Estimating winter wheat yield by assimilation of remote sensing data with a four-dimensional variation algorithm considering anisotropic background error and time window

文献类型： 外文期刊

第一作者： Wu, Shangrong

作者： Wu, Shangrong;Yang, Peng;Chen, Zhongxin;Ren, Jianqiang;Sun, Liang;Li, He

作者机构：

关键词： Data assimilation; Crop yield estimation; Remotely sensed LAI; Background error; Time window; Anisotropic

期刊名称：AGRICULTURAL AND FOREST METEOROLOGY （ 影响因子：4.651； 五年影响因子：5.142 ）

ISSN： 0168-1923

年卷期： 2021 年 301 卷

页码：

收录情况： SCI

摘要： To further improve the yield estimation accuracy of regional winter wheat, based on En4DVar algorithm, an anisotropic background error and time window four-dimensional variation (ABT-4DVar) algorithm was constructed by introducing a variation time window. Based on a comparison with the simulated crop yield without data assimilation at a single point scale and in a typical test area, the effectiveness and feasibility of the constructed ABT-4DVar algorithm were effectively verified. On this basis, using the official statistics as verification data, the ABT-4DVar algorithm was applied to a winter wheat yield estimation system by assimilating remotely sensed LAI into the WOFOST (WOrld FOod STudies) crop growth model at a regional scale. The yield estimation results of winter wheat in Hengshui city showed that the RE between the average estimated yield and official statistics was 3.18%, and the REs between the average estimated yields and the official statistics of the 11 counties were all within 14.80%. The yield estimation results of winter wheat in Hengshui city indicated that the ABT-4DVar algorithm had good performance in regional yield estimation and that the assimilation algorithm could provide technology for crop growth evaluation and yield simulation.

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