Importance of forest stand structures for gross rainfall partitioning on China's Loess Plateau

Large-scale ecological restoration in the arid and semi-arid Loess Plateau region of northern China is challenged by the intensifying water stress due to the changes in precipitation regimes. Although the importance of Gross Precipitation Partitioning (GRP) has been well recognized in forest hydrology, especially in dry areas, the processes are not understood because site- or region-specific factors complicate the accurate quantifications. This study integrates meta-analysis and field observation to compare patterns of GRP in forest stands that had different origins (plantations vs. native forests) and tree species (deciduous vs. evergreen) compositions. We aimed at quantifying the dominant biotic and abiotic factors controlling each of the GRP components to form empirical relationships between the GRP components and the influencing factors via the Boosted Regression Trees (BRT) model. We found a convergence in the GRP components among the examined stands that have diverse tree species and origins. Our results indicated that, unlike stem flow (SF) and canopy interception (I-c), the throughfall (TF) did not differ between natural and plantation stands. Meanwhile, from the perspective of species composition, the broadleaf forest stands had significantly higher SF rates than the coniferous stands. We found that stand structures exerted limited influence on TF, but significantly affected SF and I-c. We hypothesized that the residence time of the GRP components was important in explaining the matrix of influencing factors. The cumulative influences of stand structure factors played a more important role than species in most conditions. Based on the most influential factors (cumulative explanatory power > 70 %) selected from the BRT model, we successfully built a general formula to represent the GRP processes across the diverse forest stands in the Loess Plateau. Our study provides insights into the underlying mechanism of GRP for developing more realistic forest hydrological models. An improved understanding of GRP and better models are important for guiding large scale reforestation efforts that account for hydrological processes across stand species and origins.