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Updated: Sep 9, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Synergizing rice productivity sustainability through an integrated water-nitrogen management strategy based on
Zhilin Xiao1, Ying Zhang1, Yu Yan1
1Jiangsu Key Laboratory of Crop Genetics and Physiology / Jiangsu Key Laboratory of Crop Cultivation and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, Jiangsu, 225009, China.
Abstract:
Despite advances in rice water and nitrogen (N) management, previous studies still fail to quantitatively balance economic benefit and environmental cost on the basis of high yield, and lack robust N diagnostic thresholds for rice production. In a three-year field experiment, treatments comprised two irrigation regimes, conventional irrigation (CI) and alternate wetting and drying (AWD), and four N rates (0, 180, 270, and 360 kg N ha-1). Results suggest that AWD significantly outperformed CI, enhancing grain yield (12.39%-16.02%), agronomic N efficiency (12.27%-22.30%), and economic benefits (27.36%-38.07%), while mitigating global warming potential (GWP) by 25.90%-29.59%. Distinctively, this is the first study to incorporate an inverse normalization-based trade-off model between yield, economic benefit, and GWP under AWD in the lower reaches of the Yangtze River, identifying 235.37-273.09 kg N ha-1 as the optimal N range in this region. Compared to the rate for maximum yield (311.12 kg N ha-1), this optimized N range maximized economic profitability and N use efficiency while reducing GWP, with a negligible yield penalty of only 0.60%-2.38%. Furthermore, we establish quantitative diagnostic thresholds for dry matter and N accumulation at key growth stages, providing a robust tool for in-season N management in this region. Unlike traditional leaf color diagnostics, these thresholds are quantitative field indicators that can directly guide in-season topdressing decisions. This integrated water-N management strategy based on multi-objective optimization provides a viable pathway for the sustainable intensification of rice systems.
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