Spatiotemporal Optimization Management of Water-Nitrogen for Carbon Emissions Mitigation

The escalation in carbon emissions caused by agricultural production has attracted increasing attention, irrigation and nitrogen fertilization are the two main sources of carbon emissions. Under the influence of global warming and water shortage, the development of low-carbon agriculture has grown up to be an inevitable trend. From the perspective of agricultural carbon emission reduction, this study proposes regional water and nitrogen precise management approach that can optimize irrigation and nitrogen fertilizer application in space and time. In this study, proceeding from the point-scale water-nitrogen coupling experiment, by analyzing the response relationship between nitrogen and water on crop yield, a regional crop water-nitrogen coupled production function model was constructed. The verification results show that the model has superior fitting accuracy for corn and wheat. R 2 and NRMSE were 0.88, 0.8 and 10.50%, 7.76%, respectively. Then a spatiotemporal optimization model was built to realize the grid-scale regional water and nitrogen management after being combined with the cellular automaton model. The case study shows that the optimized irrigation and nitrogen scheme can save 2.73% of agricultural water, decrease nitrogen fertilizer by 9.69% and reduce crop carbon emission by 4.39%, and the correlation analysis of irrigation and fertilization can provide accurate guidance for regional irrigation and fertilization systems. Therefore, considering the contribution of agricultural "carbon reduction sources" for carbon neutrality, water-saving and nitrogen-reducing should be paid attention to in low-carbon agricultural development, which is conducive to the green and sustainable development of agriculture.