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<p>Global climate extremes and intensifying water supply–demand imbalance have increased the uncertainty and variability of regional water availability. Conventional irrigation regimes fail to adapt to dynamic crop water requirements under real-time climate fluctuations and spatial water demand heterogeneity, limiting yield improvement and water-use efficiency. This study proposes a synergistic “simulation–optimization” framework for regional crop irrigation scheduling to coordinate yield enhancement and water conservation. The WOFOST model is calibrated using Sobol sensitivity analysis and particle swarm optimization and coupled with a multi-objective optimization model to generate dynamically adjustable irrigation strategies responding to real-time meteorological changes. Applied to the Sanjiang Plain and Songnen Plain of Heilongjiang Province (332,500 km²), the proposed method improves model accuracy, increases regional yield by 1.5% and reduces irrigation water use by 8.0% compared with traditional irrigation modes. The dynamic scheduling strategy significantly reduces water demand estimation errors, achieving 10.1% water savings compared with conventional irrigation practices. This study provides a theoretical basis and technical support for refined, dynamic water resource regulation to achieve coordinated yield increase and water conservation in regional rice production.</p>

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Dynamic regulation of grid-scale high-efficiency precision irrigation for rice under climate variability

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月21日

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  • Wenhao Dong,
  • YaoWen Xu,
  • Lili Zhangzhong,
  • Xianghui Xu,
  • Shiyu Wei,
  • Ziqiang Sun,
  • Yingshan Chen,
  • Pingan Zhang,
  • Mo Li

摘要

Global climate extremes and intensifying water supply–demand imbalance have increased the uncertainty and variability of regional water availability. Conventional irrigation regimes fail to adapt to dynamic crop water requirements under real-time climate fluctuations and spatial water demand heterogeneity, limiting yield improvement and water-use efficiency. This study proposes a synergistic “simulation–optimization” framework for regional crop irrigation scheduling to coordinate yield enhancement and water conservation. The WOFOST model is calibrated using Sobol sensitivity analysis and particle swarm optimization and coupled with a multi-objective optimization model to generate dynamically adjustable irrigation strategies responding to real-time meteorological changes. Applied to the Sanjiang Plain and Songnen Plain of Heilongjiang Province (332,500 km²), the proposed method improves model accuracy, increases regional yield by 1.5% and reduces irrigation water use by 8.0% compared with traditional irrigation modes. The dynamic scheduling strategy significantly reduces water demand estimation errors, achieving 10.1% water savings compared with conventional irrigation practices. This study provides a theoretical basis and technical support for refined, dynamic water resource regulation to achieve coordinated yield increase and water conservation in regional rice production.