Impact of Data Length on the Uncertainty of Hydrological Copula Modeling
Publication: Journal of Hydrologic Engineering
Volume 20, Issue 4
Abstract
Three Archimedean copulas were employed to model annual maximum flood peak data of different lengths. Estimation methods based on ranks were employed for parameter estimation. Marginals were modeled with the generalized extreme value (GEV) distribution. Then, uncertainty in modeling results was investigated with the change in data length. The joint and conditional return periods were also analyzed with the selected copula model to see how it varied with data length. Results showed that the accuracy of modeling deteriorated with the decrease in data length and that the best-fitting copula model depended on the data length. The uncertainty of modeling results may be due to the uncertainty of the flow itself when the data length is shortened. The data length has a negative effect not only on copula modeling but may also have an adverse effect on the marginal, which is an important factor when using a copula model to do bivariate analysis.
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Acknowledgments
The authors gratefully acknowledge the helpful comments and suggestions from the editor and anonymous reviewers. This study was supported by the National Natural Science Fund of China (No. 51190091 and 41071018), the Program for New Century Excellent Talents in University (NCET-12-0262), the China Doctoral Program of Higher Education (20120091110026), the Qing Lan Project, the Skeleton Young Teachers Program, and the Excellent Disciplines Leaders in Midlife-Youth Program of Nanjing University.
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Published In
Journal of Hydrologic Engineering
Volume 20 • Issue 4 • April 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Jan 2, 2014
Accepted: Jun 10, 2014
Published online: Aug 6, 2014
Discussion open until: Jan 6, 2015
Published in print: Apr 1, 2015
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