Assimilation of MODIS-LAI into the WOFOST model for forecasting regional winter wheat yield

文献类型： 外文期刊

第一作者： Ma, Guannan

作者： Ma, Guannan;Huang, Jianxi;Wu, Wenbin;Zou, Jinqiu;Fan, Jinlong;Wu, Sijie

作者机构：

关键词： Remote sensing;Crop growth model;Sensitivity analysis;Data assimilation;Yield

期刊名称：MATHEMATICAL AND COMPUTER MODELLING （ 影响因子：1.366； 五年影响因子：1.602 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： Crop growth models have been applied successfully in forecasting crop yield at a local scale, while satellite remote sensing has the advantage of retrieving regional crop parameters. The new assimilation method of integrating the crop growth model with remote sensing has presented great potential in regional crop yield assessment. In this study, the Moderate Resolution Imaging Spectrometer (MODIS) leaf area index (LAI) data product was assimilated into the World Food Studies (WOFOST) crop growth model. Using the Extended Fourier Amplitude Sensitivity Test (EFAST) global sensitivity analysis approach, several local and regional crop parameters were identified to be recalibrated. The Shuffled Complex Evolution (SCE) optimization algorithm was used to estimate the emergence date, initial biomass and initial available soil water by minimizing the differences between the corrected MODIS-LAI and simulated LAI. Results indicated that the accuracy of water-limited crop yield was improved significantly after the assimilation. The root mean square error (RMSE) reduced from 983 kg/ha to 474 kg/ha and 667 kg/ha respectively in two different optimization schemes.

分类号： O14

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