Assimilation of SMOS Soil Moisture for Quantifying Drought Impacts on Crop Yield in Agricultural Regions
Assimilation of SMOS Soil Moisture for Quantifying Drought Impacts on Crop Yield in Agricultural Regions
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DOI：
10.1109/jstars.2014.2315999
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发表时间：
2014-09-01
影响因子：
5.5
通讯作者：
Bayer, Cimelio
中科院分区：
文献类型：
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作者：
Chakrabarti, Subit;Bongiovanni, Tara;Bayer, Cimelio
本研究通过作物生长模型和遥感观测相结合，研究了农业干旱对作物产量的影响。土壤水分（SM）产品从SM和海洋盐度（SMOS）的使命在25公里处获得的尺度缩小到1公里的空间分辨率，与作物模型兼容。降尺度算法是基于信息理论的学习，并使用数据驱动的高分辨率遥感产品，是敏感的SM和原位SM之间的概率关系。缩小的SM值同化在作物模型中使用Enhancement卡尔曼滤波器为基础的增广状态向量技术，估计状态和参数同时进行。降尺度和同化框架实施主要是农业地区的拉普拉塔盆地（LPB）在巴西的两个生长季节。这一雨水灌溉地区在第二个生长季节受到农业干旱的影响，表现为与第一个生长季节相比降水量明显减少。在验证现场将缩小的SM与原位SM进行比较，均方根差（RMSD）为0.045 m（3）/m（3）。将缩小同化框架估计的作物产量与国家农业咨询公司和巴西地理和生态研究所提供的产量进行了比较。同化产量在两个季节都有所改善，在第二个季节受到农业干旱的影响。同化产量与观测产量的差异在第一生长季为16.8%，在第二生长季为4.37%。
This study investigates the effects of agricultural drought on crop yields, through integration of crop growth models and remote sensing observations. The soil moisture (SM) product from SM and Ocean Salinity (SMOS) mission obtained at 25 km was downscaled to a spatial resolution of 1 km, compatible with the crop models. The downscaling algorithm is based upon information theoretic learning and uses data-driven probabilistic relationships between high-resolution remotely sensed products that are sensitive to SM and in situ SM. The downscaled SM values are assimilated in the crop model using an Ensemble Kalman filter-based augmented state-vector technique that estimates states and parameters simultaneously. The downscaling and assimilation framework are implemented for predominantly agricultural region of the lower La-Plata Basin (LPB) in Brazil during two growing seasons. This rain-fed region was affected by agricultural drought in the second season, indicated by markedly lower precipitation compared to the first growing season. The downscaled SM was compared with the in situ SM at a validation site and the root mean square difference (RMSD) was 0.045 m(3)/m(3). The crop yields estimated by the downscaling-assimilation framework were compared with those provided by the Companhia Nacional de Asastecimento (CONAB) and Instituto Brasileiro de Geografia e Estatistica (IBGE). The assimilated yields are improved during both seasons with increased improvement during the second season that was affected by agricultural drought. The differences between the assimilated and observed crop yields were 16.8% during the first growing season and 4.37% during the second season.