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

Abstract 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.