Ding et al. (2025) Parameterization and irrigation optimization for foxtail millet using the aquacrop model

Identification

• Journal: Irrigation Science
• Year: 2025
• Date: 2025-12-15
• Authors: Yimin Ding, Ke Tao, Jian Jin, Zhenyuan Sun, Jia Zhang, Lei Zhu
• DOI: 10.1007/s00271-025-01067-0

Research Groups

• School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, China
• Key Laboratory of the Internet of Water and Digital Water Governance of the Yellow River, Ningxia University, Yinchuan, China
• Field Scientific Observation and Research Station for Agricultural Irrigation in Ningxia Yellow River Irrigation Area of Water Resources Ministry, Yinchuan, China
• Institute of Agricultural Resources and Environment, Ningxia Academy of Agricultural and Forestry Sciences, Yinchuan, China

Short Summary

This study establishes the first comprehensive parameter set for foxtail millet in the AquaCrop model and develops optimized irrigation strategies to enhance water use efficiency in water-limited regions, achieving a mean yield of 0.573 kg·m⁻² and water productivity of 1.46 kg·m⁻³ with significantly improved yield stability.

Objective

• To establish the first comprehensive AquaCrop model parameter set for foxtail millet.
• To determine precise, growth-stage-specific irrigation trigger thresholds for foxtail millet through simulation studies based on the validated model.
• To develop optimized irrigation strategies to enhance water use efficiency and support climate-resilient millet production in water-limited regions.

Study Configuration

• Spatial Scale: Field experiments conducted in Ningxia Hui Autonomous Region, China (105.9°E, 36.98°N, elevation 1400 m), using 7 m × 7 m plots.
• Temporal Scale: Two-year (2022–2023) field experiment for model calibration and validation. Long-term simulations (20 years, 1998–2017) using historical meteorological data for irrigation optimization.

Methodology and Data

• Models used: AquaCrop-OS V2.0 (an open-source implementation of FAO AquaCrop model version 6.0). Morris method for sensitivity analysis.
• Data sources:
  • Two-year (2022–2023) deficit irrigation experiment with 9 treatments and 3 replicates.
  • Monitored farmland state variables: above-ground biomass, canopy cover (CC), soil moisture, and grain yield.
  • 20-year (1998–2017) daily meteorological data (maximum/minimum temperature, precipitation, reference evapotranspiration) from an automatic weather station.
  • Soil hydraulic properties (sandy loam).

Main Results

• The AquaCrop model accurately simulated foxtail millet growth, with biomass, canopy cover, yield, and soil water storage estimations showing R² > 0.85 and NRMSE < 10% during the validation period.
• Soil water simulations were reliable (R² ranging from 0.75 to 0.97), though slight underestimations occurred under extreme drought conditions.
• Optimal irrigation trigger thresholds were identified as 0%, 60%, 15%, and 0% of total available water (TAW) depletion for the emergence, expansion, maturity, and senescence growth stages, respectively.
• This optimal strategy achieved a mean yield of 0.573 kg·m⁻² (5.73 t·ha⁻¹) and water productivity (WP) of 1.46 kg·m⁻³.
• The strategy significantly enhanced interannual yield stability, reducing the coefficient of variation (CV) from 23.33% (rainfed) to 5.77%.
• The multi-year average net irrigation water requirement (NIR) for the optimal strategy was only 69 mm.

Contributions

• Provides the first comprehensive and validated AquaCrop model parameter set specifically for foxtail millet.
• Introduces a novel threshold-triggered, growth-stage-specific irrigation strategy that dynamically adapts to soil moisture status.
• Offers a scalable and scientifically grounded solution for precision water management in arid regions, balancing yield and water productivity.
• Significantly improves yield stability for foxtail millet under varying climatic conditions, supporting climate-resilient production.

Funding

• National Natural Science Foundation of China (52209059)
• Ningxia Natural Science Foundation (2023AAC05013)
• The University First-class Discipline Construction Project of Ningxia, China (No. NXYLXK2021A03)

Citation

@article{Ding2025Parameterization,
  author = {Ding, Yimin and Tao, Ke and Jin, Jian and Sun, Zhenyuan and Zhang, Jia and Zhu, Lei},
  title = {Parameterization and irrigation optimization for foxtail millet using the aquacrop model},
  journal = {Irrigation Science},
  year = {2025},
  doi = {10.1007/s00271-025-01067-0},
  url = {https://doi.org/10.1007/s00271-025-01067-0}
}