The impact of drought on wheat (Triticum aestivum L.) production is shown, using an example data set of almost 60 yr from six climate-specific regions in Poland. Drought was measured using the standardized precipitation index (SPI) and the hydro-thermal coefficient of Selyaninov (HTC). Yield trends were estimated by Bayesian linear regression over two periods, 1961–1991 and 1992–2019, identified by a changepoint detection method. Bayesian inference is used as it allows the estimation of a credible interval of regression coefficients instead of point estimates and asymptotic confidence intervals, thus comparisons between regression coefficients are more meaningful. We detected an increase in yield in both time periods and in all regions. The average winter wheat yield increased by 97% in the first period and by 35% in the second (19.8–39.1 dt ha⁻¹ and 32.9–44.5 dt ha⁻¹, respectively). Spring wheat yield increased by 96% in the first period and by 42% in the second (16.8–37.9 and 22.9–32.5 dt ha⁻¹, respectively). Yield losses in drought years were estimated using the paired t test to compare mean difference between real yields and yields estimated from regression lines for nondrought years. The highest yield losses due to drought were in regions I (–19.3% spring wheats, –6.3% winter ones) and III (–16.1% spring and –8.3% winter wheats) over the 1992–2019 period.

中文翻译：

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1961 年至 2019 年干旱对波兰小麦产量的影响

干旱对小麦 ( Triticum aestivum ) 的影响L.) 使用来自波兰六个气候特定区域的近 60 年示例数据集显示了产量。干旱是使用标准化降水指数 (SPI) 和 Selyaninov (HTC) 的水热系数来测量的。产量趋势通过贝叶斯线性回归估计两个时期，1961-1991 年和 1992-2019 年，通过变化点检测方法确定。使用贝叶斯推理是因为它允许估计回归系数的可信区间而不是点估计和渐近置信区间，因此回归系数之间的比较更有意义。我们检测到两个时间段和所有地区的产量都有所增加。第一阶段冬小麦平均产量增加了 97%，第二阶段增加了 35%（19.8-39.1 dt ha ^-1和 32.9–44.5 dt ha ^-1，分别）。春小麦产量在第一阶段增加了 96%，在第二阶段增加了 42%（分别为 16.8-37.9 和 22.9-32.5 dt ha ^-1）。使用配对t检验估计干旱年份的产量损失，以比较非干旱年份的实际产量与回归线估计的产量之间的平均差异。1992 年至 2019 年期间，干旱导致的产量损失最大的是区域 I（–19.3% 春小麦，–6.3% 冬小麦）和 III 区（–16.1% 春小麦和 –8.3% 冬小麦）。