🔬 Science
6d ago
HydroGraphNet boosts watershed predictions of daily flow and nitrogen in sparse data regions
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Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models have shown strong basin-scale performance, their ability to generalize spatially is limited, particularly under data-scarce conditions. To address this gap, a team of researchers led by the Center for Advanced Bioenergy and Bioproducts Innovation (CABBI) propose HydroGraphNet, a knowledge-guided graph machine learnin
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