自然电位的小波分析与概率成像联合方法及其在滑坡监测中的应用探索

Study on the mechanism and monitoring of landslides is important for both the basic research and hazard mitigation. Rainfall is one of the key factors of inducing landslides. As a low-cost method sensitive to fluid, self-potential method could monitor continuously the water flow inside the slope and provide a new approach for landslide monitoring. In the current proposal, the core work is on the tomography of self-potential data from modeling, laboratory experiment, and field observation. We’ll develop a joint method combining wavelet analysis and charge occurrence probability tomography for self-potential data. Some statistical analyses will be adopted to evaluate the parameter effect on the joint tomography results. The 3D numerical models with slope topography, fracture, permeability, and rainfall effect will be simulated using the Comsol Multiphysics software. We’ll validate the joint tomography method based on the above synthetic self-potential data. As the further validation, after designing and doing laboratory experiment and field observation test, we’ll process the experimental and field data using our joint tomography method. Finally, we’ll assess the tomography effect of our joint method and its possible application for landslide monitoring. The joint tomography method combining wavelet analysis and charge occurrence probability provides a new method for self-potential data analysis and interpretation. This study may strengthen the study on the methodology of landslide monitoring.

滑坡机理与监测研究具有重要的科学意义和减灾价值。降雨是诱发滑坡的重要因素之一，自然电位法由于具有对流体敏感、成本较低、适于连续观测等特点，可有效监测坡面内部水的流动分布，从而为滑坡监测提供新途径。本项目拟通过开展自然电位数据的成像方法、数值模型、室内实验和野外试验等系列研究，构建基于自然电位数据的小波分析与概率成像联合方法，结合统计方法，考察不同参数对联合方法成像效果的影响；设计考虑坡面、裂隙、渗流层、降雨等影响的三维数值模型，基于正演计算获得自然电位合成数据，开展三维概率成像、小波分析以及联合成像研究，检验联合成像方法的有效性;开展室内实验和野外观测试验，获取自然电位实验和观测数据，评估联合方法的成像效果和应用前景。本项目拟开展的自然电位小波分析与概率成像联合方法及相关成果具有创新性和科学意义，可望改善自然电位成像效果，为其在滑坡监测中的应用奠定理论方法基础。