干旱是影响华北地区冬小麦产量的主要农业气象灾害之一,作物生长模型是评估干旱对作物产量影响主要方法之一,但作物生长模型对极端天气气候条件下(如干旱)作物产量模拟效果仍存在不确定性。为提高作物模型在干旱条件下对作物产量模拟的...干旱是影响华北地区冬小麦产量的主要农业气象灾害之一,作物生长模型是评估干旱对作物产量影响主要方法之一,但作物生长模型对极端天气气候条件下(如干旱)作物产量模拟效果仍存在不确定性。为提高作物模型在干旱条件下对作物产量模拟的精准性,该研究利用调参验证后的农业生产系统模型(agricultural production systems simulator,APSIM),通过查阅与华北地区冬小麦相关的186篇大田试验文献获得1 876对观测数据,以作物水分亏缺指数为干旱指标,评估APSIM模型在冬小麦拔节-开花和开花-成熟阶段干旱对产量影响的模拟效果,提出APSIM在拔节-开花和开花-成熟阶段干旱对小麦产量影响的修正系数。基于历史气候条件、SSP245和SSP585未来气候情景资料,分析了冬小麦拔节-开花和开花-成熟阶段干旱时空分布特征,并采用修正系数校正后的APSIM模型评估华北地区冬小麦拔节-开花和开花-成熟阶段不同等级干旱对其产量的影响。结果表明,APSIM模型低估了拔节-开花阶段干旱对冬小麦产量影响程度,轻旱、中旱和重旱校正系数分别为0.85、0.91和0.85;APSIM模型可准确模拟开花-成熟阶段轻旱和中旱对冬小麦产量影响,但高估了重旱对冬小麦产量影响,重旱校正系数为1.33。历史和未来气候情景下,拔节-开花和开花-成熟阶段干旱导致冬小麦减产率均呈由北到南依次递减的空间分布特征,且开花-成熟阶段干旱对冬小麦负面影响高于拔节-开花阶段。未来气候情景下冬小麦拔节-开花和开花-成熟阶段不同等级干旱导致的冬小麦减产率均低于历史气候条件。未来干旱对华北冬小麦产量的负面影响程度有所缓解。研究为有效评估干旱对冬小麦影响提供方法支撑。展开更多
为提高旱地小麦气候适宜程度动态分析的能力,利用黄土丘陵典型区域定西1971-2005年逐日气象资料及大田资料,建立小麦日气候适宜度模型,计算各生长阶段(营养生长阶段、营养与生殖生长并进阶段、生殖生长阶段)及全生育期综合气候适宜度,...为提高旱地小麦气候适宜程度动态分析的能力,利用黄土丘陵典型区域定西1971-2005年逐日气象资料及大田资料,建立小麦日气候适宜度模型,计算各生长阶段(营养生长阶段、营养与生殖生长并进阶段、生殖生长阶段)及全生育期综合气候适宜度,确定气候适宜性综合评价标准。通过本土化APSIM(Agricultural Production System Simulator)平台,模拟小麦逐日生物量,采用动态逼近误差平方和方法,确定气候适宜性诊断分析标准。通过等级百分比比较的方法,检验诊断分析标准,并定量、动态分析2002-2005年旱地小麦各生长阶段及全生育期气候适宜程度。结果表明,基于APSIM的诊断分析标准评价结果与基于综合评价标准的结果相比,气候适宜性等级相同和级差为1的占86%~90%;2002-2005年旱地小麦各生长阶段及全生育期诊断分析结果均为较适宜,与研究区实际情况基本相符。该优化方法为旱地小麦气候适宜性分析的动态跟踪提供了一定技术支持。展开更多
为提高干旱环境下甘肃春小麦生产应对旱情的能力,利用APSIM (agricultural production system simulator)平台,模拟1971-2012年甘肃省4大春小麦主产区(河西内陆河灌溉春小麦种植区、陇中黄土高原春小麦种植区、洮岷高寒冬春小麦混种区...为提高干旱环境下甘肃春小麦生产应对旱情的能力,利用APSIM (agricultural production system simulator)平台,模拟1971-2012年甘肃省4大春小麦主产区(河西内陆河灌溉春小麦种植区、陇中黄土高原春小麦种植区、洮岷高寒冬春小麦混种区、陇西黄土高原冬春小麦兼种区)的小麦生长过程,构建基于水分胁迫的小麦干旱致灾强度指数模型,对甘肃省春小麦干旱致灾强度和风险时空分布进行了定量评价和分析。结果表明:甘肃春小麦干旱致灾强度指数总体呈现北高南低的趋势,由于河西春小麦生产具备灌溉条件,陇中、陇西黄土高原春麦种植地区为干旱致灾强度较高且实际影响最大的地区,受干旱影响最小的是洮岷高寒春麦区。在小麦生长不同阶段,各主产区对旱情的敏感程度不同,轻度致灾强度(≥0.20)情况下,洮岷高寒春麦区的开花期和灌浆期、陇西冬春麦兼种区的灌浆期以及陇中干旱春麦区的开花期致灾概率较大,均大于0.6;中度致灾强度(≥0.40)情况下,陇西冬春麦兼种区致灾概率最大出现在开花期,为0.46。展开更多
籽粒蛋白质积累过程的准确模拟对黄土丘陵区旱地小麦优质生产的有效调控有重要意义。利用甘肃省定西市安定区凤翔镇安家沟村2016-2017年大田试验数据及定西市安定区1971-2017年气象资料,建立基于APSIM(agricultural production systems ...籽粒蛋白质积累过程的准确模拟对黄土丘陵区旱地小麦优质生产的有效调控有重要意义。利用甘肃省定西市安定区凤翔镇安家沟村2016-2017年大田试验数据及定西市安定区1971-2017年气象资料,建立基于APSIM(agricultural production systems simulator)的旱地小麦籽粒蛋白质含量模型,采用相关性分析方法检验,并定量分析了耕作方式(传统耕作、传统耕作+秸秆覆盖、免耕及免耕+秸秆覆盖)和播期(正常播期、早播、晚播)对小麦籽粒蛋白质含量的影响。结果表明:3个播期处理和4种耕作方式下,产量和籽粒蛋白质含量模拟值和观测值之间的均方根误差(RMSE)分别为66.4~121.9 kg·hm-2和0.2%~1.1%;归一化均方根误差(NRMSE)分别为1.23%~9.66%和1.31%~9.94%,模型模拟精度较高。播期对旱地小麦籽粒蛋白质含量的影响显著,正常播期的蛋白质含量最高,晚播明显降低了蛋白质含量。4种耕作方式的小麦产量与籽粒蛋白质含量均呈开口向下的二次曲线关系,随着蛋白质含量的升高,产量呈先增加后减少的态势,经过秸秆覆盖的耕作方式(传统耕作+秸秆覆盖和免耕+秸秆覆盖)比不覆盖的耕作方式(传统耕作和免耕)更利于小麦籽粒蛋白质含量的提高。展开更多
Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)...Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.展开更多
文摘干旱是影响华北地区冬小麦产量的主要农业气象灾害之一,作物生长模型是评估干旱对作物产量影响主要方法之一,但作物生长模型对极端天气气候条件下(如干旱)作物产量模拟效果仍存在不确定性。为提高作物模型在干旱条件下对作物产量模拟的精准性,该研究利用调参验证后的农业生产系统模型(agricultural production systems simulator,APSIM),通过查阅与华北地区冬小麦相关的186篇大田试验文献获得1 876对观测数据,以作物水分亏缺指数为干旱指标,评估APSIM模型在冬小麦拔节-开花和开花-成熟阶段干旱对产量影响的模拟效果,提出APSIM在拔节-开花和开花-成熟阶段干旱对小麦产量影响的修正系数。基于历史气候条件、SSP245和SSP585未来气候情景资料,分析了冬小麦拔节-开花和开花-成熟阶段干旱时空分布特征,并采用修正系数校正后的APSIM模型评估华北地区冬小麦拔节-开花和开花-成熟阶段不同等级干旱对其产量的影响。结果表明,APSIM模型低估了拔节-开花阶段干旱对冬小麦产量影响程度,轻旱、中旱和重旱校正系数分别为0.85、0.91和0.85;APSIM模型可准确模拟开花-成熟阶段轻旱和中旱对冬小麦产量影响,但高估了重旱对冬小麦产量影响,重旱校正系数为1.33。历史和未来气候情景下,拔节-开花和开花-成熟阶段干旱导致冬小麦减产率均呈由北到南依次递减的空间分布特征,且开花-成熟阶段干旱对冬小麦负面影响高于拔节-开花阶段。未来气候情景下冬小麦拔节-开花和开花-成熟阶段不同等级干旱导致的冬小麦减产率均低于历史气候条件。未来干旱对华北冬小麦产量的负面影响程度有所缓解。研究为有效评估干旱对冬小麦影响提供方法支撑。
文摘为提高旱地小麦气候适宜程度动态分析的能力,利用黄土丘陵典型区域定西1971-2005年逐日气象资料及大田资料,建立小麦日气候适宜度模型,计算各生长阶段(营养生长阶段、营养与生殖生长并进阶段、生殖生长阶段)及全生育期综合气候适宜度,确定气候适宜性综合评价标准。通过本土化APSIM(Agricultural Production System Simulator)平台,模拟小麦逐日生物量,采用动态逼近误差平方和方法,确定气候适宜性诊断分析标准。通过等级百分比比较的方法,检验诊断分析标准,并定量、动态分析2002-2005年旱地小麦各生长阶段及全生育期气候适宜程度。结果表明,基于APSIM的诊断分析标准评价结果与基于综合评价标准的结果相比,气候适宜性等级相同和级差为1的占86%~90%;2002-2005年旱地小麦各生长阶段及全生育期诊断分析结果均为较适宜,与研究区实际情况基本相符。该优化方法为旱地小麦气候适宜性分析的动态跟踪提供了一定技术支持。
文摘为提高干旱环境下甘肃春小麦生产应对旱情的能力,利用APSIM (agricultural production system simulator)平台,模拟1971-2012年甘肃省4大春小麦主产区(河西内陆河灌溉春小麦种植区、陇中黄土高原春小麦种植区、洮岷高寒冬春小麦混种区、陇西黄土高原冬春小麦兼种区)的小麦生长过程,构建基于水分胁迫的小麦干旱致灾强度指数模型,对甘肃省春小麦干旱致灾强度和风险时空分布进行了定量评价和分析。结果表明:甘肃春小麦干旱致灾强度指数总体呈现北高南低的趋势,由于河西春小麦生产具备灌溉条件,陇中、陇西黄土高原春麦种植地区为干旱致灾强度较高且实际影响最大的地区,受干旱影响最小的是洮岷高寒春麦区。在小麦生长不同阶段,各主产区对旱情的敏感程度不同,轻度致灾强度(≥0.20)情况下,洮岷高寒春麦区的开花期和灌浆期、陇西冬春麦兼种区的灌浆期以及陇中干旱春麦区的开花期致灾概率较大,均大于0.6;中度致灾强度(≥0.40)情况下,陇西冬春麦兼种区致灾概率最大出现在开花期,为0.46。
文摘籽粒蛋白质积累过程的准确模拟对黄土丘陵区旱地小麦优质生产的有效调控有重要意义。利用甘肃省定西市安定区凤翔镇安家沟村2016-2017年大田试验数据及定西市安定区1971-2017年气象资料,建立基于APSIM(agricultural production systems simulator)的旱地小麦籽粒蛋白质含量模型,采用相关性分析方法检验,并定量分析了耕作方式(传统耕作、传统耕作+秸秆覆盖、免耕及免耕+秸秆覆盖)和播期(正常播期、早播、晚播)对小麦籽粒蛋白质含量的影响。结果表明:3个播期处理和4种耕作方式下,产量和籽粒蛋白质含量模拟值和观测值之间的均方根误差(RMSE)分别为66.4~121.9 kg·hm-2和0.2%~1.1%;归一化均方根误差(NRMSE)分别为1.23%~9.66%和1.31%~9.94%,模型模拟精度较高。播期对旱地小麦籽粒蛋白质含量的影响显著,正常播期的蛋白质含量最高,晚播明显降低了蛋白质含量。4种耕作方式的小麦产量与籽粒蛋白质含量均呈开口向下的二次曲线关系,随着蛋白质含量的升高,产量呈先增加后减少的态势,经过秸秆覆盖的耕作方式(传统耕作+秸秆覆盖和免耕+秸秆覆盖)比不覆盖的耕作方式(传统耕作和免耕)更利于小麦籽粒蛋白质含量的提高。
基金funded by the Deputy of Research Affairs, Lorestan University, Iran (Contract No. 1400-6-02-518-1402)
文摘Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.
