| 刘强,高雪慧,王钧.不同降水年型下大气CO2浓度和温度对旱地春小麦产量的响应模拟[J].干旱地区农业研究,2023,(2):230~237 |
| 不同降水年型下大气CO2浓度和温度对旱地春小麦产量的响应模拟 |
| Response simulation of CO2 concentration and temperature on spring wheat yield in dryland under different precipitation types |
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| DOI：10.7606/j.issn.1000-7601.2023.02.25 |
| 中文关键词: 春小麦 产量 降水年型 CO2 温度 响应模拟 |
| 英文关键词:spring wheat yield precipitation type CO2 temperature response simulation |
| 基金项目:甘肃省教育厅优秀研究生“创新之星”项目（2021CXZX-406）；甘肃省高等学校创新基金支持项目（2021B-122）；甘肃省教育厅产业支撑计划项目（2021CYZC-15）；甘肃农业大学学科发展基金支持项目（GAU-XKFZJJ-2020-13） |
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| 中文摘要: |
| 为量化不同降水年型CO2浓度升高、增温对旱地春小麦（Triticum aestivum L.）产量的影响，本研究基于甘肃省陇中地区气象数据、土壤数据和管理数据驱动APSIM模型，设置不同CO2浓度和温度增量变化来模拟甘肃陇中未来气候情景，分析气候变化情景对春小麦产量稳定性和可持续性的影响，评估不同气候处理对应的产量风险。结果表明：APSIM模型模拟的干旱年和湿润年小麦产量的归一化均方根误差NRMSE小于13%，一致性指标D大于0.85，平水年产量的归一化均方根误差NRMSE大于20%，一致性指标D小于0.8，表明APSIM模型对干旱年和湿润年春小麦产量模拟的精确性高于平水年春小麦产量的模拟。CO2浓度和温度对春小麦产量均具有显著影响，且温度对小麦产量的变化具有主导影响。在增温和CO2浓度共同升高条件下，降水效应表现为湿润年>平水年>干旱年，二者协同所导致的产量减产效应表现为平水年>干旱年>湿润年。对比不同降水年型产量的变异系数和可持续性指数发现，干旱年增温2.5~3℃小麦产量风险最大；湿润年增温2~2.5℃小麦产量风险最大；平水年增温1℃小麦产量风险最大。 |
| 英文摘要: |
| The purpose of this study was to quantify the effects of elevated CO2 concentration and temperature increment on dryland spring wheat (Triticum aestivum L.) yields in different precipitation year patterns. Based on the APSIM model driven by meteorological data, soil data and management data in Longzhong, Gansu Province, different CO2concentration and temperature increment changes were set to simulate future climate scenarios in Longzhong, Gansu Province, analyze the impact of climate change scenarios on yield stability and sustainability of spring wheat, and assess the yield risk corresponding to different climate treatments. The results showed that the normalized root mean square error NRMSE of wheat yield in drought and wet years simulated by the APSIM model was less than 13% and the consistency index D was greater than 0.85, while the normalized root mean square error NRMSE of yield in flat water years was greater than 20% and the consistency index D was less than 0.8, indicating that the accuracy of the APSIM model for spring wheat yield simulations in drought and wet years was higher than that in normal water years. Both CO2concentration and temperature had significant effects on spring wheat yield, and temperature had a dominant effect on the variation of wheat yield. The effect of precipitation was wet year > normal year > drought year, and the effect of yield reduction due to the synergy of the two was normal year > drought year > wet year. Comparing the values of coefficient of variation and sustainability index under different precipitation year types found that the wheat yield risk was greatest under the treatment of 2.5~3℃ warming in drought year; the wheat yield risk was greatest under the treatment of 2~2.5℃ warming in wet year; and the wheat yield risk was greatest under the treatment of 1℃ warming in flat water year. |
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