近43年来黑龙江气候变化对农作物产量影响的模拟研究

从近43年来黑龙江省各地气候变化趋势的角度出发, 利用黑龙江省1961—2003年逐日气象资料, 采用世界粮食研究模型 (WOFOST) 和气候变化趋势的数学分析方法, 计算并分析了近43年来黑龙江省各地各主要作物模拟产量变化趋势的空间特征和各地气候要素变化趋势的空间特征, 讨论了气候变化趋势对主要粮食作物模拟产量变化趋势的影响。结果表明:气候变化趋势的空间差异对各主要作物模拟产量变化趋势的空间分布具有重要影响, 但不同作物影响不同。近43年来黑龙江省玉米模拟产量变化趋势增加, 平均增加幅度为4.81%/10a, 气温变化趋势的增高是其模拟产量变化趋势增加的主要气候因素。黑龙江省大豆模拟产量变化趋势总体上呈降低趋势, 平均降低幅度为1.52%/10a;气候变化趋势对北部和南部区域的大豆模拟产量变化趋势作用不同, 气温变化趋势的增高是北部大豆优势种植区域模拟产量变化趋势增加的主要气候因素, 气温和降水量的相应变化趋势是南部大豆种植区域模拟产量变化趋势降低的主要气候因素。     

气候变化对我国南方双季稻发育和产量的影响

基于WOFOST作物模式,结合气候模式输出的气候情景资料,模拟研究了未来100a(2001-2100年)气候变化对我国南方双季稻发育和产量的影响。结果表明：未来气候情景下,我国南方大部分地区双季稻(早稻、晚稻)的生长期会有所缩短;产量可能会有所下降,但下降的幅度不是很大,其中早稻受气候变化的影响较大。     

灌浆期升温和干旱胁迫对江苏冬小麦产量和干物质分配的影响

利用修订的WOFOST模型,结合全球气候变化的大背景以及江苏省冬小麦的实际情况,在冬小麦灌浆期进行了升温胁迫和干旱胁迫模拟,研究了江苏省冬小麦在气候变化背景下的农业气象灾害损失,并检验了WOFOST模型对复合胁迫的模拟能力.利用江苏省徐州、淮安和常州三个站点2008—2017年气象、土壤和冬小麦产量等资料,基于WOFOST作物模型,从地上部分的干物重和干物质分配两个角度探讨升温胁迫和干旱胁迫以及二者的复合胁迫对冬小麦产量形成的影响.结果表明,灌浆期升温和干旱复合胁迫严重影响冬小麦籽粒干物质积累和产量.升温(1℃、2℃、3℃)胁迫、干旱(轻度、中度、重度)胁迫以及二者复合胁迫均导致冬小麦减产率不同程度增大,籽粒干物质分配比例不同程度降低,复合胁迫的影响程度大于单一胁迫.升温对江苏南部冬小麦减产程度最大,籽粒干物质积累受阻最为严重;干旱对江苏中部冬小麦产量影响最为严重,籽粒干物质积累程度由南到北递减;复合胁迫下,减产率多表现为由南至北递增,而干物质积累程度递减.     

WOFOST模型对河南省冬小麦模拟的适用性分析

为进一步研究WOFOST模型在河南省冬麦区的适用性,以河南省30个农业气象观测站1991—2014年冬小麦观测资料、历史气象资料和土壤资料为依据,对WOFOST模型进行逐站调参和验证,分别建立了30个站的冬小麦模型参数。其中1991—2010年为模型调参年份,2011—2014年为模型验证年份。各站开花期和成熟期调参模拟的归一化均方根误差NRMSE分别小于5%和3%,验证误差分别为3.7%和2.9%。除潢川和固始外,模型对其余各站产量模拟的归一化均方根误差NRMSE全省各站均小于20.0%,验证误差全省平均为15.2%,大部分站点观测值和模拟值相关系数r通过了显著检验。利用调参后的模型模拟2011—2014年冬小麦生长动态变化可知,模拟地上部总干物重与实测单株干物重、模拟LAI与单株叶面积有较一致的变化趋势,拟合度较高。因此,WOFOST模型对河南省冬小麦主要发育阶段、产量及干物质积累模拟能力较强,具有良好的应用前景。     

黑龙江省气候变化趋势对小麦产量的影响

利用黑龙江省1961～2003年逐日气象资料,采用世界粮食研究模型(WOFOST)和气候变化趋势分析的数学方法,分析了气候变化趋势对小麦产量变化趋势的影响.在黑龙江省中部、东部和北部相对湿润的小麦种植区域,辐射量降低趋势是小麦模拟产量降低趋势的主要气候原因;在松嫩平原西南部的齐齐哈尔市、大庆市和哈尔滨市,降水量增加的趋势是小麦模拟产量增加趋势的主要气候原因;在西北部的北安、五大连池、克山和克东4县,辐射量增加趋势是小麦模拟产量增加趋势的主要气候原因;黑龙江省小麦模拟产量变化趋势百分率的平均值为-1.57%/10a.     

遥感信息与作物模型结合在冬小麦区域模拟中的应用

遥感数据与作物模型结合是当前农业信息技术应用研究的重要内容和发展趋势之一,能够解决单独利用遥感或作物模型无法解决的问题。为了开展大范围、区域性作物生长过程的模拟和产量预测,首先对作物模型WOFOST进行了订正和验证,使得调整后的模型适于模拟河南新乡县冬小麦生长;根据实际生产分三类情形模拟新乡县2002—2003年度冬小麦的生长发育状况;利用全生育期内能获取的Landsat-7 ETM+数据反演叶面积指数,结合WOFOST模型的模拟情况,确定每个像元对应的冬小麦的生长状况,从而在像元上实现了WOFOST模型对冬小麦生长的模拟;最后对照比较本研究方法的结果与当年新乡县冬小麦的统计情况,结果相近,验证了本文研究方法的技术可行性。     

广州市城市电力消费对气候变化的响应

低纬度地区的城市电力消费对气候变化有较为敏感的响应。该文引入了气候变化对农业产量和能源影响的研究方法, 分别建立了气候变化对电力消费影响强度的动态评估模型和降温度日模型, 对广州市城市电力消费对气候变化的响应作了深入分析。结果表明:广州市城市电力消费量主要受到气温、湿度、风速等气象因子的影响, 其中气温为关键性因子; 综合考虑各气候因子和气候变化的稳定性, 1956—2005年的近50年, 广州市气候变化对城市电力消费影响强度是持续稳定增加的, 正强度出现的概率呈现出增大趋势, 以10%/10a的速度增长; 通过对广州市降温度日的分析可知, 5—10月为主要的降温时期, 其气温的升高对降温度日强度变化影响很大, 达到46.6%/ ℃, 同时, 广州市的降温期长度变率也呈递增趋势, 因此, 气温的升高引发的降温度日的增加对广州市城市电力消费有深刻影响; 在未来气候变暖情景下, 夏季平均最高气温每升高1 ℃, 广州市全年单位工业产值耗电将增加2.02%, 5—10月的平均气温每升高1 ℃, 居民生活用电量的百分比将增加1.25%。在未来, 气候变暖将使城市用电压力有继续增大的趋势。     

气候变化对河西走廊中部地区主要农作物的影响

利用河西走廊中部的张掖市6县区30 a(1981～2010)的气温、降水数据及主要农作物春小麦、玉米的生育期及产量资料,运用数理统计和积分回归进行统计分析了河西走廊中部30 a来的气候变化(温度、降水)特征及气候变化(气温、降水)对主要农作物(春小麦、玉米)生育期及产量的影响。结果表明,随着气候变暖,河西走廊中部30 a年来平均气温总体呈上升趋势,气候倾向率为3.85℃/100 a,各地年降水量均明显增加,年平均降水量从1980年代的191.1 mm增加到近10 a的210.5mm;河西走廊中部气候变暖使该地区春小麦、玉米播种期提前,使小麦的生育期缩短,玉米的生育期延长。气温升高对春小麦、玉米不同生育期及产量形成的影响效应不同;降水增多对春小麦、玉米的各生育期及产量形成呈现出不同的影响效应,且影响效应表现出地域性差异。     

巴楚县冬小麦生长期气候变化特征及其对冬小麦发育期的影响

利用新疆巴楚气象站1983—2012年逐日气象资料及冬小麦生育期资料,采用线性回归、Pearson相关系数方法,分析了巴楚县气候要素和冬小麦生育期的变化特征,以及气候变化对生育期的影响。结果表明:(1)近30 a巴楚县冬小麦生育期内气候变暖趋势明显,月平均气温、月最高气温和月最低气温整体呈上升趋势,日照时数减少,降水量增多。(2)冬小麦播种、抽穗和成熟期提前,越冬开始和返青期延后,全生育期呈缩短趋势。冬前冬小麦生育天数增加,越冬开始—返青期、返青—抽穗期长度缩短,抽穗—成熟期延长。(3)1—2月气温降低是巴楚冬小麦返青期延后的主要原因,而抽穗和成熟期提前则主要受3—4月、4—6月的气温升高影响。     

气候变化对环青海湖地区天然牧草影响研究

近47a来环青海湖地区的气候变化特征及其对环湖盆地草地生态环境的影响,分析表明：环青海湖地区年平均温度升高、年蒸发量减少比较显著,而降水量呈增加趋势,气候有向暖湿化过渡的趋势。随着气候变化,环湖盆地天然草地植被盖度,高度和产量变化明显。在全球气候变暖的背景下,环青海湖地区,随气温升高、降水增加牧草产量有所增加,     

Influence of Climate Change on Winter Wheat Growth in North China During 1950-2000

1. IntroductionChinese agriculture has undergone tremendousstructural changes over the last decades. The averagestaple crop productivity has doubled in 25 yr while thepopulation increased by 25 % [China Statistical Year-book (CSY), 2003]. Winter wheat is one of China'smost important staple food crops, with a total farm-ing area of nearly 24 million hectares and a produc-tion exceeding 92 million ton in 2002 (CSY, 2003).Although China has been the world's largest wheatproducer since 1983 (…     

安徽淮北平原冬小麦气候适宜度分析及作物年景评估

选取安徽省淮北平原37个气象站1960-2016年逐日气象资料,构建气温、降水、日照及气候适宜度模型,分析气候变暖背景下冬小麦气候适宜度时空演变特征,揭示冬小麦生育期气候风险,评判农业气候年景。结果表明：淮北平原冬小麦不同生育期对气候因子适宜程度不同,单要素各生育期适宜度均为灌浆-乳熟期较高,返青-拔节期较低,其中降水适宜度分蘖期最低;全生育期温度适宜度最高、日照适宜度次之、降水适宜度最低,水分是冬小麦生长的限制因子。气候综合适宜度灌浆-乳熟期最高,分蘖期降水适宜度最低,并且其序列变异系数大,常遭遇秋冬连旱,引起产量波动;全生育期气候适宜度呈东高西低分布,淮北中东部较高,而淮北西部及沿淮地区较低,冬小麦生产风险相对较高。1961-2016年全生育期温度适宜度线性增大趋势显著,降水适宜度线性趋势不明显,而日照适宜度呈显著的线性减小趋势;综合来看,全生育期气候适宜度无明显线性增减趋势,空间上淮北东部略有增大,而西部及沿淮地区略有减小,气候风险增加。淮北平原多数年份气候适宜度适中,适宜性偏差年发生概率高于偏好年。基于气候适宜度评判冬小麦气候年景等级,评估结果与实际产量增减情况基本相符,表明农业气候年景模型评估精度能满足业务服务需求,具有推广应用价值。     

新源县冬小麦对气候变化的响应

根据新源县气象站1982—2018年冬小麦生育期、产量及同期气温、降水、日照时数资料,采用线性回归、pearson相关系数、3 a直线滑动平均等统计方法,研究了近37 a来新源县冬小麦对气候变化的响应。结果表明:近37 a来新源县冬小麦冬前生育期显著推迟,返青至乳熟期显著提前,春、夏季生育期提前主要受3月上、中旬气温影响。出苗—越冬开始期显著缩短、乳熟—成熟期显著延长,其它各生育期间隔无显著变化,全生育期缩短是由播种期显著推迟造成的。冬小麦气候产量与营养生长期的气象要素显著相关。播种期显著推迟导致冬前的热量积累不足,建议播种期提前10 d左右,利于形成壮苗。     

气候变化对雨养冬小麦水分利用效率的影响估算

研究气候变化对雨养冬小麦水分利用效率的影响规律,可为农业适应气候变化提供科学依据。通过构建代表站雨养冬小麦产量和土壤水分变化量的模拟方程,分析水分利用效率的历史变化,并结合两种区域气候模式PRECIS和REGCM4.0输出的4种不同气候变化情景资料,估算未来2021—2050年雨养冬小麦水分利用效率的可能变化。结果表明:1981—2010年甘肃、山西和河南代表站的雨养冬小麦水分利用效率呈二次曲线变化趋势,最大值出现在2003年前后。4种气候变化情景的模拟结果均显示:2021—2050年冬小麦全生育期耗水量明显增加,各代表站不同情景平均增加6.2%;产量有增有减,平均产量变化率为1.4%;水分利用效率平均减小3.8%,且变率减小。区域气候模式PRECIS估算的水分利用效率的减小量A2情景大于B2情景,REGCM4.0模式估算的水分利用效率的减小量RCP8.5情景大于RCP4.5情景。整体来看,RCP气候情景对雨养冬小麦水分利用效率的负面影响更大。     

山东省冬小麦产量动态集成预报方法

在新型统计检验聚类分析 (CAST) 方法对山东省冬小麦种植区进行合理分区的基础上,利用基于作物产量历史丰歉气象影响指数、关键气象因子影响指数、气候适宜度指数、WOFOST (world food study) 作物生长模型分别建立各区域冬小麦产量动态预报方法,利用这4种方法分别对2004—2011年山东省冬小麦产量进行动态预报,在分析历史预报结果平均准确率的基础上,剔除预报准确率低于90.0%的预报方法,确定每种方法的权重系数,采用加权方法建立山东省冬小麦产量动态集成预报方法。结果表明:4种单一产量预报方法在各区域各时段的预报准确率很不稳定,波动范围较大。而集成预报方法对山东省各区域冬小麦产量动态预报准确率相对于4种单一预报方法均有所提高,预报准确率普遍在95.0%以上,且其预报结果稳定性较好,变化比较平稳, 集成预报方法更适合在业务上应用。     

气候变化对福建冬种小麦生产的影响

使用福建省３１个县小麦产量资料及相应各地的气象资料,通过气象产量与经膨胀处理后的气象因子进行相关分析,得知影响福建冬种小麦产量的关键气象因子是３月份的降水量和上年１１月中旬至１２月上旬的平均气温。分析了冬种小麦生长期气候资源变化及关键气象因子的年代变化,得出近年气候变化不利于福建冬种小麦的生产。最后对福建冬种小麦种植区重新进行了划分,对福建冬种小麦生产布局提出了建议。     

Numerical Simulation Study on the Impacts of Tropospheric O_3 and CO_2 Concentration Changes on Winter Wheat. Part Ⅱ: Simulation Results and Analyses

With the rapid development of industrialization and urbanization, the enrichment of tropospheric ozone and carbon dioxide concentration at striking rates has caused effects on biosphere, especially on crops. It is generally accepted that the increase of CO2 concentration will have obverse effects on plant productivity while ozone is reported as the air pollutant most damaging to agricultural crops and other plants. The Model of Carbon and Nitrogen Biogeochemistry in Agroecosystems (DNDC) was adapted to evaluate simultaneously impacts of climate change on winter wheat. Growth development and yield formation of winter wheat under different O3 and CO2 concentration conditions are simulated with the improved DNDC model whose structure has been described in another paper. Through adjusting the DNDC model applicability, winter wheat growth and development in Gucheng Station were simulated well in 1993 and 1999, which is in favor of modifying the model further. The model was validated against experiment observation, including development stage data, leaf area index, each organ biomass, and total aboveground biomass. Sensitivity tests demonstrated that the simulated results in development stage and biomass were sensitive to temperature change. The main conclusions of the paper are the following: 1) The growth and yield of winter wheat under CO2 concentration of 500 ppmv, 700 ppmv and the current ozone concentration are simulated respectively by the model. The results are well fitted with the observed data of OTCs experiments. The results show that increase of CO2 concentration may improve the growth of winter wheat and elevate the yield. 2) The growth and yield of winter wheat under O3 concentration of 50 ppbv, 100 ppbv, 200 ppbv and the based concentration CO2 are simulated respectively by the model. The simulated curves of stem, leaf, and spike organs growth as well as leaf area index are well accounted with the observed data. The results reveal that ozone has negative effects on the growth and yield of winter wheat. Ozone accelerates the process of leaf senescence and causes yield loss. Under very high ozone concentration, crops are damaged dramatically and even dead. 3) At last, by the model possible effects of air temperature change and combined effects of O3 and CO2 are estimated respectively. The results show that doubled CO2 concentration may alleviate negative effect of O3 on biomass and yield of winter wheat when ozone concentration is about 70-80 ppbv. The obverse effects of CO2 are less than the adverse effects of O3 when the concentration of ozone is up to 100 ppbv. Future work should determine whether it can be applied to other species by adjusting the values of related parameters, and whether the model can be adapted to predict ozone effects on crops in farmland environment.     

Numerical Simulation Study on the Impacts of Tropospheric O3 and CO2 Concentration Changes on Winter Wheat. Part II: Simulation Results and Analyses

With the rapid development of industrialization and urbanization, the enrichment of tropospheric ozone and carbon dioxide concentration at striking rates has caused effects on biosphere, especially on crops. It is generally accepted that the increase of CO2 concentration will have obverse effects on plant productivity while ozone is reported as the air pollutant most damaging to agricultural crops and other plants. The Model of Carbon and Nitrogen Biogeochemistry in Agroecosystems (DNDC) was adapted to evaluate simultaneously impacts of climate change on winter wheat. Growth development and yield formation of winter wheat under different O3 and CO2 concentration conditions are simulated with the improved DNDC model whose structure has been described in another paper. Through adjusting the DNDC model applicability, winter wheat growth and development in Gucheng Station were simulated well in 1993 and 1999, which is in favor of modifying the model further. The model was validated against experiment observation, including development stage data, leaf area index, each organ biomass, and total aboveground biomass. Sensitivity tests demonstrated that the simulated results in development stage and biomass were sensitive to temperature change. The main conclusions of the paper are the following: 1) The growth and yield of winter wheat under CO2 concentration of 500 ppmv, 700 ppmv and the current ozone concentration are simulated respectively by the model. The results are well fitted with the observed data of OTCs experiments. The results show that increase of CO2 concentration may improve the growth of winter wheat and elevate the yield. 2) The growth and yield of winter wheat under O3 concentration of 50 ppbv, 100 ppbv, 200 ppbv and the based concentration CO2 are simulated respectively by the model. The simulated curves of stem, leaf, and spike organs growth as well as leaf area index are well accounted with the observed data. The results reveal that ozone has negative e ects on the growth and yield of winter wheat. Ozone accelerates the process of leaf senescence and causes yield loss. Under very high ozone concentration, crops are damaged dramatically and even dead. 3) At last, by the model possible effects of air temperature change and combined effects of O3 and CO2 are estimated respectively. The results show that doubled CO2 concentration may alleviate negative effect of O3 on biomass and yield of winter wheat when ozone concentration is about 70-80 ppbv. The obverse effects of CO2 are less than the adverse effects of O3 when the concentration of ozone is up to 100 ppbv. Future work should determine whether it can be applied to other species by adjusting the values of related parameters, and whether the model can be adapted to predict ozone e ects on crops in farmland environment.     

Effects of drought on winter wheat yield in north China during 2012�C2100

Winter wheat is one of China’s most important staple food crops, and its production is strongly influenced by weather, especially droughts. As a result, the impact of drought on the production of winter wheat is associated with the food security of China. Simulations of future climate for scenarios A2 and A1B provided by GFDL-CM2, MPI_ECHAM5, MRI_CGCM2, NCAR_CCSM3, and UKMO_HADCM3 during 2001-2100 are used to project the influence of drought on winter wheat yields in North China. Winter wheat yields are simulated using the crop model WOFOST (WOrld FOod STudies). Future changes in temperature and precipitation are analyzed. Temperature is projected to increase by 3.9-5.5 for scenario A2 and by 2.9-5.1 for scenario A1B, with fairly large interannual variability. Mean precipitation during the growing season is projected to increase by 16.7 and 8.6 mm (10 yr)-1 , with spring precipitation increasing by 9.3 and 4.8 mm (10 yr)-1 from 2012-2100 for scenarios A2 and A1B, respectively. For the next 10-30 years (2012-2040), neither the growing season precipitation nor the spring precipitation over North China is projected to increase by either scenario. Assuming constant winter wheat varieties and agricultural practices, the influence of drought induced by short rain on winter wheat yields in North China is simulated using the WOFOST crop model. The drought index is projected to decrease by 9.7% according to scenario A2 and by 10.3% according to scenario A1B during 2012-2100. This indicates that the drought influence on winter wheat yields may be relieved over that period by projected increases in rain and temperature as well as changes in the growth stage of winter wheat. However, drought may be more severe in the near future, as indicated by the results for the next 10-30 years.