Uncertainty in Simulating the Impact of Cultivar Improvement on Winter Wheat Phenology in the North China Plain
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The phenology model is one of the major tools in evaluating the impact of cultivar improvement on crop phenology. Understanding uncertainty in simulating the impact is an important prerequisite for reliably interpreting the effect of cultivar improvement and climate change on phenology. However, uncertainty induced by different temperature response functions and parameterization methods have not been properly addressed. Based on winter wheat phenology observations during 1986–2012 in 47 agro-meteorology observation stations in the North China Plain (NCP), the uncertainty of the simulated impacts caused by four widely applied temperature response functions and two parameterization methods were investigated. The functions were firstly calibrated using observed phenology data during 1986–1988 from each station by means of two parameterization methods, and were then used to quantify the impact of cultivar improvement on wheat phenology during 1986–2012. The results showed that all functions and all parameterization methods could reach acceptable precision (RMSE < 3 days for all functions and parameterization methods), however, substantial differences exist in the simulated impacts between different functions and parameterization methods. For vegetative growth period, the simulated impact is 0.20 day (10 yr)–1 [95% confidence interval:–2.81–3.22 day (10 yr)–1] across the NCP, while for reproductive period, the value is 1.50 day (10 yr)–1 [–1.03–4.02 day (10 yr)–1]. Further analysis showed that uncertainty can be induced by both different functions and parameterization methods, while the former has greater influence than the latter. During vegetative period, there is a significant positive linear relationship between ranges of simulated impact and growth period average temperature, while during reproductive period, the relationship is polynomial. This highlights the large inconsistency that exists in most impact quantifying functions and the urgent need to carry out field experiment to provide realistic impacts for all functions. Before applying a simulated effect, we suggest that the function should be calibrated over a wide temperature range.
Key wordsobserved phenology temperature response function parameterization method renewing cultivar
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