Zhang et al. (2025) Incorporating water and temperature factors enhanced the performance of the stomatal conductance model for soybeans cultivated under plastic film mulching with drip irrigation in the northeast black soil region

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-12-03
• Authors: Chunhui Zhang, Tianxiao Li, Qiang Fu, Renjie Hou, Mo Li, Dong Liu, Fanying Kong, Mingxuan Liu
• DOI: 10.1016/j.agwat.2025.110028

Research Groups

• School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
• Joint Laboratory for International Cooperation on Cold Region Black Soil Habitat Health of the Ministry of Education, Harbin, Heilongjiang 150030, China
• Key Laboratory of Effective Utilization of Agricultural Water Resources of the Ministry of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
• Heilongjiang Provincial Key Laboratory of Water Resources and Water Conservancy Engineering in Cold Region, Northeast Agricultural University, Harbin, Heilongjiang 150030, China

Short Summary

This study aimed to enhance stomatal conductance model performance for soybeans under plastic film mulching with drip irrigation (PFMDI) in northeast China by incorporating water response (f(θ)) and leaf-air temperature difference (ΔT) factors. The corrected Unified Stomatal Optimization (USO) model, particularly with the f(θ) factor, demonstrated significantly improved accuracy and applicability across diverse hydrothermal conditions.

Objective

• To simulate the stomatal conductance of soybean under diverse PFMDI conditions in black soil regions using the Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL), and Unified Stomatal Optimization (USO) models.
• To evaluate the simulation performance of each model after incorporating the water response function (f(θ)) and leaf-air temperature difference (ΔT) factors.
• To investigate the differences in the applicability of each model under different PFMDI conditions.

Study Configuration

• Spatial Scale: Field experiment conducted at the Acheng Experimental Base of Northeast Agricultural University in Harbin, Heilongjiang Province, China (127°05′E, 45°23′N). The experimental field consisted of 5 m × 8 m plots.
• Temporal Scale: Soybean growing season from May to September 2024 (120–130 days maturity period). Soil water content measurements were taken on 10 dates from July to September 2024. Leaf gas exchange measurements were conducted on clear days between 9:00 and 11:00 AM.

Methodology and Data

• Models used:
  • Ball-Woodrow-Berry (BWB) model
  • Ball-Berry-Leuning (BBL) model
  • Unified Stomatal Optimization (USO) model
  • Modified versions of BWB, BBL, and USO incorporating:
    • Water response function (f(θ))
    • Leaf-air temperature difference (ΔT) factor
    • Combined f(θ) and ΔT factors
• Data sources:
  • Soil water content: Spiral drill and 100 cm³ ring knives, determined by oven-drying method.
  • Leaf gas exchange parameters (net photosynthetic rate, stomatal conductance): Portable photosynthesis measurement system (Li-6400, LI-COR Inc., Lincoln, USA).
  • Irrigation regulation: DLS-type tensiometers installed at 20 cm depth.
  • Meteorological data: Cold Region Black Soil Data Integration and Comprehensive Analysis Platform at the experimental base.
  • Soil physicochemical properties: Laboratory analysis of samples from 0–60 cm depth.

Main Results

• The USO model exhibited superior performance in simulating stomatal conductance (gsw), followed by the BBL and BWB models.
• The water response function (f(θ)) correction factor consistently outperformed the leaf-air temperature difference (ΔT) correction factor in enhancing model performance.
• Corrected BWB, BBL, and USO models showed significant improvements in simulation accuracy:
  • Coefficient of determination (R²) increased by 11.6 %-102.2 %.
  • Relative errors (RE) decreased by 7.5 %-43.2 %.
  • Root mean square errors (RMSE) decreased by 6.7 %-33.3 %.
• The dual-factor correction (f(θ) and ΔT combined) generally resulted in lower simulation accuracy compared to single-factor corrections, attributed to conflicts between the factors under substantial discrepancies in soil moisture and temperature.
• The corrected models demonstrated strong reliability and universality, with simulated curves predominantly falling within the 95 % confidence intervals of observed data across various soil relative water content (SRWC) and ΔT conditions.
• PFMDI treatments significantly improved SRWC, net photosynthetic rate (A), and gsw, while reducing ΔT, maintaining leaf temperatures within the optimal range for Rubisco enzyme activity.

Contributions

• This study innovatively integrates water response (f(θ)) and leaf-air temperature difference (ΔT) factors into classical stomatal conductance models (BWB, BBL, USO) to address their limited adaptability under complex water-heat conditions of plastic film mulching with drip irrigation (PFMDI) in the northeast black soil region.
• It establishes a theoretical foundation for the rational selection and enhancement of stomatal conductance models, improving the simulation accuracy of water and carbon cycle processes under complex hydrothermal conditions.
• The revised models provide a reliable quantitative tool for precision irrigation in China's core grain-producing region, offering actionable technical support for local soybean production practices and contributing to food security and sustainable agricultural development.

Funding

• National Natural Science Foundation of China Key Program (52539003)
• The National Natural Science Foundation of China General Program (52579033, 42577373)

Citation

@article{Zhang2025Incorporating,
  author = {Zhang, Chunhui and Li, Tianxiao and Fu, Qiang and Hou, Renjie and Li, Mo and Liu, Dong and Kong, Fanying and Liu, Mingxuan},
  title = {Incorporating water and temperature factors enhanced the performance of the stomatal conductance model for soybeans cultivated under plastic film mulching with drip irrigation in the northeast black soil region},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.110028},
  url = {https://doi.org/10.1016/j.agwat.2025.110028}
}