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Reliability Assessment of Long-Service Gravity Dams Based on Historical Water Level Monitoring Data

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Publicado en:Water vol. 17, no. 23 (2025), p. 3374-3391
Autor principal: Lu Yuzhou
Otros Autores: Qi Huijun, Li, Ziwei, Du Xiaohu, Lin Chaoning, Sheng Taozhen, Li Tongchun
Publicado:
MDPI AG
Materias:
Load
Dams
Monte Carlo simulation
Accuracy
Datasets
Random variables
Parameter identification
Decision making
Water levels
Hydrology
International organizations
Engineering
Methods
Probability distribution
Hydraulics
Risk assessment
Parameter estimation
Acceso en línea:Citation/Abstract
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Resumen:This paper addresses the challenge of systemic extreme risk in long-service gravity dams under human-controlled operation. It is the first study to construct a Generalized Extreme Value (GEV) distribution model using long-term operational monitoring data. The model, validated by multiple statistical tests and engineering boundary conditions, is then applied within a Response Surface Method-Monte Carlo (RSM-MC) reliability framework. Results indicate that the historical GEV model accurately captures the high-water-level tail characteristics and significantly overcomes the risk underestimation inherent in the uniform distribution model. Compared to the Log-Pearson Type III (Log-P3) design condition model, the GEV model yields a significantly lower probability of failure, e.g., the probability of cracking at the dam heel, the most sensitive failure mode, is reduced by nearly six times. This quantitative difference fully demonstrates GEV’s ability to precisely quantify the effective risk reduction achieved by human control, establishing a more scientific and realistic foundation for risk assessment of long-service gravity dams.
ISSN:2073-4441
DOI:10.3390/w17233374
Fuente:Publicly Available Content Database