Abstract
A classical approach to flood frequency modeling is based on the choice of the probability distribution to best describe the analyzed series of annual or seasonal maximum flows. In the paper, we discuss the two main problems, the uncertainty and instability of the upper quantile estimates, which serve as the design values. Ways to mitigate the above-mentioned problems are proposed and illustrated by seasonal maximum flows at the Proszówki gauging station on the Raba River. The inverse Gaussian and generalized exponential distributions, which are not commonly used for flood frequency modeling, were found to be suitable for Polish data of seasonal peak flows. At the same time, the heavy tailed distributions, which are currently recommended for extreme hydrological phenomena modeling, were found to be inappropriate. Applying the classical approach of selecting the best fitted model to the peak flows data, significant shifts in the upper quantile estimates were often observed when a new observation was added to the data series. The method of aggregation, proposed by the authors, mitigates this problem. Elimination of distributions that are poorly fitted to the data series increases the stability of the upper quantile estimates over time.
Highlights
The main goal of flood frequency analysis (FFA) is to assess the size of the probable flood peak flows
The classical and alternative approaches to the estimation of the upper quantiles of the probability distribution of maximum seasonal flows were presented for the Proszówki gauging station on the Raba River
Despite the multiplicity of probability distributions that have been proposed for flood frequency modeling, the analysis of Polish data of seasonal maximum flows from 37 gauging stations shows that new models are still desirable
Summary
The main goal of flood frequency analysis (FFA) is to assess the size of the probable flood peak flows. As the true probability distribution function (PDF), which describes the analyzed series of annual or seasonal maximum flows, is not known, the flood frequency analysis refers to a hypothetical distribution whose parameters are estimated based on the observation series. Due to many practical applications, interest has been focused on the upper quantile estimates. Their values are necessary when most hydraulic structures are dimensioned and when the limits of flood zones are determined. The most commonly used design value is the 1% quantile estimate (Qmax1% ) and it represents the probable maximum flow that is exceeded on average once in a hundred years.
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