Emergence of Heavy Tails in Streamflow Distributions: the Role of
Spatial Rainfall Variability
- Hsing-Jui Wang,
- Ralf Merz,
- Soohyun Yang,
- Larisa Tarasova,
- Stefano Basso
Ralf Merz
Helmholtz Centre for Environmental Research (UFZ)
Author ProfileSoohyun Yang
Helmholtz Centre for Environmental Research-UFZ
Author ProfileLarisa Tarasova
Helmholtz Centre for Environmental Research - UFZ
Author ProfileStefano Basso
Helmholtz Centre for Environmental Research
Author ProfileAbstract
Flow events with low frequency often cause severe damages, especially if
their magnitudes are higher than suggested by historical observations.
Heavier right tail of streamflow distribution indicates the increasing
probability of high flows. In this paper, we investigate the role played
by spatially variable rainfall for enhancing the tail heaviness of
streamflow distributions. We synthetically generated a wide range of
spatially variable rainfall inputs and fed them to a continuous
probabilistic model of the catchment water transport to simulate
streamflow in five catchments with distinct areas and geomorphological
properties. Meanwhile, we used a comparable approach to analyze rainfall
and runoff records from 175 German catchments. We identified the effects
of spatially variable rainfall on tails of streamflow distributions from
both simulation scenarios and data analyses. Our results show that the
tail of streamflow distribution becomes heavier with increasing spatial
rainfall variability only beyond a certain threshold. This finding
indicates a capability of catchments to buffer growing heterogeneities
of rainfall, which we term catchment resilience to increasing spatial
rainfall variability. The analyses suggest that the runoff routing
process controls this property. In fact, both small and elongated
catchments are less resilient to increasing spatial rainfall variability
due to their intrinsic runoff routing characteristics. We show the links
between spatial rainfall characteristics and catchment geometry and the
possible occurrence of high flows. The data analyses we performed on a
large set of case studies confirm the simulation results and provide
confidence for the transferability of these findings.