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Estimating potential yield of wheat production in china based on cross-scale data-model fusion

机译:基于跨尺度数据模型融合的中国小麦潜在产量估算

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The response of the agro-ecological system to the environment includes the response of individual crop's physiological process and the adaption of the crop community to the environment and its change. Observation and simulation at the single scale level cannot fully explain the above process. It is necessary to develop cross-scale agro-ecological models and study the interaction of agro-ecological processes across different scales. Two typical agro-ecological models (DSSAT and AEZ) are employed in this study and a framework for effective cross-scale data-model and model-model fusion is proposed and illustrated based on the application of DSSAT and AEZ models. The site-specific crop model is up-scaled by using this data-model fusion method, observed data from 36 different agricultural observation stations nationwide and historical weather stations observations (1962–1990) are employed and average crop productivity are estimated. Comparison of the estimation results shows the major consistency across the two models and also indicates specific directions for further improvement. This would help the future efforts in cross-scale crop model fusion.
机译:农业生态系统对环境的响应包括单个作物的生理过程的响应以及作物群落对环境及其变化的适应。单尺度的观察和模拟不能完全解释上述过程。有必要建立跨尺度的农业生态模型,研究跨不同尺度的农业生态过程的相互作用。本研究采用两种典型的农业生态模型(DSSAT和AEZ),并基于DSSAT和AEZ模型的应用,提出并说明了有效的跨尺度数据模型和模型模型融合的框架。使用该数据模型融合方法对特定地点的作物模型进行了放大,使用了来自全国36个不同农业观测站的观测数据和历史气象站的观测值(1962-1990年),并估算了平均作物生产率。估计结果的比较显示了两个模型之间的主要一致性,还指出了进一步改进的具体方向。这将有助于跨尺度作物模型融合的未来工作。

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