Substantial Contribution of Woody Components to Rainfall Interception in Chinese Forests: Insights from a Refined Analytical Model

Assessing rainfall interception (I_R) is a critical yet uncertain aspect in hydrological cycle, particularly the quantification of relative contributions from leaves and woody components (e.g., branches, stems, and trunks) to I_R. Nevertheless, the role of woody components in I_R estimation remains largely unexplored and thereby has been constantly overlooked. This study addressed this challenge and refined the widely-used Gash model to distinguish woody interception (I_W) from leaf interception (I_L). We incorporated the spatial variability of vegetation traits alongside satellite data in 2019 into the refined model, and spanned China’s major forest types. The refined model showed a strong agreement with field observations in estimating I_R (r=0.83, p<0.01) and the fraction of rainfall interception to precipitation (I_R/P) (r=0.77, p<0.01). The average I_R was 112.4 ± 32.1 mm (with I_R/P of 14.7 ± 8.2%) in 2019, of which I_L accounted for 77.9% and I_W contributed the rest 22.1%. Among different forest types, I_W/I_R exhibited the highest values in deciduous needle-leaf forests (DNF, mean: 51.9%) but lowest values in evergreen broad-leaf (EBF, mean: 14.3%). In addition, I_W/I_R was larger in the non-growing season than that of growing season in some forest types, such as exceeding 60% in winter for DNF, indicating that more rainwater was intercepted by woody components than by leaves. Our study underscores the substantial role of woody components in I_R,particularly in needle-leaf forests, that are prevalent globally, a finding that can provide novel methods and valuable parameters for global hydrological models to improve the accuracy of model predictions.