Abstract

The determination of the return period of frequent discharges requires the definition of flood peak thresholds. Unlike daily data, the volume of data to be processed with the generalization of hourly data loggers or even with an even finer temporal resolution quickly becomes too large to be managed by hand. We therefore propose an algorithm that automatically extracts flood characteristics to compute partial series return periods based on hourly series of flow rates. Thresholds are defined through robust analysis of field observation-independent data to obtain five independent flood peaks per year in order to bypass the 1-year limit of annual series. Peak over thresholds were analyzed using both Gumbel’s graphical method and his ordinary moments method. Hydrological analyses exhibit the value in the convergence point revealed by this dual method for floods with a recurrence interval around 5 years. Pebble-bedded rivers on impervious substratum (Ardenne rivers) presented an average bankfull discharge return period of around 0.6 years. In the absence of field observation, the authors have defined the bankfull discharge as the Q0.625 computed with partial series. Annual series computations allow Q100 discharge determination and extreme floods recurrence interval estimation. A comparison of data from the literature allowed for the confirmation of the value of Myer’s rating at 18, and this value was used to predict extreme floods based on the area of the watershed.

Highlights

  • In many hydrological and geomorphological studies, determining the return period of hydrological events or estimating the discharge value for a given return period is often required

  • While the computation of the flood frequency in annual series is only dependent upon the lowest annual flood, the newly developed algorithm for extracting peaks over threshold in partial series gave us the possibility to test a greater number of threshold parameters across a wide range of stations

  • The first purpose of this paper was the development of an algorithm to cope with the large amount of hourly discharge data in return period estimations through the automatic extraction of flood characteristics

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Summary

Introduction

In many hydrological and geomorphological studies, determining the return period of hydrological events or estimating the discharge value for a given return period is often required. Among the great variety of laws governing statistics and probability used to estimate return period of given discharge value from the series of historical flows Two problems arise: (1) how best to choose between working with either annual series (Ta ) or partial series (Tp ); (2) which threshold flow should be used to select floods for the partial series method. Annual series do not allow for an estimation of recurrence intervals of bankfull discharge of less than 1 year. This is a problem because such recurrences occur regularly on many rivers in Wallonia, in the Ardenne [7]. Depending on the threshold values used for the partial series method, there are significant differences between the two procedures (Ta and Tp ) for predicting a flood with low

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