466 citations · 466 across the 3 of their papers we have counts for
3 papers
Distinct hydrologic response patterns and trends worldwide revealed by physics-embedded learning
Haoyu Ji, Yalan Song, Tadd Bindas +9
To track rapid changes within our water sector, Global Water Models (GWMs) need to realistically represent hydrologic systems' response patterns - such as baseflow fraction - but a…
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models
Amirmoez Jamaat, Yalan Song, Farshid Rahmani +3
Data assimilation (DA) enables hydrologic models to update their internal states using near-real-time observations for more accurate forecasts. With deep neural networks like long…
Differentiable modeling to unify machine learning and physical models and advance Geosciences
Chaopeng Shen, Alison P. Appling, Pierre Gentine +27
Process-Based Modeling (PBM) and Machine Learning (ML) are often perceived as distinct paradigms in the geosciences. Here we present differentiable geoscientific modeling as a powe…