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 been shown to be a robust indicator of flood tail propensity across analyses with varying data lengths. Analyzing extensive datasets covering Atlantic Europe, northern Europe, and the continental United States, we uncover distinct patterns: prevalent heavy tails in Atlantic Europe, diverse behavior in the continental United States, and predominantly non-heavy tails in northern Europe. The regional tail behavior has been observed in relation to the interplay between terrain and meteorological characteristics, and we 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.

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Publication Details

Journal
Hydrology and earth system sciences
Published
2025-03-20
DOI
https://doi.org/10.5194/hess-29-1525-2025
Citations
3
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
2.45
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article

Constructing a geography of heavy-tailed flood distributions: insights from common streamflow dynamics

Ralf Merz, Stefano Basso, Hsing-Jui Wang
3 citations
Hydrology and earth system sciences
Hydrology and Watershed Management Studies
2.45
article

Constructing a geography of heavy-tailed flood distributions: insights from common streamflow dynamics

Ralf Merz, Stefano Basso, Hsing-Jui Wang
article en
3 citations

Abstract

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 been shown to be a robust indicator of flood tail propensity across analyses with varying data lengths. Analyzing extensive datasets covering Atlantic Europe, northern Europe, and the continental United States, we uncover distinct patterns: prevalent heavy tails in Atlantic Europe, diverse behavior in the continental United States, and predominantly non-heavy tails in northern Europe. The regional tail behavior has been observed in relation to the interplay between terrain and meteorological characteristics, and we 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.

Hydrology and earth system sciencesVol. 29(6)
Helmholtz Centre for Environmental Research (DE), National Taiwan University (TW), Norwegian University of Science and Technology (NO), Martin Luther University Halle-Wittenberg (DE), National Taipei University (TW)
Openalex Percentile: Top 13%
Hydrology and Watershed Management Studies
2.45
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