College of Geology Engineering and Geomatics, Chang'an University, Xi'an, 710064, Shaanxi, China.
Sci Rep. 2021 Dec 10;11(1):23824. doi: 10.1038/s41598-021-02623-2.
Loess presents very unique collapsible behaviour due to its special under-compactness, weak cementation and porousness. Many environmental issues and geological hazards including subgrade subsidences, slope collapses or failures, building cracking and so on are directly caused by the collapsible deformation of loess. Such collapsible behaviour may also severe accidents due to sinkholes, underground caves or loess gullies. Moreover, with the increasing demand of construction and development in the loess areas, an in-depth research towards effective evaluation of loess collapsibility is urged. Currently no studies have made attempts to explore a rather complete and representative area of Loess Plateau. This paper thus provides a novel approach on spatial modelling over Jin-Shan Loess Plateau as an extension to experimental studies. The in-lab experiment results have shown that shown that the porosity ratio and collapsibility follow a Gaussian distribution and a Gamma distribution respectively for both sampling areas: Yan'an and Lv Liang. This establishes the prior intuition towards spatial modelling which provides insights of potential influential factors on loess collapsibility and further sets a potential direction of the loess studies by considering an extra dimension of spatial correlation. Such modelling allows robust predictions taken into account of longitudinal information as well as structural parameters and basic physical properties. Water contents, dry densities, pressure levels and elevations of samples are determined to be statistically significant factors which affect the loess collapsibility. All regions in Lv Liang area are at risk of high collapsibility with average around 0.03, out of which roughly a third of them are predicted to be at high risk. Clear spatial patterns of higher expected collapsibility in the southwest comparing to the northeast are shown adjusting for influential covariates. On reference guidelines for potential policy makings, county-level regions with the highest expected loess collapsibility are also identified.
黄土由于其特殊的欠压实、弱胶结和多孔性，呈现出非常独特的湿陷性。许多环境问题和地质灾害，包括路基沉降、边坡崩塌或失稳、建筑物开裂等，直接是由黄土的湿陷变形引起的。这种湿陷性也可能导致地面塌陷、地下洞穴或黄土冲沟等严重事故。此外，随着黄土地区建设和发展需求的增加，迫切需要对黄土湿陷性进行深入研究。目前，还没有研究试图探索黄土高原一个相当完整和有代表性的地区。因此，本文提出了一种新的方法，对金闪黄土高原进行空间建模，作为实验研究的延伸。室内实验结果表明，延安和吕粱两个采样区的孔隙比和湿陷性分别服从高斯分布和伽马分布。这为空间建模提供了先验直觉，揭示了潜在的影响黄土湿陷性的因素，并通过考虑空间相关性的额外维度，为黄土研究开辟了潜在的方向。这种建模允许稳健的预测，同时考虑到纵向信息以及结构参数和基本物理特性。样品的含水量、干密度、压力水平和高程被确定为影响黄土湿陷性的统计显著因素。吕粱地区所有地区都存在高湿陷性风险，平均约为 0.03，其中大约三分之一被预测为高风险。通过调整有影响的协变量，可以清楚地显示出西南地区比东北地区预期湿陷性更高的空间模式。在参考潜在政策制定的指导方针时，还确定了预计黄土湿陷性最高的县级地区。
