[Objective] High arch dams constructed in alpine gorge areas are equipped with numerous observation instruments. Developing objective deformation analysis models and safety monitoring criteria has important theoretical significance and application value. This study aims to overcome the deficiencies of existing methods by proposing a novel method for monitoring the deformation safety of in-service high arch dams. [Methods] We constructed a deformation principal component (DPC) analysis model taking observation point group (OPG) with similar spatiotemporal deformation patterns as research object. Adaptive adjustment approach, Gaussian mutation disturbance, and Tent chaotic disturbance were introduced to optimize the search ability of the sparrow search algorithm (SSA). Using the Improved SSA (ISSA), the parameter optimization approach of the DPC model was established. A 4-level monitoring criterion system was proposed by comprehensively considering the deviation degree between the DPC and the elastic state and the combined control limit of DPCs. Using the radial deformation observation data of the studied dam, the effectiveness of the proposed methodology was verified. [Results] (1) Compared with SSA, ISSA showed improvements in convergence speed and optimization accuracy according to the results of benchmark function testing. (2) Deformation regularities of observation points located in the same area were similar, whereas those at different locations varied largely. (3) The DPC model optimized by ISSA had the most stable and the best generalization performance. For the fitting results of observation groups A-C, the values of the multiple correlation coefficient were 0.997 7, 0.998 1, and 0.997 0, respectively, the values of residual standard deviation were 0.200 6, 0.182 3, and 0.257 3, respectively, and the values of mean absolute percentage error were 0.152 9, 0.269 9, and 0.294 3, respectively. (4) The DPC criteria enabled the 4-level precision monitoring. The physical significance and the probabilistic interpretation were clear. If an abnormal state occurred, it indicated that the deformation similarity characteristics of OPGs changed to some extent. [Conclusion] (1) The established DPC model shows good performance in characterizing the main deformation patterns of OPGs with similar spatiotemporal deformation characteristics. (2) ISSA shortens the computation time, avoids premature convergence, and improves the DPC model performance. (3) The proposed DPC criteria exhibit greater rigor in probabilistic and physical significance compared with the information entropy criterion. Compared with the confidence ellipsoid method, the proposed criteria provide greater practicality for engineering applications. In engineering applications, the most appropriate countermeasures should be determined through scientific analysis, practical application experience, and site-specific conditions. In future research and practice, it is essential to strengthen studies on the deformation feedback mechanisms of high arch dams and adjacent mountain slopes. Special attention should be paid to the impacts of strong earthquakes, cold-wave shocks, freeze-thaw cycles, dissolution, and carbonation, as well as their coupled effects. In addition, an intelligent database and sharing platform should be established. This will facilitate the efficient management and utilization of in-situ observation data of high arch dams, which can improve the efficiency of 4-level precision monitoring.