LAUSR

The direct current (DC) resistivity method is extensively used to predict water‐inrush disasters in tunnel prospecting. However, during DC resistivity inversion, different initial models can significantly affect the inversion results, often resulting in convergence at a local optimum. To overcome these challenges, we propose a new method for DC data inversion that uses prior information as a reference model. First, the resistivity distribution of the surrounding rock mass was estimated based on detailed geological analysis. Next, an initial homogeneous resistivity model was constructed by averaging the observed tunnel resistivity values. Finally, the initial model was developed by incorporating borehole rock samples and water content data. The effectiveness of the method' was assessed using a series of synthetic models of typical water‐bearing structures. We then applied this approach to the Laomacao Tunnel in the Yunnan Central Water Diversion Project (southwestern China), where drilling data were used as a priori information to optimize the initial model together with the average tunnel resistivity values, successfully identifying the water‐bearing structure ahead of the tunnel face. Overall, the proposed method enhances the understanding of sudden surges, aiding in the prevention and control of water disasters in tunnels.