Articles | Volume 27, issue 3
https://doi.org/10.5194/hess-27-689-2023
https://doi.org/10.5194/hess-27-689-2023
Research article
 | 
09 Feb 2023
Research article |  | 09 Feb 2023

A mixed distribution approach for low-flow frequency analysis – Part 1: Concept, performance, and effect of seasonality

Gregor Laaha

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Cited articles

Coles, S.: An introduction to statistical modeling of extreme values, in: Springer series in statistics, Springer, London, New York, ISBN 978-1-85233-459-8, 2001. a
Deutsche Vereinigung für Wasserwirtschaft (Ed.): Ermittlung von Hochwasserwahrscheinlichkeiten, no. M 552 in DWA-Regelwerk, August 2012 Edn., oCLC: 809196700, DWA, Hennef, ISBN 978-1-85233-459-8, 2012. a, b
Fischer, S., Schumann, A., and Schulte, M.: Characterisation of seasonal flood types according to timescales in mixed probability distributions, J. Hydrol., 539, 38–56, https://doi.org/10.1016/j.jhydrol.2016.05.005, 2016. a, b
Gauster, T., Laaha, G., and Koffler, D.: lfstat – calculation of low flow statistics for daily stream flow data, R package version 0.9.12, CRAN [code], https://CRAN.R-project.org/package=lfstat, last access: 8 November 2022. a
Gumbel, E. J.: Distributions des valeurs extremes en plusiers dimensions, Publ. Inst. Statist. Univ., Paris, 9, 171–173, 1960. a
Short summary
Knowing the severity of an extreme event is of particular importance to hydrology and water policies. In this paper we propose a mixed distribution approach for low flows. It provides one consistent approach to quantify the severity of summer, winter, and annual low flows based on their respective annualities (or return periods). We show that the new method is much more accurate than existing methods and should therefore be used by engineers and water agencies.