作物模型区域应用两种参数校准方法的比较

Comparion of two calibration approaches for regional simulation of crop model

区域模拟的目的是利用有限的空间数据模拟出产量等作物性状的时空变异规律。然而站点作物模型应用到区域范围时涉及到数据归一化、参数简化、模型的校准和验证等问题。利用CERES-Rice模型对作物模型在我国的区域应用进行了尝试并对部分参数进行了校准。首先利用田间观测数据在各实验点上对模型进行了详细的站点校准,以验证模型在我国的模拟能力;其次,以我国水稻种植区(精确到亚区)为单位,运用平均值和标准差(RMSE)两种方法进行了区域校准和验证,即找出能反映出品种空间差异的代表性品种参数集;然后分别运用两种方法的校准结果,模拟水稻产量和成熟期,并将模拟结果与实测值进行了比较。结果表明:区域校准能反映出水稻生育期和产量的时空变化规律,其中RMSE法较平均值法效果好。目前作物模型区域应用过程中还存在大量的误差来源,有待进一步研究。

The purpose of regional simulation is to predict the variability of yield at both spatial and temporal scale, by using very limited geographical data. However, there are some uncertainties which related to regional simulation, e. g. model complexity, imperfect data, regional calibration and validation etc. This study demonstrated how the regional calibration works by using the CERES-Rice model. Firstly, the model was calibrated and validated at site specific scale; then two regional calibration approaches, average approach and RMSE approach were employed to identify a representative cultivar for each sub-AEZ （Ago-Ecological Zone）. The results shows： the regional simulation can simulate the yield variability spatially and temporally, RMSE approach is better than average one. Further endeavor was needed to decrease the uncertainties of regional simulation.