The Syr Darya and Amu Darya rivers in Central Asia are critical water sources for the region. However, hydrological monitoring remains challenging due to limited ground-based observations. In this study, we applied a fully remote sensing-based approach to quantify the water balance dynamics of these two large catchments from 2003 to 2024.

We utilized total water storage anomalies (TWSA) from GRACE and GRACE-FO, satellite-based precipitation (P) from CHIRPS, and actual evapotranspiration (AET) from MODIS. Monthly water balance components were assessed, with precipitation representing input, evapotranspiration representing loss, and GRACE-derived TWSA reflecting residual storage changes.

The results reveal a strong correlation between P–AET and GRACE-derived storage changes, confirming that satellite observations can effectively track basin-scale water balance in data-scarce regions. Nonetheless, divergences are observed in certain months, particularly during winter and spring, likely due to contributions from snow accumulation and subsequent melt. Runoff data from ERA5-Land further show a sharp increase from April to June, highlighting the influence of spring snowmelt. Seasonal analysis illustrates storage gains during winter due to precipitation and snow accumulation, followed by depletion in spring–summer driven by evapotranspiration and water withdrawals.

This study demonstrates the potential of integrating multiple satellite datasets to monitor hydrological variability in the Syr Darya and Amu Darya basins. This approach provides a solid framework for supporting water resource management and offers new insights into how climate variability affects water availability in Central Asia.