We used SUFI-2 for the first time to calibrate the phenology module of the APSIM-wheat model for 10 spring wheat cultivars cultivated in northeast Australia (south-eastern Queensland). Calibration resulted in an average root mean square error (RMSE) of 5.5 days for developmental stages from stem elongation up to flowering. Projections from 33 climate models under the representative concentration pathway 8.5 were used for simulations at 17 sites. Using adapted sowing times, we simulated significantly shorter crop cycles and grain yield improvements for the period 2036–2065 relative to 1990–2019 for three selected cultivars (Hartog, Scout and Gregory). Photoperiod and vernalisation sensitivities were shown to be the largest and smallest contributors to total uncertainties in the simulated flowering day and grain yield, respectively. Uncertainties in climate models had a relatively minor contribution to the total uncertainties in the simulated values of target traits. This contribution significantly increased when climate change impact on the target traits was quantified.

中文翻译：

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气候模型和 APSIM 物候参数对春小麦模拟不确定性的贡献：SUFI-2 算法在澳大利亚东北部的应用

我们首次使用 SUFI-2 对澳大利亚东北部（昆士兰州东南部）种植的 10 个春小麦品种的 APSIM-小麦模型的物候模块进行了校准。校准导致从茎伸长到开花的发育阶段的平均均方根误差 (RMSE) 为 5.5 天。代表性浓度路径 8.5 下 33 个气候模型的预测用于 17 个地点的模拟。使用适应的播种时间，我们模拟了 2036-2065 年相对于 1990-2019 年三个选定品种（Hartog、Scout 和 Gregory）显着缩短的作物周期和谷物产量的提高。光周期和春化敏感性分别是模拟开花日和谷物产量总不确定性的最大和最小贡献者。气候模型的不确定性对目标性状模拟值的总不确定性的贡献相对较小。当量化气候变化对目标性状的影响时，这种贡献显着增加。