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作物模型在农业生产管理和决策中发挥着重要作用,而物候期模拟是作物模型正确模拟作物生长发育和产量形成过程的基础。作物模型模拟物候发育的常用算法一般是基于积温的计算,同时也考虑光周期和春化作用的影响,但是水分胁迫对物候发育的次级影响却较少被考虑在内。该研究以连续2季(2013-2014和2014-2015)的遮雨棚下土柱试验和连续3季(2012-2013、2013-2014和2014-2015)的遮雨棚下大田试验数据和前人研究成果为基础提出了冬小麦物候期对水分胁迫的响应机制理论假设,并以土壤相对有效含水率为水分胁迫指标校正冬小麦物候期水分胁迫响应函数。该研究以2014-2015生长季土柱试验各处理试验数据来建立冬小麦物候期水分胁迫响应函数,确定发育加速点A、发育减速点D和发育停止点S所对应的相对有效含水率值分别为0.30、0.10和0。结果发现拔节期和开花期模拟值和观测值之间的均方根误差(root mean square error,RMSE)分别为0.8和1.7 d,绝对相对误差(absolute relative error,ARE)分别低于0.68%和2.09%。然后用2013-2014生长季土柱试验各处理数据进行验证,结果发现拔节期和开花期模拟值和观测值之间的RMSE分别约为0.9和1.1 d,ARE分别在1.37%和1.68%以下。最后再用3年独立大田试验数据对上述修正后的冬小麦物候期算法进行验证,结果发现开花期和成熟期的模拟值与观测值之间的RMSE分别约为2.4和2.0 d,ARE分别低于4.21%和2.67%;与DSSAT-CERES-Wheat模型的模拟结果进行比较,发现修正算法能反映出水分胁迫对冬小麦物候期造成的差异(有提前也有推迟),而DSSAT-CERES-Wheat模型无法体现这种差异,且开花期和成熟期的模拟值与观测值之间的RMSE分别约为4.0和5.5 d,误差最大分别为8和6 d。这表明校正后的冬小麦物候期算法模拟精度得到了较大提高,能在一定程度上描述和量化水分胁迫对冬小麦物候期的影响机制,可用来模拟不同水分胁迫条件下不同品种冬小麦的物候期。
Crop models play an important role in agricultural production management and decision-making, and phenophase simulation is the basis for the crop model to correctly simulate crop growth and yield formation. Commonly used algorithms for crop model development that simulate phenological development are generally based on the calculation of accumulated temperatures and the effects of photoperiod and vernalization, but the secondary effects of water stress on phenological development are less often taken into account. In this study, the soil column test under shelter and the field test data under shelter for three consecutive seasons (2012-2013, 2013-2014 and 2014-2015) were used in two consecutive seasons (2013-2014 and 2014-2015) Based on the results, the theoretical hypothesis of the response mechanism of winter wheat phenophase to water stress was put forward. The response function of winter wheat phenological stress response was corrected by the relative effective water content of soil. In this study, the response function of winter wheat phenological stress response was established based on the data from soil column test in the growing season 2014-2015. The relative effective moisture content corresponding to development acceleration point A, development deceleration point D and development stop point S were 0.30, 0.10 and 0. The results showed that root mean square error (RMSE) between simulated and observed values at jointing and anthesis was 0.8 and 1.7 days respectively, and absolute relative error (ARE) was lower than 0.68% and 2.09%. The results of soil column test from 2013 to 2014 showed that the RMSEs between simulated and observed values at jointing and flowering were about 0.9 and 1.1 days, respectively, with AREs below 1.37% and 1.68%, respectively. Finally, the independent winter field test data were used to validate the above revised winter wheat phenology algorithm. The results showed that the RMSEs between the simulated and observed values at flowering and maturity were about 2.4 and 2.0 days respectively, and the AREs were lower than 4.21% and 2.67%, respectively. Comparing with the simulation results of DSSAT-CERES-Wheat model, it was found that the modified algorithm could reflect the difference of winter wheat phenophase caused by water stress (with advance and postponement), but DSSAT-CERES-Wheat model could not reflect The difference between the simulated and observed values at flowering and maturity was about 4.0 and 5.5 d, respectively, with the maximum error of 8 and 6 days, respectively. This indicates that the corrected winter wheat phenology algorithm simulation accuracy has been greatly improved, which can describe and quantify the impact of water stress on the winter wheat phenology to a certain extent, and can be used to simulate the phenological periods of winter wheat under different water stress conditions.