Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

文献类型： 外文期刊

第一作者： Xiong, Wei

作者： Xiong, Wei;Yang, Di;Xiong, Wei;Porter, Cheryl H.;Jones, James W.;Skalsky, Rastislav;Balkovic, Juraj;Skalsky, Rastislav;Balkovic, Juraj

作者机构：

关键词： climate change impact;EPIC;calibration

期刊名称：JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS （ 影响因子：6.66； 五年影响因子：5.836 ）

ISSN： 1942-2466

年卷期： 2016 年 8 卷 3 期

页码：

收录情况： SCI

摘要： Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

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