Articles | Volume 24, issue 7
https://doi.org/10.5194/hess-24-3775-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-3775-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jul 2020
Research article |
| 24 Jul 2020
| 24 Jul 2020
The influence of assimilating leaf area index in a land surface model on global water fluxes and storages
Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, USA
Viviana Maggioni
Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, USA
Azbina Rahman
Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, USA
Paul Houser
Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, USA
Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, USA
Timothy Sauer
Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, USA
Sujay Kumar
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD 20771, USA
David Mocko
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD 20771, USA
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Cited
13 citations as recorded by crossref.
- The joint assimilation of satellite observed LAI and soil moisture for the global root zone soil moisture production and its impact on land surface and ecosystem variables Y. Xu et al. https://doi.org/10.1016/j.agrformet.2024.110299
- A synthetic experiment to investigate the potential of assimilating LAI through direct insertion in a land surface model A. Rahman et al. https://doi.org/10.1016/j.hydroa.2020.100063
- A systematic review of the NASA Land Information System (LIS): Two decades of advancements in hydrological modeling, data assimilation, and operational earth system applications S. Marshall et al. https://doi.org/10.1016/j.jhydrol.2025.134784
- Improving Surface Property Retrievals in Boreal Seasonal Snowpacks Through Multiscale Modeling of Subgrid Reflectance S. Singh & A. Barros https://doi.org/10.1109/JSTARS.2026.3667435
- Spatiotemporal prediction and attribution of groundwater storage anomaly using enhanced hybrid deep learning modeling with uncertainty quantification J. Yin et al. https://doi.org/10.1016/j.jenvman.2026.128766
- Leaf area index and soil water content responses to pre-commercial thinning in Norway spruce plantations under climate change J. Černý et al. https://doi.org/10.17221/79/2025-JFS
- Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. https://doi.org/10.3389/frwa.2021.789352
- Improving Dynamic Vegetation Modeling in Noah‐MP by Parameter Optimization and Data Assimilation Over China's Loess Plateau Z. Shu et al. https://doi.org/10.1029/2022JD036703
- The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model A. Rahman et al. https://doi.org/10.3390/rs14030437
- Assimilation of Remotely Sensed Leaf Area Index for Improving Land Surface Simulation Performance at a Global Scale X. Ling et al. https://doi.org/10.1109/JSTARS.2024.3388006
- Long-term Simulation of Gross Primary Productivity and its Impact Evaluation Based on a Mechanism and Data Co-Driven Model X. Zhang et al. https://doi.org/10.1007/s11269-025-04239-x
- Joint assimilation of satellite soil moisture and vegetation conditions improves estimates of gross primary production and evapotranspiration over South Asia A. Chakraborty & M. Saharia https://doi.org/10.1016/j.agrformet.2025.110765
- Characterizing Hydrologic Vulnerability under Nonstationary Climate and Antecedent Conditions Using a Process-Informed Stochastic Weather Generator S. Rahat et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001557
13 citations as recorded by crossref.
- The joint assimilation of satellite observed LAI and soil moisture for the global root zone soil moisture production and its impact on land surface and ecosystem variables Y. Xu et al. https://doi.org/10.1016/j.agrformet.2024.110299
- A synthetic experiment to investigate the potential of assimilating LAI through direct insertion in a land surface model A. Rahman et al. https://doi.org/10.1016/j.hydroa.2020.100063
- A systematic review of the NASA Land Information System (LIS): Two decades of advancements in hydrological modeling, data assimilation, and operational earth system applications S. Marshall et al. https://doi.org/10.1016/j.jhydrol.2025.134784
- Improving Surface Property Retrievals in Boreal Seasonal Snowpacks Through Multiscale Modeling of Subgrid Reflectance S. Singh & A. Barros https://doi.org/10.1109/JSTARS.2026.3667435
- Spatiotemporal prediction and attribution of groundwater storage anomaly using enhanced hybrid deep learning modeling with uncertainty quantification J. Yin et al. https://doi.org/10.1016/j.jenvman.2026.128766
- Leaf area index and soil water content responses to pre-commercial thinning in Norway spruce plantations under climate change J. Černý et al. https://doi.org/10.17221/79/2025-JFS
- Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. https://doi.org/10.3389/frwa.2021.789352
- Improving Dynamic Vegetation Modeling in Noah‐MP by Parameter Optimization and Data Assimilation Over China's Loess Plateau Z. Shu et al. https://doi.org/10.1029/2022JD036703
- The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model A. Rahman et al. https://doi.org/10.3390/rs14030437
- Assimilation of Remotely Sensed Leaf Area Index for Improving Land Surface Simulation Performance at a Global Scale X. Ling et al. https://doi.org/10.1109/JSTARS.2024.3388006
- Long-term Simulation of Gross Primary Productivity and its Impact Evaluation Based on a Mechanism and Data Co-Driven Model X. Zhang et al. https://doi.org/10.1007/s11269-025-04239-x
- Joint assimilation of satellite soil moisture and vegetation conditions improves estimates of gross primary production and evapotranspiration over South Asia A. Chakraborty & M. Saharia https://doi.org/10.1016/j.agrformet.2025.110765
- Characterizing Hydrologic Vulnerability under Nonstationary Climate and Antecedent Conditions Using a Process-Informed Stochastic Weather Generator S. Rahat et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001557
Saved (final revised paper)
Latest update: 01 Jun 2026
Short summary
This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.
This study assesses the extent to which a land surface model can be optimized via the...
