Abstract：Climate models and stable hydrogen and oxygen isotope techniques are two major approaches currently used to investigate hydrological cycle processes. Their coupling can improve the quantitative analysis, simulation, and prediction of hydrological cycle processes. This study systematically reviews and compares their advantages, limitations, and coupling potential, with the aim of providing methodological insights for the quantitative investigation of hydrological cycle changes. Climate models can continuously simulate and predict hydrological cycle processes across different spatial and temporal scales and distinguish the hydrometeorological and ecohydrological effects of climate change and human activities through numerical experiments. However, their representation of key processes, including groundwater flow, surface water-groundwater interactions, and cryosphere-atmosphere interactions, remains inadequate, while considerable uncertainties persist in parameterization schemes and simulation results. Stable hydrogen and oxygen isotope techniques can use differences in the isotopic composition and fractionation characteristics of different water bodies to identify water sources, transport pathways, and transformation relationships, thereby providing independent information for hydrological process diagnosis, model calibration, and error constraint. Nevertheless, their application is limited by insufficient observation sites, inadequate sampling representativeness, complex fractionation mechanisms, and difficulties in scale extrapolation. The two approaches are highly complementary, and their effective coupling can improve the quantitative interpretation, simulation, and prediction of hydrological cycle processes. However, substantial bottlenecks remain. Future research should promote the further development of this field by strengthening observation networks as the foundation, advancing mechanistic understanding as the driving force, improving model standardization as the technical support, enhancing data assimilation constraints as the safeguard, and pursuing intelligent integration as a key breakthrough.