Dam Health Diagnosis Model Based on Cumulative Distribution Function

Traditional methods for diagnosing dam health often rely on single point measurements, which require assumptions about the distributions of these measurements. These approaches fail to integrate multiple measured values for joint diagnosis and overlook the true distribution of the measured values, l...

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Bibliographic Details
Published in:Water resources management 2023-09, Vol.37 (11), p.4293-4308
Main Authors: Jiang, Zhenxiang, Wu, Bo, Chen, Hui
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Atmospheric Sciences
Civil Engineering
Dam engineering
Dams
Diagnosis
Distribution
Distribution functions
Earth and Environmental Science
Earth Sciences
Engineering
Environment
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Hydrology/Water Resources
Hypotheses
Methods
Normal distribution
Safety engineering
Safety management
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Summary:Traditional methods for diagnosing dam health often rely on single point measurements, which require assumptions about the distributions of these measurements. These approaches fail to integrate multiple measured values for joint diagnosis and overlook the true distribution of the measured values, leading to potential misdiagnosis. This paper proposes a dam health diagnosis method based on kernel density estimation (KDE) and copula functions to address these limitations. The method incorporates a measurement analysis flow that extends from a single point to multiple points and establishes criteria for dam health diagnosis. In addition, this paper proposes to select the optimal copula function based on the Akaike information criterion (AIC). An engineering example is presented to demonstrate the proposed method's effectiveness in diagnosing a dam's health without assuming a specific measurement distribution function. This research contributes to the field of engineering safety management by enabling comprehensive dam health diagnosis from local dam states to the entire dam structure.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-023-03553-6