Abstract
Agricultural irrigation of the South Jingyang tableland in Shaanxi Province, China has led to a continuous rise of the groundwater level and has triggered a series of loess landslides, thereby seriously affecting the life and property safety of local residents. Research shows that the major cause of the landslide in the loess layer of the South Jingyang tableland is the rising groundwater level. Therefore, the research on the formation mechanism of landslide in this area should include the investigation of the stratigraphic structure and groundwater level distribution characteristics. On this basis, a series of approaches, such as electrical resistivity tomography (ERT), borehole, and laboratory tests, was carried out on the South Jingyang tableland, and the groundwater level distribution and stratigraphic structure in the study area were determined. The qualitative relationship between resistivity value and water content at different depths was detected using the inversion results of ERT and borehole data. Through laboratory tests, the quantitative relationship between resistivity values under different water contents was established. The precise depth of the groundwater level was inferred by connecting the qualitative relationship with the quantitative relationship, and then a detailed 3D geological model was established by linking the inversion results of ERT with the field borehole lithology data and geological survey data. The detection results show that when the qualitative and quantitative analyses of the ERT inversion results were combined, the distribution of the groundwater level was accurately judged. The ERT is effective in reflecting the stratigraphic structure and hydrological characteristics of the Loess Plateau, and its potential as a supplementary technology for detecting the groundwater level is reasonable. This study addresses the limitation and inaccuracy in determining the stratum structure and groundwater level by solely relying on borehole information or ERT. The established 3D geological model not only provides a basis for the study of groundwater table fluctuation, but also a technical guidance for the stability evaluation of loess slope, landslide prediction, and early warning in the study area.