Deformation is one of the critical response quantities reflecting the structural safety of dams. To enhance outlier identification and denoising in dam deformation monitoring data, this study proposes a novel preprocessing method based on optimized Variational Mode Decomposition (VMD) and Kernel Density Estimation (KDE). The approach systematically processes data in three steps: First, VMD decomposes raw data into intrinsic mode functions without recursion. The parallel Jaya algorithm is used to adaptively optimize VMD parameters for improved decomposition. Second, the intrinsic mode functions containing outlier and noise characteristics are identified and separated using sample entropy and correlation coefficients. Finally, KDE thresholds are applied for outlier localization, while a data superposition method ensures effective denoising. Validation using simulated deformation data and Global Navigation Satellite Systems (GNSS)-based observed horizontal deformation from dam engineering demonstrates the method’s robustness in accurately identifying outliers and denoising data, achieving superior preprocessing performance.

Granite residual soil is widely distributed in Southeast Fujian. Large-scale engineering construction leads to the exposure of residual soil slopes to the natural environment. Affected by seasonal climate factors, the soil of slopes experiences a dry–wet cycle for a long time. The repeated changes in water content seriously affect the shear strength of soil, and then affect the stability of the slope. In order to explore the influence of the dry–wet cycle on the shear strength of granite residual soil in Fujian, an indoor dry–wet cycle simulation test was carried out for shallow granite residual soil on a slope in Fuzhou, and the relationship between water content, dry–wet cycle times, and the shear strength index, including the cohesion and internal friction angle of the granite residual soil, was discussed. The results show that when the number of dry–wet cycles is constant, the cohesion and internal friction angle of the granite residual soil decrease with an increase in water content. The relationship between the cohesion, internal friction angle, and water content can be described using a power function. Meanwhile, the fitting parameters of the power function are also a function of the number of wet and dry cycles. The prediction formulas of the cohesion and internal friction angle considering the number of dry–wet cycles and water content are established, and then the prediction formula of shear strength is obtained. The ratio of the predicted value of shear strength to the test value shall be within ±15%. An error transfer analysis based on the point estimation method shows that the overall uncertainty of the predicted value of shear strength caused by the combined uncertainty of the predicted value of cohesion and the internal friction angle and the single-variable uncertainty of the predicted value of shear strength caused only by the uncertainty of the predicted value of either the cohesion or internal friction angle increases first and then decreases with an increase in the number of dry–wet cycles. All increase with an increasing water content. The maximum standard deviation of the proposed shear strength prediction model of granite residual soil is less than 9%.

There are a large number of reservoir dams in China, of which embankment dams account for more than 90%, and public safety will be seriously endangered in case of dam failure. Overtopping is the leading cause of dam failure, and the existing research mainly focuses on the study of the failure process, with less research on the change in the deformation field during the failure process. In this study, the measured deformation field data of a modeled embankment dam during the whole process of impoundment, operation, and failure were obtained by carrying out indoor small-scale model experiments of overtopping failure, embedding inclinometers inside the dam body, and setting vertical displacement measurement markers on the surface. A refined analysis of the measured deformation data shows that the dam body displaces vertically downward during the impoundment stage and the vertical displacement at the dam crest has the largest amplitude; the internal horizontal displacement changes to the left bank and downstream side, and the amplitude of the internal horizontal displacement (upstream and downstream direction and dam axis direction) on the right dam sections is more significant than that in the middle of the dam; during the breaching stage, the time sequence of the sudden change in each internal horizontal displacement measuring point is from the downstream side to the upstream side and from the higher elevation to the lower elevation, which is basically consistent with the process of overtopping of embankment dams; and the overall sudden change in left and right bank horizontal displacements within the downstream side of the dam crest and the downstream side of the dam body gauges is significant, and the sudden change in upstream and downstream horizontal displacement (U&D HD) within the downstream side of the dam crest gauges is significant. The experimental analysis results can support the disaster mechanism of embankment dam failure and the theory of early warning of failure.