Scale-dependent model-observation inconsistencies in global terrestrial water storage models

Accurate representation of terrestrial water storage is essential for water resource management and climate adaptation, yet model‑observation inconsistencies hinder global water cycle assessment. Here we show, using a unified multi‑scale framework, that seven model products with diverse modeling strategies and varying structural completeness exhibit scale‑dependent performance against Gravity Recovery and Climate Experiment observations across global, climate-zone, and basin scales. Globally, hydrological models show the highest temporal correlation (0.94) but underperform spatially (0.32), whereas the assimilation system balances both dimensions with higher spatial agreement (0.73). Across climate zones, the assimilation system maintains robust performance, while physical models degrade in polar regions (−0.40). From large to small basin scales, hydrological model performance deteriorates systematically, whereas the assimilation system retains higher consistency and directional accuracy. These findings demonstrate that satellite observation-constrained assimilation substantially reduces inconsistencies relative to model‑driven products, offering essential guidance for climate adaptation and water management strategies. Using a satellite observation-constrained assimilation system can mitigate hydrological models’ inconsistencies, leading to improved global performance and maintaining robustness across various climate zones, according to analysis of model-observation inconsistencies across global, climate-zone, and multiple basin scales.