Constructing a geography of heavy-tailed flood distributions: insights
from common streamflow dynamics.
Abstract
Heavy-tailed flood distributions depict the higher occurrence
probability of extreme floods. Understanding the spatial distribution of
heavy tail floods is essential for effective risk assessment.
Conventional methods often encounter data limitations, leading to
uncertainty across regions. To address this challenge, we utilize
hydrograph recession exponents derived from common streamflow dynamics,
which have proven to be a robust indicator of flood tail propensity
across analyses with varying data lengths. Analyzing extensive datasets
from Germany, the United Kingdom (UK), Norway, and the United States
(US), we uncover distinct patterns: prevalent heavy tails in Germany and
the UK, diverse behavior in the US, and predominantly nonheavy tails in
Norway. The regional tail behavior has been observed in relation to the
interplay between terrain and meteorological characteristics, and we
further conducted quantitative analyses to assess the influence of
hydroclimatic conditions using Köppen classifications. Notably, temporal
variations in catchment storage are a crucial mechanism driving highly
nonlinear catchment responses that favor heavy-tailed floods, often
intensified by concurrent dry periods and high temperatures.
Furthermore, this mechanism is influenced by various flood generation
processes, which can be shaped by both hydroclimatic seasonality and
catchment scale. These insights deepen our understanding of the
interplay between climate, physiographical settings, and flood behavior,
while highlighting the utility of hydrograph recession exponents in
flood hazard assessment.