Liu et al. (2025) Enhanced evapotranspiration prediction by incorporating plant stomatal-hydraulic co-regulation into hydrological model

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-11-20
• Authors: Yong Liu, Huandi Li, Xiang Zeng, Rui Zhu, Peiran Jing, Qifan Zhang, Xiang Li, Yanxuan Wang
• DOI: 10.1016/j.jhydrol.2025.134586

Research Groups

• State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China
• National Engineering Research Center of Eco-Environment in the Yangtze River Economic Belt, China Three Gorges Corporation, Wuhan 430010, China
• College of Agricultural Science and Engineering, Hohai University, Nanjing 211100, China
• School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
• Pearl River Water Resources Research Institute, Pearl River Water Resources Commission of the Ministry of Water Resources, Guangzhou 510611, China

Short Summary

This study enhances hydrological predictions by integrating a plant stomatal-hydraulic co-regulation scheme into the SWAT model. The modified model significantly improves the simulation of runoff, soil moisture, and evapotranspiration, particularly during drought conditions, by accurately representing vegetation transpiration dynamics.

Objective

• To improve the representation of vegetation transpiration (ETP) in distributed hydrological models by incorporating plant hydraulic regulation and canopy conductance, thereby enhancing the accuracy of regional water cycle predictions.

Study Configuration

• Spatial Scale: Qingyang River Basin of the Shennongjia region, China.
• Temporal Scale: Not explicitly detailed in the provided text, but includes calibration and validation periods.

Methodology and Data

• Models used: Soil and Water Assessment Tool (SWAT) model, modified SWAT (M-SWAT) incorporating an improved plant hydraulics scheme coupled with a stomatal optimization model, and original SWAT (O-SWAT).
• Data sources: Not explicitly detailed in the provided text.

Main Results

• The M-SWAT model significantly outperformed the O-SWAT model in simulating runoff and soil moisture dynamics.
• M-SWAT improved the estimation of evapotranspiration by 41.16% (PBIAS).
• M-SWAT dynamically adjusts canopy conductance, reflecting the downregulation of transpiration during drought stages and preventing rapid declines in soil water content in FRSE and FRST subbasins.
• The O-SWAT model overestimates ETP during drought, leading to unrealistic rapid reductions in soil moisture and generating spurious runoff processes.
• O-SWAT's compensation for runoff bias due to vegetation transpiration and soil water content biases failed to effectively correct the bias in relatively drought years.

Contributions

• Introduction of an improved plant hydraulics scheme coupled with a stomatal optimization model into the Soil and Water Assessment Tool (SWAT) framework.
• Demonstration of the critical importance of incorporating plant hydraulics and stomatal optimization for enhancing the accuracy of the SWAT model in predicting regional water cycle processes.
• Highlighting the deficiencies of traditional hydrological models in representing plant physiological processes, particularly during drought conditions.

Funding

• Not explicitly detailed in the provided text.

Citation

@article{Liu2025Enhanced,
  author = {Liu, Yong and Hu, Tiesong and Li, Huandi and Zeng, Xiang and Zhu, Rui and Jing, Peiran and Zhang, Qifan and Li, Xiang and Wang, Yanxuan},
  title = {Enhanced evapotranspiration prediction by incorporating plant stomatal-hydraulic co-regulation into hydrological model},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134586},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134586}
}