Articles | Volume 27, issue 10
https://doi.org/10.5194/hess-27-2019-2023
https://doi.org/10.5194/hess-27-2019-2023
Research article
 | 
26 May 2023
Research article |  | 26 May 2023

A mixed distribution approach for low-flow frequency analysis – Part 2: Comparative assessment of a mixed probability vs. copula-based dependence framework

Gregor Laaha

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Cited articles

Ahmadi, F., Radmaneh, F., Sharifi, M. R., and Mirabbasi, R.: Bivariate frequency analysis of low flow using copula functions (case study: Dez River Basin, Iran), Environ. Earth Sci., 77, 1–16, 2018. a
Ahn, K.-H. and Palmer, R. N.: Use of a nonstationary copula to predict future bivariate low flow frequency in the Connecticut river basin, Hydrol. Process., 30, 3518–3532, 2016. a
Ashkar, F., Jabi, N. E., and Issa, M.: A bivariate analysis of the volume and duration of low-flow events, Stoch. Hydrol. Hydraul., 12, 97–116, 1998. a
Aucoin, F.: FAdist: Distributions that are Sometimes Used in Hydrology, R package version 2.4, CRAN [code], https://CRAN.R-project.org/package=FAdist (last access: 13 October 2022), 2022. a
Dahl, D. B., Scott, D., Roosen, C., Magnusson, A., and Swinton, J.: xtable: Export Tables to LaTeX or HTML, R package version 1.8-4, CRAN [code], https://CRAN.R-project.org/package=xtable (last access: 13 October 2022), 2022. a
Short summary
In seasonal climates with a warm and a cold season, low flows are generated by different processes so that return periods used as a measure of event severity will be inaccurate. We propose a novel mixed copula estimator that is shown to outperform previous calculation methods. The new method is highly relevant for a wide range of European river flow regimes and should be used by default.