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A probabilistic assessment of climate change impacts on yield and nitrogen leaching from winter wheat in Denmark

机译：丹麦气候变化对冬小麦产量和氮淋失影响的概率评估

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Climate change will impact agricultural production both directly and indirectly, but uncertainties related to likely impacts constrain current political decision making on adaptation. This analysis focuses on a methodology for applying probabilistic climate change projections to assess modelled wheat yields and nitrate leaching from arable land in Denmark. The probabilistic projections describe a range of possible changes in temperature and precipitation. Two methodologies to apply climate projections in impact models were tested. Method A was a straightforward correction of temperature and precipitation, where the same correction was applied to the baseline weather data for all days in the year, and method B used seasonal changes in precipitation and temperature to correct the baseline weather data. Based on climate change projections for the time span 2000 to 2100 and two soil types, the mean impact and the uncertainty of the climate change projections were analysed. Combining probability density functions of climate change projections with crop model simulations, the uncertainty and trends in nitrogen (N) leaching and grain yields with climate change were quantified. The uncertainty of climate change projections was the dominating source of uncertainty in the projections of yield and N leaching, whereas the methodology to seasonally apply climate change projections had a minor effect. For most conditions, the probability of large yield reductions and large N leaching losses tracked trends in mean yields and mean N leaching. The impacts of the uncertainty in climate change were higher for loamy sandy soil than for sandy soils due to generally higher yield levels for loamy sandy soils. There were large differences between soil types in response to climate change, illustrating the importance of including soil information for regional studies of climate change impacts on cropping systems.
机译：气候变化将直接或间接地影响农业生产，但与可能影响有关的不确定性限制了当前有关适应的政治决策。这项分析的重点是采用概率性气候变化预测方法来评估丹麦的耕地中模拟的小麦单产和硝酸盐淋失的方法。概率预测描述了温度和降水可能变化的范围。测试了两种将气候预测应用于影响模型的方法。方法A是对温度和降水的直接校正，其中对一年中所有天的基准天气数据进行了相同的校正，方法B使用了降水和温度的季节性变化来校正基准天气数据。根据2000年至2100年期间的气候变化预测和两种土壤类型，分析了气候变化预测的平均影响和不确定性。将气候变化预测的概率密度函数与作物模型模拟相结合，量化了氮（N）淋失和谷物产量随气候变化的不确定性和趋势。气候变化预测的不确定性是产量和氮淋失预测中不确定性的主要来源，而季节性应用气候变化预测的方法影响较小。在大多数情况下，大幅度减产和大量氮淋失的可能性追踪了平均产量和平均氮淋失的趋势。壤质沙质土壤对气候变化不确定性的影响要比砂质土壤高，这是由于壤质沙质土壤的单产普遍较高。应对气候变化的土壤类型之间存在很大差异，这说明了将土壤信息纳入区域气候变化对种植系统影响的研究的重要性。

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