As an important engineering system for integrated allocation of water resources and hydroelectric energy development in river basins, cascade dam systems exhibit complex systematic characteristics characterized by the superposition, transmission and amplification of multi-source risks during operation. With China’s vigorous promotion of basin cascade development and the continuous strengthening of dam safety risk management system construction, risk management of cascade dam systems has become a research priority in the field of hydraulic engineering safety. Concentrated on the risk transmission effects within cascade dam systems, advances in the aspects of risk probability calculation, loss assessment, risk classification and coordinated regulation were reviewed. It is pointed out that future research should focus on the high-fidelity simulation of dam-break flood propagation in cascade systems, the coupling analysis of multi-source risks, the improvement of risk assessment frameworks, the formulation of multi-dimensional coordinated regulation strategies and the construction of intelligent river basin management platforms, with the aim of systematically enhancing the risk prevention and control capabilities as well as the regulation level of cascade dam systems.

To address the issues of high fitting difficulty and frequent underfitting of the temperature component in traditional dam displacement monitoring models when applied to high-altitude concrete dams. The effects of air temperature, radiation, reservoir water temperature, and insulation layers on the boundary temperature of the dam body were analyzed. Additionally, considering the lag effect of dam displacement caused by the transmission of external temperature within the dam body, a lag function was constructed using the Rayleigh distribution. The particle swarm optimization algorithm was employed to optimize the lag days, resulting in an improved displacement monitoring model for high-altitude concrete dams with improved temperature components. The improved model was validated using data from two monitoring points at different locations on a high-altitude concrete gravity dam. The results demonstrate that, compared to the traditional model, the improved model exhibits higher fitting accuracy and better predictive performance, making it suitable for application in high-altitude concrete dams.

The noise pollution cannot be avoided for dam deformation, seepage, stress-strain, and other safety monitoring data. It is difficult to achieve excellent denoising effect for the traditional linear noise reduction method. On the basis of reconstructing the phase space of dam safety monitoring data time sequences, with the cross application of local tangent space alignment method, maximum likelihood estimate, adaptive neighborhood and other methods, using the reconstructed phase space as a bridge, and through the extraction of deep information of the monitoring data sequences, the denoised data sequences of dam safety monitoring is obtained. Based on the application of prototype test data, it is evident that the noise reduction effect of the method proposed in this paper is superior to that of the wavelet soft-thresholding method and the fixed neighborhood local tangent space alignment (LTSA) method, demonstrating certain value for engineering applications.

By introducing the detection mode of UAV-mounted infrared and visible dual-light imaging, the non-destructive and fast detection technique of earth-rock embankment leakage is proposed for the more intuitive and efficient leakage detection of earth-rock embankments. The altitude setting of a UAV is discussed considering the imaging effect of the dual light equipment. The implementation procedure of using UAV-mounted infrared and visible dual-light imaging to detect the leakage of earth-rock embankment project is proposed, and the site detection tests of actual project are carried out under various weather conditions. The results of the tests reveal that this detection method can effectively discover the slope leakage and piping in the earth-rock embankment, and it is simple, efficient, and intuitive, with good performance at night. This detection method is excellent for the leakage inspection of large-volume and long-linear embankment projects. The limitations of this method in the practical engineering such as being affected by complex ground conditions, temperature changes, and surface sensing are also discussed.

The acoustic emission (AE) technique is suitable for monitoring and evaluating hydraulic concrete damage due to its good response to material damage. While continuously advancing conventional AE analysis methods, various advanced digital processing technologies and intelligent algorithms have been applied to deeply explore the damage information and evaluate hydraulic concrete damage. An intelligent framework for evaluating hydraulic concrete damage based on AE has been established, according to the working principle of the AE monitoring system for hydraulic concrete damage. Based on the content involved in this framework, a review is conducted on the current research status of hot topics such as conventional analysis methods, signal processing methods, acoustic source localization (ASL) methods, AE source recognition methods, and deep learning technique applications. The complex characteristics of AE signals of hydraulic concrete damage and the research needs of how to overcome the adverse effects have been summarized, aiming to continuously improve the framework and achieve the construction of an intelligent platform for evaluating hydraulic concrete damage based on AE.

Degradation of cement-based materials with the infrastructure engineering constructed in 20 th century for the end of service–life is increasingly concerned. Acoustic emission (AE) as an intrinsic physical phenomenon of energy emission happening inside material or structure can effectively support a precise sensation of health of material and structure based on its spatiotemporal information. This review briefly introduced the sensing principle and analysis method of AE and summarized the supports from AE to description of degradation process, influence factors, and cement–based material degradation such as alkali aggregate reaction, corrosion induced cracking, fatigue damage, and freeze–thaw spalling. In addition, the potential aspects to enrich AE research on the degradation of cement–based materials were also discussed via considering the time–dependent and large-scale feature of hydraulic structure.