ASSIMILATION OF FIELD MEASURED LAI INTO CROP GROWTH MODEL BASED ON SCE-UA OPTIMIZATION ALGORITHM

文献类型： 外文期刊

第一作者： Ren, Jianqiang

作者： Ren, Jianqiang;Yu, Fushui;Chen, Zhongxin;Ren, Jianqiang;Yu, Fushui;Chen, Zhongxin;Du, Yunyan;Qin, Jun

作者机构：

关键词： Crop growth model;EPIC;Data assimilation;Optimization algorithm;LAI;Yield estimation

期刊名称：2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5

ISSN： 2153-6996

年卷期： 2009 年

页码：

收录情况： SCI

摘要： Assimilating external data into crop growth model to Improve accuracy of crop growth monitoring and yield estimation has been being a research focus in recent years In this paper, the shuffled complex evolution (SCE-UA) global optimization algorithm was used to assimilate field measured LAI into EPIC model to simulate yield, sowing date and nitrogen fertilizer application amount of summer maize in Huanghuaihai Plain in China. The results showed that RMSE between simulated yield and field measured yield of summer maize was 0.84 t ha(-1) and the R-2 was only 0 033 without external data assimilation. While the performances of EPIC model of simulating yield, sowing date and nitrogen fertilizer application amount of summer maize was better through assimilating field measured LAI into the EPIC model. The RMSE of between simulated yield and field measured yield of summer maize was 0.60 t ha(-1) and the R-2 was 0.5301. The relative error between simulated sowing date and real sowing date of summer maize was 2 28% On the simulation of nitrogen fertilizer application rate, the relative error was -6 00% compared with local statistical data These above accuracy could meet the need of crop growth monitoring and yield estimation at regional scale. It proved that assimilating field measured LAI Into crop growth model based on SCE-UA optimization algorithm to monitor crop growth and estimate crop yield was feasible

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