Research Summary
Areas of Interest: Large scale computational hydrology Land surface processes Water-carbon-nutrient interactions under global change Hydrologic scaling issues High performance subsurface reactive transport modeling
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Research Keywords
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Projects
Recent Publications
Does grouping watersheds by hydrographic regions offer any advantages in fine-tuning transfer learning model for temporal and spatial streamflow predictions?
Khoshkalam, Y., Rousseau, A. N., Rahmani, F., Shen, C. & Abbasnezhadi, K., Apr 2025, In: Journal of Hydrology. 650, 132540.Research output: Contribution to journal › Article › peer-review
Spatiotemporal Variability of Channel Roughness and its Substantial Impacts on Flood Modeling Errors
Al Mehedi, M. A., Saki, S., Patel, K., Shen, C., Cohen, S., Smith, V., Rajib, A., Anagnostou, E., Bindas, T. & Lawson, K., Jul 2024, In: Earth's Future. 12, 7, e2023EF004257.Research output: Contribution to journal › Article › peer-review
Improving River Routing Using a Differentiable Muskingum-Cunge Model and Physics-Informed Machine Learning
Bindas, T., Tsai, W. P., Liu, J., Rahmani, F., Feng, D., Bian, Y., Lawson, K. & Shen, C., Jan 2024, In: Water Resources Research. 60, 1, e2023WR035337.Research output: Contribution to journal › Article › peer-review
The Geometry of Flow: Advancing Predictions of River Geometry With Multi-Model Machine Learning
Chang, S. Y., Ghahremani, Z., Manuel, L., Erfani, S. M. H., Shen, C., Cohen, S., Van Meter, K. J., Pierce, J. L., Meselhe, E. A. & Goharian, E., Oct 2024, In: Water Resources Research. 60, 10, e2023WR036733.Research output: Contribution to journal › Article › peer-review
Deep dive into hydrologic simulations at global scale: Harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1.0-hydroDL)
Feng, D., Beck, H., De Bruijn, J., Sahu, R. K., Satoh, Y., Wada, Y., Liu, J., Pan, M., Lawson, K. & Shen, C., Sep 26 2024, In: Geoscientific Model Development. 17, 18, p. 7181-7198 18 p.Research output: Contribution to journal › Article › peer-review
Development of objective function-based ensemble model for streamflow forecasts
Lin, Y., Wang, D., Zhu, J., Sun, W., Shen, C. & Shangguan, W., Mar 2024, In: Journal of Hydrology. 632, 130861.Research output: Contribution to journal › Article › peer-review
Bathymetry Inversion Using a Deep-Learning-Based Surrogate for Shallow Water Equations Solvers
Liu, X., Song, Y. & Shen, C., Mar 2024, In: Water Resources Research. 60, 3, e2023WR035890.Research output: Contribution to journal › Article › peer-review
Probing the limit of hydrologic predictability with the Transformer network
Liu, J., Bian, Y., Lawson, K. & Shen, C., Jun 2024, In: Journal of Hydrology. 637, 131389.Research output: Contribution to journal › Article › peer-review
Transfer learning framework for streamflow prediction in large-scale transboundary catchments: Sensitivity analysis and applicability in data-scarce basins
Ma, K., Shen, C., Xu, Z. & He, D., May 2024, In: Journal of Geographical Sciences. 34, 5, p. 963-984 22 p.Research output: Contribution to journal › Article › peer-review
Closure to "applying Knowledge-Guided Machine Learning to Slope Stability Prediction"
Pei, T., Qiu, T. & Shen, C., Sep 1 2024, In: Journal of Geotechnical and Geoenvironmental Engineering. 150, 9, 07024013.Research output: Contribution to journal › Comment/debate › peer-review
Metamorphic testing of machine learning and conceptual hydrologic models
Reichert, P., Ma, K., Höge, M., Fenicia, F., Baity-Jesi, M., Feng, D. & Shen, C., Jun 13 2024, In: Hydrology and Earth System Sciences. 28, 11, p. 2505-2529 25 p.Research output: Contribution to journal › Article › peer-review
Performance evaluation of deep learning based stream nitrate concentration prediction model to fill stream nitrate data gaps at low-frequency nitrate monitoring basins
Saha, G., Shen, C., Duncan, J. & Cibin, R., Apr 2024, In: Journal of Environmental Management. 357, 120721.Research output: Contribution to journal › Article › peer-review
Deep learning insights into suspended sediment concentrations across the conterminous United States: Strengths and limitations
Song, Y., Chaemchuen, P., Rahmani, F., Zhi, W., Li, L., Liu, X., Boyer, E., Bindas, T., Lawson, K. & Shen, C., Aug 2024, In: Journal of Hydrology. 639, 131573.Research output: Contribution to journal › Article › peer-review
LSTM-Based Data Integration to Improve Snow Water Equivalent Prediction and Diagnose Error Sources
Song, Y., Tsai, W. P., Gluck, J., Rhoades, A., Zarzycki, C., McCrary, R., Lawson, K. & Shen, C., Jan 2024, In: Journal of Hydrometeorology. 25, 1, p. 223-237 15 p.Research output: Contribution to journal › Article › peer-review
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Song, Y., Knoben, W. J. M., Clark, M. P., Feng, D., Lawson, K., Sawadekar, K. & Shen, C., Jul 15 2024, In: Hydrology and Earth System Sciences. 28, 13, p. 3051-3077 27 p.Research output: Contribution to journal › Article › peer-review