气候变化对全球粮食安全的影响已引起广泛关注，量化气候变化对主要农作物的影响是理解气候变化对粮食安全影响的基础。2015年，《巴黎协定》上提出“将全球平均气温升幅控制在较工业革命前2.0℃以内，并努力限制在1.5℃以内”的两种升温目标。作为我国主要粮食作物之一，小麦的生产容易受到气候变暖的影响，准确理解1.5℃和2.0℃升温情景下中国小麦产量的变化特征对于我国粮食安全至关重要。虽自《巴黎协定》以来，关于两种升温情景对中国小麦产量影响的研究已有所开展，但目前研究更关注两种升温情景下气候变化对小麦产量平均状况的影响，对于两种升温情景下温度、降水以及CO₂等要素对小麦产量的影响差异尚无深入分析，同时在未来中国干旱形式加剧的背景下，中国小麦产量受干旱影响情况需要进一步分析。

为系统分析两种升温情景下气候变化对中国小麦产量影响，本研究在原始单点AquaCrop作物模型基础上开发空间二维AquaCrop作物模型，并利用长时间序列的农气站点记录数据分区校验作物模型，然后分别对基准时期（1986-2005年）、1.5℃升温情景（2020-2039年）和2.0℃升温情景（2040-2059年）下中国主要麦区的小麦生长过程进行模拟，分析两种升温情景下中国主要麦区小麦产量较基准时期的变化，同时通过多组情景设置方案探究了温度、降水和CO₂对小麦产量的影响及差异，最后多角度分析了未来两种升温情景下干旱对中国小麦产量的影响。这有助于理解1.5℃和2.0℃升温情景下气候变化对中国小麦产量影响的规律，对保障粮食安全意义重大。主要成果与结论如下：

（1）基于单点AquaCrop作物模型设计空间二维AquaCrop作物模型，校验了一套空间精细、中国本地化的小麦作物模型参数，构建了适用于中国小麦种植区的小麦生长过程模拟与产量预测的空间化模型。

在原始单点AquaCrop作物模型基础上开发了空间二维AquaCrop作物模型（Spatial-AquaCrop，SPAC），扩展了AquaCrop作物模型的空间应用能力；同时依据数据的可获得性，在每一小麦种植亚区内选取尽量多的、空间分布均匀的代表性校验站点，基于SCE-UA算法完成对该作物模型小麦作物参数的本地化校验，校验之后的作物模型对小麦产量的模拟精度满足模型本地化应用的要求，形成了一套空间精细、本地化的小麦作物模型参数，为两种升温情景下气候变化对中国小麦产量影响的研究奠定了模型基础。

（2）1.5℃升温情景下，中国春小麦和冬小麦产量较基准时期分别增加约17%和19%；2.0℃升温情景下分别增加约27%和28%。两种升温情景下春小麦产量的稳定性增加，冬小麦产量的稳定性下降。

与基准时期相比，1.5℃升温情景下中国春麦区和冬麦区的小麦产量分别增加了约17.02%和18.76%；2.0℃升温情景下分别增加了约26.54%和27.97%。两种升温情景对不同小麦种植亚区的小麦产量影响存在差异。春麦区中东北春麦区、西北春麦区东南部的定西、临夏以及海东小麦产量增幅较大，北部春麦区小麦增幅较小。冬麦区中黄淮冬麦区虽大部分区域出现增产，但山东、河北和河南三省交界处，以及山东的潍坊、东营的冬小麦出现减产。与基准时期相比，1.5℃和2.0℃升温情景下，春麦区小麦产量的变异系数分别下降了9.25%和11.45%，产量年际波动降低，稳定性增强；但冬麦区小麦产量的变异系数分别增加了7.18%和12.88%，产量年际波动增大，稳定性下降。

（3）1.5℃和2.0℃升温情景下，CO₂是中国小麦产量增加的主要原因，其次是温度和降水。

两种升温情景下，CO₂使小麦产量增加的幅度明显高于温度和降水。1.5℃升温情景下，CO₂、温度和降水分别使春小麦产量增加了约14.5%、3.41%和1.08%；使冬小麦产量增加了约15.6%、5.54%和1.07%；2.0℃升温情景下，CO₂、温度和降水使春小麦产量分别增加了约20.1%、3.97%和1.49%；使冬小麦产量分别增加了约20.8%、6.70%和1.37%。每种升温情景下，CO₂施肥效应对不同小麦种植亚区的影响不存在明显差异；温度的变化虽使中国小麦产量整体呈现增产特征，但使北部春麦区、冀鲁豫三省交界处、以及山东的潍坊和东营、湖北东部的小麦出现减产。降水变化对北部春麦区、北部冬麦区和黄淮冬麦区的小麦增产作用更明显。

（4）1.5℃和2.0℃升温情景下，中国小麦多年平均因旱减产总量较基准时期分别增加了约105万吨和155万吨，干旱对冬麦区影响比春麦区严重。

1.5℃和2.0℃升温情景下，中国小麦多年平均因旱减产总量较基准时期分别增加约105万吨和155万吨，冬小麦多年平均因旱减产总量较基准时期分别增加了约83万吨和135万吨；春小麦多年平均因旱减产总量分别增加了约22万吨和20万吨。1.5℃和2.0℃升温情景下春麦区因旱减产发生的频率较基准时期分别增加了约4%和2%；平均因旱减产率较基准时期分别增加了2.11%和1.55%；累积因旱减产率较基准时期分别增加了10.13%和2.33%。两种升温情景下，冬麦区因旱减产发生的频率均增加了约3%；1.5℃升温情景下平均因旱减产率和基准时期相比变化不大，但2.0℃升温情景下增加了约1.05%；累积因旱减产率较基准时期分别增加了约3.53%和7.19%。两种升温情景下冬麦区更容易受到干旱的影响，主要表现为未来两种升温情景下冬麦区多年平均因旱减产总量、因旱减产发生的频率、平均因旱减产率和累积因旱减产率均高于春麦区。

The impact of climate change on global food security has attracted widespread attention, and quantifying the climate change impact on major crops is the basis for understanding the impact of climate change on food security. The Paris Agreement signed in 2015 proposed to control the global average temperature rise within 2.0 °C compared with the preindustrial revolution period and endeavoured to control the temperature rise within 1.5 °C. Wheat is one of the major food crops in China. It is very important for the food security of China to understand the wheat yield changes in China under 1.5℃ and 2.0℃ warming scenarios. Though the studies on the impact of the two warming scenarios on China's wheat yield have been carried out since the signing of the Paris Agreement, current studies focus more on the impact of climate change on the average wheat yield under the two warming scenarios. And little is known about the different influences of temperature, precipitation and CO₂ on China's wheat under the two warming scenarios. Meanwhile, the drought will intensify under the two future warming scenarios in China, and the drought influences on China's wheat yield needs to be further analyzed.

To systematically analyze the impact of climate change on wheat yield of China under the two warming scenarios, the Spatial-AquaCrop model (SPAC) was developed based on the original single-point AquaCrop model in this study. And the long-time sequence of agrometerological station record data is used to verify the crop model. We firstly simulated China wheat yield under the baseline period (1986-2005), the 1.5°C warming scenario (2020-2039) and the 2.0°C warming scenario (2040-2059). And then we analysed the changes of wheat yield in China under the two warming scenarios compared with the baseline period. Next the different influences of the temperature, precipitation and CO₂ on wheat yield were explored. Finally, we analysed the different influences of drought on wheat yield between the baseline period and the two warming scenarios. This can help to deeply understand the law of climate change and drought impact on China's wheat yield under the 1.5°C and 2.0°C warming scenarios, which is of great significance to ensuring food security. The main conclusions are as follows:

(1) Based on the single-point AquaCrop model, the Spatial AquaCrop model (SPAC) is designed, a set of spatially refined and localized wheat crop model parameters are verified, and a spatial model suitable for China wheat growth process simulation and yield prediction is constructed.

Based the the single-point AquaCrop model, a spatial AquaCrop model (Spatial-AquaCrop, SPAC) is developed based on the MATLAB, which expanded the spatial application capability of the original AquaCrop model. Meanwhile, according to the availability of data in each wheat planting sub-region, select as many representative verification stations as possible, and complete the verification of the wheat crop parameters based on the SCE-UA algorithm. After verification, the simulation accuracy of wheat yield meets the requirements of model application, and a set of spatially refined and localized wheat crop model parameters is formed. This provides a model foundation for the study of the impact of climate change on China's wheat yield under two warming scenarios.

(2) Under the 1.5 °C warming scenarios, the spring wheat yield and winter wheat yield would increase 17% and 19%, respectively, compared with the baseline period. Under the 2.0 °C warming scenarios, the spring wheat yield and winter wheat yield would increase 27% and 28%. The stability of spring wheat yield would increase, but the stability of winter wheat yield would decrease under the two warming scenarios.

Under the 1.5 °C warming scenarios, the spring wheat yield and winter wheat yield would increase 17.02% and 18.76%, respectively, compared with the baseline period, and under the 2.0 °C warming scenarios, the spring wheat yield and winter wheat yield would increase 26.54% and 27.97%. The spring wheat yield in Dongbei spring wheat sub-region, Dingxi, Linxia and Haidong would have the largest increase, while the yield of Beibu spring wheat sub-region increased slightly. Though the wheat yield at most areas of the Huanghuai winter wheat sub-region would increase, the wheat yield would decrease at the junction of Shandong, Hebei and Henan provinces, as well as in Weifang and Dongying in Shandong. Under the two warming scenarios, the coefficient of variation for spring wheat would decrease 9.25% and 11.45% respectively, but the coefficient of variation for winter wheat would increase 7.18% and 12.88%, which indicates that the stability of spring wheat yield would increase, but the stability of winter wheat yield would decrease. For each spring wheat region, except for Beibu spring wheat sub-region, the stability of wheat yield in the other three spring wheat sub-regions would increase compared with the baseline period; For each winter wheat region, except the Beibu winter wheat sub-region, the wheat yield stability of the other four winter wheat sub-region would decrease.

 (3) Under the 1.5°C and 2.0°C warming scenarios, the CO₂ was the main reason for the increase of wheat yield, followed by temperature and precipitation.

Under the 1.5℃ warming scenarios, the CO₂, temperature and precipitation would increase the spring wheat yield by about 14.5%, 3.41% and 1.08%, respectively; and would increase winter wheat yield by about 15.6%, 5.54% and 1.07%, respectively. Under the 2.0℃ warming scenario, the CO₂, temperature and precipitation would increase the spring wheat yield by about 20.1%, 3.97% and 1.49%, respectively; and would increase winter wheat yield by about 20.8%, 6.70% and 1.37%, respectively. Under each warming scenario, there is no significant difference in the effect of CO₂ at the different wheat sub-regions. Though the temperature factor would cause the wheat yield increase as a whole, it would reduce the wheat yield in the Beibu spring wheat sub-region, the junction of the Hebei, Shandong and Henan, Weifang and Dongying of Shandong and the eastern part of Hubei. The precipitation factor had the most obvious positive effect on wheat yield in the Beibu spring wheat sub-region, Beibu winter wheat sub-region and Huanghuai winter wheat sub-region.

(4) Under the 1.5°C and 2.0°C warming scenarios, the annual average wheat production reduction due to drought in China increased by about 1.05 million tons and 1.55 million tons respectively compared with the baseline period. The impact of drought on winter wheat would be more severe than that of spring wheat.

Compared with the baseline period, under the 1.5°C and 2.0°C warming scenarios, the annual average wheat production reduction due to drought increased by about 1.05 million tons and 1.55 million tons respectively. The annual average winter wheat production reduction due to drought increased by about 0.83 million tons and 1.35 million tons respectively and the annual average spring wheat production reduction due to drough increased by about 0.22 million tons and 0.20 million tons respectively. For spring wheat, under the 1.5℃ and 2.0℃ warming scenarios, the frequency of drought-related yield reduction in China's spring wheat planting-regions would increase by about 4% and 2%, respectively, compared with the baseline period; the average yield loss ratio would increase by 2.11% and 1.55%, the cumulative yield reduction ratio would increase by 10.13% and 2.33%. For winter wheat, the frequency of drought-related winter wheat yield reduction would increase by 3%; the average winter wheat yield loss ratio caused by drought would not change much under the 1.5°C warming scenario, but would increase by about 1.05% under the 2.0°C warming scenario, the cumulative yield reduction ratio of winter wheat yield due to drought would increase by 3.53% and 7.19%. The winter wheat is more susceptible to drought under the two warming scenarios. The annual average winter wheat production reduction due to drought, the frequency, average yield loss ratio and cumulative yield reduction ratio caused by drought in winter wheat areas are more serious than those in spring wheat areas.