| Comparison of physical-based, data-driven and hybrid modeling approaches for evapotranspiration estimation X Hu, L Shi, G Lin, L Lin Journal of Hydrology 601, 126592, 2021 | 93 | 2021 |
| Estimation of actual irrigation amount and its impact on groundwater depletion: A case study in the Hebei Plain, China X Hu, L Shi, J Zeng, J Yang, Y Zha, Y Yao, G Cao Journal of Hydrology 543, 433-449, 2016 | 55 | 2016 |
| Improving surface roughness lengths estimation using machine learning algorithms X Hu, L Shi, L Lin, V Magliulo Agricultural and Forest Meteorology 287, 107956, 2020 | 31 | 2020 |
| Impacts of a revised surface roughness parameterization in the Community Land Model 5.1 R Meier, EL Davin, GB Bonan, DM Lawrence, X Hu, G Duveiller, C Prigent, ... Geoscientific Model Development 15 (6), 2365-2393, 2022 | 24 | 2022 |
| Optical-based and thermal-based surface conductance and actual evapotranspiration estimation, an evaluation study in the North China Plain X Hu, L Shi, L Lin, B Zhang, Y Zha Agricultural and Forest Meteorology 263, 449-464, 2018 | 24 | 2018 |
| A comprehensive study of deep learning for soil moisture prediction Y Wang, L Shi, Y Hu, X Hu, W Song, L Wang Hydrology and Earth System Sciences Discussions 2023, 1-38, 2023 | 21 | 2023 |
| Enhancing streamflow estimation by integrating a data-driven evapotranspiration submodel into process-based hydrological models X Lian, X Hu, J Bian, L Shi, L Lin, Y Cui Journal of Hydrology 621, 129603, 2023 | 20 | 2023 |
| Multiphysics‐informed neural networks for coupled soil hydrothermal modeling Y Wang, L Shi, X Hu, W Song, L Wang Water Resources Research 59 (1), e2022WR031960, 2023 | 20 | 2023 |
| Nonlinear boundaries of land surface temperature–vegetation index space to estimate water deficit index and evaporation fraction X Hu, L Shi, L Lin, Y Zha Agricultural and Forest Meteorology 279, 107736, 2019 | 20 | 2019 |
| The data-driven solution of energy imbalance-induced structural error in evapotranspiration models X Hu, L Shi, G Lin Journal of Hydrology 597, 126205, 2021 | 12 | 2021 |
| Data‐driven discovery of soil moisture flow governing equation: A sparse regression framework W Song, L Shi, L Wang, Y Wang, X Hu Water Resources Research 58 (8), e2022WR031926, 2022 | 11 | 2022 |
| Estimation of photosynthetic parameters from hyperspectral images using optimal deep learning architecture X Deng, Z Zhang, X Hu, J Li, S Li, C Su, S Du, L Shi Computers and Electronics in Agriculture 216, 108540, 2024 | 9 | 2024 |
| Reconstructing the Unsaturated Flow Equation From Sparse and Noisy Data: Leveraging the Synergy of Group Sparsity and Physics‐Informed Deep Learning W Song, L Shi, X Hu, Y Wang, L Wang Water Resources Research 59 (5), e2022WR034122, 2023 | 6 | 2023 |
| Parameter variability across different timescales in the energy balance-based model and its effect on evapotranspiration estimation X Hu, L Shi, X Lian, J Bian Science of the Total Environment 871, 161919, 2023 | 4 | 2023 |
| Physics-constrained Gaussian process regression for soil moisture dynamics L He, Q Zhang, L Shi, Y Wang, L Wang, X Hu, Y Zha, K Huang Journal of Hydrology 616, 128779, 2023 | 4 | 2023 |
| Evapotranspiration partitioning by integrating eddy covariance, micro-lysimeter and unmanned aerial vehicle observations: a case study in the North China Plain J Bian, X Hu, L Shi, L Min, Y Zhang, Y Shen, F Zhao, Y Zha, X Lian, ... Agricultural Water Management 295, 108735, 2024 | 3 | 2024 |
| Towards data-driven discovery of governing equations in geosciences W Song, S Jiang, G Camps-Valls, M Williams, L Zhang, M Reichstein, ... Communications Earth & Environment 5 (1), 589, 2024 | 2 | 2024 |
| A novel hybrid modelling framework for GPP estimation: Integrating a multispectral surface reflectance based Vcmax25 simulator into the process-based model X Hu, L Shi, L Lin, S Li, X Deng, L Li, J Bian, X Lian Science of The Total Environment 921, 171182, 2024 | 2 | 2024 |
| Synergizing Intuitive Physics and Big Data in Deep Learning: Can We Obtain Process Insights While Maintaining State‐Of‐The‐Art Hydrological Prediction Capability? L He, L Shi, W Song, J Shen, L Wang, X Hu, Y Zha Water Resources Research 60 (12), e2024WR037582, 2024 | 1 | 2024 |
| Self-correcting deep learning for estimating rice leaf nitrogen concentration with mobile phone images J Li, L Shi, X Mo, X Hu, C Su, J Han, X Deng, S Du, S Li Computers and Electronics in Agriculture 227, 109497, 2024 | 1 | 2024 |
