Differentiable, learnable, regionalized process-based models with
physical outputs can approach state-of-the-art hydrologic prediction accuracy

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Differentiable, learnable, regionalized process-based models with physical outputs can approach state-of-the-art hydrologic prediction accuracy

Water Resources Research (WRR), 2022

28 March 2022

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Papers citing "Differentiable, learnable, regionalized process-based models with physical outputs can approach state-of-the-art hydrologic prediction accuracy"

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Title
Leveraging Exogenous Signals for Hydrology Time Series Forecasting Junyang He Judy Fox Alireza Jafari Ying-Jung Chen Geoffrey C. Fox AI4TS 72 0 0 14 Nov 2025
Physics-guided Emulators Reveal Resilience and Fragility under Operational Latencies and Outages Sarth Dubey Subimal Ghosh Udit Bhatia AI4CE 58 0 0 21 Oct 2025
Scientifically-Interpretable Reasoning Network (ScIReN): Discovering Hidden Relationships in the Carbon Cycle and Beyond Joshua Fan Haodi Xu Feng Tao Md Nasim Marc Grimson Yiqi Luo Daniel Schwalbe-Koda 174 0 0 16 Jun 2025
Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential EquationsInternational Conference on Learning Representations (ICLR), 2025 Abdolmehdi Behroozi Chaopeng Shen and Daniel Kifer AI4CE 358 3 0 13 May 2025
Distinct hydrologic response patterns and trends worldwide revealed by physics-embedded learningNature Communications (Nat Commun), 2025 Haoyu Ji Yalan Song Tadd Bindas Chaopeng Shen Yuan Yang ... F. Rahmani Ather Abbas H. Beck Yoshihide Wada K. Lawson 182 1 0 14 Apr 2025
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic modelsJournal of Hydrology (J. Hydrol.), 2025 Amirmoez Jamaat Yalan Song F. Rahmani Jiangtao Liu K. Lawson Chaopeng Shen AI4CE 191 0 0 23 Feb 2025
A Deep State Space Model for Rainfall-Runoff Simulations Yihan Wang Lujun Zhang Annan Yu N. Benjamin Erichson Tiantian Yang 350 2 0 28 Jan 2025
Knowledge-guided Machine Learning: Current Trends and Future Prospects Anuj Karpatne X. Jia Vipin Kumar 274 22 0 24 Mar 2024
Towards Interpretable Physical-Conceptual Catchment-Scale Hydrological Modeling using the Mass-Conserving-PerceptronWater Resources Research (WRR), 2024 Yuan-Heng Wang Hoshin V. Gupta AI4CE 503 8 0 25 Jan 2024
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 841 19 0 08 Oct 2023
Time Series Predictions in Unmonitored Sites: A Survey of Machine Learning Techniques in Water ResourcesEnvironmental Data Science (EDS), 2023 J. Willard C. Varadharajan X. Jia Vipin Kumar AI4TS 235 16 0 18 Aug 2023
Learning Regionalization using Accurate Spatial Cost Gradients within a Differentiable High-Resolution Hydrological Model: Application to the French Mediterranean RegionWater Resources Research (WRR), 2023 Ngo Nghi Truyen Huynh P. Garambois Franccois Colleoni B. Renard H. Roux J. Demargne M. Jay-Allemand P. Javelle 121 14 0 02 Aug 2023
Probing the limit of hydrologic predictability with the Transformer network Jiangtao Liu Yuchen Bian Chaopeng Shen AI4TS 175 21 0 21 Jun 2023
Differentiable modeling to unify machine learning and physical models and advance Geosciences Chaopeng Shen A. Appling Pierre Gentine Toshiyuki Bandai H. Gupta ... Chris Rackauckas Tirthankar Roy Chonggang Xu Binayak Mohanty K. Lawson AI4CE 339 16 0 10 Jan 2023
Bathymetry Inversion using a Deep-Learning-Based Surrogate for Shallow Water Equations SolversWater Resources Research (WRR), 2022 Xiaofeng Liu Yalan Song Chaopeng Shen AI4CE 197 14 0 05 Mar 2022