HydroGraphNet boosts watershed predictions of daily flow and nitrogen in sparse data regions

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 Bioenerg
Source
Phys.org
Opens original article in a new tab


