Spatiotemporally optimize water-nitrogen management of crop planting in response to carbon emissions mitigation

Abstract

Greenhouse gas emissions from irrigation and nitrogen fertilizer applications in agriculture are attracting increasing attention, and the development of low-carbon agriculture has become an inevitable trend in the implementation of carbon neutrality. However, the optimization of water and nitrogen in crop planting still lacks precise management at the grid scale. From the perspective of agricultural carbon emission reduction, this study proposes a precise regional water and nitrogen management approach that can optimize irrigation and nitrogen fertilizer application in space and time. In this study, a coupled crop water-nitrogen production function model was constructed by analyzing the response relationship between nitrogen and water on crop yield. The verification results showed that the model had superior fitting accuracy, with R2 and NRMSE values of 0.88, 10.50%, 0.8 and 7.76% for maize and wheat, respectively. After combining the water-nitrogen coupling function with the cellular automaton model, a spatiotemporal optimization model was developed to realize grid-scale regional water and nitrogen management. The case study showed that the optimized irrigation and nitrogen scheme could save 2.73% of agricultural water, decrease nitrogen fertilizer use by 9.69%, and reduce carbon emissions by 4.39%. 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” to carbon neutrality, water saving, and nitrogen reduction should be considered in low-carbon agricultural development, which is conducive to the green and sustainable development of agriculture.