Wang et al. (2026) Improved estimation of evapotranspiration and gross primary productivity by incorporating soil moisture feedbacks into a coupled ecosystem model

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2026
• Date: 2026-02-24
• Authors: Shuai Wang, Yingping Wang, Lu Zhang, Lei Cheng, Xuxin Lei, Chenhao Fu, Yao Lai, Shujing qin, Pan Liu
• DOI: 10.1016/j.agrformet.2026.111069

Research Groups

• State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, PR China
• CSIRO Environment, Clayton South, VIC, Australia

Short Summary

This study developed a fully coupled ecosystem model that explicitly incorporates dynamic soil moisture feedbacks to improve the consistent estimation of gross primary productivity (GPP) and evapotranspiration (ET). The model demonstrated robust performance across 32 diverse sites, significantly enhancing GPP and ET predictions, especially under dry soil conditions, compared to non-coupled approaches.

Objective

• To develop a fully coupled ecosystem model that explicitly considers interactions and feedbacks among photosynthesis, evapotranspiration, stomatal conductance, and soil moisture dynamics to improve the accuracy and consistency of GPP and ET estimations.

Study Configuration

• Spatial Scale: 32 sites across diverse terrestrial ecosystems globally.
• Temporal Scale: Long-term flux observations, with model evaluation performed at daily, monthly, and annual scales.

Methodology and Data

• Models used: A newly developed fully coupled ecosystem model that integrates photosynthesis, evapotranspiration, stomatal conductance, and soil moisture dynamics.
• Data sources: Long-term flux observations (likely eddy covariance data) collected from 32 diverse sites.

Main Results

• The developed coupled model robustly reproduced daily GPP and ET across all evaluated sites.
• Water use efficiency (WUE) validation showed strong performance with an R² of 0.51 at monthly scales and 0.79 at annual scales.
• Incorporating dynamic soil moisture feedbacks substantially improved model performance:
  • Nash-Sutcliffe efficiency (NSE) for GPP increased from 0.56 ± 0.39 to 0.64 ± 0.24.
  • NSE for ET increased from 0.41 ± 0.71 to 0.65 ± 0.22.
• Performance improvements were particularly notable under dry soil moisture conditions (normalized soil water content < 0.3).

Contributions

• Developed a novel, fully coupled ecosystem model that explicitly integrates dynamic soil moisture feedbacks with photosynthesis, evapotranspiration, and stomatal conductance, addressing a critical gap in existing models.
• Demonstrated the significant importance of incorporating time-varying soil moisture feedbacks for accurate modeling of terrestrial carbon and water fluxes.
• Provides a robust framework for assessing ecosystem responses to drought and climate variability, enhancing understanding for water resource and carbon management under climate change.

Funding

Not specified in the provided text.

Citation

@article{Wang2026Improved,
  author = {Wang, Shuai and Wang, Yingping and Zhang, Lu and Cheng, Lei and Lei, Xuxin and Fu, Chenhao and Lai, Yao and qin, Shujing and Liu, Pan},
  title = {Improved estimation of evapotranspiration and gross primary productivity by incorporating soil moisture feedbacks into a coupled ecosystem model},
  journal = {Agricultural and Forest Meteorology},
  year = {2026},
  doi = {10.1016/j.agrformet.2026.111069},
  url = {https://doi.org/10.1016/j.agrformet.2026.111069}
}

Generated by BiblioAssistant using gemini-2.5-flash (Google API)