Journal Articles
- Peijun Li, Yalan Song, Ming Pan, Kathryn Lawson and Chaopeng Shen, 2025, "Ensembling differentiable process-based and data-driven models with diverse meteorological forcing datasets to advance streamflow simulation", Hydrology and Earth System Sciences
- Jiangtao Liu, Chaopeng Shen, Fearghal O'Donncha, Yalan Song, Wei Zhi, E . Hylke Beck, Tadd Bindas, Nicholas Kraabel and Kathryn Lawson, 2025, "From RNNs to Transformers: benchmarking deep learning architectures for hydrologic prediction", Hydrology and Earth System Sciences
- Amirmoez Jamaat, Yalan Song, Farshid Rahmani, Jiangtao Liu, Kathryn Lawson and Chaopeng Shen, 2025, "Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models", Journal of Hydrology
- Yuan Yang, Ming Pan, Dapeng Feng, Mu Xiao, Taylor Dixon, Robert Hartman, Chaopeng Shen, Yalan Song, Agniv Sengupta, Luca Delle Monache and F . Martin Ralph, 2025, "Improving streamflow simulation through machine learning-powered data integration and its potential for forecasting in the Western U.S.", Hydrology and Earth System Sciences
- Kamlesh Sawadekar, Yalan Song, Ming Pan, Hylke Beck, Rachel McCrary, Paul Ullrich, Kathryn Lawson and Chaopeng Shen, 2025, "Improving differentiable hydrologic modeling with interpretable forcing fusion", Journal of Hydrology
- Xiaofeng Liu and Yalan Song, 2025, "Scientific Machine Learning of Flow Resistance Using Universal Shallow Water Equations With Differentiable Programming", Water Resources Research
- M . Wouter Knoben, Ashwin Raman, J . Gaby Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, van Katie Werkhoven, W . Andrew Wood and P . Martyn Clark, 2025, "Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?", Hydrology and Earth System Sciences
- Yalan Song, Tadd Bindas, Chaopeng Shen, Haoyu Ji, M . Wouter Knoben, Leo Lonzarich, P . Martyn Clark, Jiangtao Liu, van Katie Werkhoven, Sam Lamont, Matthew Denno, Ming Pan, Yuan Yang, Jeremy Rapp, Mukesh Kumar, Farshid Rahmani, Cyril Thébault, Richard Adkins, James Halgren, Trupesh Patel, Arpita Patel, Kamlesh Arun Sawadekar and Kathryn Lawson, 2025, "High-Resolution National-Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics-Informed Machine Learning", Water Resources Research
- Yalan Song, Piyaphat Chaemchuen, Farshid Rahmani, Wei Zhi, Li Li, Xiaofeng Liu, Elizabeth W Boyer, Tadd Bindas, Kathryn Lawson and Chaopeng Shen, 2024, "Deep learning insights into suspended sediment concentrations across the conterminous United States: Strengths and limitations", Journal of Hydrology, 639, pp. 131573
- Yalan Song, Wouter J. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar and Chaopeng Shen, 2024, "When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling", Hydrology and Earth System Sciences, 28, (13), pp. 3051-3077
- Xiaofeng Liu, Yalan Song and Chaopeng Shen, 2024, "Bathymetry Inversion Using a Deep-Learning-Based Surrogate for Shallow Water Equations Solvers", Water Resources Research, 60, (3)
- Yalan Song, Wen-Ping Tsai, Jonah Gluck, Alan Rhoades, Colin Matthew Zarzycki, Rachel McCrary, Kathryn Lawson and Chaopeng Shen, 2024, "LSTM-based data integration to improve snow water equivalent prediction and diagnose error sources", Journal of Hydrometeorology, 25, (1), pp. 223-237
- Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Yalan Song, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Binayak Mohanty, Tirthankar Roy, Chonggang Xu and Kathryn Lawson, 2023, "Differentiable modelling to unify machine learning and physical models for geosciences", Nature Reviews Earth & Environment, 4, pp. 552–567
