Flood frequency analysis using mean daily flows vs. instantaneous peak flows

Author:

Bartens Anne,Shehu BoraORCID,Haberlandt Uwe

Abstract

Abstract. In many cases, flood frequency analysis (FFA) needs to be carried out on mean daily flows (MDF) instead of instantaneous peak flows (IPF), which can lead to underestimation of design flows. Typically, correction methods are applied to the MDF data to account for such underestimation. In this study, we first analyse the error distribution of MDF-derived flood quantiles over 648 catchments in Germany. The results show that using MDF instead of IPF data can lead to underestimation of the mean annual peak flow (MHQ) by up to 80 % and mainly depends on the catchment area but appears to be influenced by gauge elevation as well. This relationship is shown to differ for summer vs. winter floods. To correct such underestimation, different linear models based on predictors derived from MDF hydrograph and catchment characteristics are investigated. Apart from the catchment area, a key predictor in these models is the event-based ratio of flood peak to flood volume (p/V ratio) obtained by the MDF data. The p/V models applied to either MDF-derived events or statistics seem to outperform other reference correction methods. Moreover, they require a minimum data input, are easily applied, and are valid for the entire study area. The best results are achieved when the L moments of the MDF maximum annual series are corrected with the proposed model, which reduces the flood quantile errors by up to 60 %. The approach behaves particularly well in smaller catchments (<500 km2), where reference methods fall short. However, the limit of the proposed approach is reached for catchment sizes under 100 km2, where the hydrograph information from the daily series is no longer capable of approximating instantaneous flood dynamics and gauge elevations below 100 m, where the difference between MDF and IPF floods is very small.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Copernicus GmbH

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