High-frequency monitoring of reservoir inundation and water storage changes is crucial for reservoir functionality assessment and hydrological model calibration. Although the integration of optical data with synthetic aperture radar (SAR) backscattering coefficients (backscatters) offers an effective approach, conventional methods struggle to consistently provide accurate retrievals over diverse regions and seasons. In this study, we introduce reservoir- and monthly-specific classification models to enhance the integration of Sentinel-1 SAR backscatters with optical-based water dynamics. Our method covers 721 reservoirs with a capacity greater than 0.1 km3 in China during 2017-2021. Furthermore, we leverage multisource satellite altimetry records (e.g., ICESat-2, CryoSat-2, and GEDI) and digital elevation models to derive hypsometry relationship (i.e., water level-water area relationship) for reservoirs, enabling the transformation of inundated areas into monthly water storage changes for 662 reservoirs, representing 93% of the total storage capacity of large reservoirs. Validation against in-situ measurements at 80 reservoirs reveals improved monthly inundated area monitoring compared to existing data sets. Additionally, our reservoir water storage change estimates exhibit an average R2 of 0.79 and a mean relative root mean square error (rRMSE) of 21%. Our findings highlight reservoir water increases from May/June to November and declines in winter-spring in most regions. However, the inter-annual patterns vary among regions, with increases in Northeast China, the Yellow River basin (YR), and Southwest China, contrasted by declines in Eastern and Northwest China. Inter- and intra-annual variability in reservoir water storage is mainly influenced by natural inflow in Northeast and Northwest China, while anthropogenic factors dominate in the YR, Eastern, and Southwest China. Reservoirs can supply water, control flood and provide electricity. Without high temporal frequency data on inundated area and water storage over a large spatial extent, we could not clearly understand how and to which degree numerous reservoirs have altered the natural water cycle and provided multiple benefits to people all across the world. The development of remote sensing technology has facilitated the long-term monitoring of inundated areas and water levels of large quantities of reservoirs. However, high-temporal-resolution monitoring remains challenging. In this study, by developing a novel method which integrates active microwave remote sensing data with optical remote sensing observations, we largely improved the satellite-based monthly inundated area and water storage change monitoring at almost all large reservoirs in China. The results reveal distinct seasonal patterns and interannual variations of reservoir water in different regions of China. Specifically, we found that reservoirs in Northeast China, the Yellow River basin, and Southwest China generally expanded, whereas those in Eastern and Northwest China generally shrank during 2017-2021. The climatic and anthropogenic impacts on the inter- and intra-annual variations in reservoir water across different regions were also analyzed. A new methodology for integrating synthetic aperture radar backscattering coefficients with optical remote sensing-based inland surface water dynamics is developed Monthly inundated area and water storage changes of 721 large reservoirs in China during 2017-2021 are retrieved at improved accuracy Impacts of natural climate and human control on the inter- and intra-annual variations in reservoir water across different regions in China are analyzed