Exploring the uncertainty in projected wheat phenology, growth and yield under climate change in China

文献类型： 外文期刊

第一作者： Liu, Huan

作者： Liu, Huan;Liu, Huan;Liu, Huan;Xu, Yinlong;Liu, Huan;Xiong, Wei;Xiong, Wei;Pequeno, Diego N. L.;Hernandez-Ochoa, Ixchel M.;Krupnik, Timothy J.;Burgueno, Juan

作者机构：

关键词： wheat (Triticum aestivum L; ); Climate change; Climate -crop modeling; Model ensemble; Uncertainty

期刊名称：AGRICULTURAL AND FOREST METEOROLOGY （ 影响因子：6.424； 五年影响因子：7.021 ）

ISSN： 0168-1923

年卷期： 2022 年 326 卷

页码：

收录情况： SCI

摘要： Exploring and quantifying the uncertainties in climate impact assessment with multiple climate-crop models is crucial to reducing the total uncertainty and guiding adaptation strategies for crop production. Here, we carried out a climate-crop ensemble simulation to measure the uncertainty in estimated climate impacts on China's wheat productivity by the 2050s. The ensemble included the simulations conducted with the three-DSSAT wheat model ensemble. As for the future climate, five Global Climate projections (GCMs) under two Representative Concentration Pathways (RCP4.5 and 8.5) and two CO2 concentrations were selected. Our results indicate that the median of simulated yield change was between 4.5% -5.5%, and-7.7% --5.6%respectively under elevated and current CO2 concentrations by 2050s compared to 1981-2010. The median of simulated phenology change was nearly-12 --10d In percentage terms, higher uncertainty in national yield change was observed compared to phenology change. The total relative contributions of climate projections, crop models, and RCP scenarios have been more than 70% of the total uncertainty of national phenology and yield change. Crop models have accounted for the largest uncertainty of irrigated yield, while crop models and climate projections almost contributed a similar share of the total uncertainty of rainfed yield. These findings highlight the distribution of uncertainty and sources of uncertainty both at the national and grid scales, which would provide a more comprehensive understanding of uncertainties in future yield prediction. Our results also showed that larger uncertainty has been observed in warmer regions (growing season average temperature > 20 degrees C) than in cooler regions, while the wet regions (growing season rainfall > 400 mm) would suffer smaller uncertainty than dry regions. These findings emphasize the relationships between uncertainty and climate factors, which offers in-sights for improving crop models and designing adaptation strategies.

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