Abstract: To quantify the relative contributions of climate change and human activities to terrestrial water storage anomalies (TWSA) in China, an integrated assessment framework was developed by combining GRACE/GRACE-FO satellite data, multi-source climate factors, and an improved water balance model. A machine learning approach was used to fill the data gap between 2017 and 2018, and an enhanced Gradient Boosting Machine (GBM) model was applied to reconstruct climate-driven TWSA based on precipitation, temperature, and evapotranspiration. The reconstructed results achieved high fitting accuracy across nine major river basins (R > 0.9). Results indicate a declining trend in national TWSA from 2005 to 2020, with the most significant decreases observed in the Haihe (−14.64 mm/a) and Huaihe (−11.74 mm/a) River basins, while the Yangtze and Pearl River basins showed increasing trends. Attribution analysis reveals a growing influence of human activities in arid and semi-arid regions, with the Yellow River basin reaching nearly 90% contribution from human activities by 2017, whereas humid regions remained predominantly climate-driven. These findings provide quantitative insights into key influencing factors and support regional water resource management under changing climate conditions. To quantify the relative contributions of climate change and human activities to terrestrial water storage anomalies (TWSA) in China, we develop an integrated assessment framework that combines GRACE/GRACE-FO satellite observations, multi-source climatic factors, and an improved water balance model. Machine learning is used to fill the data gap between 2017 and 2018, and an improved gradient boosting machine model is introduced to reconstruct climate-driven TWSA based on precipitation, air temperature, evapotranspiration, and other factors, achieving high fitting accuracy across China’s nine major river basins (correlation coefficients all exceed 0.9). The results indicate that terrestrial water storage in China showed an overall declining trend during 2005—2020, with the most pronounced decreases occurring in the Haihe (−14.64 mm/a) and Huaihe (−11.74 mm/a) river basins, while the Yangtze and Pearl River basins exhibited increasing trends. Contribution analysis reveals that the influence of human activities has continued to intensify in arid and semi-arid regions, with their contribution in the Yellow River basin reaching nearly 90% by 2017, whereas TWSA in humid regions is mainly driven by climate change. These findings provide a quantitative basis for identifying key driving factors and supporting regional water resources management.