Articles | Volume 18, issue 10
https://doi.org/10.5194/hess-18-4223-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-4223-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Oct 2014
Research article |
| 28 Oct 2014
Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India
G. M. Tsarouchi
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Grantham Institute for Climate Change, Imperial College London, London, UK
W. Buytaert
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Grantham Institute for Climate Change, Imperial College London, London, UK
Department of Civil and Environmental Engineering, Imperial College London, London, UK
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Cited
27 citations as recorded by crossref.
- Modeling crop growth and land surface energy fluxes in wheat–maize double cropping system in the North China Plain F. Liu et al. https://doi.org/10.1007/s00704-020-03353-7
- The use of a shuffled complex evolution algorithm for calibration of a dynamic leaf emergence model leads to better spatial ETa predictions M. Heuer et al. https://doi.org/10.2166/nh.2025.180
- MODIS Evapotranspiration Downscaling Using a Deep Neural Network Trained Using Landsat 8 Reflectance and Temperature Data X. Che et al. https://doi.org/10.3390/rs14225876
- Evaluation of a regional crop model implementation for sub-national yield assessments in Kenya W. Ellenburg et al. https://doi.org/10.1016/j.agsy.2023.103819
- Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration Y. Ke et al. https://doi.org/10.1016/j.isprsjprs.2017.02.006
- Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback F. Liu et al. https://doi.org/10.1007/s11442-017-1423-3
- Agricultural drought characteristics in a typical plain region considering irrigation, crop growth, and water demand impacts Y. Zhang et al. https://doi.org/10.1016/j.agwat.2023.108266
- Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches Y. Ke et al. https://doi.org/10.3390/rs8030215
- Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China J. Zou et al. https://doi.org/10.1007/s00376-018-8160-0
- Land use modelling needs to better account for multiple cropping to inform pathways for sustainable agriculture K. Waha et al. https://doi.org/10.1038/s43247-025-02724-0
- Coupled surface water-groundwater-crop model considering the impact of irrigation using different calibration targets Y. Zhang et al. https://doi.org/10.1016/j.jhydrol.2025.134556
- Progress in joint application of crop models and hydrological models Y. You et al. https://doi.org/10.1016/j.agwat.2024.108746
- Estimation of winter wheat yield by assimilating MODIS LAI and VIC optimized soil moisture into the WOFOST model J. Zhang et al. https://doi.org/10.1016/j.eja.2024.127497
- Coupling the land surface model Noah-MP with the generic crop growth model Gecros: Model description, calibration and validation J. Ingwersen et al. https://doi.org/10.1016/j.agrformet.2018.06.023
- A review of integrated crop growth and hydrological models for sustainable agriculture in the midwest: Challenges and opportunities F. Pourmansouri et al. https://doi.org/10.1016/j.agwat.2026.110368
- Cropland expansion delays vegetation spring phenology according to satellite and in-situ observations G. Zhao et al. https://doi.org/10.1016/j.agee.2023.108651
- Vegetation Growth Models Improve Surface Layer Flux Simulations of a Temperate Grassland C. Klein et al. https://doi.org/10.2136/vzj2017.03.0052
- A review of coupled hydrologic and crop growth models S. Siad et al. https://doi.org/10.1016/j.agwat.2019.105746
- Coupled hydrology-crop growth model incorporating an improved evapotranspiration module Y. Zhang et al. https://doi.org/10.1016/j.agwat.2020.106691
- An NDVI-Based Statistical ET Downscaling Method S. Tan et al. https://doi.org/10.3390/w9120995
- Implementation of a dynamic specific leaf area (SLA) into a land surface model (LSM) incorporated crop-growth model Z. Li et al. https://doi.org/10.1016/j.compag.2023.108238
- Blue and green water re-distribution dependency on precipitation datasets for a tropical Indian River basin A. Dey et al. https://doi.org/10.1016/j.ejrh.2023.101361
- Simulation of Crop Water Demand and Consumption Considering Irrigation Effects Based on Coupled Hydrology‐Crop Growth Model Y. Zhang et al. https://doi.org/10.1029/2020MS002360
- Annual evapotranspiration retrieved from satellite vegetation indices for the eastern Mediterranean at 250 m spatial resolution D. Helman et al. https://doi.org/10.5194/acp-15-12567-2015
- Relevance of feedbacks between water availability and crop systems using a coupled hydrological–crop growth model S. Chevuru et al. https://doi.org/10.5194/hess-29-4219-2025
- Diagnostic Framework for Evaluating How Parametric Uncertainty Influences Agro‐Hydrologic Model Projections of Crop Yields Under Climate Change T. Karimi et al. https://doi.org/10.1029/2021WR031249
- The benefits and trade-offs of multi-variable calibration of the WaterGAP global hydrological model (WGHM) in the Ganges and Brahmaputra basins H. Hasan et al. https://doi.org/10.5194/hess-29-567-2025
27 citations as recorded by crossref.
- Modeling crop growth and land surface energy fluxes in wheat–maize double cropping system in the North China Plain F. Liu et al. https://doi.org/10.1007/s00704-020-03353-7
- The use of a shuffled complex evolution algorithm for calibration of a dynamic leaf emergence model leads to better spatial ETa predictions M. Heuer et al. https://doi.org/10.2166/nh.2025.180
- MODIS Evapotranspiration Downscaling Using a Deep Neural Network Trained Using Landsat 8 Reflectance and Temperature Data X. Che et al. https://doi.org/10.3390/rs14225876
- Evaluation of a regional crop model implementation for sub-national yield assessments in Kenya W. Ellenburg et al. https://doi.org/10.1016/j.agsy.2023.103819
- Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration Y. Ke et al. https://doi.org/10.1016/j.isprsjprs.2017.02.006
- Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback F. Liu et al. https://doi.org/10.1007/s11442-017-1423-3
- Agricultural drought characteristics in a typical plain region considering irrigation, crop growth, and water demand impacts Y. Zhang et al. https://doi.org/10.1016/j.agwat.2023.108266
- Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches Y. Ke et al. https://doi.org/10.3390/rs8030215
- Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China J. Zou et al. https://doi.org/10.1007/s00376-018-8160-0
- Land use modelling needs to better account for multiple cropping to inform pathways for sustainable agriculture K. Waha et al. https://doi.org/10.1038/s43247-025-02724-0
- Coupled surface water-groundwater-crop model considering the impact of irrigation using different calibration targets Y. Zhang et al. https://doi.org/10.1016/j.jhydrol.2025.134556
- Progress in joint application of crop models and hydrological models Y. You et al. https://doi.org/10.1016/j.agwat.2024.108746
- Estimation of winter wheat yield by assimilating MODIS LAI and VIC optimized soil moisture into the WOFOST model J. Zhang et al. https://doi.org/10.1016/j.eja.2024.127497
- Coupling the land surface model Noah-MP with the generic crop growth model Gecros: Model description, calibration and validation J. Ingwersen et al. https://doi.org/10.1016/j.agrformet.2018.06.023
- A review of integrated crop growth and hydrological models for sustainable agriculture in the midwest: Challenges and opportunities F. Pourmansouri et al. https://doi.org/10.1016/j.agwat.2026.110368
- Cropland expansion delays vegetation spring phenology according to satellite and in-situ observations G. Zhao et al. https://doi.org/10.1016/j.agee.2023.108651
- Vegetation Growth Models Improve Surface Layer Flux Simulations of a Temperate Grassland C. Klein et al. https://doi.org/10.2136/vzj2017.03.0052
- A review of coupled hydrologic and crop growth models S. Siad et al. https://doi.org/10.1016/j.agwat.2019.105746
- Coupled hydrology-crop growth model incorporating an improved evapotranspiration module Y. Zhang et al. https://doi.org/10.1016/j.agwat.2020.106691
- An NDVI-Based Statistical ET Downscaling Method S. Tan et al. https://doi.org/10.3390/w9120995
- Implementation of a dynamic specific leaf area (SLA) into a land surface model (LSM) incorporated crop-growth model Z. Li et al. https://doi.org/10.1016/j.compag.2023.108238
- Blue and green water re-distribution dependency on precipitation datasets for a tropical Indian River basin A. Dey et al. https://doi.org/10.1016/j.ejrh.2023.101361
- Simulation of Crop Water Demand and Consumption Considering Irrigation Effects Based on Coupled Hydrology‐Crop Growth Model Y. Zhang et al. https://doi.org/10.1029/2020MS002360
- Annual evapotranspiration retrieved from satellite vegetation indices for the eastern Mediterranean at 250 m spatial resolution D. Helman et al. https://doi.org/10.5194/acp-15-12567-2015
- Relevance of feedbacks between water availability and crop systems using a coupled hydrological–crop growth model S. Chevuru et al. https://doi.org/10.5194/hess-29-4219-2025
- Diagnostic Framework for Evaluating How Parametric Uncertainty Influences Agro‐Hydrologic Model Projections of Crop Yields Under Climate Change T. Karimi et al. https://doi.org/10.1029/2021WR031249
- The benefits and trade-offs of multi-variable calibration of the WaterGAP global hydrological model (WGHM) in the Ganges and Brahmaputra basins H. Hasan et al. https://doi.org/10.5194/hess-29-567-2025
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