Handling the stochastic uncertainty of flood statistics in regionalization approaches

ABSTRACT

Regional flood frequency analyses are highly affected by the number of gauged catchments and lengths of observation periods at the individual gauges. Therefore, information is unevenly distributed in the region of interest. In particular, the occurrence of single extreme floods that are observed or not observed at some gauges, depending on the observation period, may have a large impact on the regionalization. We evaluated the impact of the sample length on the regionalization of a type-specific statistical mixture-model. In a case study it is shown how the regionalization error can be reduced by more than 50% if the sample sizes increase. We compare three approaches to handling this stochastic uncertainty in regionalization. The alignment of the statistical distribution parameters to consider the impact of extreme floods proved to be most beneficial when aiming to obtain homogeneous regionalized flood quantiles for hydrologically similar regions in a region with heterogeneous observation periods.

KEYWORDS:

• regional flood frequency analyses
• sample effect
• uncertainty
• extreme floods
• flood statistics

Editor A. Castellarin; Associate Editor I. Prosdocimi

Editor A. Castellarin; Associate Editor I. Prosdocimi

Acknowledgements

We are grateful to Bayerisches Landesamt für Umwelt, www.lfu.bayern.de, for providing the discharge data. The manuscript provides all the information needed to replicate the results. R-Codes for flood typology, flood event separation and the statistical model are available in the R-package FloodR (github.com/PhilippBuehler).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the German Research Foundation (“Deutsche Forschungsgemeinschaft,” DFG) under Grant [FOR 2416] “Space-Time Dynamics of Extreme Floods (SPATE).”