Simulation and Optimization of Double-Season Rice Yield in Jiangxi Province Based on High-Accuracy Surface Modeling–Agricultural Production Systems sIMulator Model

The accurate estimation of double-season rice yield is critical for ensuring national food security. To address the limitations of traditional crop models in spatial resolution and accuracy, this study innovatively developed the HASM-APSIM coupled model by integrating High-Accuracy Surface Modeling (HASM) with the Agricultural Production Systems sIMulator (APSIM) to simulate the historical yield of double-season rice in Jiangxi Province from 2000 to 2018. The methodological advancements included the following: the localized parameter optimization of APSIM using the Nelder–Mead simplex algorithm and NSGA-II multi-objective genetic algorithm to adapt to regional rice varieties, enhancing model robustness; coarse-resolution yield simulations (10 km grids) driven by meteorological, soil, and management data; and high-resolution refinement (1 km grids) via HASM, which fused APSIM outputs with station-observed yields as optimization constraints, resolving the trade-off between accuracy and spatial granularity. The results showed that the following: (1) Compared to the APSIM model, the HASM-APSIM model demonstrated higher accuracy and reliability in simulating historical yields of double-season rice. For early rice, the R-value increased by 14.67% (0.75→0.86), RMSE decreased by 34.02% (838.50→553.21 kg/hm2), MAE decreased by 31.43% (670.92→460.03 kg/hm2), and MAPE dropped from 11.03% to 7.65%. For late rice, the R-value improved by 27.42% (0.62→0.79), RMSE decreased by 36.75% (959.0→606.58 kg/hm2), MAE reduced by 26.37% (718.05→528.72 kg/hm2), and MAPE declined from 11.05% to 8.08%. (2) Significant spatiotemporal variations in double-season rice yields were observed in Jiangxi Province. Temporally, the simulated yields of early and late rice aligned with statistical yields in terms of numerical distribution and interannual trends, but simulated yields exhibited greater fluctuations. Spatially, high-yield zones for early rice were concentrated in the eastern and central regions, while late rice high-yield areas were predominantly distributed around Poyang Lake. The 1 km resolution outputs enabled the precise identification of yield heterogeneity, supporting targeted agricultural interventions. (3) The growth rate of double-season rice yield is slowing down. To safeguard food security, the study area needs to boost the development of high-yield and high-quality crop varieties and adopt region-specific strategies. The model proposed in this study offers a novel approach for simulating crop yield at the regional scale. The findings provide a scientific basis for agricultural production planning and decision-making in Jiangxi Province and help promote the sustainable development of the double-season rice industry.