TY  - JOUR
A1  - Merz, Bruno
A1  - Basso, Stefano
A1  - Fischer, Svenja
A1  - Lun, David
A1  - Bloeschl, Guenter
A1  - Merz, Ralf
A1  - Guse, Bjorn
A1  - Viglione, Alberto
A1  - Vorogushyn, Sergiy
A1  - Macdonald, Elena
A1  - Wietzke, Luzie
A1  - Schumann, Andreas
T1  - Understanding heavy tails of flood peak distributions
JF  - Water resources research
N2  - Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. 
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage. 
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented. 

In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice. 
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system. 
We then discuss to which extent the current knowledge supports or contradicts these hypotheses. 
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms. 

We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
KW  - extreme events
KW  - flood frequency
KW  - flood risk
KW  - upper tail
Y1  - 2022
U6  - https://doi.org/10.1029/2021WR030506
SN  - 0043-1397
SN  - 1944-7973
VL  - 58
IS  - 6
PB  - American Geophysical Union
CY  - Washington
ER  -