004 on the Heifangtai terrace were collected to establish a landslide volume-date and retreating distance database. Eleven loess landslides are selected to construct a numerical model for parameter back analysis, and the accuracy of the simulation results is quantitatively evaluated by the centroid distance and overlapping area. Different volumes and receding distance rates of landslides are fitted to determine the relationship between cracks and potential volume, and different volumes and parameters are combined to simulate the spatial distribution of potential loess landslides. The results of this study reveal that landslide volumes mainly range between 1 × 103 and 5 × 105 m3, and the historical occurrence probability reaches 0.551. The optimal parameters are estimated by the maximum likelihood method to obtain a uniform distribution parameter value probability model, and the results show that the error of the estimated length within a range of 0.05 from the optimal parameter does not exceed 15%. In the selected slope slide case, farmland near the toe of the slope primarily includes exposed hazards with probabilities greater than 0.7. This work provides a useful reference for local disaster reduction and a theoretical methodology for hazard assessments. Keywords Loess landslide . Numerical simulation . Maximum likelihood estimation . Parameter probability . Spatial distribution Introduction Loess is widely distributed worldwide, although the widest distribution and greatest thickness of loess are located on the Loess Plateau in the central and western regions of China (Liu 1985). The plateau occupies approximately 317,000 km2 and is distributed in Gansu, Shanxi, Ningxia, Henan, and Shaanxi provinces, where vast numbers of loess geological hazards are distributed. Considering the soil properties, water erosion, agricultural irrigation, and earthquakes in Northwest China, this area is prone to catastrophic loess landslides (Xu et al. 2007; Zhang and Liu 2010), which not only incur very large economic losses but also cause massive casualties and suffering (Metternicht et al. 2005; Huang and Li 2014). The Badiqo brickyard landslide of the Bailu tableland occurred on 17 September 2011 and caused 32 casualties (Zhuang and Peng 2014). Furthermore, on 15 March 2019, a landslide occurr
