基于EPIC模型的冬小麦生长模拟参数全局敏感性分析

    Global sensitivity analysis of growth simulation parameters of winter wheat based on EPIC model

    • 摘要: 模型参数的敏感性分析是模型本地化、区域化过程中不可或缺的重要环节。局部敏感性分析忽略了参数间的相互耦合作用对模型结果的间接影响,从而导致敏感参数选取具有一定的片面性。该研究以河北衡水冬小麦试验区为研究区,使用全局敏感性分析方法分析EPIC模型在冬小麦产量模拟中的敏感参数。研究表明:收获指数(HI)、生长季峰值点(DLAI)、潜在热量单位(PHU)、最大作物高度(HMX)是影响模型本地化最为关键的参数(总敏感指数>0.1);作物的播种日期、收获日期及种植密度是影响区域尺度的作物产量估计最为敏感参数(总敏感指数>0.1)。研究同时表明全局敏感性分析方法可用于作物生长模型本地化、区域化研究,且优于传统局部敏感性分析方法。

       

      Abstract: Sensitivity analysis of model parameters is a very important step in the process of model localization and regionalization. Local sensitivity analysis neglected the indirect effect of interactions among parameters on the model results, which resulted in the one-sidedness of choosing sensitive parameters. Sensitive parameters of winter wheat yield simulation in EPIC model were analyzed by global sensitivity analysis in Hengshui experimental area. The results showed that normal harvest index (HI), point in the growing season when leaf area begins to decline due to leaf senescence (DLAI), potential heat units (PHU) and maximum crop height (HMX), with a total sensitivity index exceeding 0.1, were the key parameters which effected the model localization. And planting date, harvesting date, and planting population, with a total sensitivity index above 0.1, were the most sensitive parameters which effected the yield estimation of winter wheat at regional scale. The study suggests that global sensitive analysis is more effective for model localization and regionalization than the local sensitivity analysis.

       

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