CTRIP-HyDAS: A Global-Scale Data Assimilation Framework for SWOT-Derived Discharge Using Synthetic Observations at High Resolution (1/12°)
CTRIP-HyDAS : un cadre d'assimilation de données à l'échelle mondiale pour les débits dérivés de SWOT utilisant des observations synthétiques à haute résolution (1/12°)
Verma, Kaushlendra ; Munier, Simon ; Boone, Aaron ; Le Moigne, Patrick
Année de publication
2026
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.</div>
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