Root zone storage as a key driver of catchment precipitation partitioning in the Budyko framework

Quantification of long-term partitioning of precipitation into evaporation and runoff is a fundamental pursuit in catchment hydrology. The Budyko framework provides a theoretical basis for this and estimates the evaporative fraction based on the aridity index via the Budyko curve. However, deviations from the global-average Budyko curve suggest additional controls on precipitation partitioning beyond the aridity index. We hypothesized that root zone storage capacity (S_r), defined as maximum subsurface water accessible to vegetation roots, is a key driver of these deviations. The relationship between S_r  and precipitation partitioning in the Budyko space was investigated globally across >5000 catchments. S_r was calculated using the memory method based on streamflow observations and water balance. The omega parameter (ω) from Fu’s equation was used to determine the catchment’s position in the Budyko space, reflecting precipitation partitioning. Results revealed a strong positive correlation (Spearman’s ρ=0.68) between S_r and ω globally indicating S_r as a dominant driver of precipitation partitioning. Further analysis based on Köppen-Geiger climatic zone classification revealed variations in the S_r-ω relationship, with the strongest correlations observed in cold (ρ=0.87) and Mediterranean (ρ=0.83) climates, followed by temperate (ρ=0.76), tropical (ρ=0.64) and arid climates (ρ=0.61). These findings indicate that the influence of S_r on precipitation partitioning varies across different climatic regions, with a particularly strong impact observed in cold and Mediterranean climates. This study extends prior theoretical and regional insights to a global scale confirming S_r as a governing factor in modulating catchment precipitation partitioning in the Budyko space. Vice-versa, the water and energy limits of the Budyko space provide a theoretical basis for the upper limits in S_r found in nature. The findings emphasize the variability of the S_r-ω relationship across climatic zones and underscore the importance of incorporating S_r dynamics in global water resources assessments.