两种不同产量历史丰歉气象影响指数确定方法在农业气象产量预报中的对比研究

利用吉林省1980—2015年春玉米单产数据、50个气象站逐日气象资料,基于欧式距离和相关系数建立综合诊断指标,利用综合诊断指标研究分析预报年与历史年春玉米气象产量丰歉气象影响指数的关系,以此构建春玉米产量预报模型,对吉林省春玉米产量进行动态预报。产量预报模型对2003—2012年的预报试验结果表明,产量丰歉趋势ΔY的平均正确率均在60%以上,加权分析法的单产预报准确率除2009年外,均高于80.0%,且各时段的预报准确率均高于大概率法的。对2013—2015年吉林省春玉米产量的预报检验结果表明,加权分析法对产量丰歉趋势ΔY的预报结果稍好;加权分析法单产预报准确率几乎都在90.0%以上,普遍高于大概率法的。说明加权分析法建立的产量预报模型预报效果更好,可在业务上应用。     

基于关键气象因子的河北省马铃薯产量预报

基于1983—2019年河北省马铃薯产量数据及同期河北省21个气象站逐旬平均气温、降水量、日照时数,采用因子膨化及相关分析方法,确定影响河北省马铃薯产量的关键气象因子,建立马铃薯产量预报模型,并利用预报模型对1983—2015年马铃薯产量进行回代检验,对2016—2019年马铃薯单产进行预报。结果表明:马铃薯产量对7—9月的气温、日照时数比较敏感,且气温对马铃薯产量的影响大于日照时数。各起报时间预报产量趋势回代检验正确率为75.7%~91.7%,预报产量回代检验准确率为83.6%~91.4%;2016—2019年历年产量预报准确率为83.5%~95.3%,且随着起报时间的后移,预报准确率逐渐提高。     

中国油菜产量动态预报方法研究

油菜是我国主要的油料作物之一,开展油菜产量动态预报对农业生产和国家食物安全都具有重要意义.利用全国及主产区油菜产量资料、发育期资料、生理气象指标、日最高气温、日最低气温、日降水量和日日照时数等资料,通过相似系数和欧氏距离建立综合诊断指标,根据历史年油菜产量丰歉气象影响指数,研究分析预报年的油菜产量丰歉气象影响指数,以此建立全国、各主产区油菜产量动态预报方法.结果表明,预报试验和预报检验的丰歉趋势预报正确率、实际单产预报准确率均较高,能够满足业务服务的需要.该方法可使业务预报的时效提前,并实现动态跟踪预报,具有良好的业务应用前景.     

基于AEZ模型的产量动态预报研究

利用洛阳地区1981-2014年夏玉米产量资料、9个气象站点的逐日观测资料、农田0-50 cm土壤墒情资料,结合夏玉米生物学特性,采用农业生态区域法(AEZ模型),计算了夏玉米不同生长阶段的气候生产潜力,通过气候生产潜力与夏玉米产量的相关关系,建立以旬为尺度的夏玉米产量动态预报模型,并进行历史回代和试报检验。结果表明:气候生产潜力与夏玉米单产增减率呈显著正相关,气候生产潜力可以客观地反映夏玉米单产水平及其动态变化。构建的产量动态预报模型对1981-2010年单产历史回代检验的准确率为88.3%~90.7%,单产丰歉趋势回代检验准确率为65.5%~75.9%;对2011-2014年模型准确性试报检验,单产预报准确率为82.7%~87.5%,趋势预报准确率为50.0%~100.0%。     

早稻产量综合动态预报方法研究

利用湖南省早稻产量与发育期、日最高气温、日最低气温、日降水量和日日照时数等资料及早稻生理气象指标,在丰歉气象影响指数动态预报方法的基础上,引进早稻生育期内对产量有较大影响的关键气象因子,建立了早稻产量综合动态预报方法.结果表明,该方法在早稻产量增减趋势预报和定量预报上,正(准)确率都有所提高.     

春玉米产量动态预报技术的改进方法探索

为及时、准确地进行玉米产量预报,为吉林省玉米产量预报业务提供参考依据,为政府调控提供科技支撑,利用吉林省19802016年春玉米产量和50个气象站逐日气温、降水量、日照时数等资料,基于相似距离和相关系数构建综合诊断指标筛选气温、降水量、日照时数等各类气象要素历史相似年,根据各类气象要素历史相似年与预报年的玉米产量丰歉气象影响指数之间的关系,建立吉林省春玉米产量动态预报模型。同时,对历史相似年的筛选方法进行改进,利用欧氏距离直接筛选综合气候历史相似年,根据气候历史相似年与预报年的玉米产量丰歉气象影响指数之间的关系,构建春玉米产量预报模型。对比改进前、后的产量预报模型的预报,结果表明:两种方法在吉林省玉米单产预报中,预报准确率均较高,普遍在85%以上。产量预报模型对20022013年的预报检验结果表明,改进方法后20022013年单产预报平均准确率提高了3.9个百分点,均方根误差降低了4个百分点,标准差降低了2。对20142016年的预报检验结果表明,改进方法的玉米产量预报结果优于传统方法的预报结果。改进方法比传统方法准确率更高,稳定性更强,应用价值更高。     

渭南市冬小麦产量预报模型研究

利用1998—2012年渭南市气象与冬小麦产量数据,利用直线滑动平均模拟趋势产量,结合调和权重法预测趋势产量,采用SPSS20.0软件对气象产量进行逐步回归,得到年景和定量气象产量预测模型。统计趋势产量与气象产量合计值,得到年景(或定量)预报产量。通过验证,年景和定量产量预报准确率较高。     

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。     

荆州市冬小麦产量动态预报方法对比研究

利用湖北省荆州市1970—2016年日照、降水、温度及冬小麦生长期、产量数据,采用作物丰歉指数、气候适宜指数方法,开展了荆州市冬小麦产量动态预报,并对两种预报方法的效果进行检验。结果表明,丰歉指数方法的预报准确率高于气候适宜指数法,计算过程也相对简单。在产量预报精度不下降的前提下,4月10日可作为产量预报的最优预报日期。     

夏玉米产量动态预报方法研究

利用洛阳市1981—2014年夏玉米产量资料、生育期内的气象资料,结合夏玉米的生物学特性,分别构建夏玉米温度、光照、水分适宜度模型,利用夏玉米生长季内不同时段的气候适宜度指数与气象产量的相关关系,构建夏玉米产量预报模型,并分别利用1981—2010年、2011—2014年数据进行回代、预报检验。结果表明,气候适宜度与夏玉米气象产量存在显著的相关性,两者变化趋势一致。1981—2010年各时段预报模型的单产回代检验准确率在89.19%~91.42%之间,趋势回代检验准确率达89.66%~96.55%。2011—2014年预报检验,预报准确率最高为96.16%,最低为91.05%,趋势预报准确率最高为100%,最低为75%,预报准确率较高,建立的产量动态预报模型可以在业务上推广应用。     

Crop yield model validation for Cameroon

A crop simulation model must first be capable of representing the actual performance of crops grown in any region before it can be applied to the prediction of climate variability and change impacts. A cropping systems model (CropSyst) simulations of crop productivity in the sub-Saharan Central African (using Cameroon as the case study) region, under the current climate were compared with observed yields of maize, sorghum, groundnut, bambara groundnut and soybean from eight sites. The model produced both over-and-under estimates, but with a mean percentage difference of only –2.8%, ranging from –0.6% to –4.5%. Based on these results, we judged the CropSyst simulations sufficiently reliable to justify use of the model in assessing crop growth vulnerability to climatic changes in Cameroon and else where.     

黑龙江省产量预报评分系统

随着农业气象业务现代化的建设和农业气象工作的深入及拓展 ,对农业气象情报预报工作提出了更高的要求和更多的任务。产量预报是农业气象情报预服务的重要组成部分 ,是政府部门制定粮食计划和农业生产决策不可缺少的依据和信息。该评分系统对产量预报准确与否进行检验 ,以保证信息的可靠性。1　系统运行的硬件和软件环境产量预报评分系统运行的硬件是 586以上档次微机。另有辅助设备数字化仪 (ＳｕｍｍａＳｋｅｔｃｈⅢ )、彩色打印机 ( )ＥＰＳＯＮＬＱ -1 60 0 )、鼠标 (ＭｉｇｈｔｙＣＡＴ)。系统运行于Ｗｉｎｄｏｗｓ环境下 ,支持中西文…     

Weather yield model for the semi tropical region (Pakistan)

Weather models are essential tools for checking of the effect of the weather elements in terms of their effect on the production of the crop. This research is an attempt to see the effect of only two variables i.e., temperature and rainfall for the division Faisalabad (semitropical region of Pakistan).The model fitted is of the linear form:the values of a,b, c have been found. The expected yield has been calculated by using the aridity indices (X1 and X2 ) and the result in the form of coefficient of determination R2 has been found equal to 0.166. The significance of the regression coefficient has been tested, which shows that the contribution to the yield from aridity index at germination and that at ripening is significant.The wheat yields are the results of a wide variety of variables, most of which show varying degree of relationship with one another, some positive and some negative in terms of output. These variables may be technology, fertilizers, pesticides, epidemics, kinds of seeds used, market price of crop and the area under cultivation etc, which can be the source of variation in the wheat yield. Since rainfall during germination and temperature at the ripening periods are the necessary factors for the yield of wheat, for this purpose these parameters have been studied in order to their contribution.     

Quantitative evaluation of climatic variability and risks for wheat yield in India

This study comprises (1) an analysis of recent climate trends at two sites in north-west India (Ludhiana in Punjab and Delhi) and (2) an impact and risk assessment for wheat yields associated with climatic variability. North-west Indian agriculture is dominated by rice-wheat rotation in which the wheat season (‘rabi’, November to March) is characterized by predominantly dry conditions—superimposed by very high inter-annual variability of rainfall (17 to 260 mm in Ludhiana and <1 to 155 mm in Delhi). While rainfall remained without discernable trend over the last three decades, minimum and average temperatures showed increasing trends of 0.06 and 0.03°C year^???1, respectively, at Ludhiana. The site in (metropolitan) Delhi was apparently influenced by city-effects, which was noticeable from the decrease in solar radiation of 0.09 MJ m^???2 day^???1 year^???1. The CERES-wheat model was used to calculate yields of rainfed wheat that were at both locations highly correlated with seasonal rainfall. An assessment framework was developed to quantify yield impacts due to rainfall variability in three steps: (1) data from different years were aggregated into four classes, i.e., years with scarce, low, moderate, and high rainfall, (2) yield records of each rainfall class were ranked according to yield to facilitate (3) a comparison of yields with identical rank, i.e. among the best yield of each class, the second-best, etc. The class with moderate rainfall was taken as baseline yield to compute yield impacts of other rainfall scenarios. Years with scarce rainfall resulted in only 34% (Ludhiana) and 35% (Delhi) of the baseline yield. The yields in years with low rainfall accounted for 61% (Delhi) and 49% (Ludhiana) of the baseline yields. In Ludhiana, high rainfall years resulted in 200% yield as compared to the baseline yield, whereas they reached only 105% in Delhi. Low-intensity (1× and 3×) irrigation decreased the relative yield losses, but entailed a higher vulnerability in terms of absolute yield losses. Only high-intensity (4×) irrigation buffered wheat yields against adverse rainfall years. Early sowing was beneficial for wheat yields under all rainfall scenarios. The framework could be a valuable decision-support tool at the farm level where seasonal rainfall variability is high.     

施秉县油菜高产栽培的气候条件及防灾对策

从施秉县气候变化出发，分析了施秉县油菜高产栽培生长发育过程中对光、热、水等气象条件的需求，并就早苔早花、“湿害”、冰雹等灾害进行了防治对策的探讨。     

Climate and global grain yield variability

Historical grain yields from several countries were analyzed to determine the variability of grain yield. This was accomplished by assuming a linear technology trend and analyzing the deviations from this trend. The deviation was assumed to be primarily an effect of weather. Using 10 percent deviation from trend as a threshold, it was determined that for each of seven countries the probability of a poor yield year ranged from 17 in India and the United States to 33 percent in Canada and the U.S.S.R. The probability of two consecutive poor wheat yield years was highest in Canada (17 percent) and lowest in Argentina (6 percent). The probability of a poor year occurring in the same year in both the United States and the U.S.S.R. was about 7–8 percent. The highest variability in yield has occurred in Canada, but variability in India has increased substantially since the 1960's.     

A New Economic Assessment Index for the Impact of Climate Change on Grain Yield

The impact of climate change on agriculture has received wide attention by the scientific community. This paper studies how to assess the grain yield impact of climate change, according to the climate change over a long time period in the future as predicted by a climate system model. The application of the concept of a traditional ＂yield impact of meteorological factor （YIMF）＂ or ＂yield impact of weather factor＂ to the grain yield assessment of a decadal or even a longer timescale would be suffocated at the outset because the YIMF is for studying the phenomenon on an interannual timescale, and it is difficult to distinguish between the trend caused by climate change and the one resulting from changes in non-climatic factors. Therefore, the concept of the yield impact of climatic change （YICC）, which is defined as the difference in the per unit area yields （PUAY） of a grain crop under a changing and an envisaged invariant climate conditions, is presented in this paper to assess the impact of global climate change on grain yields. The climatic factor has been introduced into the renowned economic Cobb-Douglas model, yielding a quantitative assessment method of YICC using real data. The method has been tested using the historical data of Northeast China, and the results show that it has an encouraging application outlook.     

金溪茶叶生产气候条件论证及高产对策

根据茶叶的生长特性，从气候学的角度讨论了在金溪县种植茶叶的可行性，并提出了具体的高产对策。     

马铃薯优质高产气候指标及灾害防御方法

通过商洛市7县区1991—2015年马铃薯生育期监测资料和气象观测资料对比分析,结合多元回归分析计算结果,得出了商洛马铃薯优质高产所需的光、温、水气候指标;找出影响商洛马铃薯优质高产的主要气象灾害(春季冻害,块茎膨大期连阴雨)及发生指标,确定了马铃薯生长期内主要病虫害(晚疫病和早疫病)及发生指标;提出针对性的防御方法,为各级政府和农民采取科学合理的管理措施提供依据,为商洛马铃薯优质高产提供技术支撑。     

江苏省单季晚稻产量预报的分段加权动态模式

本文利用灰色系统GM(1,1)模型逐段滑动平均模拟趋势产量y_t,根据单季晚稻的穗数、粒数和粒重对最终产量的贡献确定出生育三个阶段的权重,算出各阶段的气象产量。通过MAICE逐步回归方法分别建立各介生育阶段末气候产量的预测模式,分段加权动态地进行单季晚稻的产量预测。最后还作了1986—1988年产量的试报。