In their recent publication in Nature Water, researchers Junyang Gou and Prof. Benedikt Soja introduced a finely resolved model of terrestrial water storage using a novel deep learning approach. By integrating satellite observations with hydrological models, their method achieves remarkable accuracy even in smaller basins. This model promises significant benefits across various domains, including hydrology, climate science, sustainable water management, and hazard prediction.
Reference
Gou, Junyang , Soja, Benedikt
Nature Water (2024), doi: 10.1038/s44221-024-00194-w
Commentary
Sun, Alexander
external pageLearning to downscale satellite gravimetry data through artificial intelligence
Nature Water (2024), doi: 10.1038/s44221-024-00199-5
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