The Xin'anjiang model has been widely applied in watershed rainfall-runoff simulation and hydrological forecasting, with significant international influence. In the model, the soil tension water storage capacity is the core parameter for runoff generation calculation, theoretically defined as the water retained by the soil between field capacity and wilting point. However, both hydrological research and practical applications have demonstrated that this theoretical physical interpretation is not strictly accurate. With the recent availability of massive global hydrological datasets and the deepening understanding of multi-scale hydrological mechanisms—especially advances in eco-hydrology—it is now possible to refine the concept and physical explanation of tension water storage capacity.Through theoretical analysis and validation with independent data sources, this study argues that soil tension water storage capacity should be redefined as the root zone storage capacity of terrestrial ecosystems. Clarifying this concept is of great theoretical significance for hydrology and provides a foundation for methodological innovations in determining this core parameter. Traditionally, root zone storage capacity is determined through parameter calibration based on watershed rainfall-runoff data, which is severely constrained in data-scarce regions. This study proposes a novel approach to infer ecosystem root zone storage capacity through surface fluxes: at the landscape scale, it can be retrieved from terrestrial ecosystem flux observations, while at larger scales—even globally—it can be accurately calculated using atmospheric-land surface reanalysis datasets or remotely sensed evaporation data.

Numerous studies have shown that the root zone storage capacity obtained through this new approach significantly enhances the accuracy of watershed runoff simulations, with particularly notable improvements in ungauged basins regions. The shift in perspective from soil physical hydrology to ecosystem hydrology helps clarify the fundamental runoff generation mechanisms in watersheds and reveals the physical meaning of empirical parameters in conceptual hydrological models, thereby advancing the theoretical development of watershed hydrological simulations.