Summary
A hydrological model is a useful tool to study the effects of human activities and climate change on hydrology. Accordingly, the performance of hydrological modeling is vitally significant for hydrologic predictions. In watersheds with intense human activities, there are difficulties and uncertainties in model calibration and simulation. Alternative approaches, such as machine learning techniques and coupled models, can be used for streamflow predictions. However, these models also suffer from their respective limitations, especially when data are unavailable. Satellite-based remote sensing may provide a valuable contribution for hydrological predictions due to its wide coverage and increasing tempo-spatial resolutions. In this review, we provide an overview of the role of satellite-based
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