Abstract

Statistical models of freshet flows are the basis for the design of hydrotechnical structures and for undertaking all and any activities related with flood threat. With regard to the method of data preparation for estimation and to the estimation procedure itself, the methods applied in such situations can be divided into two parts - FFA (Flood Frequency Analysis) and POT (Peak Over Threshold). In this study a comparison of those methods is made, using an original mixture of distributions (FFA) and an original procedure of distribution estimation (POT) for six selected water gauges on the river Odra.

Highlights

  • Statistical elaboration of freshet flows has been the basis for the estimation of high quantiles of transgression

  • Those values are necessary at the stage of design of hydrotechnical structures, identification of areas with elevated risk of flood threat, etc

  • The methods used in the case of estimation of maximum flows can be divided into two parts [4], in relation to the method of preparation of data for the estimation, and to the estimation procedure itself

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Summary

Introduction

Statistical elaboration of freshet flows has been the basis for the estimation of high quantiles of transgression. On the basis of multi-year observations obtained in this manner, probability distributions of maximum flows are estimated In this case the list of distributions used is extensive [4], [5] and contains over a dozen distributions of various types, starting with the three-parameter gamma distribution (Pearson type III), and ending with GEV type distributions. In the first step we determine the distribution of maximum flows is all high-flow events of the analysed multi-year period (Fig.). Where: is the value of the maximum annual flow; is the threshold and is the flow above the threshold; is the mean number of high-flow events in the year It is a distribution with three parameters of GPD distribution and of Poisson distribution.

River Odra and its catchment basin
Methods
Results
Conclusions
The advantages of using both distributions are the following
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