Multiple methods reveal the value of underwater tunnel monitoring data

Monitoring data of structural deformation and water level fluctuations are important for understanding the behaviour of underwater tunnels. In this study, the correlation between cross-sectional deformation and water level was investigated using multiple and synergistic analysis methods. By applying the Seasonal and Trend decomposition using Loess algorithm, the time series of deformation of two adjacent underwater tunnels were separated into trend, seasonal and residual components. The seasonal components were validated through mechanical models derived from the modified rigid ring model and the elastic centre method. The fitting results of trend components were validated using engineering experience. The nature of tunnel sections with different correlations was also explored, revealing that tunnel sections covered by impermeable layers or with an overlying ‘hydraulic pathway’ have higher correlations. The results of this work provide valuable insights for understanding the behaviour of underwater tunnels during operation, with potential applicability to coastal tunnels with similar hydraulic conditions.