Liu et al. (2026) Optimized Decision Model for Soil-Moisture Control Lower Limits and Evapotranspiration-Based Irrigation Replenishment Ratios Based on AquaCrop-OSPy, PyFAO56, and NSGA-II and Its Application

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Identification

• Journal: Agriculture
• Year: 2026
• Date: 2026-04-04
• Authors: Xu Liu, Zhaolong Liu, Wenhui Tang, Zhichao An, Jun Liang, Yanling Chen, Yuxin Miao, Hainie Zha, Krzysztof Kuśnierek
• DOI: 10.3390/agriculture16070806

Research Groups

Research conducted at a field site in Laoling City, Shandong Province, China.

Short Summary

This study developed a multi-objective simulation optimization framework integrating crop and irrigation models with an evolutionary algorithm to optimize winter wheat irrigation strategies for maximizing yield and minimizing water input. The framework identified Pareto-optimal strategies and an optimal two-irrigation scheme for a specific wet growing season in the North China Plain.

Objective

• To develop and apply a multi-objective simulation optimization framework to jointly optimize soil moisture lower control limits (irrigation trigger thresholds) and evapotranspiration-based irrigation replenishment ratios across key winter wheat growth stages.

Study Configuration

• Spatial Scale: Single field site in Laoling City, Shandong Province, China.
• Temporal Scale: 2024–2025 winter wheat growing season (one wet season).

Methodology and Data

• Models used: AquaCrop-OSPy crop model, PyFAO56 soil moisture balance and irrigation scheduling model, NSGA-II evolutionary optimization algorithm.
• Data sources: Field experiment measurements (canopy cover, aboveground biomass, grain yield, and soil moisture content in the 0–0.60 m soil layer) from Laoling City, Shandong Province, China, under subsurface sprinkler and shallow subsurface drip irrigation treatments.

Main Results

• The AquaCrop-OSPy model showed good agreement with observations for canopy cover and grain yield (coefficient of determination, R², 0.87–0.94; normalized root mean square error, NRMSE, 2.24–3.75%; root mean square error, RMSE, 0.029–0.054 kg·m⁻² for grain yield).
• For aboveground biomass, R² was 0.99, with RMSE ranging from 0.102 to 0.111 kg·m⁻² and NRMSE from 14.25% to 15.49%.
• The PyFAO56 model simulated root-zone soil moisture dynamics with satisfactory accuracy (R² of 0.86 and RMSE of 5%).
• Multi-objective optimization generated 23 Pareto-optimal irrigation strategies, with irrigation volumes ranging from 0.051 to 0.128 m, corresponding yields from 0.98 to 1.08 kg·m⁻², and irrigation water use efficiency (IWUE) from 8 to 19 kg·m⁻³.
• Correlation analysis indicated that lower soil moisture control limits during the regreening–jointing stage and higher limits during the flowering–maturity stage were key for high yields and IWUE.
• An optimal irrigation scheme, identified by the Entropy-Weighted Ranked Minimum Distance method, involved two irrigations (one at the end of the jointing stage and another at the beginning of the grain filling stage) with a total depth of 0.075 m, achieving a simulated yield of 1.04 kg·m⁻² and an IWUE of 16 kg·m⁻³.

Contributions

• Development of a flexible, process-based AquaCrop-PyFAO56-NSGA-II framework for jointly optimizing stage-specific irrigation control thresholds and evapotranspiration-based replenishment ratios for winter wheat.
• Identification of a set of Pareto-optimal irrigation strategies that balance grain yield maximization and irrigation water minimization for winter wheat in the North China Plain.
• Provided a proof-of-concept evaluation of the framework's utility in a well-instrumented single-site field setting, identifying an optimal two-irrigation strategy for the monitored wet season conditions.

Funding

Not specified in the provided text.

Citation

@article{Liu2026Optimized,
  author = {Liu, Xu and Liu, Zhaolong and Tang, Wenhui and An, Zhichao and Liang, Jun and Chen, Yanling and Miao, Yuxin and Zha, Hainie and Kuśnierek, Krzysztof},
  title = {Optimized Decision Model for Soil-Moisture Control Lower Limits and Evapotranspiration-Based Irrigation Replenishment Ratios Based on AquaCrop-OSPy, PyFAO56, and NSGA-II and Its Application},
  journal = {Agriculture},
  year = {2026},
  doi = {10.3390/agriculture16070806},
  url = {https://doi.org/10.3390/agriculture16070806}
}