Spatial Simulation and Optimization of Cropping Structure Under Climate and Land Use Change Conditions Considering Synergistic Economic Benefits and Carbon Reduction in Crop Growth Processes

Abstract

The climate and land use changes caused by the natural environment and socioeconomic development have potential impacts on the green and sustainable development of agriculture. To accommodate agricultural production under multiple scenarios of future climate and land-use change, this study proposes a “simulation–optimization” modeling approach based on a crop growth model with a synergistic “carbon emission–economic benefit” approach. This approach is based on climate change conditions and it accurately simulates future land use changes and crop growth processes, establishes a carbon emission intensity optimization model, and generates a spatial planting structure optimization and regulation scheme based on intelligent optimization algorithms under changing scenarios. The results of the model application show that the planting structure option in the future scenario can increase economic benefit by up to 14.8% compared to the current scenario while simultaneously reducing total greenhouse gas emissions by 6.77%. Correlation analysis of planting area, irrigation water volume, carbon intensity value and unilateral water use efficiency can be used to obtain the coordination level of each county under different regulation scenarios. This “simulation–optimization” modeling approach provides an effective approach to achieve synergistic and coordinated development of regional agricultural benefits and carbon reduction by fine-tuning the planting structure, which promotes low-carbon and high-quality development of regional agriculture.