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A Study on Dynamic Forecast Technique of Regional Rice Productivity

机译：区域水稻生产力动态预测技术研究

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摘要

Dynamic forecast of crop productivity is critical for food security and decision-making of agriculture manager. Based on the Rice Cultivational Simulation-Optimization and Decision-making System (RCSODS) and aggregation methods on the model inputs, and combined normal year meteorological data and spatial interpolation technique of weather data, the dynamic forecast technique of regional rice productivity was discussed in this study. The model and the aggregation methods were validated with the experimental data from eight National agro meteorological stations located in Jiangsu province and statistical yields. Rice productivity of Jiangsu was forecasted dynamically with observed meteorological data and normal year weather data generated from the monthly meteorological data. The results showed the RMSEs of development stages and yields between simulated and observed values were 5.0 d and 1344kg/ha and the NRMSEs were 1.6% and 16.7% respectively, which indicated RCSODS could simulate the rice development process better and yield well. The RMSE and NRMSE between simulated and statistical county yields were 1081kg/ha and 13.2%, which showed the aggregation method on the meteorological data, soil attributes, variety and cultural method in county level was suitable to the regional application of rice model. The forecast yield would generally be equal to simulated yield with the delay of forecast time.
机译：作物生产力的动态预测对于粮食安全和农业管理者的决策至关重要。在水稻栽培模拟优化决策系统（RCSODS）和模型输入汇总方法的基础上，结合常年气象数据和气象数据的空间插值技术，探讨了水稻区域生产力动态预测技术。学习。利用江苏省八个国家农业气象站的实验数据和统计产量，对模型和聚合方法进行了验证。利用观测的气象数据和由每月气象数据产生的常年天气数据，动态预测了江苏省的水稻产量。结果表明，RCSODS可以更好地模拟水稻的发育过程，且产量高，模拟值与实测值之间的RMSE分别为5.0 d和1344kg / ha，NRMSE分别为1.6％和16.7％。模拟和统计县级产量之间的RMSE和NRMSE分别为1081kg / ha和13.2％，这表明县级气象数据，土壤属性，品种和养殖方法的聚合方法适合于水稻模型的区域应用。随着预测时间的延迟，预测产量通常将等于模拟产量。

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