Dynamic multi-objective optimization of rice irrigation integrating crop growth and water cycle dynamics: Promoting synergies in water conservation, production enhancement, and emission reduction

Abstract

An optimized rice irrigation system is critical not only for conserving water resources and ensuring global food security, but also for mitigating environmental pollution caused by inefficient water use and excessive carbon emissions. This study, conducted in the Changgang Irrigation District of Lanxi County, integrates daily rice physiological growth data and meteorological parameters with the EPIC crop growth model, the crop photosynthetic production model, and hydrological cycle dynamics. A multi-objective optimization and regulation model is formulated to achieve synergistic goals of water conservation, emission reduction, and production enhancement through dynamic irrigation control. Results demonstrate that the optimized strategy reduces water use by 12.56 %, improves water use efficiency by 2.11 %, increases yield by 3.05 %, and decreases the carbon footprint by 7.80 % compared to the current irrigation scenario. Incorporating CMIP6 climate change scenario models into the optimization framework further reveals that the irrigation requirement is lowest under the SSP126–2023–2030 scenario and highest under the SSP126–2031–2040 scenario. Future climate warming accelerates rice maturation and shortens the growing period, increasing irrigation demand in June and July while reducing it in August. This study provides a scientific basis for optimizing irrigation schedules under changing climatic conditions, addressing challenges of water scarcity, emissions, and productivity. The findings offer practical decision-making tools to achieve sustainable agricultural water management and enhance rice production efficiency.