Optimizing water allocation in irrigation districts for enhanced sustainability and climate resilience.

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🔬研究者:Demonstrates an integrated optimization approach for water-carbon-yield tradeoffs in agriculture using crop models and ML.

🏢実務担当者:Quantifies potential savings in water use and GHG emissions from coordinated irrigation allocation, useful for farm management and sustainability reporting.

🏛政策担当者:Provides evidence for national water and carbon reduction targets in agriculture sector.

INTRODUCTION Irrigation plays a crucial role in enhancing agricultural productivity. However, it simultaneously increases water consumption and greenhouse gas (GHG) emissions, a challenge that is further exacerbated by climate change. While many irrigation strategies have been proposed, their potential to balance crop yield growth, water productivity improvement and carbon emission reduction in large-scale irrigation districts remains unclear. OBJECTIVES This study aims to establish a decision-relevant, scalable basis for climate-resilient irrigation management by testing whether coordinated irrigation allocation across large irrigation districts can jointly sustain food production while improving water-use efficiency and reducing GHG emissions under climate change. An integrated optimization perspective is used to delineate the achievable potential and limits of irrigation allocation for aligning food security with water conservation and carbon-neutrality goals. METHODS In this study, the DSSAT crop model was used to simulate the biophysical response of main crops under irrigation and climate conditions, and water production function was extracted from random forest to realize rapid prediction. Then, the Pareto optimal irrigation strategy among grain yield, water productivity and greenhouse gas emission reduction was identified by NSGA-II, and it was calibrated and verified under the data of typical irrigation areas. RESULTS Using an integrated framework, we show that irrigation optimization increases irrigation water productivity by 11.84%, while reducing water use by 8.6% and GHG emissions by 45.3%. Under climate change scenarios, optimized allocation decreases irrigation volume by 6.9-9.3%, with crop yields rising in two-thirds of scenarios, reaching gains of up to 31.3%. Nationwide, crop water productivity is projected to rise by 0.68%-18.55%, accompanied by a reduction in GHG emissions of 7.49%-32.90%. These results demonstrate that coordinated irrigation optimization can effectively decouple agricultural production from water consumption and carbon emissions, highlighting its potential as a robust and scalable strategy for safeguarding food security while advancing agricultural sustainability and carbon-neutrality objectives.

• semanticscholar https://doi.org/10.1016/j.jare.2026.01.055first seen 2026-07-15 05:53:52