Abstract This study provides statistical emulators of global by gridded crop models included in the Inter-Sectoral Impact Model Intercomparison Project Fast Track project to estimate irrigated crop yields and associated irrigation water withdrawals simulated at the grid cell level. An ensemble of crop model simulations is used to build a panel of monthly summer weather variables and corresponding annual yields and irrigation water withdrawals from five gridded crop models. This dataset is then used to estimate crop-specific response functions for each crop model. The average normalized root mean square errors for the response functions range from 3% to 6% for irrigated yields and 2% to 8% for irrigated water withdrawal. Further in- and out-of-sample validation exercises confirm that the statistical emulators are able to replicate the crop models’ spatial patterns of irrigated crop yields and irrigation water withdrawals, both in levels and in terms of changes over time, although accuracy varies by model and by region. The emulators estimated in this study therefore provide a reliable and computationally efficient alternative to global gridded crop yield models.

中文翻译：

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灌溉作物产量和灌溉用水需求的统计模拟器

摘要 本研究提供了包含在跨部门影响模型比对项目快速通道项目中的全球网格作物模型的统计仿真器，以估计在网格单元级别模拟的灌溉作物产量和相关灌溉用水量。一组作物模型模拟用于构建一组每月夏季天气变量以及来自五个网格作物模型的相应年产量和灌溉用水量。然后使用该数据集来估计每个作物模型的作物特定响应函数。响应函数的平均归一化均方根误差范围为 3% 至 6%（灌溉产量）和 2% 至 8%（灌溉取水量）。进一步的样本内和样本外验证练习证实，统计模拟器能够在水平和随时间的变化方面复制作物模型的灌溉作物产量和灌溉用水提取的空间模式，尽管准确性因时间而异模型和区域。因此，本研究中估计的模拟器为全球网格作物产量模型提供了可靠且计算效率高的替代方案。