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

Evaporative loss of interception ( E i ) is the first process occurring during rainfall, yet its role in large-scale surface water balance has been largely underexplored. Here we show that E i 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 E i , 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 E i changes, and rainfall intensity, rather than vegetation attributes, determines the fraction of E i in gross precipitation ( E i / P ). Rain events have become less frequent and more intense since 2000, driving a global decline in E i (and E i / 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. Canopy rainfall interception ( E i ) is a key component of global water cycle. Here, the authors quantify E i using flux tower data and machine learning, and find that rainfall gets less partitioned into E i as it gets more intense and less frequent.