Abstract
A novel approach of combining regionalization and satellite observations of various hydrological variables were employed to significantly improve prediction of streamflow signatures at “geopolitically ungauged” basins. Using the proposed step-wise physiography and climate-based regionalization approach, the model performance at ungauged basins reached 80% of performance of locally calibrated parameters and significantly outperformed the global regionalization parameters. The proposed water level based flow correlation was found to help diagnose models and outperform the existing performance metrics of simulated water levels at ungauged basins. The study also set up the first multi-national, multi-catchment hydrological model in the Greater Mekong region, the top global biodiversity and major disaster risk hotspot in the world through sequential and iterative refinement of the existing global hydrological model. New model setup or existing models in the poorly-gauged and ungauged basins could benefit from the proposed approach to predict and evaluate models at ungauged basins.
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