Impact of Data Length on the Uncertainty of Hydrological Copula Modeling

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. (C) 2014 American Society of Civil Engineers.