CTRIP‐HyDAS: A Global‐Scale Data Assimilation Framework for SWOT‐Derived Discharge Using Synthetic Observations at High Resolution (1/12°)

Abstract The integration of satellite‐based observations into hydrological models offers transformation potential for improving discharge predictions globally, especially in regions lacking in situ measurements. This study presents CTRIP‐HyDAS, a global‐scale hydrological data assimilation framework that merges SWOT‐derived discharge observations with the CTRIP river routing model at 1/12° spatial resolution. The framework was applied at the global scale and evaluated using Observing System Simulation Experiments under controlled discharge observation uncertainty scenarios (10%, 20%, and 40%). Performance metrics computed globally show widespread improvements, with Assimilation Index (AI) values exceeding 0.7 in most regions and relative errors reduced to within 5%–10% under low‐error conditions. To illustrate the framework's adaptability, six representative river basins, that is, Amazon, Congo, Ganges, Indus, Mississippi, and Reka, were selected to showcase HyDAS performance under diverse hydrological regimes. A physics‐based localization method enabled efficient propagation of corrections beyond the observed swath. These findings confirm the scalability and robustness of CTRIP‐HyDAS for global SWOT‐based assimilation and underline its potential to enhance discharge prediction and water management in data‐scarce regions.