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Abstract

The statistical distributions of observed flood peaks often show heavy-tailed behaviour, meaning that extreme floods are more likely to occur than for distributions with an exponentially receding tail. Falsely assuming light-tailed behaviour can lead to an underestimation of extreme floods. Robust estimation of the tail is often hindered due to the limited length of time series. Therefore, a better understanding of the processes controlling the tail behaviour is required. Here, we analyse how the spatial variability of rainfall and runoff generation affects the flood peak tail behaviour in catchments of various sizes. This is done using a model chain consisting of a stochastic weather generator, a conceptual rainfall-runoff model, and a river routing routine. For a large synthetic catchment, long time series of daily rainfall with varying tail behaviours and varying degrees of spatial variability are generated and used as input for the rainfall-runoff model. In this model, the spatial variability and mean depth of a sub-surface storage capacity are varied, affecting how locally or widely saturation excess runoff is triggered. Tail behaviour is characterized by the shape parameter of the generalized extreme value (GEV) distribution. Our analysis shows that smaller catchments tend to have heavier tails than larger catchments. For large catchments especially, the GEV shape parameter of flood peak distributions was found to decrease with increasing spatial rainfall variability. This is most likely linked to attenuating effects in large catchments. No clear effect of the spatial variability of the runoff generation on the tail behaviour was found.