基于WOFOST作物生长模型的冬小麦干旱影响评估技术

为了反映作物与干旱的相互关系,人为再现干旱灾害对作物产量的影响程度,选择华北地区冬小麦干旱灾害为研究对象,对作物生长模型WOFOST在区域上进行适应性进行分析、检验的基础上,然后利用区域作物模型实现干旱灾害对作物影响定量分析和动态评估。以减产率和气象条件作为灾害严重程度划分的标准,利用数值模拟试验,确定导致减产的主要气象因子及其量值,对研究区干旱灾害进行影响评估,包括典型灾害年份影响评估和年代际灾害影响评估,并给出了评估结果。     

温度导致的我国东北三省玉米产量波动模拟

东北三省处在我国高纬度地区,一直以来玉米生长季由温度导致的低温冷害是影响东北三省玉米生产波动的主要农业气象灾害;作物模式能对作物重要生理生态过程及其与气象、土壤等环境条件的关系进行数值模拟,人为再现农作物生长发育过程.借助WOFOST作物模型在东北三省玉米生产适应性验证的基础上,对该三省区近46a来(1961～2006年)因温度导致的玉米产量波动情况进行了模拟分析.结果显示,黑龙江、吉林、辽宁三省区的玉米产量波动趋势基本相一致,且随着年份的增加产量波动有减小的趋势,产量波动最大的是黑龙江省,波动范围-20%～12%;产量波动最小的是辽宁省,波动范围-15%～8%.     

中国作物低温冷害监测与模拟预报研究进展

低温冷害是影响中国粮食生产的重要灾害之一,气候变化使中国特别是东北地区的低温冷害时有发生,东北中部冷害每8年发生一次,开展作物低温冷害研究对于中国粮食安全具有重要意义.从冷害形成机理上可以分为延迟型冷害、障碍型冷害及混合型冷害3类,其冷害指标主要针对不同作物有所差别.基于站点的冷害监测小尺度,GIS等新技术提供的精确温度指标可进行区域监测.遥感技术通过监测下垫面温度(LST)和植被指数(如NDVI)可监测障碍型冷害.基于数理统计、气候模式和作物模型耦合、天气预报的发育期和产量预报的低温冷害预报方法已得到应用.作物模型可依据作物发育进程和产量损失等对冷害损失评估,同时与遥感信息等结合可进行区域灾害评估.最后讨论了中国低温冷害监测和预报新技术的发展方向.     

温度对玉米生长和产量的影响

为了明确气温变化对玉米生长发育和产量的影响,建立玉米低温冷害监测和气象评估模式,在东北地区中部的榆树市进行了玉米分期播种试验。试验采用3个品种,设置早、中、晚3个播种期,进行玉米生长发育进程、叶面积指数、生物量、产量和温度等观测。结果表明：玉米的生长速率与温度密切相关,平均气温每升高1 ℃,出苗速率提升17%,营养生长速率提升5%;积温每增加100 ℃·d,玉米最大叶面积指数增加10%,最大生物量和产量增加8%;玉米生长发育期(日平均气温稳定>10 ℃期间)间平均气温降低0.7 ℃,或活动积温减少100 ℃·d,玉米成熟期将延迟7 d,发生一般低温冷害,玉米单产减少8%;气温下降1 ℃,或积温减少140 ℃·d,生育期延迟10 d,发生严重低温冷害,减产10%以上;在水分条件比较适宜的前提条件下,气候变暖对东北地区玉米单产提高是有利的。     

河套灌区不同强度低温冷害对玉米生物量累积和产量的影响

深入揭示不同发育期、不同强度和持续日数的低温冷害对玉米生物量累积和产量的影响,对农业防灾减灾具有重要意义。本文以河套灌区玉米低温冷害为研究对象,在对WOFOST模型进行参数校准的基础上,通过数值模拟试验方法,对模型在研究区域上的适应性进行了分析、检验,同时探讨了不同发育阶段出现不同强度和持续日数低温对玉米贮存器官生物量累积和产量的影响。结果表明:在玉米出苗-灌浆期中的每个发育期发生低温时,玉米贮存器官生物量累积和产量对低温强度和持续日数的响应程度基本一致;当降温强度不同、持续日数相同时,灌浆期低温对玉米产量和贮存器官生物量累积的影响最大;当降温强度相同,持续日数不同时,低温持续日数1 d,玉米拔节至抽雄期发生的低温对贮存器官生物量和产量的影响最大,低温持续日数大于3 d时,玉米灌浆期发生的低温对贮存器官生物量和产量的影响最大;发生时段不同时,出苗至拔节期发生的低温,玉米产量和贮存器官生物量随低温持续日数增加而减少,但持续日数相同,不同低温强度对其影响差别不大;其他发育阶段随着低温强度加大,持续日数增加,玉米产量和贮存器官生物量减少。本文结果较好地反映了研究区低温冷害对玉米生长影响的实际情况,可为当地农业生产决策提供科学依据。     

气候变暖对东北玉米低温冷害分布规律的影响

利用东北地区48个农气站1961-2010年气象资料和近20多年玉米生育期资料,建立生育阶段热量指数和冷害指数,分析气候变暖对东北玉米4个生育阶段热量及低温冷害分布格局的影响。结果表明:热量指数总体表现为明显的增加趋势;平均温度、热量指数的年代际变化特征明显,中晚、晚熟区的上升趋势均小于早、中熟区;冷害频率总体表现为明显的减小趋势;气候变暖对两个熟型区域4个生育阶段的冷害影响并不一致,早、中熟区的冷害平均频率最大值均出现在20世纪60年代,中晚、晚熟区的冷害平均频率最大值均出现在70年代,两个熟型区域的最小值均出现在21世纪初。研究结果可为未来东北地区调整玉米种植制度和生产布局,为适应气候变化和趋利避害提供科学依据。     

玉米低温冷害动态评估和预测方法

为了防御和减轻玉米低温冷害,应用改进的玉米生长发育和干物质积累动态模型,采用新的玉米低温冷害指标和参数,建立了玉米低温冷害发生及损失程度的动态预测和评估方法.该方法遵循积温学说和玉米生物学、生态学原理,用相对积温作为发育期预报和灾害判别的主导因子,用干物质亏缺率代表冷害减产率.经代表地区不同气候年型的验证和试用,证明该冷害预报和评估方法具有较好的客观性和适用性,经过参数和指标调整后,可应用于东北地区各地.     

基于干热风危害指数的黄淮海地区冬小麦干热风灾损评估

全球气候变化背景下,农业气象灾害呈上升态势。干热风灾害发生区域、次数和强度都发生了明显的变化。研究干热风灾害对农作物的影响对于我国农业可持续发展、保障粮食安全等均具有重要的现实意义。利用黄淮海地区68个气象台站1961—2010年的逐日气象资料,和54个农业气象试验站1981—2006年小麦的发育期、产量、干热风灾害等数据,采用公认的中国气象局2007年发布的气象行业标准《小麦干热风灾害等级》中冬小麦干热风灾害指标,计算干热风危害指数,进一步细化发育期,确定冬小麦抽穗前气象条件对气象产量影响的关键气象因子,分离干热风年冬小麦气象产量,构建重度干热风影响下干热风危害指数与冬小麦抽穗—成熟阶段气象条件对气象产量影响的统计模型,进行1981—2006年黄淮海地区冬小麦干热风灾损的评估。结果表明:(1)重度干热风危害下,1981—2006年期间黄淮海各地区冬小麦不同发育时段的干热风危害指数平均在抽穗—开花时段最大,乳熟—成熟时段居中,开花—乳熟时段最小,分别为0.17、0.15和0.14,平均0.15;(2)冬小麦抽穗前气象条件对气象产量影响的关键气象因子为:播种—出苗期间的最低气温、拔节—孕穗期间的平均气温和孕穗—抽穗期间的平均气温,各个单因子相关系数分别为0.64、0.86和0.99,均达到极显著水平。其中播种—出苗的最低气温可决定小麦出苗的迟早和苗情;拔节—孕穗期间,在小花原基形成期—四分体形成期气温偏低可延长小穗、小花分化时间,防止退化,提高结实率;孕穗—抽穗的平均气温偏高有利于提早抽穗,延长后期灌浆时间,且晴天有利于开花授粉;(3)分离干热风年冬小麦气象产量后,构建了重度干热风影响下干热风危害指数与冬小麦抽穗—成熟3个阶段气象条件对气象产量影响的统计模型,验证结果表明该模型客观上能够综合地反映干热风在不同发育阶段对小麦产量的影响。进一步灾损评估表明:重度干热风危害下,黄淮海地区冬小麦减产率在21.52%—39.80%之间,平均为27.83%。     

基于GIS的四川盆周北部山区夏玉米农业气象灾害风险评估——以旺苍县为例

气象灾害是制约我国农业发展的主要因素之一,明确夏玉米农业气象灾害风险对于防灾减灾具有重要意义。本研究基于自然灾害风险理论,以四川盆地北部山区的典型区域(旺苍县)1981—2018年气象数据和玉米产量数据为基础,确定影响夏玉米生产的主要致灾因子,并结合孕灾环境敏感性及承灾体脆弱性构建夏玉米综合农业气象灾害风险评估模型,对四川盆地北部山区夏玉米生产过程中的农业气象灾害风险进行评估。结果表明: 研究期间,成熟期高温、花期暴雨、成熟期暴雨、灌浆期连阴雨和孕穗期干旱是影响研究区夏玉米生长发育的主要农业气象灾害。旺苍县夏玉米农业气象灾害综合风险分布大致呈西南-东北走向,高风险和较高风险区分布区域约占旺苍县总面积的二分之一;灾害风险高值区主要位于研究区西南部,基本与致灾因子危险性高值区一致;灾害风险低值区多集中在西部边缘,此区域亦为成熟期高温、成熟期暴雨、花期暴雨气象灾害的低风险区。     

辽宁省玉米复合农业气象灾害判识及特征

玉米生产过程中常常遭受复合农业气象灾害,为了解辽宁省玉米复合农业气象灾害发生规律和特征,本研究对复合农业气象灾害进行定义和分类,对1961-2017年辽宁省50个气象站玉米生长季的复合农业气象灾害发生情况进行判识,探讨典型年复合农业气象灾害对玉米产量的影响.结果表明:1961-2017年,大部分年份辽宁省玉米复合农业气...     

气候变化背景下东北三省春玉米产量潜力的时空特征

以东北三省春玉米种植区为研究区域,利用当地地面气象观测资料、农业气象观测站春玉米多年试验资料和县级春玉米实际产量资料,使用验证后的农业生产系统模拟模型(APSIM-Maize),分析研究区域春玉米1961—2015年不同水平产量潜力及实际产量的时空分布特征,并解析气候波动对产量潜力的影响.结果表明: 1961—2015年,研究区域春玉米潜在产量平均值为12.2 t·hm^-2,且呈现明显的经向和纬向空间分布,即由南向北递减、西部高于东部.研究区域春玉米可获得产量平均值为11.3 t·hm^-2,与潜在产量呈相似的分布特征.在目前农户的栽培水平下,春玉米农户潜在产量和农户实际产量全区多年平均值分别为6.5和4.5 t·hm^-2.在品种和栽培管理措施不变的条件下,研究区潜在产量、可获得产量和农户潜在产量总体呈显著减少趋势,减幅分别为0.34、0.25和0.10 t·hm^-2·(10 a)^-1.农户实际产量呈增加趋势,增幅为1.27 t·hm^-2·(10 a)^-1.气候波动使东北三省春玉米潜在产量、可获得产量和农户潜在产量年际间波动范围分别为10.0～14.4、9.8～13.3和4.4～8.5 t·hm^-2.     

Maize potential yields and yield gaps in the changing climate of northeast China

Northeast China (NEC) is not only one of the major agricultural production areas in China, but it is also the most susceptible to climate variability. This led us to investigate the impact of climate change on maize potential yield and yield gaps in this region, where maize accounts for about 30% of the nation's production. The APSIM‐Maize model was calibrated and validated for maize phenology and yields. The validated model was then used to estimate potential yields, rain‐fed potential yields, and yield gaps for assessing the climate impacts on maize productivity in NEC. During maize growing seasons from 1981 to 2010, the analysis indicates a warming trend all across NEC, whereas the trends in solar radiation and total precipitation tended to decrease. When the same hybrid was specified in APSIM for all years, a simulated increase of maximum temperature resulted in a negative impact on both potential yield and rain‐fed potential yield. A simulated increase in minimum temperature produced no significant changes in potential or rain‐fed potential yield. However, the increase of minimum temperature was shown to result in a positive impact on the on‐farm yield, consistent with our finding that farmers adopted longer season hybrids for which the increase in minimum temperature provided better conditions for germination, emergence, and grain filling during night time. The gap between potential and rain‐fed potential yields was shown to be larger at locations with lower seasonal precipitation (<500 mm). Our results indicate that regions with the largest yield gaps between rain‐fed potential and on‐farm yields were located in the southeast of NEC. Within NEC, on‐farm maize yields were, on average, only 51% of the potential yields, indicating a large exploitable yield gap, which provides an opportunity to significantly increase production by effective irrigation, fertilization, herbicide, and planting density in NEC.     

How do various maize crop models vary in their responses to climate change factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO₂], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly ?0.5 Mg ha^?1 per °C. Doubling [CO₂] from 360 to 720 μmol mol^?1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO₂] among models. Model responses to temperature and [CO₂] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.     

辽宁省玉米旱灾时空分布特征及综合风险评价

以辽宁省气象数据、空间数据和田间管理数据集为基础,首先,依据自然灾害风险形成理论,从危险性、脆弱性、暴露性和防灾减灾能力四因子入手,选择10个副指标,构建辽宁省玉米旱灾综合风险评价指标体系,并利用组合加权法和GIS空间分析方法,确定其权重及区域化。利用自然灾害风险指数法和加权综合评价方法,建立辽宁省玉米旱灾综合风险评价模型,并进行了辽宁省玉米旱灾时空分布特征分析及综合风险评价研究。结果表明：（1）自1960年以来,研究区干旱频率总体呈上升趋势,尤其2010年以后有明显增加态势。其中1970-1979年间干旱发生频率较低,2010-2019年间干旱频率最高。不管是月尺度、季节尺度、生长季尺度还是年际尺度,辽宁省西北部干旱频率普遍较高,而东南部干旱频率较低。干旱强度呈现从辽宁省中部地区向东西地区两个方向递减的趋势,高值出现在辽宁省中部的阜新、锦州、铁岭、辽阳、盘锦、鞍山、营口和大连等地。干旱历时从辽宁省东部向西部区域递减的趋势,其中高值出现在铁岭北部、盘锦、鞍山、营口和丹东南部等地,低值分布在朝阳西南部、葫芦岛西北部、本溪西部和丹东等地。（2）从4个因子角度来说,辽宁省朝阳西部和葫芦岛西北部玉米旱灾危险性指数较低以外其他区域玉米旱灾危险性指数均较高。然而,辽宁省西北玉米主产区玉米旱灾脆弱性指数和暴露性指数均较高,且防灾减灾能力较低。当4个因子加权综合评价时,辽宁省西北部玉米旱灾综合风险呈现较高的现象。研究结果可为保障辽宁省粮食安全及制定防灾减灾政策提供理论依据和科学指导。     

Evaluation of the yield and nitrogen use efficiency of the dominant maize hybrids grown in North and Northeast China

Breeding high-yielding and nutrient-efficient cultivars is one strategy to simultaneously resolve the problems of food security,resource shortage,and environmental pollution.However,the potential increased yield and reduction in fertilizer input achievable by using high-yielding and nutrient-efficient cultivars is unclear.In the present study,we evaluated the yield and nitrogen use efficiency(NUE) of 40 commercial maize hybrids at five locations in North and Northeast China in 2008 and 2009.The effect of interaction between genotype and nitrogen(N) input on maize yield was significant when the yield reduction under low-N treatment was 25%-60%.Based on the average yields achieved with high or low N application,the tested cultivars were classified into four types based on their NUE:efficient-efficient(EE) were efficient under both low and high N inputs,high-N efficient(HNE) under only high N input,low-N efficient(LNE) under only low N input,and nonefficient-nonefficient under neither low nor high N inputs.Under high N application,EE and HNE cultivars could potentially increase maize yield by 8%-10% and reduce N input by 16%-21%.Under low N application,LNE cultivars could potentially increase maize yield by 12%.We concluded that breeding for N-efficient cultivars is a feasible strategy to increase maize yield and/or reduce N input.     

Factors affecting summer maize yield under climate change in Shandong Province in the Huanghuaihai region of China

Clarification of influencing factors (cultivar planted, cultivation management, climatic conditions) affecting yields of summer maize (Zea mays L.) would provide valuable information for increasing yields further under variable climatic conditions. Here, we report actual maize yields in the Huanghuaihai region over the past 50 years (1957–2007), simulated yields of major varieties in different years (Baimaya in the 1950s, Zhengdan-2 in the 1970s, Yedan-13 in the 1990s, and Zhengdan-958 in the 2000s), and factors that influence yield. The results show that, although each variety change has played a critical role in increasing maize yields, the contribution of variety to yield increase has decreased steadily over the past 50 years (42.6%–44.3% from the 1950s to the 1970s, 34.4%–47.2% from the 1970s to the 1990s, and 21.0%–37.6% from the 1990s to the 2000s). The impact of climatic conditions on maize yield has exhibited an increasing trend (0.67%–22.5% from the 1950s to the 1970s, 2.6%–27.0% from the 1970s to the 1990s, and 9.1%–51.1% from the 1990s to the 2000s); however, interannual differences can be large, especially if there were large changes in temperature and rainfall. Among climatic factors, rainfall had a greater positive influence than light and temperature on yield increase. Cultivation measures could change the contribution rates of variety and climatic conditions. Overall, unless there is a major breakthrough in variety, improving cultivation measures will remain important for increasing future summer maize yields in the Huanghuaihai region.     

Negative effects of climate warming on maize yield are reversed by the changing of sowing date and cultivar selection in Northeast China

Northeast China (NEC) accounts for about 30% of the nation's maize production in China. In the past three decades, maize yields in NEC have increased under changes in climate, cultivar selection and crop management. It is important to investigate the contribution of these changing factors to the historical yield increases to improve our understanding of how we can ensure increased yields in the future. In this study, we use phenology observations at six sites from 1981 to 2007 to detect trends in sowing dates and length of maize growing period, and then combine these observations with in situ temperature data to determine the trends of thermal time in the maize growing period, as a measure of changes in maize cultivars. The area in the vicinity of these six sites accounts for 30% of NEC's total maize production. The agricultural production systems simulator, APSIM‐Maize model, was used to separate the impacts of changes in climate, sowing dates and thermal time requirements on maize phenology and yields. In NEC, sowing dates trended earlier in four of six sites and maturity dates trended later by 4–21 days. Therefore, the period from sowing to maturity ranged from 2 to 38 days longer in 2007 than it was in 1981. Our results indicate that climate trends alone would have led to a negative impact on maize. However, results from the adaptation assessments indicate that earlier sowing dates increased yields by up to 4%, and adoption of longer season cultivars caused a substantial increase in yield ranging from 13% to 38% over the past 27 years. Therefore, earlier sowing dates and introduction of cultivars with higher thermal time requirements in NEC have overcome the negative effects of climate change and turned what would have otherwise been a loss into a significant increase in maize yield.     

基于减产概率的辽宁水稻灾害风险区划

关于灾害风险评价的危险性研究多考虑某一种或者多种灾害的出现概率,由于多数灾害指标难以与作物产量直接相关,常常出现有灾无害现象,难以正确评价灾害风险;依据产量变异的风险研究多从产量变异出发,但对不同减产程度的风险评价研究较少。以辽宁水稻减产风险为例,分析了辽宁省水稻歉年减产率、灾年减产率变异系数及5%和10%两种减产率等级风险概率的空间分布特征。采用K-平均聚类算法将辽宁省水稻产量灾害风险划分为高、较高、中、低4类风险区。结果显示:水稻单产歉年减产率的分布总体呈中部、东部低,向东北西南增高的趋势。水稻单产的灾年减产率变异系数具有西北-东南方向条带状分布特点,中部、东部最小,整体上呈向西南、东北方向递增的趋势。减产率大于5%和10%的风险概率的低值区主要分布于辽宁中部,中值区主要分布于中部、北部、东南,高值区主要分布于东北、西部、南部,整体呈中间低,四周高的特点。辽宁省水稻产量灾害的不同等级风险区域呈整体上分散,小面积连片的特点。辽宁西部、东北部为高风险区,中南部地区为较高风险区,而辽宁中部、东南部为中、低风险区。探讨了各地区的地形气候特征与水稻减产的关系,给出了针对不同区域水稻产量灾损的防御措施。