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Recent global decline in rainfall interception loss due to altered rainfall regimes

Earth Sciences

Recent global decline in rainfall interception loss due to altered rainfall regimes

X. Lian, W. Zhao, et al.

Discover groundbreaking insights from researchers Xu Lian, Wenli Zhao, and Pierre Gentine as they explore the role of evaporative loss of interception in the global surface water balance. Using advanced hybrid machine learning models, they've revealed that changes in rainfall patterns since 2000 have significantly impacted ecosystem functions and flood risks.

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~3 min • Beginner • English
Abstract
Evaporative loss of interception (Ei) is the first process occurring during rainfall, yet its role in large-scale surface water balance has been largely underexplored. Here we show that Ei can be inferred from flux tower evapotranspiration measurements using physics-informed hybrid machine learning models built under wet versus dry conditions. Forced by satellite and reanalysis data, this framework provides an observationally constrained estimate of Ei, which is on average 84.1 ± 1.8 mm per year and accounts for 8.6 ± 0.2% of total rainfall globally during 2000–2020. Rainfall frequency regulates long-term average Ei changes, and rainfall intensity, rather than vegetation attributes, determines the fraction of Ei in gross precipitation (Ei/P). Rain events have become less frequent and more intense since 2000, driving a global decline in Ei (and Ei/P) by 4.9% (6.7%). This suggests that ongoing rainfall changes favor a partitioning towards more soil moisture and runoff, benefiting ecosystem functions but simultaneously increasing flood risks.
Publisher
Nature Communications
Published On
Dec 10, 2022
Authors
Xu Lian, Wenli Zhao, Pierre Gentine
Tags
Evaporative loss
interception
surface water balance
machine learning
rainfall patterns
ecosystem functions
flood risks
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