生态与农业气象

生态与农业气象研究进展

Progress in Ecological and Agricultural Meteorology Research

1 生态气象

1 Ecological meteorology

1.1 Estimation of vegetation water content using hyperspectral vegetation indices:A comparison of crop water indicators in response to water stress treatments for summer maize

Vegetation water content is one of the important biophysical features of vegetation health,and its remote estimation can be utilized to real-timely monitor vegetation water stress.Here,we compared the responses of canopy water content (CWC),leaf equivalent water thickness (EWT),and live fuel moisture content (LFMC) to different water treatments and their estimations using spectral vegetation indices (VIs) based on water stress experiments for summer maize during three consecutive growing seasons in 2013−2015 in the North China Plain.Results showed that CWC was sensitive to different water treatments and exhibited an obvious singlepeak seasonal variation.EWT and LFMC were less sensitive to water variation and EWT stayed relatively stable while LFMC showed a decreasing trend.Among ten hyperspectral VIs,green chlorophyll index (CIgreen),red edge normalized ratio (NRred edge),and red-edge chlorophyll index (CIred edge) were the most sensitive VIs responding to water variation,and they were optimal VIs in the prediction of CWC and EWT.(Zhou Guangsheng)

1.2 Climate-associated rice yield change in the Northeast China Plain:A simulation analysis based on CMIP5 multi-model ensemble projection

Multi-model ensemble climate projections in combination with crop models are increasingly used to assess the impact of future climate change on agricultural systems.In this study,we used a biophysical process-oriented CERES-Rice crop model driven by downscaled future climate data from 28 Global Climate Models (GCMs) under two emissions scenarios:representative concentration pathway (RCP) 4.5 and RCP8.5,for phase five of the Coupled Model Intercomparison Project (CMIP5) to project the effects of climate change on rice yields in three future time periods in the Northeast China Plain (NECP).The results showed that without consideration of CO2effects,rice yield would increase by 1.3%,1.3%,and 0.4% in the 2030s,2060s,and 2090s,respectively,under the RCP4.5 scenario.Rice yield would change by +1.1%,−2.3%,and −10.7% in the 2030s,2060s,and 2090s,respectively,under the RCP8.5 scenario.With consideration of CO2effects,rice yield during the 2030s,2060s,and 2090s would increase by 5.4%,10.0%,and 11.6% under RCP4.5,and by 6.4%,12.9%,and 15.6% under RCP8.5,respectively.The rice-growing season would be shortened by 2 to 5 weeks in the future.Overall,the future climate would have positive effects on rice yields in the NECP.Although uncertainties in our study on the impact of climate change on rice might arise from the choice of crop model and GCMs,the results are important for informing policy makers and developing appropriate strategies to improve rice productivity in China.(Zhou Guangsheng)

1.3 Climatic suitability and spatial distribution for summer maize cultivation in China at 1.5 and 2.0 global warming

Evaluating climatic suitability of crop cultivation lays a foundation for agriculture coping with climate change scientifically.Herein,we analyse changes in the climatically suitable distribution of summer maize cultivation in China at 1.5 (GW1.5) and 2.0 (GW2.0) global warming in the future according to the temperature control targets set by the Paris Agreement.Compared with the reference period (1971–2000),the summer maize cultivation climatically suitable region (CSR) in China mainly shifts eastwards,and its acreage significantly decreases at both GW1.5 and GW2.0.Despite no dramatic changes in the CSR spatial pattern,there are considerable decreases in the acreages of optimum and suitable regions (the core of the main producing region),indicating that half-a-degree more global warming is unfavourable for summer maize production in China’s main producing region.When the global warming threshold increases from GW1.5 to GW2.0,the centres-of-gravity of optimum areas shift northeastward under RCP4.5 and RCP8.5,the centresof-gravity of both suitable and less suitable areas shift northwestward,though the northward trend is more prominent for the less suitable areas,and the centre-of-gravity of unsuitable areas shifts southeastward.Generally,half-a-degree more global warming drives the cultivable areas of summer maize to shift northward in China,while the west region shows a certain potential for expansion of summer maize cultivation.(Zhou Guangsheng)

1.4 Tracking chlorophyll fluorescence as an indicator of drought and rewatering across the entire leaf lifespan in a maize field

Plant growth and photosynthesis in response to water status have been extensively investigated.However,elucidating the photosynthetic process and its indicators under a drought episode and rewatering across the entire leaf lifespan is often neglected.In this experiment,three water treatments were set during two growth seasons:a control treatment,moderate persistent drought (T1),and severe persistent drought (T2).Maize leaf chlorophyll fluorescence emission was analyzed to determine the regulative responses of the photosynthetic potentials and photosystem II (PSII) photochemistry process to drought and rewatering in situ.A severe drought episode during the peak vegetative growth stage resulted in decreases in chlorophyll content,the maximal efficiency of PSII photochemistry (Fv/Fm),and photochemical quenching,but increases in non-photochemical quenching and the yield for dissipation by downregulation.Rewatering only restored partial PSII functions in plants that had undergone historical drought episodes.An analysis of non-photochemical pathways of thermal dissipation indicates that regulative photoprotection of the photosystem apparatus may occur through heat dissipation when an effect of severe drought episode appeared on a young leaf; however,rewatering did not enhance photoprotection with leaf aging.Compared to the control treatment,the yield of T1 and T2 decreased by 25.1% and 27.1% in 2015,and 26.4% and 54.3% in 2016,respectively.The chlorophyll content was significantly and closely correlated withFv/Fm(R=0.65,P＜0.001) and the maximum versus minimum fluorescence yield in the dark-adapted state (Fm/Fo) (R=0.72,P＜0.001).Additionally,the two parameters can be suggested to feasibly track chlorophyll content changes and the degree of leaf senescence in responses to a drought episode and its interaction with leaf aging:Fm/Foand the relative limitation to photosynthesis (RLP).The current results may provide a profound insight into better understanding the underlying mechanism of photosynthetic potentials and photochemistry efficiency and photoprotection in response to drought episodes and rewatering over the entire leaf lifespan.(Zhou Guangsheng)

1.5 Vertical distributions of chlorophyll and nitrogen and their associations with photosynthesis under drought and rewatering regimes in a maize field

In this study,we characterize the vertical leaf distribution of chlorophyll (Chl) and nitrogen (N) content and their associations with leaf photosynthetic responses inZea maysL.under field watering regimes.We simulated five precipitation patterns,including a drought-rewatering sequence using an electric-powered,rainproof shelter.The results indicate the vertical leaf Chl and N distribution versus the cumulative leaf-area index (LAIc) fit well into a significant quadratic function.The simulated precipitation patterns significantly influenced the parabolic curve trajectory patterns and their parameters.Chlorophyll and N contents had the same trend,with a close and positive relationship.Drought stress followed by rewatering increased the slopes of the linear equations but narrowed the parabolic opening of the quadratic functions.This finding implies that the relationship between Chl and N content can be used to estimate responses to drought and rewatering.The findings also suggested that the relationship patterns between Chl and N levels could be an assessment tool for N-fertilizer managements under different drought conditions to maintain high yields in maize production.Principal component analysis indicated the correlations between functional traits in maize leaves and the responses to drought and rehydration.These findings help to improve drought management and cultivar selection,which will be important in coping with the severe intensity and high frequency of episodic drought events expected from climate change.(Zhou Guangsheng)

1.6 Effects of elevated CO2 on Stipa baicalensis photosynthesis depend on precipitation and growth phase

Elevated atmospheric CO2concentration and simultaneous precipitation change affect plant physiology and growth either directly or indirectly.The main objective of this study was to investigate the effects of elevated CO2and precipitation change,alone or in combination,on photosynthesis and growth inStipa baicalensisunder differential growth phases.Elevated CO2showed a consistently significant increase in net photosynthesis rate (Anet),water-use efficiency (WUE),leaf area and biomass.However,elevated CO2did not mitigate the negative effects of severe drought stress.Increase ofAnetunder elevated CO2attributed toCiin the early growth phase,but WUE and Rubisco carboxylation (Vcmax) was the main inductor in the later growth phase.Effects of elevated CO2onS.baicalensiswere closely associated with precipitation conditions,and the influence on photosynthetic capacity was also related to the growth phase.Drought significantly reducedAnetin June and August,increased WUE in June but did not show effect in August.Precipitation enhancement was beneficial to leaf area and biomass accumulation.Elevated CO2and enhanced precipitation in combination promotedAnetby 158% and 93.4% in June and August,respectively; moreover,their interaction increased the total biomass by 44.4%.Our results suggested that the elevated CO2concentration in the future might be beneficial to the growth ofS.baicalensis,but elevated CO2influence onS.baicalensismight strongly depend on precipitation conditions and the growth phase.(Zhou Guangsheng)

1.7 Estimating green biomass ratio with remote sensing in arid grasslands

It is difficult to estimate green biomass ratio (GBR),the ratio of green aboveground biomass to total aboveground biomass,using common broad-band vegetation indices in arid grasslands due to similar spectral features between bare soil and non-photosynthetic vegetation in near-infrared (NIR) and visible bands.We evaluated the performance of the broad-band RVI (ratio vegetation index),NDVI (normalized difference vegetation index),SAVI (soil-adjusted vegetation index),MSAVI (modified soil-adjusted vegetation index),OSAVI (optimized soiladjusted vegetation index),NDVIgreen(green normalized difference vegetation index),CI (canopy index),and NCI (normalized canopy index) for GBR estimation in the desert steppe of Inner Mongolia,China.We also explored best narrow-band hyperspectral vegetation indices for GBR estimation using hyperspectral remotely sensed data and GBR measurements during 2009 and 2010 growing seasons in the desert steppe.Broad-band vegetation indices were not suitable for GBR estimation.The best narrow-band vegetation indices used reflectance at 2069 and 2042 nm,particular 1.5× (R2069−R2042) / (R2069+R2042+0.5).The index could partially overcome the influence of bare soil cover.It explained 68% of the variance of GBR and dramatically improved GBR estimation accuracy over common broad-band indices.More importantly,the accuracy was not affected by varying bare soil cover.Nevertheless,caution is required for the index application within varying growing seasons.The development of this index is an important resource for future spectral sensors that will permit GBR monitoring at regional scales in arid grasslands.Our results show that remote imagery can monitor GBR in the desert steppe and potentially in many arid grasslands.(Zhou Guangsheng)

1.8 Potential yields,yield gaps,and optimal agronomic management practices for rice production systems in different regions of China

Understanding crop potential yields,yield gaps,and optimal agronomic management practices helps in identifying the limiting factors,scope,and ways to achieve sustainable intensified agricultural production.Here,using detailed field trial data collected from 1981 to 2009 at 11 agro-meteorological experimental stations and the crop model CERES-Rice,we investigated changes in potential yields,water- and nitrogen-stressed yields,and yield gaps of rice in the major rice cultivation regions of China during the collection period.We further identified the optimal nitrogen application rate,transplanting date,and cultivar traits for the sustainable intensification of rice production systems in different regions.Owing to climate change,the potential rice yields declined or changed little in the middle and lower reaches of the Yangtze River (MLRYR),while they increased or changed little in the Northeastern China Plain (NECP) during 1981–2009.Rice yield gaps shrank in the major rice production regions because the actual yields increased and approached the potential yields.The average yield gap was 16.0% in the 2000s,with water and nitrogen stresses being the limiting factors in the NECP and water stress being the major limiting factor in the MLRYR.The nitrogen application rate was suggested to be increased by 47.5% and 21.7% for single rice (i.e.,rice cultivated in a single season per year) in the NECP and MLRYR,respectively,and increased by 5.2% for early rice (i.e.,rice cultivated in the early season in a rice-rice rotation system per year).However,it was suggested to be reduced by 13.1% for late rice (i.e.,rice cultivated in the late season in a rice-rice rotation system per year).Early transplanting could increase the yield,while late transplanting could decrease the yield.The impacts were greater for single rice in the NECP and late rice in the MLRYR than for single rice and early rice in the MLRYR.Cultivars with longer growth durations,and greater spikelet numbers and grain weights,could significantly increase the rice yield by 14.8%–45.6%.The optimal cultivars,combined with advancing transplanting by 10 d,could increase rice yields by 29.2%–68.9%.Our findings provide new approaches,important insights,and effective options for the sustainable intensification of rice production systems in different regions of China.(Zhou Guangsheng)

1.9 Contrasting responses of steppe Stipa ssp.to warming and precipitation variability

Climate change,characterized by warming and precipitation variability,restricted the growth of plants in arid and semiarid areas,and various functional traits are impacted differently.Comparing responses of functional traits to warming and precipitation variability and determining the critical water threshold of dominate steppe grasses from Inner Mongolia facilitates the identification and monitoring of water stress effects.A combination of warming (ambient temperature,+1.5 and +2.0 ) and varying precipitation (−30%,−15%,ambient,+15%,and +30%) manipulation experiments were performed on fourStipaspecies (S.baicalensis,S.bungeana,S.grandis,andS.breviflora) from Inner Mongolia steppe.The results showed that the functional traits of the four grasses differed in their responses to precipitation,but they shared common sensitive traits (root/shoot ratio,R/S,and specific leaf area,SLA) under ambient temperature condition.Warming increased the response of the four grasses to changing precipitation,and these differences in functional traits resulted in changes to their total biomass,with leaf area,SLA,and R/S making the largest contributions.Critical water thresholds of the four grasses were identified,and warming led to their higher optimum precipitation requirements.The four steppe grasses were able to adapt better to mild drought (summer precipitation decreased by 12%–28%) when warming 1.5 rather than 2.0 .These results indicated that if the Paris Agreement to limit global warming to 1.5 is accomplished,this will increase the probability for sustained viability of theStipasteppes in the next 50–100 years.(Lyu Xiaomin)

1.10 Projection of heat injury to single-cropping rice in the middle and lower reaches of the Yangtze River,China under future global warming scenarios

Based on simulation results from the 16 CMIP5 model runs under three Representative Concentration Pathways (RCP2.6,RCP4.5,and RCP8.5) in combination with the recent five years of growth-stage data from agrometeorological observation stations in the middle and lower reaches of the Yangtze River,changes in heat injury and spatial distribution patterns of single-cropping rice in China during the early (2016–2035),middle (2046–2065),and late (2080–2099) 21st century were projected by using quantitative estimations.Relative to the reference period (1986–2005),the occurrence probabilities of heat injury to single-cropping rice under different RCP scenarios increased significantly,showing a trend of mild > moderate > severe.The occurrence probabilities increased with time and predicted emissions,especially the average and maximum occurrence probabilities,which were 48% and 80%,respectively,in the late 21st century under the RCP8.5 scenario.The spatial patterns of the occurrence probabilities at each level of heat injury to single-cropping rice did not change,remaining high in the middle planting region and low in the east.The high-value areas were mainly in central Anhui and southeastern Hubei provinces,and the areas extended to the northwest and northeast of the cultivation area over time.Under the RCP2.6,RCP4.5,and RCP8.5 scenarios,the total area of heat injury to single-cropping rice showed a significant linear increasing trend of 7.4 × 103,19.9 × 103,and 35.3 × 103ha year–1,respectively,from 2016 to 2099,and the areas of heat injury were greatest in the late 21st century,accounting for～25%,～40%,and～59% of the cultivation area.(Lyu Xiaomin)

1.11 Evapotranspiration over a rainfed maize field in Northeast China:How are relationships between environment and terrestrial evapotranspiration mediated by leaf area?

As a central process in the hydrological system and the climate system,terrestrial evapotranspiration is a key factor furthering our understanding of the climate change processes.Knowledge of factors controlling the variability in evapotranspiration is crucial for the prediction of the fate of terrestrial ecosystems under environmental changes.Based on long-term (2005–2014) eddy covariance flux data observed at a rainfed maize site in Northeast China,the purpose of this study was to clarify the environmental regulation of actual evapotranspiration (ET) and the extent to which the regulatory effects on ET are directly or indirectly mediated by changes in biotic factors,using the structural equation modeling (SEM) method.The results showed that annual total ET was 397 ± 35 mm for the rainfed maize site in comparison with 575 ± 169 mm of precipitation (Prec),with an ET/Prec ratio ranging from 0.43 (2012) to 1.14 (2014).It was revealed that net radiation (Rn) was the primary controlling factor of the maize ET,followed by leaf area index (LAI),vapor pressure deficit (VPD),air temperature (Ta),and soil water content (SWC).The adjusted SEM models explained 71%,67%,and 67% of the variation in daily ET of the maize growing season (ETgs) for dry,normal,and moist years,respectively.Rn and VPD dominated ETgs in an increasing order of dry,normal,and moist years.Conversely,the effects of LAI and Ta on ETgs followed the opposite trend.This indicated that drought may increase the sensitivity of maize ET to temperature changes,and decrease the sensitivity of maize ET to radiation changes.In SEM analysis,LAI played an important mediating role in the relationship among climate,soil variables,and ETgs.Rn,VPD,Ta,and SWC all had significant indirect effects on ETgs mediated through LAI.At the annual scale,it was identified that most active days could be a robust predictor of annual ET.(Zhou Li)

1.12 Direct and indirect effects of environmental factors on daily CO2 exchange in a rainfed maize cropland—A SEM analysis with 10-year observations

The carbon budget of agricultural ecosystems is of great importance to the global carbon balance.In this study,the structural equation modeling (SEM) method was employed to quantify the direct and indirect effects of environmental factors on daily net ecosystem CO2exchange (NEE) in a rainfed maize cropland,Northeast China.The results showed that net radiation (Rn) was the most important factor controlling daily NEE,followed by the leaf area index (LAI),air temperature (Ta),vapor pressure deficit (VPD),and clearness index (Kt).The strong effect of Rn was mainly attributed to its direct effect,while Ta and VPD showed comparable or even higher indirect effects than direct effects,indicating that Ta and VPD influenced NEE mainly through regulating canopy development on a daily scale.Moreover,the responses of NEE to individual environmental factors differed greatly among multiyear climatic conditions.Ta and VPD were shown to be more important in warm (WM) years and warm and dry (WD) years than in normal (NM) years and cold and wet (CW) years.LAI was the primary controlling factor of daily NEE in WD years,resulting in large indirect effects of Ta and VPD on NEE.Kt had a large effect on daily NEE only in CW years.SWC had significant effects on daily NEE in WM and WD years but in the opposite direction,i.e.,daily NEE increased with SWC in WD years but decreased with SWC in CW years.The partitioning of direct and indirect effects of environmental factors with SEM can greatly enhance the understanding of the controlling mechanism of NEE and remind researchers to consider the distinct effects of environmental factors on NEE among multiyear climatic conditions in future models.(Zhou Li)

1.13 Identifying climate risk causing maize (Zea mays L.) yield fluctuation by time-series data

A long time series in crop yield is usually expressed as a long-term trend and a short-term fluctuation due to agricultural technological advance and climatic anomaly.The real climate risk is related to the short-term fluctuation in crop yield.In the paper,the climate risk of maize yield response to long-term climate variables is tested with the long time series (1961–2015) by a trend baseline method.The long time series of maize yield is divided into short-term fluctuating meteorological yield and long-term trend yield.The long time series of climate variables are also divided into fluctuating variables and trend variables.After that,Pearson correlation analysis between fluctuating maize yield and fluctuating climate variables is used to identify risk factor causing maize yield fluctuation.Our results reveal that the main risk factors are night-time precipitation and extreme high temperature in growing season.Comparing climate risks in maize-producing provinces,much more climate risks are identified in some regions such as Liaoning Province.The results provide useful information for reducing maize yield loss under climatic change.(Ji Yuhe)

1.14 Global warming from 1.5 to 2.0 will lead to increase in precipitation intensity in China

The impact of global warming on extreme precipitation over China is projected based on CMIP5 simulations under three representative concentration pathway scenarios.When global warming is 1.5 above the pre-industrial (1861−1890),precipitation intensity and frequency increase,which leads to an increase relative to the period 1986−2005 in total wet daytime precipitation in Northeast China,North China,and the Qinghai-Tibet Plateau.However,South China and Southwest China experience fewer precipitation days and less total precipitation despite increasing simple daily intensity (SDII).Under 2.0 of warming,the number of wet days (R1mm) increases to north of 30 °N and decreases to the south,whereas the number of consecutive dry days (CDD) displays the opposite pattern.The other eight extreme precipitation events increase during the simulation period nationwide,with varying intensity.An increase in global warming from 1.5 to 2.0 is projected to lead to an increase in precipitation intensity over China,except for some scattered regions in the northwest and southwest of the country.More frequent extreme precipitation days are also expected,although decreases in R1mm are projected in North China and extend to Northwest China.An overall small decrease in CDD is predicted for China.All annual regional-mean precipitation events have an apparent linear relationship with global mean temperature,except for CDD.The rate of increase of extreme precipitation with temperature in the future on an annual scale is much faster than for a reference period (1986−2005),whereas no noticeable difference exists on a daily scale.The relationships between daily precipitation extremes and temperature for the present days and for the future show a quadratic polynomial structure,increasing up to 19 but decreasing at higher temperatures.There is a significant positive influence on extreme precipitation when warming is limited to 1.5 ,compared with a limit of 2.0 .(Zhou Mengzi)

1.15 不同干旱条件下夏玉米全生育期冠层吸收光合有效辐射比的高光谱遥感反演

冠层吸收光合有效辐射比（FAPAR）是植被生产力遥感模型的重要参数。但关于不同干旱条件下作物全生育期的FAPAR遥感反演研究仍未见报道。本研究利用2015年夏玉米5个灌水处理模拟试验的高光谱反射率和FAPAR观测资料，分析了不同干旱条件下夏玉米关键生育期FAPAR和高光谱反射率变化特征，探讨了FAPAR与反射率、一阶导数光谱反射率和植被指数的关系。结果表明： 轻度水分胁迫和充分供水条件下，FAPAR较高；重度水分胁迫和重度持续干旱条件下，FAPAR较低。冠层可见光、近红外光和短波红外光区的反射率与FAPAR分别呈负相关、正相关和负相关关系。FAPAR与可见光和短波红外光区的383、680和1980 nm附近的反射率的相关性最强，相关系数均达−0.87。一阶导数光谱反射率与FAPAR相关性强且稳定的波段为580、720和1546 nm，相关系数分别为−0.91、0.89和0.88。9个常用植被指数与FAPAR呈线性或对数关系，其中，增强型植被指数、复归一化植被指数、土壤调节植被指数和修正的土壤调节植被指数与FAPAR的关系模型最好，决定系数(R2）均在0.88以上，平均相对误差分别为16.6%、16.6%、16.7%和16.2%；基于一阶导数光谱反射率与FAPAR的对数关系在（720±5）nm波段处的模拟效果较好，R2达0.86；直接选择反射率数据估算FAPAR的效果较差，R2最高为0.81。研究结果可为FAPAR的准确反演及评估作物干旱状况提供支撑。（周广胜）

1.16 干旱条件下夏玉米地-气温差的影响因素及其模拟

地—气温差指标表征作物水分亏缺状况已经被广泛研究，但地—气温差随作物生育进程的变化特征及其影响因子的观测研究仍较少，制约着地—气温差的准确模拟。基于夏玉米2014年三叶期和2015年拔节期的5个灌溉水分控制试验资料的研究表明：随着夏玉米生育进程的推进，土壤水分的变化显著影响了夏玉米农田的地—气温差，土壤水分亏缺越严重，地—气温差越高。在整个水分处理期间，归一化植被指数是地—气温差的主要影响因子且两者呈显著的线性关系，但不同生育期地—气温差还受其他因子的影响：三叶期后受冠层吸收光合有效辐射比影响且呈显著的线性关系，三叶期至拔节期则受土壤相对湿度和空气相对湿度的影响且呈显著的线性关系。在此基础上，基于2014年试验资料建立了夏玉米全生育期地—气温差模拟模型、营养生长期地—气温差模拟模型和生殖生长期地—气温差模拟模型，并利用2015年夏玉米拔节期5个灌溉水分控制试验资料进行了模型验证，结果表明，夏玉米全生育期地—气温差模型可以解释2015年地—气温差变异的63%，但地—气温差分生育期模拟模型，即营养生长期地—气温差模拟模型和生殖生长期地—气温差模拟模型综合的模拟结果则可解释2015年地—气温差变异的79%。研究结果为基于地—气温差的作物干旱指标定量评估作物干旱提供了依据。（周广胜）

1.17 夏玉米三叶期持续干旱下不同叶位叶片含水量变化及其与光合作用的关系

植物干物质的累积依赖于群体光合速率，而群体光合速率又与单叶的光合能力密切有关。叶片光合作用与其含水量密切相关，目前关于不同叶位叶片含水量对持续干旱的响应及其与光合作用的关系还未见报道。以华北夏玉米郑单958为材料，设置6个不同灌水处理，模拟不同灌溉量下持续干旱对夏玉米不同叶位叶片生理特性的影响，分析夏玉米顶部开始的第1、3、5叶位叶片的水分变化及其与净光合速率的关系。结果表明：夏玉米不同叶位的叶片最大含水量不同，且随干旱进程的推进叶片含水量的变化速率也不同，第1叶的叶片含水量下降速率高于第3、5叶，第1叶的最大含水量高于第3、5叶，且可进行光合产物积累的叶片含水量下限随叶位的增加而增大。同时，第1叶的叶片含水量与土壤水分呈显著相关，且与净光合速率的相关性也非常强。第1叶可进行光合产物积累的叶片水分下限（净光合速率为零时的叶片含水量）最小，表明其耐旱性最强，对干旱具有指导意义。研究结果可为提高冠层光合作用模拟的准确性及夏玉米干旱发生发展的监测预警提供参考。（周广胜）

1.18 玉米叶片水分利用效率的保守性

水分利用效率是植物个体或生态系统水分利用过程的重要特征参数，可表征不同时空尺度的植物碳—水耦合关系，对植物适应气候变化研究具有重要意义。本研究以玉米为例，利用中国气象局固城农业气象野外科学试验基地2013—2014年玉米不同灌溉方案模拟试验资料，对不同叶位叶片的水分利用效率特征及其影响因素进行分析。结果表明：植株顶部第1片叶片水分利用效率在拔节期和乳熟期呈现明显的峰值，反映出明显的周期变化规律及其与叶片生理生态特征的紧密相关。在相同环境条件下，不同叶位叶片的水分利用效率不存在显著性差异，即玉米叶片水分利用效率具有空间稳定性与叶龄保守性。同时，研究指出叶片光合速率和蒸腾速率在叶位之间的协调变化是导致空间稳定性和叶龄保守性的主要原因。研究结果可为植物水分关系研究提供参考，也可为水分利用效率的尺度化研究提供依据。（周广胜）

1.19 1.5和2 ℃升温阈值下中国温度和降水变化的预估Ⅲ

基于CMIP5 耦合气候模式模拟结果对1.5 和2 ℃升温阈值时中国温度和降水变化的分析表明，1.5 升温阈值时，中国年平均升温由南向北加强且在青藏高原地区有所放大，季节尺度上升温的空间分布与其类似，就区域平均而言，RCP2.6、RCP4.5和RCP8.5情景下中国年平均气温分别升高1.83、1.75和1.88 ℃，气温的季节变幅以冬季升高最为显著；除华南和西南地区外中国大部分地区年平均降水量增多，降水的季节差异明显，以夏季降水的分布模态与年平均降水量的分布最为相似，区域平均的年降水量分别增加5.03%、2.82%和3.27%，季节尺度上以冬季降水增幅最大。2 ℃升温阈值时，RCP4.5和RCP 8.5情景下中国年平均温度的空间分布与1.5 ℃升温阈值基本一致，中国年平均气温分别升高2.49和2.54 ℃，季节尺度上气温的变化以秋、冬季增幅最大；中国范围内年平均降水量基本表现为增多趋势，其中，西北和长江中下游部分地区表现为明显的季节差异，区域平均的年降水量分别增加6.26%和5.86%。与1.5 ℃升温阈值相比较，2 ℃升温阈值时中国年平均温度在RCP4.5和RCP8.5情景下分别升高0.74和0.76 ℃，降水则分别增加3.44%和2.59%，空间上温度升高以东北、西北和青藏高原最为显著，降水则在东北、华北、青藏高原和华南地区增加最为明显。（周梦子）

2 农业气象

2 Agricultural meteorology

2.1 Possible impact of climate change on apple yield in Northwest China

Apples (Malus pumilaMill.) are widely cultivated in 95 countries and regions around the globe.China is the world’s largest producer of apples.Prediction of apple yield in the context of climate change has become an important topic of research.The study sites in this investigation include 28 apple-producing base counties located in Shaanxi Province of the northwest Loess Plateau.In this study,grey relational analysis was used to examine 88 climatic factors and to extract those factors that significantly influence the meteorological yield (MY) of apples.A support vector machine (SVM) was used to make a quantitative prediction of changes in MY in the apple-producing areas of Shaanxi Province from the years 2000–2099 under 2 climate change scenarios,RCP 4.5 and RCP 8.5.In addition,fuzzy information granulation was used to analyze the variation trends and variation spaces of MY from 2020 to 2049 and 2050 to 2099,compared with the 1990–2019 reference period.The results showed that for the 10-day and monthly climatic factors affecting the MY of apples,climate resource factors are more influential than meteorological disaster factors and spring factors are significantly more influential than other seasonal factors.Overall,there are more and broader climate resource factors affecting MY,and spring climatic conditions are more important for it.In the RCP 4.5 scenario,9 base counties showed slight decreases,2 counties showed significant decreases,15 counties maintained or had slightly increased,and 2 counties showed significant increases.The variation of unit yield was −1.44–1.85 t ha−1.In the RCP 8.5 scenario,10 base counties showed slight decreases,2 counties showed significant decreases,12 counties maintained or had slightly increased,and 4 counties showed significant increases.The variation of unit yield was −2.43–2.78 t ha−1.For both future climate change scenarios,the uncertainty of MY increased with time.(Guo Jianping)

2.2 Spatial-temporal variation in irrigation water requirement for the winter wheat-summer maize rotation system since the 1980s on the North China Plain

The irrigation water requirement (IR) is crucial for optimizing agricultural water management and reallocation and for adjusting the planting structure.Based on the datasets derived from 277 meteorological stations and 42 agro-meteorological stations from 1980 to 2012,the simplified water balance equation was employed to estimate the IR in the winter wheat-summer maize rotation system.The results indicated that,for the two crops,the crop coefficients varied with time and space at different growth stages,with low or moderate variability levels.The average values ofKcini,KcmidandKcendwere 0.69,1.17,0.34 and 0.76,1.13,0.43 for winter wheat and summer maize,respectively.The region located to the most of northern parts of the Yellow River had reduced precipitation and increased reference evapotranspiration (ETo) during the rotation cycle; moreover,in the southern part of this region,the precipitation increased significantly with distinctly decreased ETo.In the North China Plain (NCP),the IR for the winter wheat,summer maize and rotation cycle all had no significant trend change,for which the multi-year average values were 341.1,250.5 and 592.5 mm,respectively.The region with higher IR was primarily located in the northern Shandong and the most of northern parts of the Yellow River,where the IR level was remarkably aggravated in dry seasons.Additionally,the IR increased in the northern NCP region and in the junction area between Hebei and Shandong,and IR decreased with a trend of 10 mm decade−1in other areas.In addition,the magnitude of the station and time intervals for abrupt change of IR varied with different growing seasons.(Fang Shibo)

2.3 The relationship between NDVI and climate factors at different monthly time scales:A case study of grasslands in Inner Mongolia,China (1982–2015)

There are currently only two methods (the within-growing season method and the inter-growing season method) used to analyze the normalized difference vegetation index (NDVI) –climate relationship at the monthly time scale.What are the differences between the two methods,and why do they exist? Which method is more suitable for the analysis of the relationship between them? In this study,after obtaining NDVI values (GIMMS NDVI3g) near meteorological stations and meteorological data of Inner Mongolian grasslands from 1982 to 2015,we analyzed temporal changes in NDVI and climate factors,and explored the difference in Pearson correlation coefficients (R) between them via the above two analysis methods and analyzed the change inRbetween them at multiple time scales.The research results indicated that:(1) NDVI was affected by temperature and precipitation in the area,showing periodic changes； (2) NDVI had a high value ofRwith climate factors in the within-growing season,while the significant correlation between them was different in different months in the inter-growing season； (3) with the increase in time series,the value ofRbetween NDVI and climate factors showed a trend of increase in the within-growing season,while the value ofRbetween NDVI and precipitation decreased,but then tended toward stability in the inter-growing season； and (4) when exploring the NDVI–climate relationship,we should first analyze the types of climate in the region to avoid the impacts of rain and heat occurring during the same period,and the inter-growing season method is more suitable for the analysis of the relationship between them.(Fang Shibo)

2.4 Evaluation of Fengyun-3C soil moisture products using in-situ data from the Chinese Automatic Soil Moisture Observation Stations:A case study in Henan Province,China

Soil moisture (SM) products derived from passive satellite missions are playing an increasingly important role in agricultural applications,especially crop monitoring and disaster warning.Evaluating the dependability of satellite-derived soil moisture products on a large scale is crucial.In this study,we assessed the level 2 (L2) SM product from the Chinese Fengyun-3C (FY-3C) radiometer against in-situ measurements collected from the Chinese Automatic Soil Moisture Observation Stations (CASMOS) during a one-year period from 1 January 2016 to 31 December 2016 across Henan in China.In contrast,we also investigated the skill of the Advanced Microwave Scanning Radiometer 2 (AMSR2) and Soil Moisture Active/Passive (SMAP) SM products simultaneously.Four statistical parameters were used to evaluate these products’ reliability:mean difference,root-mean-square error (RMSE),unbiased RMSE (ubRMSE),and the correlation coefficient.Our assessment results revealed that the FY-3C L2 SM products generally showed a poor correlation with the insitu SM data from CASMOS on both temporal and spatial scales.The AMSR2 L3 SM products of JAXA (Japan Aerospace Exploration Agency) algorithm had a similar level of skill as FY-3C in the study area.The SMAP L3 SM products outperformed the FY-3C temporally but showed lower performance in capturing the SM spatial variation.A time-series analysis indicated that the correlations and estimated error varied systematically through the growing periods of the key crops in our study area.FY-3C L2 SM data tended to overestimate soil moisture during May,August,and September when the crops reached maximum vegetation density and tended to underestimate the soil moisture content during the rest of the year.The comparison between the statistical parameters and the ground vegetation water content (VWC) further showed that the FY-3C SM products performed much better under a low VWC condition (＜0.3 kg m−2) than under a high VWC condition (＞0.3 kg m−2),and the performance generally decreased with increased VWC.To improve the accuracy of the FY-3C SM products,an improved algorithm that can better characterize the variations of the ground VWC should be applied in the future.(Fang Shibo)

2.5 Uncertainties in the effects of climate change on maize yield simulation in Jilin Province:A case study

Measuring the impacts of uncertainties identified from different global climate models (GCMs),representative concentration pathways (RCPs),and parameters of statistical crop models on the projected effects of climate change on crop yields can help to improve the availability of simulation results.The quantification and separation of different sources of uncertainty also help to improve understanding of impacts of uncertainties and provide a theoretical basis for their reduction.In this study,uncertainties of maize yield predictions are evaluated by using 30 sets of parameters from statistical crop models together with eight GCMs with reference to three emission scenarios for Jilin Province of Northeast China.Regression models using replicates based on bootstrap resampling reveal that yields are maximized when the optimum average growing season temperature is 20.1 for 1990–2009.The results of multi-model ensemble simulations show a maize yield reduction of 11%,with 75% probability for 2040–69 relative to the baseline period of 1976–2005.We decompose the variance so as to understand the relative importance of different sources of uncertainty,such as GCMs,RCPs,and statistical model parameters.The greatest proportion of uncertainty (＞50%) is derived from GCMs,followed by RCPs with a proportion of 28% and statistical crop model parameters with a proportion of 20% of total ensemble uncertainty.(Zhang Yi)

2.6 Spatial-temporal variations of carbon storage of the global forest ecosystem under future climate change

Forests play an important role in sequestrating atmospheric carbon dioxide (CO2).Therefore,in order to understand the spatial-temporal variations and controlling mechanisms of global forest carbon (C) storage under future climate change,an improved individual-based forest ecosystem carbon budget model and remote sensing outputs in this study were applied to investigate the spatial-temporal dynamics of global forest (vegetation+soil) C storage in the future climate change scenario.The results showed that in the future RCP4.5 (representative concentration pathways) climate scenario,the total C storage per unit area per year in vegetation and soil of the global forest ecosystem showed a trend of first decreasing and then increasing from 2006 to 2100,with an average of 22.77 kg m−2year−1.However,the evolution trends of C storage changes in vegetation and soil were different.Moreover,the average soil C storage per unit area per year was 2.87 times higher than the average vegetation C storage.The impact of climate change on total C storage in vegetation and soil of the global forest ecosystems was positive,showing an obvious increase during 2006–2100.The total C storage varied significantly in spatial distribution.Spatially,the vegetation C storage and the soil organic C storage were projected to decrease significantly in most parts of South America and the southern Africa in the Southern Hemisphere and increase in the eastern North America,western Asia,and most areas of Europe in the Northern Hemisphere.Especially in the middle and high latitude regions of the Northern Hemisphere,the total forest C stock was projected to increase by 30%–90% from 2046 to 2100.In the future,in these areas where forest C reserves were predicted to be reduced,it was suggested to increase afforestation,prohibit deforestation,and develop projects to increase forest C.Sustainable forest managements also offered opportunities for immediate mitigation and adaptation to climate change.Our findings provided not only a projection of C storage of global forest ecosystem responses to future climate change but also a useful methodology for estimating forest C storage at global levels.(Zhao Junfang)

2.7 Agricultural adaptation to drought for different cropping systems in the southern China under climate change

This study investigates agricultural adaptation to drought for different cropping systems in the southern China.The study area was divided into three regions:South China (SC),South of the Yangtze River (SYR),and Southwest China (SWC).An index of agricultural adaptation to drought (D) was established.Our findings indicated that the average total crop water demand varied greatly among the regions from 1961 to 2010 in the southern China.The maximum value was found in the SC region,followed by the SYR and SWC regions.The effects of droughts on different crops were noticeable.Frequent droughts were recorded in late rice than in early rice in the SC and SYR regions.Droughts in the SWC region mainly affected winter wheat.Moreover,the effects of droughts on crops varied during different growth stages.More frequent and serious droughts occurred during the crop critical flowering stage.Particularly,the frequency of moderate and severe droughts for late rice in the SYR region was 62% during the critical flowering stage.For the SC and SYR regions,theDvalues of early rice (0.29 and 0.29) were lower than that of late rice (0.31 and 0.33),respectively.For the SWC region,theDvalues of winter wheat and rice were both low,with averages of 0.16 and 0.29,respectively.Our study provides interesting insights for improving the drought defense abilities for different cropping systems by changing crop planting proportion on a regional scale in China.(Zhao Junfang)

2.8 Evaluating impacts of climate change on net ecosystem productivity (NEP) of global different forest types based on an individual tree-based model FORCCHN and remote sensing

Accurately assessing the NEP of global forest ecosystem is indispensable to adjusting the global carbon balance for climate change.In this study,an improved individual-based forest ecosystem carbon budget model (FORCCHN) and remote sensing outputs were applied to investigate the impacts of climate change on the NEP of global different forest types from 1982 to 2011.The contributions of carbon sinks in different forest types to carbon sinks in global forest ecosystems were explored.The global forests were categorized into five ecological types according to their habitats and generic characteristics:deciduous coniferous forest (DCF),evergreen coniferous forest (ECF),evergreen coniferous deciduous broad-leaved mixed forest (ECDBMF),deciduous broadleaved forest (DBF) and evergreen broad-leaved forest (EBF).The results showed that globally,the forest ecosystems represented a huge carbon sink and that the total carbon uptakes per unit area per year for EBF,ECF,DBF,DCF and ECDBMF forests from 1982 to 2011 were 0.388,0.116,0.082,0.048 and 0.044 kg m−2year−1,respectively.Inter-annual variability in global NEP per unit area per year among different forest types clearly existed.From 1982 to 2011,especially,the NEP increased in the EBF and ECF forests globally,but decreased in DBF forests.Moreover,there were no significant changes in the NEP of DCF and ECDBMF forests.The carbon sink areas varied among the 5 global forest types.For the DCF forest,central Asia,northern Europe and central North America were the main carbon sink regions.Central Asia,northern Europe and central North America were the main carbon sink regions for the ECF forest.For the ECDBMF forest,the carbon sink regions were mainly concentrated in the northern and central Asia.The carbon sink regions for the DBF forest were mainly concentrated in the southern Asia,southern Europe and mid-eastern North America.The carbon sink regions for the EBF forest were mainly concentrated in the northern and central South America,southern Africa and southern Asia.Finally,the individual contributions of the NEP of each of forest type to global forest’s NEP were calculated.The contributions of NEP for the EBF,ECF,DBF,DCF and ECDBMF forests to the total NEP of global forests were 57.19%,17.07%,12.17%,7.10% and 6.47%,respectively.Our findings highlight that,over the past three decades,the EBF,ECF and DBF forests have been the main contributors to the increases in net ecosystem productivity of global forests.(Zhao Junfang)

2.9 Assessing multi-risk characteristics of heat and cold stress for rice across the southern parts of China

Rice (Oryza sativa) growth is always threatened by heat as well as cold stress,when it is exposed to natural environment.Heat growing degree hours (HGDH) and cold growing degree hours (CGDH1 and CGDH2) were firstly proposed to quantify heat and cold stress occurred during different growing stages.The information diffusion method was effectively used to fit the distribution and estimate probability of single stress at each station,with an advantage of no limitation in data series.In terms of single stress,highest probability was seen in HGDH,followed by CGDH1 and CGDH2.Seven copula functions,i.e.,normal and t,Gumbel-Hougaard,Clayton,Frank,Joe,and Ali-Mikhail-Haq,were applied to fit the distribution of multistress with significant dependence,and simple calculation based on single stress was used to quantify the probability for multi-stress with independence.In these copulas,t was the most chosen one in the fitting of HGDH-CGDH1,HGDH-CGDH2,CGDH1-CGDH2,and HGDH-CGDH1-CGDH2,selected by the statistic of Akaike information criterion.Regarding bi-stress,higher joint probability was in HGDH-CGDH1,relative to HGDH-CGDH2 and CGDH1-CGDH2.As expected,the co-occurrence probability of tri-stress was lower than that of bi-stress in the magnitude and spatial extent,while joint probability of tri-stress was larger.Given the condition of occurrence of HGDH or CGDH1,the joint probability of HGDH-CGDH1 was higher than other pairs of bi-stress and tri-stress.It was special that higher joint probability of CGDH1-CGDH2 was detected under the condition of CGDH2 relative to CGDH1.Joint probability of tri-stress was lower under the condition of HGDH-CGDH1,in comparison with HGDH-CGDH2 and CGDH1-CGDH2.Hazards of single stress and multi-stress were expressed by the integration of intensity of stress index and corresponding probability.Most consistent conclusions agreed that the central Fujian,Zhejiang,and northeastern Jiangxi were exposed to higher hazard,derived from not only single stress but also multi-stress.These results can be helpful in provision of information regarding prevention and adaptation strategies for rice cultivation as a response to extreme temperature stress.(Huo Zhiguo)

2.10 春玉米积温稳定性及在发育期预报中的应用

修正已有积温模型，提高积温稳定性，对积温指标更好地应用于农业生产实践有重要意义。基于东北地区春玉米的生长发育情况，综合分析影响积温稳定性的气象因素，订正常用的活动积温模型。在进行积温稳定性评价基础上，将订正模型应用于春玉米的发育期预报中。结果表明：温度条件是影响积温稳定性的最主要因素，基于温度因子得到的订正模型，在出苗—抽雄阶段和抽雄—成熟阶段较原模型年际间变异系数分别平均减小了0.42%和1.42%，订正模型计算的积温稳定性更好。分别利用1981—2010年及2011—2017年资料进行回代及预报检验，发现订正模型对抽雄期的预报结果改进不明显，对成熟期的预报结果误差较原活动积温模型在回代及预报检验中分别降低了3.78 d 和1.1 d。（郭建平）

2.11 冬小麦籽粒品质评价及其对气象因子的响应研究

选用南北方冬麦区主要推广品种作试验材料，通过田间分期播种试验方法，采用方差分析、主成分分析对冬小麦籽粒性状和内在品质进行分析评价，利用线性相关、二次曲线相关和逐步回归等方法，选择影响显著的气象因子绘制品质响应曲线，构建冬小麦品质预测模型。结果表明：各供试小麦品种均属中蛋白品种，其主要品质性状中，淀粉含量最高且变异程度最小，蛋白质含量次高变异程度居中，脂肪含量最低但变异程度最大;蛋白质、脂肪和产量区域差异显著，各品质含量地域分布总体呈北方较南方高而稳定的特点;蛋白质组分氨基酸品质可由3个主成分解释，一般非必需氨基酸谷氨酸含量最高，必需氨基酸蛋氨酸含量最低，北方麦区氨基酸品质优于南方麦区，表明北方气温日较差大更利于提高氨基酸含量; 脂肪组分脂肪酸品质可由4个主成分解释，一般不饱和脂肪酸亚油酸含量最高，饱和脂肪酸十五碳一烯酸含量最低。温湿条件是影响冬小麦籽粒品质的主要气象因子，可通过调整开花—成熟期气温日较差和降低土壤湿度的方式提高蛋白质或氨基酸品质，通过调节开花—成熟期最低气温和土壤湿度的方式提高脂肪或脂肪酸品质。（郭建平）

2.12 晋北农牧交错带作物气候生产潜力分布特征及其对气候变化的响应

选取晋北农牧交错带1961—2016年19个气象站点逐日气象资料以及1981—2016年5种粮食作物发育期观测资料，采用作物生产潜力逐级订正法，分析不同作物各级生产潜力分布特征，并基于各级生产潜力变化倾向率建立统计模型，分析辐射、气温、降水等气候要素变化对气候生产潜力的影响。结果表明：1961—2016年，晋北各作物光温生产潜力空间分布特征为玉米、谷子、高粱和大豆东高西低，马铃薯空间分布差异较小；各作物气候生产潜力空间分布特征为玉米、谷子和高粱东南高西北低，马铃薯东西高中部低，大豆空间分布差异较小；气候要素变化对不同作物气候生产潜力的影响不同，辐射变化对5种作物气候生产潜力的影响为负效应；气温变化对大部分地区喜温作物（ 玉米、大豆、谷子和高粱）气候生产潜力的影响为正效应，对喜凉作物马铃薯的影响是负效应，气候变暖对改善晋北地区热量不足有利；降水变化是影响晋北作物气候生产潜力变化出现明显空间差异的主要因素，降水减少对于东北部降水偏少地区的影响为负效应，而对于南部降水较多地区未表现负效应，降水基本满足作物生长需要。为适应当前气候变化，需加强高光合效率和抗旱作物品种的选育，合理密植，调整播期，优化农业布局，因地制宜地推广农业集雨灌溉和农业节水灌溉技术，以提高农业气候资源利用率，促进粮食作物稳产高产。（郭建平）

2.13 气象因子对半冬性小麦灌浆速度的影响效应研究

选用黄淮海冬麦区4个半冬性小麦品种郯麦98、山农18、徐麦33、皖麦52为试验材料，通过分期播种试验，利用方差分析、相关分析、逐步回归和通径分析等方法，对半冬性小麦籽粒灌浆速度变化趋势和气象因子对灌浆速度的影响进行了分析。结果表明，正常播期冬小麦灌浆速度波动性最小、千粒重最大，迟播10 d冬小麦灌浆速度波动性最大、千粒重最小；华北区品种郯麦98灌浆速度表现最稳定、千粒重最高，而黄淮区品种皖麦52灌浆速度最大；半冬性小麦灌浆持续期为35～39 d；南北气候差异是影响各品种冬小麦灌浆速度不同的原因之一。半冬性小麦各播期灌浆速度的变化趋势一致，灌浆速度变化与相关显著气象因子的变化规律相符合；灌浆峰值期一般出现在开花后15～25d，迟播冬小麦最大灌浆速度出现时间较对照处理提前，不利于提高粒重；气温条件对冬小麦灌浆速度影响显著，其中最高气温要素是影响不同播期品种灌浆速度的共有关键因子。通径分析表明，最高气温对灌浆速度的作用由自身的直接效应决定，而日照时数与最低气温对灌浆速度的作用与间接效应一致；最高气温平均值对灌浆速度的影响最重要，日照时数和最低气温平均值对灌浆速度的影响较弱；最高和最低气温平均值、日照时数均为灌浆速度的限制因子，其中最高气温平均值对灌浆速度变化的决策作用最大。（郭建平）

2.14 不同品性冬小麦籽粒灌浆特性研究

为揭示冬小麦干物质积累过程的动态变化，利用不同品种冬小麦分期播种的灌浆速率资料，建立了Logistic模型，定量分析了不同播期条件下不同品性冬小麦的灌浆特性，并探讨了冬小麦灌浆特性对气象因子的响应情况。结果表明，籽粒灌浆质量与开花后天数的关系符合Logistic生长曲线方程。基于Logistic模型求算的各次级参数能够较好地表征冬小麦籽粒灌浆特性，半冬性品种较春性品种灌浆高峰期出现时间早；春性品种的粒重渐增期和粒重快增期持续时间一般长于半冬性品种；半冬性品种的平均活跃灌浆期较春性品种短；早播和正常播种条件下，春性品种最大和平均灌浆速率均高于半冬性品种，而迟播条件下春性品种最大和平均灌浆速率均低于半冬性品种；适期晚播更利于春性品种灌浆和千粒重增加。灌浆特性的变异系数分布总体呈春性品种大于半冬性品种，表明播期对春性品种的影响更大。不同籽粒灌浆特性对气象因子的响应不同，其中孕穗—成熟期内的平均气温、孕穗—乳熟期内的降水量、播种—乳熟期内的日照时数与冬小麦灌浆特性相关密切，基于灌浆特性与气象因子建立的逐步回归方程决定系数为0.507～0.875，均通过了0.01水平的显著性检验。（郭建平）

2.15 基于热量指数的东北春玉米冷害指标

构建春玉米冷害指标是冷害研究的基础，对我国春玉米安全生产和品种布局具有重要参考意义。以我国东北三省春玉米为研究对象，以具有明确生物学意义的热量指数为春玉米冷害指示因子，利用气象资料、春玉米生育期资料和冷害灾情资料，计算春玉米不同生育阶段平均热量指数，建立春玉米冷害样本序列，基于K-S分布拟合检验和95%置信区间上限阈值的方法，厘定春玉米冷害指标阈值，构建我国东北春玉米不同生育阶段冷害指标，并采用独立的春玉米冷害灾情样本验证指标的合理性。研究结果表明：东北三省春玉米冷害指标在生殖生长和营养生长与生殖生长并进期热量指数的阈值较高，营养生长期略低；指标验证结果与历史灾情记录完全吻合的比率为80.0%，完全吻合和相差1级的比率为100%，且各灾害程度验证得到的准确率均高于75%。（王培娟）

2.16 1961—2015年黄淮海平原夏玉米干旱识别及时空特征分析

利用黄淮海平原内气象数据、农业气象数据、夏玉米实际灾情资料，参考标准化降水指数SPI的计算公式，结合实际干旱灾情数据构建夏玉米干旱指数SPI10和SPI30，并分析黄淮海平原夏玉米生长季干旱的时空分布特征。结果表明：播种—抽雄期、抽雄—成熟期的旬尺度SPI10干旱阈值分别为−0.10和−0.35、月尺度SPI30干旱阈值分别为−0.60和−0.65，灾情验证结果显示时间尺度更小的SPI10在反映黄淮海平原夏玉米干旱特征方面效果更好。基于SPI10分析了黄淮海平原夏玉米干旱的时空分布特征，发现播种—抽雄期的平均干旱频率和干旱强度均明显高于抽雄—成熟期，并且干旱强度的时空分布特征均与干旱频率较为一致，一般表现为干旱频率越高的地区，累计干旱强度也越强；同时，75%的年份中播种—抽雄期的干旱范围大于抽雄—成熟期。综合以上结果，黄淮海平原夏玉米在营养生长阶段更容易受到水分缺失的影响，更易发生干旱胁迫。（王培娟）

2.17 基于气象因子的赣南脐橙气候品质指标评价模型

基于江西省赣州市11个脐橙主产县2008—2011年脐橙品质和气象数据，采用相关普查、逐步回归和主成分回归分析等方法筛选影响脐橙品质的关键气象因子，建立脐橙气候品质指标评价模型。结果表明：6—11月的温度、日照、降水是影响脐橙品质形成的关键气象因子；可溶性固形物与9—10月平均气温、10月气温日较差和日照呈极显著正相关，与10月降水量呈极显著负相关；VC含量与10月最高气温、日照、气温日较差呈显著正相关；可食率与10月气温日较差、7—10月最高气温和8—10月日照呈显著负相关；总酸含量与10—11月平均气温、10月最低气温、7—10月降水量呈显著负相关；单果重与6—11月平均气温、6—7月最高气温和10月降水量呈显著正相关；分别建立了基于气象因子的可溶性固形物、总酸、固酸比、VC、可食率、单果重等6个脐橙品质指标的评价模型，模型验证结果表明，各品质指标模拟的平均相对误差均小于12%，其中可溶性固形物和可食率的平均相对误差小于5%。（王培娟）

2.18 地表土壤水分的卫星遥感反演方法研究进展

土壤水分是影响农业生产的重要因子之一，掌握农田地表土壤水分对农业生产实践有着重要的意义和作用。目前监测土壤水分的方法有传统的点尺度物理监测、基于物理模型和数学计算方法的模拟技术以及遥感监测方法。而随着遥感技术的发展，逐渐克服了前两种方法由于采样点限制以及所需参数复杂等制约因素。从不同的遥感波段和遥感方法划分，介绍了可见光—近红外遥感、热红外遥感、微波遥感的发展现状及不同波段所对应的研究方法，并对各种方法的优势和局限性进行了总结，加强改进模型方法研究，增强主被动微波结合反演方法的利用对于减少植被对土壤水分的影响有很大的益处，这也是今后遥感技术反演农田地表土壤水分的趋势。（房世波）

2.19 甘肃省春玉米灾损风险评估

干旱是影响西北地区春玉米生产的主要气象灾害。应用甘肃省1980—2011年71个县（市）的春玉米播种面积和总产量资料，以风险理论为基础，采用风险评估技术方法，探讨了甘肃省县、市春玉米产量在干旱气候条件下的波动和减产的风险水平，通过正态分布判别和偏态分布正态化，研究了西北地区春玉米不同年型减产率变化特征，分析了甘肃省玉米产量灾害风险的空间分布规律，以期为防灾减灾提供理论依据。结果显示：不同等级风险区域呈整体上分散、小面积连片的特点，河西地区减产率最高，其次为陇中地区。高风险区主要集中在陇东地区的东部，较高风险区分布在陇中、陇东大部分地区，河西地区通过灌溉可有效缓解旱灾，风险较低。不同减产率等级下风险分析可为春玉米产量风险预测及抗灾减损、农业保险指数制定和农业保险赔付等提供参考。（房世波）

2.20 中国农业气象模式（CAMM1.0）构建与应用

为发展适宜中国区域农业种植特点的农业气象模式，基于国外作物生长模拟方法，通过模式机理过程改进或重构以及应用方式革新，建立了中国农业气象模式（Chinese AgroMeteorological Model CAMM1.0）。CAMM1.0利用平均温度和土壤水分改进了作物发育进程模式，利用土壤水分改进了作物叶片光合作用、干物质分配和叶面积扩展过程模式，通过蒸发比法扩展了作物蒸散过程模式；自主建立了基于发育进程的冬小麦株高、基于遥感信息的作物灌溉、遥感数据同化、作物长势与灾害评价等模式。基于互联网技术构造了实时运转平台，主要功能包括作物生长过程实时常规模拟与用户个性化定制模拟。CAMM1.0的部分子模式采用多种方法构造，便于多模式集成。CAMM1.0对作物发育进程、光合过程、株高的模拟效果较好，但对土壤水分变化过程的拟合略差，模拟产量略偏低。CAMM1.0评价淮河流域夏玉米年际干旱减弱而涝渍增加的趋势与实际基本相符。（马玉平）

2.21 陕西苹果花期机理性预报模型的适用性评价

本文以陕西苹果花期为研究对象，基于4个机理性物候模型（顺序模型SM、平行模型PM、深度休息模型DRM和热时模型TTM），基于各果区代表站的花期数据及同期气象数据订正模型参数，利用内部检验和交叉验证（留一验证）的方法，评价模型在模拟花期上的适用性。结果表明：内部检验时各站点的最适模型各不相同，总体上SM和TTM均方根误差略低（3.30 d）；交叉验证时没有表现特别突出的模型，各模型平均的均方根误差为4.52 d，略高于内部检验。随后将TTM的参数，以两种方法（单站外推和求平均后外推）应用至果区内其他站。两种方法的均方根误差都高于国外同类研究（10.0 d），其中单站外推的均方根误差（5.90 d）又高于求平均后外推（7.21 d）。综合考虑模型的复杂性与模拟精度，推荐使用TTM并分果区模拟陕西苹果花期。（邬定荣）

2.22 江苏水稻高温热害气象指数保险风险综合区划

以江苏省为例，利用1980—2015年气象资料和水稻观测数据，基于Logistic曲线方程构建高温热害保险气象指数，并分别采用正态分布、正态对数分布和Weibull分布3种参数模型，以及基于信息扩散方法的非参数模型对水稻高温热害发生概率进行拟合。通过拟合优度检验发现，非参数模型可以较好地估算江苏各县水稻孕穗—抽穗扬花阶段高温热害发生概率，进而结合最优拟合模型，考虑农业保险的经营需求，从致灾因子危险性、孕灾环境敏感性、承灾体易损性、防灾减灾能力4个方面出发，确定相应评估指数并构建综合指数，采用聚类分析的方法进行县级水平的水稻高温热害保险风险综合区划。评估分析表明，江苏水稻高温热害保险风险呈现“西南高东北低”的特征，中高风险区是需要依靠农业保险转移风险的重点关注区域。（赵艳霞）

2.23 基于高时空分辨率的气候变化对全球主要农区气候生产潜力的影响评估

气候变化背景下，对全球主要农区气候生产潜力进行定量评估不仅可以反映出该地气候生产潜力水平与光、温、水资源配合协调的程度及地区差异，而且对提高土地生产力水平，指导农牧业生产具有重要意义。以全球主要农业区为研究对象，应用全球高时空分辨率气象格点资料和气候生产潜力模型，评估了1981—2015年气候变化对全球主要农区气候生产潜力的影响。结果表明，（1）1981—2015年全球主要农区气候生产潜力呈波动上升趋势，在7.68～8.28 t/hm2之间变化，平均为7.97 t/hm2，最大值出现在2010年，最小值出现在1987年。（2）同年际变化相似，气候生产潜力年代际增长也十分明显，其中20世纪80年代和20世纪90年代之间的增长最显著。（3）35年间，全球主要农业区平均农业气候生产潜力空间分布的基本特点是南高北低，区域差异显著。全球农业区主要集中在东亚、南亚、中亚、西亚、南欧、大洋洲南部、南美洲东部和北美洲南部等地，最高值出现在亚洲东南部，为28.9 t/hm2，北美洲南部、大洋洲南部、亚洲中部、非洲中部等地气候生产潜力较低，大部分地区在5.1 t/hm2以下。（4）35年间，亚洲西南部、中部和北部以及北美洲中部和东南部等地的农业区气候生产潜力显著提高，大部分地区提高了0.00～6.00 t/hm2；而在欧洲大部分地区、南美洲北部和东部、非洲中部和南部以及大洋洲大部分地区气候生产潜力明显减少，变化幅度在−7.99～0.00 t/hm2之间。总体而言，气候变化对亚洲和北美洲农业区农业生产有利，而对欧洲、南美洲、非洲和大洋洲农业生产不利。（赵俊芳）

2.24 基于APSIM模型的大气气溶胶直接辐射效应对我国玉米产量的影响评估

在大气气溶胶污染日益严重的时代背景下，气溶胶对农作物生长发育的影响越来越不可忽视。本文以全球气溶胶监测网（AErosol RObotic NETwork，AERONET）中具有常年观测数据的我国北京、香河和太湖为研究站点，利用AERONET 多年观测资料以及MODIS 地表反照率数据，借助6S（Second Simulation of a Satellite Signal in the Solar Spectrum）辐射传输模式，计算出2001—2014年研究站点的气溶胶直接辐射效应，评估了APSIM（Agricultural Production Systems Simulator）作物模型的适用性，运用验证适用的APSIM模型分析了气溶胶直接辐射效应对我国玉米产量的影响。结果表明：（1）验证后的APSIM 玉米模型在我国北京、香河和太湖玉米产区具有较好的适用性。APSIM 模型在模拟玉米的发育期以及产量中的模拟结果较好，其中各站点产量的相对均方根误差（NRMSE）为1.55%～6.24%，一致性指标（D）为0.80～0.99，决定系数（R2）为0.75～1.00。（2）气溶胶使得太阳直接辐射降低; 降低的趋势主要受气溶胶的净辐射通量的影响。2001—2014年期间北京、香河和太湖总辐射量分别降低31.95%、14.74%和28.30%。（3）气溶胶直接辐射效应造成玉米减产。2001—2014年期间气溶胶直接辐射效应使得北京、香河和太湖玉米产量分别减少28.44%、14.89%和13.43%。总体来说，2001—2014年期间大气气溶胶直接辐射效应使得我国北京、香河和太湖3 个高污染区的玉米产量减少13.43%～28.44%。（赵俊芳）

2.25 中国小麦干热风灾害研究进展

小麦干热风灾害是危害我国北方麦区的主要农业气象灾害之一。基于已有研究成果和实际灾情，从干热风的概念、分类及研究方法出发，对小麦干热风灾害的危害机理、气象环境成因、致灾指标、时空分布、监测预报及防御措施等方面进行了系统归纳阐述，并对未来小麦干热风灾害研究方向进行展望。我国小麦干热风灾害主要分为高温低湿型、雨后青枯型及旱风型3种，形成的气象环境成因主要受干热风天气系统、气候变暖、土壤墒情的影响，致灾指标主要分为形态学、气象学、综合指数指标。小麦干热风灾害的危害总体呈东西两边重、中间轻的分布格局，主要发生在黄淮海平原、河西走廊和新疆3个地区。气候变暖背景下，大部分地区的干热风年日数在20世纪80—90年代出现突变，近30年呈明显加重扩大趋势。基于土壤墒情影响的小麦干热风灾害等级指标构建、小麦干热风过程的灾害监测预警方法、气候变化背景下小麦干热风灾害时空分布新变化及其气象环境成因等是今后研究的重点方向。（霍治国）

2.26 江淮地区玉米涝渍指标构建及时空特征分析

江淮地区玉米涝渍灾害严重，研究揭示区域玉米涝渍灾害时空发生规律对科学开展区域防洪减灾具有重要意义。利用1981—2010年江淮地区18个站点地面气象观测数据和农业气象资料，基于作物水分盈余指数（CWSI），引入播种前底墒，根据玉米各生育阶段涝渍敏感性差异，采用层次分析法确定阶段涝渍灾害影响权重，构建适用于江淮地区玉米涝渍等级评估的玉米综合水分盈余指数（CWSIM），并根据典型涝渍年综合指数同对应减产率的线性回归方程，划分春、夏玉米不同等级涝渍的指标阈值。结果表明：（1）春玉米的轻、中、重涝指标阈值依次为：0.80≤CWSIM＜1.01，1.01≤CWSIM＜1.23，CWSIM≥1.23；夏玉米为：1.09≤CWSIM＜1.44，1.44≤CWSIM＜1.79，CWSIM≥1.79。（2）各阶段水分盈余指数（WSIM）分布规律，春玉米为：出苗—拔节期、拔节—吐丝期呈由北向南的纬向增加分布；吐丝—成熟期高值区位于安徽省西南临江一带、江苏省淮安市东部、扬州市及其周边区域，低值区位于安徽省北部及中部的中心区域、江苏省东南边缘，其余为中值区。夏玉米为：出苗—拔节期呈由北向南的纬向增加分布；拔节—吐丝期高值区位于江苏省东北部，低值区位于安徽省中部及临江一带，其余为中值区；吐丝—成熟期指数呈由西向东的经向增加分布。（3）江淮地区近30年，春玉米CWSIM值由北向南呈纬向增加分布。整体指数在不同时期的排序为1991—2000年＞1981—1990年＞2001—2010年；夏玉米CWSIM值由北向南呈近辐射状条带增加分布，不同时期指数排序为1991—2000年＞2001—2010年＞1981—1990年。安徽省沿江一带是玉米涝渍害发生的重灾区，且1991—2000年较其前后10年涝情最重。（霍治国）

2.27 湖南油菜春季涝渍灾变等级指标与灾损评估

以湖南省油菜春季涝渍灾害为例，创建基于涝渍过程的逐日灾变等级指标、灾害影响量化评价与灾损量化评估模型，探索区域农作物涝渍灾变动态监测评估的天气学方法。基于湖南省油菜春季涝渍灾变过程解析，以过程灾变判别指标为基础，采用基于假设的滚动模拟寻优、实际灾情验证与个例分析等方法，厘定轻度涝渍与重度涝渍灾变的最佳阈值，构建油菜春季涝渍过程逐日灾变等级指标；利用多元回归等方法，构建对应的灾害影响量化评价模型和减产率量化评估模型；基于个例分析，验证指标及模型结果与历史灾情记录的吻合情况。结果表明：湖南省轻度与重度涝渍灾变的最佳阈值为1.44；不同县涝渍灾变等级阈值存在一定差异，平均受灾频率越低，洪涝脆弱性越低，防灾减灾能力越强，阈值越高；基于受灾天数和重灾天数的灾害影响指数都表现为结荚期涝渍对油菜减产率影响更大，且两者的空间分布形势都与各县年平均减产率的空间分布形势基本一致；个例中，基于指标的全省重灾站数百分比的时间演变与实际灾情记录一致，减产率量化评估模型的结果也与实际灾损相匹配。油菜涝渍灾变等级指标、灾害影响指数及减产率量化评估模型，实现了对涝渍灾变过程等级的动态监测、影响与灾损的量化评估，为基于天气学方法开展区域油菜涝渍灾变等级的动态监测提供了理论支持和方法支撑，同时为历史灾情资料的补充和量化及灾情记录的再分析提供了可行的思路。（霍治国）

2.28 中国主要果树气象灾害指标研究进展

果树产业是我国广大农村农业经济收入的一项重要来源，对提高当地人民生活水平，促进当地农业经济发展具有重要意义。本研究采用分类归纳法，对我国现有主要果树气象灾害指标进行分类总结和系统阐述。从果树气象灾害指标基本概念出发，对果树气象灾害指标进行分类；分北方和南方两大区域，按照各自主要果树的气象灾害种类，综述了我国目前已有果树气象灾害指标，评述了各类指标的优缺点及适用性；从指标构成、指标构建方法、涉及果树种类、产业发展需求、创新的技术方法等方面，讨论了果树气象灾害指标研究存在的问题和未来发展方向，以期为我国主要果树的品种布局、产业优化、防灾减灾等提供信息参考，为我国果树产业健康、稳定、可持续发展提供科学保障。（霍治国）

2.29 土壤相对湿度对冬小麦干热风灾害发生的影响

以华北黄淮地区高温低湿型冬小麦干热风灾害为研究对象，基于逐日逐时气象资料、分层土壤水分资料、灾情资料等，采用历史灾情反演、独立t检验等方法，将灾情记录中无明确记载和有明确记载土壤相对湿度影响干热风灾害的样本分为A类和B类，基于两类样本相互独立，厘定各土层对干热风灾害有影响的土壤相对湿度阈值，利用随机预留样本验证阈值的合理性。结果表明：分层和整层土壤相对湿度阈值均随土层深度增加而增大，其中整层阈值平均值近似60%，独立样本检验符合率在80%左右。为便于业务应用，选取10～20 cm土层相对湿度60%为土壤相对湿度对冬小麦干热风灾害影响的临界阈值。当土壤相对湿度大于等于60%时，土壤相对湿度对冬小麦干热风灾害影响显著；当土壤相对湿度小于60%时，土壤相对湿度对冬小麦干热风灾害影响较小，独立样本检验符合率达82.5%。该文为量化评估土壤相对湿度对冬小麦干热风灾害的影响提供了科学依据。（霍治国）

2.30 江西省早稻雨洗花灾害时空变化及分区

雨洗花灾害是江西省早稻的主要农业气象灾害之一。基于1981—2017年江西省早稻种植区81个气象站逐日降水量资料和14个水稻观测站发育期和产量资料，利用旋转经验正交函数分解（REOF）等方法，探讨江西省早稻雨洗花灾害的时空变化和分区特征并得到典型场。结果表明：江西省早稻雨洗花灾害发生频率总体呈东北高、西南低，赣北南部高、两侧低的分布特征，高值区位于萍乡北部、宜春南部、新余、南昌、抚州北部至赣东北地区，发生频率在60%以上，低值区位于赣州和吉安西南部，发生频率低于40%。轻度雨洗花灾害持续影响江西省大部分地区，且自1992年以来呈现发生频率增加、影响范围扩大的趋势；重度灾害主要发生在赣东北，经历了两个活跃期和两个低发期。根据REOF分析结果，可将江西省早稻雨洗花灾害划分为赣北南部、赣中、赣东北、赣南和赣北北部5个区域。赣东北为重度雨洗花灾害高风险区，赣北南部为轻度雨洗花灾害高风险区，赣中、赣北北部为轻度雨洗花灾害次高风险区，赣南为雨洗花灾害低风险区。（霍治国）

2.31 基于改进后相对湿润度指数的山西省气象干旱时空特征

基于山西省境内较为均匀分布的70个地面气象观测站57年（1960—2016年）的逐日降水量、气温、日照时数、相对湿度、风速、水汽压等气象资料，选用国家标准中相对湿润度指数（M），在其基础上构建了改进的相对湿润度指数（M10i）作为干旱指标，以年、季为时间尺度，研究山西省干旱频率和强度的空间分布特征，并分析干旱频率和强度的年际变化规律。结果表明：改进的相对湿润度指数可很好地表征出典型干旱年；从57年的资料来看，山西干旱程度总体呈现加重的趋势；对比各年代干旱程度，以20世纪60年代干旱最轻，80年代和90年代干旱最为严重，90年代之后又呈现逐年代减轻的趋势；山西省干旱强度呈北高南低的分布，北部大部、太原中部干旱强度最强；冬季、春季干旱强度明显高于夏季和秋季；山西省历年特旱的频率明显高于其他等级的干旱，重旱频率略高于轻旱和中旱的频率；大多数年份，山西省冬季总干旱频率最高，春季次高，秋季较低，夏季最低。（霍治国）

2.32 用阴冷指数表征寒害程度的方法

针对现有寒害分析在因子选取上普遍缺少表述阴雨状况的问题，提出阴冷指数模型。基于农业和气象行业专家对海南各市县阴冷程度的排序，以及海南各市县1971—2010年逐日气象数据，采用均匀试验设计方法构建能反映低温强度和阴雨寡照综合作用的阴冷指数模型。依据阴冷指数模型，计算海南各市县1971—2010年历次阴冷过程的阴冷指数，按阴冷指数从大到小序列中的10%、30%和60%划分出重度、中度和轻度3级寒害及其指标，据此分析海南寒害的分布及变化。结果表明：寒害的地域分布特征与实际业务所监测的寒害情况相吻合，寒害的年际变化在《中国气象灾害大典》寒害记载中也得到了较好的印证，说明阴冷指数模型具有一定的实际应用性，可为寒害的监测、预警和评估提供新的技术方法。（霍治国）

2.33 湖南晚稻洪涝过程等级指标构建与演变特征

以湖南晚稻为研究对象，基于1961—2010年双季晚稻种植区68个气象站的降水资料、17个农业气象观测站的生育期观测资料，采用历史灾情反演方法，构建晚稻大田生长期3个生育时段、3个洪涝等级的洪涝灾害样本125个，应用Q-Q图拟合、W检验和r分布区间估计方法，计算晚稻分生育期（移栽—分蘖期、拔节—孕穗期、抽穗—成熟期）不同洪涝致灾等级（轻、中、重）的过程降水量临界值，构建晚稻洪涝过程等级指标，并进行独立样本验证检验；应用M-K检验等方法分析1961—2010年湖南晚稻洪涝的时空演变特征。结果表明：指标验证与历史记录有较高一致性；同一洪涝等级的指标阈值从大到小依次为抽穗—成熟期、拔节—孕穗期、移栽—分蘖期；20世纪60年代和90年代是湖南晚稻洪涝发生最严重的年代，总洪涝次数在1994年发生突变；晚稻轻涝在抽穗—成熟期发生率最高，中涝和重涝在拔节—孕穗期发生率最高；总洪涝的高发地区位于郴州、岳阳地区；随年代推移，晚稻各等级洪涝和总洪涝高发区均呈现由北向南的变化。（霍治国）

2.34 基于分期播种试验的冬小麦越冬冻害调查分析

基于冬小麦分期播种试验，结合自然大田冬小麦越冬冻害调查实况资料，分析研究2017/2018年偏冷冬年份华北北部冬小麦越冬冻害的成因及对产量的影响。结果表明：适应气候变暖，冬小麦播期推迟，但华北北部播种期不应晚于10月21日，播种期推迟或秸秆还田，应加大播种量，确保出苗率和基本苗。品种推广和生产选种时宜冬性和半冬性品种搭配种植，防御出现“冷冬”导致冬小麦越冬冻害的潜在风险。越冬冻害死苗率每增加1%，其产量减少约1 kg/hm2。冬小麦播种期受降雨且降水多的影响，晚播、播种质量差以及品种冬性与春性特性差异、除草农药使用不当等是越冬冻害死苗率增加的主要原因。（赵花荣）

2.35 不同时期灌水对冬小麦干热风的防御效应

灾前灌水是防御灾害发生的有效措施，为掌握灌水的关键发育期及适宜灌水量，在防雨棚和自然大田进行冬小麦抽穗期、开花期、灌浆初期灌水试验。结果表明：在开花期，灌水100、150 mm自然大田干热风穗的发生率比遮雨棚降低31.77%、32.85%，而穗粒重自然大田比防雨棚提高12.25%、5.45%；无论开花期还是抽穗—灌浆初期，灌水处理的千粒重均比对照大，防雨棚中随灌水时间推后千粒重逐渐增大，而自然大田以开花期灌水千粒重最大，为47.664 g。灌水100、150 mm处理，灌水效率自然大田均比防雨棚高，且均以开花期灌水效率最高，为4.110 g/(m2·mm)，防雨棚灌水150 mm比灌水100 mm高约0.2 g/(m2·mm)，而自然大田受自然降水补给调节土壤水分，灌水150 mm比灌水100 mm低0.565～1.301 g/(m2·mm)。灌水对干热风防御效应效果自然大田较防雨棚更为显著，且以开花期灌水效应最为显著。（赵花荣）