Detection of landslide groundwater based on magnetic resonance sounding given complex topography

Effective detection of groundwater in landslide areas is crucial for landslide monitoring. The magnetic resonance sounding (MRS) method is a geophysical technique that can directly detect groundwater. However, its application in landslide groundwater monitoring is often hindered by the complex topography of landslides. This paper presents an MRS framework that accounts for the impact of landslide topography on groundwater detection. The framework includes the use of drone photogrammetry to obtain high-precision topography data and real-time kinematic equipment to acquire the coordinates of key points along the MRS coil. A threedimensional finite element model is then constructed to calculate the alternating magnetic field generated by the MRS coil and the kernel function required for MRS inversion. Two typical landslide topography models-terrace and gully-are constructed and analyzed using numerical simulations. The results indicate that landslide topography significantly impacts the quality of groundwater information retrieved by MRS in both onedimensional and two-dimensional inversions, affecting the accurate detection and identification of infiltration surfaces, sliding zone water, and bedrock surfaces. If accurate topography data are obtained and appropriate kernel functions are calculated, the accuracy of the inversion can be greatly improved. An example of using the MRS method to detect groundwater in a complex landslide in the Three Gorges Reservoir area of China is then presented. The MRS inversion results that consider landslide topography are confirmed using borehole data, electrical resistivity tomography detection results, and on-site drainage tunnel investigations. The water-content distribution inside the landslide body is obtained, providing information helpful to define sliding zones in multilevel landslides. The proposed landslide MRS detection framework makes it possible to apply MRS methods to the detection of landslide groundwater distribution, analysis of seepage fields, and discrimination of landslide geological structures.