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Editorial

New Methods and Technologies of Hydraulic Engineering Safety Assessment

State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Xi’an University of Technology, Xi’an 710048, China
*
Author to whom correspondence should be addressed.
Water 2025, 17(12), 1773; https://doi.org/10.3390/w17121773
Submission received: 30 May 2025 / Accepted: 6 June 2025 / Published: 13 June 2025

1. Introduction to the Special Issue

Water conservation projects, encompassing functions such as flood control, power generation, water supply, and irrigation, play an indispensable role in the sustenance and advancement of human society [1,2,3,4]. Hydraulic structures, particularly dams and reservoirs, are examples of critical infrastructure. While providing essential services, they also present significant safety challenges. The operational complexity of these structures, especially aging ones or those in intricate environments, often surpasses initial engineering and scientific estimations, making a comprehensive understanding of their safety characteristics difficult [5,6,7,8].
Dams, as paramount components of water conservancy and hydropower projects, offer immense benefits but, concurrently, represent serious safety concerns [9,10]. Dam failures can precipitate catastrophic downstream consequences, leading to substantial loss of life and property. Issues such as deformation, cracking, and leakage significantly compromise their safe operation. Dam deformation, in particular, is characterized by inherent uncertainty, diversity, and time-varying behavior. Furthermore, fluctuations in reservoir water levels can alter the geological conditions of bank slopes, thereby affecting the matrix suction of unsaturated soil and water distribution, potentially culminating in hydrodynamic landslides [1,11,12,13,14]. Consequently, safety monitoring models predicated on prototype monitoring data are crucial for evaluating the operational safety of dams.
This Special Issue of Water is dedicated to advancing our understanding of the structural state of hydraulic structures [15,16]. It achieves this by showcasing diverse safety monitoring facilities, innovative data processing methods, and robust evaluation techniques, complemented by geotechnical testing, non-destructive evaluation, numerical simulation, and intelligent algorithms [17,18]. The collective aim is to significantly improve the safety of water conservancy projects and contribute to societal development [19,20,21].
Since the call for papers for this Special Issue, eleven high-quality manuscripts have undergone a rigorous peer-review process and have been accepted for publication. These contributions span a wide array of topics, including sophisticated data-driven models for dam deformation prediction, dynamic response analyses of hydraulic structures, safety monitoring methodologies for uplift pressure, durability assessments considering coupled seepage and dissolution effects, comprehensive modeling of long-term monitoring data, stability analyses of large-section tunnels, transient flow characterization in pipelines, resilience assessment of urban metro systems, and reliability analyses of pile foundations. A summary of these published papers is provided below to offer a clearer perspective on the scope of this Special Issue.

2. Overview of the Contributions of the Special Issue

2.1. Advanced Data-Driven Modeling and Monitoring for Dam Safety

The accurate monitoring and prediction of dam behavior are paramount for safety assurance. Several papers in this issue leverage advanced data-driven techniques to tackle these challenges. Guo, F. et al. [Contribution 1] introduce an innovative multi-teacher distillation regression model integrating clustering integration and adaptive weighting to enhance dam deformation prediction accuracy, demonstrating its superiority over existing knowledge distillation methods when applied to a concrete-faced rockfill dam. Complementing this, Zhou, B. et al. [Contribution 2] propose a dam deformation prediction model based on a multi-scale adaptive kernel ensemble, which effectively extracts signal features and identifies significant deformation trends by employing CEEMDAN for data decomposition and GSWOA for KELM parameter optimization. Addressing another critical aspect, Cheng, L. et al. [Contribution 3] present a safety monitoring method for the uplift pressure in concrete dams, utilizing optimized spatiotemporal clustering and a Bayesian panel vector autoregressive (BPVAR) model that showed higher accuracy compared to traditional machine learning models. Furthermore, Zhou, T. et al. [Contribution 4], employing K-means clustering, IDW interpolation, and D-AHP for a holistic safety evaluation, offer a comprehensive approach to modeling and data mining long-term temperature-stress–strain monitoring data from concrete gravity dams, which has proven more comprehensive than single-factor assessments.

2.2. Structural Integrity, Durability, and Hydrodynamic Performance of Hydraulic in Frastruture

Ensuring the long-term structural integrity and understanding the dynamic behavior of hydraulic infrastructure under various operational and environmental loads are critical. Ma, C. et al. [Contribution 5] investigate the dynamic response of prestressed concrete cylinder pipes (PCCPs) to rockfall impacts using a continuous–discontinuous method, providing crucial insights into impact mechanisms and highlighting vulnerable sections, which is vital for the design of protective measures in water diversion projects. The durability of anti-seepage elements is addressed by Guo, C. et al. [Contribution 6], who developed a numerical model considering seepage and dissolution coupling effects on concrete cutoff walls in earth–rock dams, successfully predicting calcium leaching processes and estimating service life. Chen, B. et al. [Contribution 7] contribute a reliability analysis of the bearing performance of corroded piles subjected to scour action, employing a chloride diffusion model and Monte Carlo simulations to assess failure probabilities under combined degradation mechanisms, finding lateral displacement to be a more sensitive failure criterion. In the realm of hydrodynamic performance, Meng, X. et al. [Contribution 8] demonstrate the application of a high-turbulence numerical simulation technique for a USBR Type III stilling basin, showcasing its efficacy in accurately simulating complex flow patterns and optimizing energy dissipation design, thereby offering a cost-effective alternative to physical model testing.

2.3. Safety Monitoring Methods for Uplift Pressure

Beyond dams, various water engineering projects face unique safety challenges. Zheng, F. et al. [Contribution 9] conduct a construction stability analysis and field monitoring of shallow-buried large-section tunnels in loess strata, using 3D numerical modeling to determine optimal excavation parameters and support timing, offering valuable guidance for similar tunneling projects. The safety of water pipelines is explored by Zhang, Q. et al. [Contribution 10], who study the characteristics and leak localization of transient flow in gas-containing water pipelines, developing a model considering unsteady friction and employing a GA-BP neural network for effective leak detection. Finally, addressing urban water-related hazards, Wang, Y. et al. [Contribution 11] present an assessment of water disaster resilience in mountainous urban metro stations using a combination weighting method and an extension cloud model, establishing a comprehensive evaluation index system and validating its applicability in a real-world case study.

3. Future Perspectives

The papers published in this Special Issue highlight significant advancements in hydraulic structure safety monitoring and management, while also pointing toward several promising directions for future research. The integration of multi-source data represents a critical frontier, necessitating the development of more sophisticated methods for combining information from traditional sensors, remote sensing technologies, and emerging Internet of Things (IoT) devices. This holistic data fusion, building upon comprehensive modeling approaches like those presented by Zhou, T. et al. [Contribution 4], will enable more robust safety assessments by capturing a wider range of structural behaviors and environmental influences.
Concurrently, advancements in artificial intelligence and edge computing are paving the way for more effective real-time monitoring and early warning systems. Future systems, inspired by the predictive capabilities demonstrated in the data-driven models for dam deformation [Contributions 1,2] and pipeline leak detection [Contribution 10], could identify anomalies and potential failures with greater accuracy and lead time, facilitating proactive interventions. As many hydraulic structures worldwide are aging, research on lifecycle management approaches is becoming increasingly vital. Such studies should encompass the entire lifespan of structures, from design to decommissioning, incorporating advanced durability analyses, such as those for cutoff walls [Contribution 6] and corroded piles [Contribution 7], to predict long-term performance and optimize maintenance strategies.
Furthermore, the impacts of climate change, including more frequent extreme weather events and altered hydrological patterns, pose significant challenges that future research must address by developing adaptive management strategies. This may involve revising design standards and enhancing the resilience of critical infrastructure, as explored in the context of urban metro stations [Contribution 11]. The development of digital twin technology for hydraulic structures also represents a particularly promising avenue. By creating comprehensive virtual replicas that are continuously updated with real-time monitoring data, digital twins, building upon dynamic response analyses [Contribution 5] and hydrodynamic simulations [Contribution 8], could integrate physical and virtual models to improve the monitoring, prediction, and operational decision-making capabilities of complex systems like dams and tunnels [Contribution 9].

4. Conclusions

This Special Issue on “New Methods and Technologies of Hydraulic Structure Safety Monitoring and Management” presents valuable contributions to advancing our understanding of hydraulic structure safety. The published papers demonstrate the effectiveness of innovative approaches in data-driven modeling and monitoring [1,2,3,4], structural integrity, durability, and hydrodynamic performance assessment [5,6,7,8], as well as addressing specialized geotechnical and operational safety challenges in diverse water engineering contexts [9,10,11].
The research presented in this Special Issue provides practical tools and methodologies for engineers and researchers working on the safety monitoring and management of hydraulic structures. By combining advanced computational methods, intelligent algorithms, and comprehensive monitoring approaches, these studies contribute to improving the safety and reliability of hydraulic structures, which are critical for water resource management, flood control, power generation, and irrigation.
We would like to express our sincere gratitude to all the authors who contributed to this Special Issue, to the reviewers who provided valuable feedback to improve the quality of the papers, and to Water’s editorial team for their support throughout the publication process. We hope that this Special Issue will stimulate further research and innovation in hydraulic structure safety monitoring and management, ultimately contributing to the sustainable development of water resources and the protection of human lives and property.

Author Contributions

C.M., J.Y. and L.C., conceptualization, writing—original draft preparation, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received grants from the National Natural Science Foundation of China (grant nos. 52409173, 52279140, 52479133) and from the Scientific Research Program Funded by the Shaanxi Provincial Education Department (grant nos. 23JY058).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

List of Contributions

  • Guo, F.; Yuan, J.; Li, D.; Qin, X. Application of a Multi-Teacher Distillation Regression Model Based on Clustering Integration and Adaptive Weighting in Dam Deformation Prediction. Water 2025, 17, 988. https://doi.org/10.3390/w17070988.
  • Zhou, B.; Wang, Z.; Fu, S.; Chen, D.; Yin, T.; Gao, L.; Zhao, D.; Ou, B. Dam Deformation Prediction Model Based on Multi-Scale Adaptive Kernel Ensemble. Water 2024, 16, 1766. https://doi.org/10.3390/w16131766.
  • Cheng, L.; Han, J.; Ma, C.; Yang, J. Safety Monitoring Method for the Uplift Pressure of Concrete Dams Based on Optimized Spatiotemporal Clustering and the Bayesian Panel Vector Autoregressive Model. Water 2024, 16, 1190. https://doi.org/10.3390/w16081190.
  • Zhou, T.; Ma, N.; Su, X.; Wu, Z.; Zhong, W.; Zhang, Y. Modeling and Data Mining Analysis for Long-Term Temperature-Stress-Strain Monitoring Data of a Concrete Gravity Dam. Water 2024, 16, 1646. https://doi.org/10.3390/w16121646.
  • Ma, C.; Tu, Y.; Zhou, Y.; Yang, J.; Cheng, L. Dynamic Response of PCCP under the Rockfall Impact Based on the Continuous–Discontinuous Method: A Case Study. Water 2024, 16, 801.
  • Guo, C.; Lu, J.; Song, Z.; Li, H.; Zhang, W.; Li, Y. Durability Analysis of Concrete Cutoff Wall of Earth-Rock Dams Considering Seepage and Dissolution Coupling Effect. Water 2024, 16, 1590. https://doi.org/10.3390/w16111590.
  • Chen, B.; Wu, C.; Zhang, W.; Fan, S.; Dai, J.; Zhang, W. Reliability Analysis of the Bearing Performance of Corroded Piles Subjected to Scour Action. Water 2025, 17, 84. https://doi.org/10.3390/w17010084.
  • Meng, X.; Zhang, C.; Zhang, B.; Wu, X.; Wang, W.; Wang, H.; Hu, Y.; Benson, D. Application Research of a High Turbulence Numerical Simulation Technique in a USBR Type III Stilling Basin. Water 2024, 16, 3568. https://doi.org/10.3390/w16243568.
  • Zheng, F.; Li, W.; Song, Z.; Wang, J.; Zhang, Y.; Liu, N.; Xiao, K.; Wang, Y. Construction Stability Analysis and Field Monitoring of Shallowly Buried Large-Section Tunnels in Loess Strata. Water 2024, 16, 2192. https://doi.org/10.3390/w16152192.
  • Zhang, Q.; Zhang, Z.; Huang, B.; Yu, Z.; Luo, X.; Yang, Z. Characteristics and Leak Localization of Transient Flow in Gas-Containing Water Pipelines. Water 2024, 16, 2459.
  • Wang, Y.; Li, Y.; Wan, R. Assessment of Water Disaster Resilience in Mountainous Urban Metro Stations by Combination Weighting Method and Extension Cloud Model. Water 2024, 16, 3266.

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Ma, C.; Yang, J.; Cheng, L. New Methods and Technologies of Hydraulic Engineering Safety Assessment. Water 2025, 17, 1773. https://doi.org/10.3390/w17121773

AMA Style

Ma C, Yang J, Cheng L. New Methods and Technologies of Hydraulic Engineering Safety Assessment. Water. 2025; 17(12):1773. https://doi.org/10.3390/w17121773

Chicago/Turabian Style

Ma, Chunhui, Jie Yang, and Lin Cheng. 2025. "New Methods and Technologies of Hydraulic Engineering Safety Assessment" Water 17, no. 12: 1773. https://doi.org/10.3390/w17121773

APA Style

Ma, C., Yang, J., & Cheng, L. (2025). New Methods and Technologies of Hydraulic Engineering Safety Assessment. Water, 17(12), 1773. https://doi.org/10.3390/w17121773

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