Status: this discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.
Examination for robustness of parametric estimators for flood statistics in the context of extraordinary extreme events
S. Fischer,R. Fried,and A. Schumann
Abstract. We compare several estimators, which are commonly used in hydrology, for the parameters of the distribution of flood series, like the Maximum-Likelihood estimator or L-Moments, with the robust estimators Trimmed L-Moments and Minimum Distances. Our objective is estimation of the 99 %- or 99.9 %-quantile of an underlying Gumbel or Generalized Extreme Value distribution (GEV), where we modify the generated random variables such that extraordinary extreme events occur. The results for a two- or three-parametric fitting are compared and the robustness of the estimators to the occurrence of extraordinary extreme events is investigated by statistical measures.
When extraordinary extreme events are known to appear in the sample, the Trimmed L-Moments are a recommendable choice for a robust estimation. They even perform rather well, if there are no such events.
Received: 29 Jul 2015 – Discussion started: 31 Aug 2015
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In the last few years to occurence of extraordinary extreme flood events rised the question for a suitable statistical model to describe this flood behaviour and give a possibility for the calculation of high quantiles. Since the occurence of these extreme events in very short time series (less than 100 years) could influence the statistical estimators leading to a too high estimation we want to use robust estimators to give a moderate weighting to these floods. The results are given here.
In the last few years to occurence of extraordinary extreme flood events rised the question for...
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