IAHS-AISH Scientific Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Characteristics and process controls of statistical flood moments in Europe - a data-based analysis

David Lun1, Alberto Viglione2, Miriam Bertola1, Jürgen Komma1, Juraj Parajka1, Peter Valent1,3, and Günter Blöschl1
David Lun et al.
  • 1TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Vienna, Austria (lun@hydro.tuwien.ac.at)
  • 2Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy
  • 3Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology, Bratislava, Slovakia

Recent studies have sought to characterize variations of the annual maximum flood discharge series over time and across space in Europe. To further support these studies, we conduct a pan-European assessment of process controls on key statistical properties of these series, including the mean annual flood (MAF), coefficient of variation (CV) and skewness (CS) of flood discharges. We analyse annual maximum flood discharge series from 2370 catchments in Europe without strong human modifications covering the period 1960-2010. We explore how the estimated moments MAF, CV and CS vary due to catchment size, climate and other controls across Europe.

The process controls on the flood moments are identified through correlation and multiple linear regression analyses and the interpretation is aided by a seasonality analysis. Precipitation-related covariates are found to be the main controls of the spatial patterns of MAF in most of Europe except for regions in which snowmelt contributes to MAF, where air temperature is more important. The Aridity Index is, by far, the most important control on the spatial pattern of CV in all of Europe. Overall, the findings suggest that, at the continental scale, climate variables dominate over land surface characteristics, such as land use and soil type, in controlling the spatial patterns of flood moments.

Finally, to provide a performance baseline for more local studies, we assess the estimation accuracy of regional multiple linear regression models for estimating flood moments in ungauged basins.

How to cite: Lun, D., Viglione, A., Bertola, M., Komma, J., Parajka, J., Valent, P., and Blöschl, G.: Characteristics and process controls of statistical flood moments in Europe - a data-based analysis, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-68, https://doi.org/10.5194/iahs2022-68, 2022.