The deep drainage tunnel project is an important measure to alleviate urban waterlogging. The construction of a deep drainage tunnel is a complicated process, involving many influencing factors, and there are correlations among these influencing factors, so the risk assessment is difficult. In this study, the ISM method, CRITIC method and cloud model are combined to build a risk assessment model for the small-diameter shield construction of a deep drainage tunnel. Firstly, the risk index system of small-diameter shield construction in a deep drainage tunnel is put forward. Secondly, the ISM method is used to divide the risk indicators and extract the key risk factors. Then, these key risk factors are weighted with the CRITIC method, and the cloud model is used to evaluate the construction risk of a small-diameter shield of a deep drainage tunnel. Finally, the feasibility and accuracy of the proposed method are verified by a practical case. It was found that the risk assessment method proposed in this study can not only effectively assess the level of security risk, but also identify the key risk factors and rank the importance of these factors. The results of this study can reduce the interference items and workload of risk assessment to a certain extent, and help provide managers with an accurate decision-making basis.

A visual deformation prediction method was proposed to improve the accuracy and visualization of the surrounding rock deformation prediction in tunnel construction, combining the Variational Modal Decomposition (VMD) and Bidirectional Long- and Short-Term Memory (BiLSTM) network. Based on the VMD method to decompose the measured data of tunnel surrounding rock deformation, the BiLSTM model was used to predict the final deformation value. The prediction results were also embedded into the tunnel’s Building Information Modeling (BIM) as plug-ins, and the data were visualized through graphs and color warnings. Taking the measured data of the arch settlement of the Loushan tunnel as an example, the results showed that the prediction results were more consistent with the measured situation, and the visualization expression could effectively warn of the risk of vault settlement in the construction stage. This study realized the combined use of surrounding rock deformation prediction and BIM technology, which could be used as a reference for similar projects.