Comparisons among four different upscaling strategies for cultivar genetic parameters in rainfed spring wheat phenology simulations with the DSSAT-CERES-Wheat model
Comparisons among four different upscaling strategies for cultivar genetic parameters in rainfed spring wheat phenology simulations with the DSSAT-CERES-Wheat model
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DOI：
10.1016/j.agwat.2021.107181
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发表时间：
2021-12
影响因子：
6.7
通讯作者：
Shang Chen;Liang He;Yinxuan Cao;Runhong Wang;Lianhai Wu;Zhao Wang;Yufeng Zou;K. Siddique
中科院分区：
文献类型：
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作者：
Shang Chen;Liang He;Yinxuan Cao;Runhong Wang;Lianhai Wu;Zhao Wang;Yufeng Zou;K. Siddique
种植系统模型被广泛用于评估气候变化对农业生产的影响和适应措施。然而，大尺度的作物生长模拟往往缺乏对作物品种变异的考虑，这些变异在作物模型中由不同的遗传系数集表示。以春小麦（Triticum aestivumL.）物候模拟为例，利用2个实验数据集，比较了4种不同的物候模拟遗传参数放大策略。第一个数据集来自阿尔泰（2014）站和杨凌（2015-2017）站40个不同春小麦品种的田间试验；第二个数据集是中国57个国家级农业气象观测站的历史观测物候记录（2010-2014）。这四种策略分别是单点代表性品种（ssp）、57点代表性品种（nrp）、不同农业生态区代表性品种（rrp）和后验分布虚拟品种（vcp）。上述后验分布是根据杨凌40个不同春小麦品种的标定参数值建立的。然后，从后验分布中随机抽取1000组vcp。结果表明，由于只使用了一个代表性品种，ssp和NRPs策略在中国春小麦物候模拟中均存在较大的误差和不确定性。rrp策略在花期和成熟度数据模拟中获得了第二高的精度和最高的精度。VCPs策略在花期模拟中精度最高，但在成熟期模拟中误差较大。VCPs策略可直接用于大规模作物生长模拟，无需繁琐的校准过程。因此，该策略被推荐用于观测值稀缺的领域以及不擅长模型参数估计的模型用户。
Cropping system models are widely used to assess the impacts of and adaptation practices to climate change on agricultural production. However, crop growth simulations at large scales have often lacked consideration of variation in crop cultivars, which were represented by different sets of genetic coefficients in crops models. In this study, taking the phenology of spring wheat (Triticum aestivumL.) as an example, we compared four different strategies for upscaling genetic parameters in phenology simulations at large scales with two experimental datasets. The first dataset was from field experiments comprising 40 different spring wheat cultivars at Altay (2014) and Yangling (2015–2017) station; the second dataset was historical (2010–2014) observed phenology records from 57 national agro-meteorological observation stations in China. The four strategies were the representative cultivar estimated at a single site (SSPs), the representative cultivar estimated at the 57 sites (NRPs), the various representative cultivars estimated at different agro-ecological zones (RRPs), and the virtual cultivars generated from the posterior distributions (VCPs). The posterior distributions aforesaid were established based on the calibrated parameter values of the 40 different spring wheat cultivars planted in Yangling. Then, 1000 sets of VCPs were randomly sampled from the posterior distributions. The results indicated that both the SSPs and NRPs strategy obtained large errors and uncertainties in spring wheat phenology simulations in China since only one representative cultivar was used. The RRPs strategy achieved the second high and the highest accuracy in anthesis and maturity data simulations. The VCPs strategy obtained the highest accuracy in anthesis simulation but relative larger errors in maturity simulation. The VCPs strategy can be directly used in large-scale crop growth simulations without tedious process of calibration. Hence, this strategy is recommended in areas where observations are scarce and for model users who not good at model parameter estimation.