Pareto-front-based optimization of irrigation and nitrogen application schedule in Sandy-soil maize: Trade-offs among yield, water productivity, nitrogen physiological efficiency, and grain nitrogen concentration

Abstract

Context Developing appropriate irrigation and nitrogen application schedules (INASs) is essential for maize production on sandy soils, where low water-retention and nutrient-holding capacities make crop performance highly sensitive to within-season water and nitrogen management. However, most crop-model-based optimization studies have focused mainly on yield and resource-use efficiency, while grain nutritional quality and the economic qualifications of optimized schedules have received less attention. Objective This study aimed to develop a CERES-Maize–NSGA-III framework to optimize INASs for shallow-buried drip-irrigated maize on sandy soil, while clarifying trade-offs among yield, crop water productivity (WP c ), nitrogen physiological efficiency (PE N ), and grain nitrogen concentration (GNC), and evaluate the economic performance of selected candidate schedules through partial-budget analysis. Methods CERES-Maize was calibrated and validated using two years of field observations and then coupled with NSGA-III to optimize irrigation timing, irrigation amount, nitrogen application timing, and nitrogen rate. Pareto-optimal schedules were further evaluated through candidate-schedule selection, weather-year stress testing, and partial-budget economic sensitivity analysis. Results and conclusions CERES-Maize reproduced maize growth, yield, seasonal water use, and total nitrogen uptake with acceptable accuracy. The Pareto front revealed clear trade-offs among yield, WP c , PE N , and GNC. The 16 high-yield (HY) candidates selected using the historical farmer-yield benchmark exceeded the corresponding weather-matched farmer yield in all five annual simulations and maintained positive ΔPNR across all tested price–cost combinations. Among these candidates, HY01 showed the strongest combined yield and partial-budget performance, with the highest five-year mean simulated yield (12,003.2 kg/ha) and the highest mean ΔPNR relative to the corresponding farmer-managed schedules (1307.83 yuan/ha) across the tested weather-year and price–cost combinations. In contrast, the distance-to-utopia compromise schedule produced lower yield than the corresponding farmer-managed schedule in each weather year and showed weather- and price–cost-dependent economic performance. Significance The proposed framework provides a biophysical optimization tool for generating candidate INASs and clarifying trade-offs among yield, WP c , PE N , and GNC in sandy-soil maize. Weather variability was evaluated only through ex-post simulations of selected candidates and was not incorporated directly into the optimization. Further field-level, operational, economic, and environmental validation is therefore required before practical implementation.