Unboxing the Water Cycle across Spatial Scales with Isotope-Enabled Hydrological Modelling

Improvements in computer power have facilitated the automatic calibration of hydrological and ecohydrological models. Still, many internal hydrological processes remain poorly understood due to their inherent complexity, strong spatial heterogeneity, and highly interactive nature. This knowledge gap largely stems from the prevailing focus on catchment celerity responses (rainfall-runoff response) in hydrological studies, while the pathways and velocities of internal water fluxes remain largely unexplored. Consequently, many hydrological models function as grey boxes – capable of reproducing discharge dynamics yet often “for the wrong reasons.”

Stable water isotopes offer a powerful means to unbox the water cycle with improved process understanding across spatial scales. As conservative tracers, ²H and ¹⁸O are independent of most biogeochemical reactions and naturally integrate spatial heterogeneity, providing effective constraints on the spatial connectivity and velocities of hydrological flow paths. In this presentation, we synthesize our experience with isotope-enabled hydrological and ecohydrological modelling to demonstrate how such frameworks enhance process representation from plot to continental scales.

We will briefly introduce how we developed or refined isotope-aided ecohydrological models at plot, river, catchment, and continental scales. We then demonstrate how these models can be used to partition hydrological fluxes and to identify key flow pathways and their corresponding velocities. Specifically, we illustrate how stable isotopes can be used to (i) quantify depth-dependent root water uptake at the plot scale, (ii) resolve geometry-controlled channel recharge and leakage at the river scale, (iii) diagnose lateral hydrological connectivity among landscape units at the catchment scale, and (iv) characterize pathways and velocities of terrestrial water cycling at the continental scale. These process-based insights not only support more robust and sustainable water management strategies, but also advance our understanding of the co-evolutionary mechanisms linking water and nutrient cycles.