基于热量指数的东北春玉米冷害指标
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摘要
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%。
Chilling damage is one of the most destructive disasters for spring maize in Northeast China(Heilongjiang Province, Jilin Province, and Liaoning Province). Proper indicators of spring maize chilling damage are important for understanding the spatio-temporal distribution characteristics of disaster, dynamic monitoring, early warning, and conducting risk assessment. Therefore, it is of great scientific significance for the safe production and reasonable spatial planting of spring maize in China. Daily time series of air temperature during the past 55 years(1961 — 2015) at 82 meteorological stations, phenology at different developmental stages of spring maize from 1981 to 2013 at 61 agro-meteorological stations, and historical chilling damage records during the past 55 years(1961 — 2015) are jointly used to establish chilling damage indicators of spring maize at different developmental stages. The heat index with significant biological basis is selected as a factor, and its average at different developmental stages of spring maize is calculated based on three physiological temperatures. And then, 15 heat index sets of spring maize chilling damage samples collected from historical disaster records are built in the context of the combinations of five developmental stages of spring maize(seedling to clover, clover to jointing, jointing to blossom, blossom to milk, milk to physiological maturity) and three chilling damage levels(light,moderate,and severe). KolmogorovSmirnov(K-S) test method is used in checking the best distribution fitting functions of the heat index sets,and 15 normal distribution functions are established by comparing three fitting functions, including normal distribution,exponent distribution, and evenly distribution. Each critical threshold of spring maize chilling damage levels at different developmental stages is determined by using the upper limit of 95% confidence interval. The rationality of the spring maize chilling damage indicator is validated by using 25 independent samples. Results show that the verification based on the spring maize chilling damage level indicators is detected to be basically consistent with historical records, with 80% assessment being thoroughly consistent and all the errors of validation samples being within one level. Meanwhile, consistent rates of chilling damage indicators for three chilling damage levels are all above 75%.
Chilling damage is one of the most destructive disasters for spring maize in Northeast China(Heilongjiang Province, Jilin Province, and Liaoning Province). Proper indicators of spring maize chilling damage are important for understanding the spatio-temporal distribution characteristics of disaster, dynamic monitoring, early warning, and conducting risk assessment. Therefore, it is of great scientific significance for the safe production and reasonable spatial planting of spring maize in China. Daily time series of air temperature during the past 55 years(1961 — 2015) at 82 meteorological stations, phenology at different developmental stages of spring maize from 1981 to 2013 at 61 agro-meteorological stations, and historical chilling damage records during the past 55 years(1961 — 2015) are jointly used to establish chilling damage indicators of spring maize at different developmental stages. The heat index with significant biological basis is selected as a factor, and its average at different developmental stages of spring maize is calculated based on three physiological temperatures. And then, 15 heat index sets of spring maize chilling damage samples collected from historical disaster records are built in the context of the combinations of five developmental stages of spring maize(seedling to clover, clover to jointing, jointing to blossom, blossom to milk, milk to physiological maturity) and three chilling damage levels(light,moderate,and severe). KolmogorovSmirnov(K-S) test method is used in checking the best distribution fitting functions of the heat index sets,and 15 normal distribution functions are established by comparing three fitting functions, including normal distribution,exponent distribution, and evenly distribution. Each critical threshold of spring maize chilling damage levels at different developmental stages is determined by using the upper limit of 95% confidence interval. The rationality of the spring maize chilling damage indicator is validated by using 25 independent samples. Results show that the verification based on the spring maize chilling damage level indicators is detected to be basically consistent with historical records, with 80% assessment being thoroughly consistent and all the errors of validation samples being within one level. Meanwhile, consistent rates of chilling damage indicators for three chilling damage levels are all above 75%.
引文
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[11]朱红蕊,刘赫男,张洪玲,等.黑龙江省玉米低温冷害风险评估及预估.气候变化研究进展,2015,11(3):173-178.
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[14]侯琼,王海梅,云文丽.河套灌区玉米低温冷害监测评估指标的研究.干旱区资源与环境,2015,29(2):179-184.
[15]陈凯奇,米娜.辽宁省玉米低温冷害和霜冻灾害风险评估.气象与环境学报,2016,32(1):89-94.
[16]李蕊,郭建平.东北春玉米积温模型的改进与比较.应用气象学报,2017,28(6):678-689.
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[19]王春乙.东北地区农作物低温冷害研究.北京:气象出版社,2008.
[20]高素华.玉米延迟型低温冷害的动态监测.自然灾害学报,2003,12(2):117-121.
[21]刘布春,王石立,庄立伟,等.基于东北玉米区域动力模型的低温冷害预报应用研究.应用气象学报,2003,14(5):616-625.
[22]杨若子,周广胜.1961-2013年东北三省玉米低温冷害强度的时空分布特征.生态学报,2016,36(14):4386-4394.
[23]吕厚荃.中国主要农区重大农业气象灾害演变及其影响评估.北京:气象出版社,2011.
[24]蔡菁菁,王春乙,张继权.东北地区玉米不同生长阶段干旱冷害危险性评价.气象学报,2013,71(5):976-986.
[25]马树庆,刘玉英,王琪.玉米低温冷害动态评估和预测方法.应用生态学报,2006,17(10):1905-1910.
[26]李祎君,王春乙.东北地区玉米低温冷害综合指标研究.自然灾害学报,2007,16(6):15-20.
[27]温克刚.中国气象灾害大典(辽宁卷).北京:气象出版社,2005.
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[29]温克刚.中国气象灾害大典(黑龙江卷).北京:气象出版社,2007.
[30]中国气象局.中国气象灾害年鉴.北京:气象出版社,2005-2014.
[31] Massey E J. The Kolmogorov-Smirnov test of goodness of fit.J Am Stat Assoc,1951,46:68-78.
[32]霍治国,李世奎,王素艳,等.主要农业气象灾害风险评估技术及其应用研究.自然资源学报,2003,18(6):692-703.
[33]盛骤,谢式千,潘承毅.概率论与数理统计.北京:高等教育出版社,1989.
[34] Wu X,Wang P J,IIuo Z G. et al. Crop drought identification index for winter wheat based on evapotranspiration in the IIuang-IIuai-IIai Plain, China. Agriculture, Ecosystems and Environment, 2018,263:18-30.
[35]郭建平,庄立伟,陈玥熤.东北玉米热量指数预测方法研究(Ⅰ)——热量指数与玉米产量.灾害学,2009,24(4):6-10.
[36] Yang J Y,IIuo Z G,Wu L,et al. Indictor-based evaluation of spatiotemporal characteristics of rice flood in Southwest China. Agriculture, Ecosystems and Environment,2016,230:221-230.
[37]汪天颖,霍治国,李旭辉,等.基于生育时段的湖南省早稻洪涝等级指标及时空变化特征.生态学杂志,2016,35(3):709-718.
[38]张桂香,霍治国,杨建莹,等.江淮地区夏玉米涝渍灾害时空分布特征和风险分析.生态学杂志,2017,36(3):747-756.
[39]杨宏毅,霍治国,杨建莹,等.江汉和江南西部春玉米涝渍指标及风险评估.应用气象学报,2017,28(2):237-246.
[40]郭建平,马树庆.农作物低温冷害监测预测理论和实践.北京:气象出版社,2009.
[2]杨菲云,郭建平,马树庆,等.QX/T167—2012北方春玉米冷害评估技术规范行业标准.北京:气象出版社,2012.
[3] Miedema P. The effects of low temperature on Zea mays. Advances in Agronomy,1982,35:93-128.
[4]郭春明,任景全,曹铁华,等.春玉米穗分化期低温对产量构成因素的影响.应用气象学报,2018,29(4):505-512.
[5]马树庆,王琪,王春乙,等.东北地区玉米低温冷害气候和经济损失风险分区.地理研究,2008.27(5):1169-1177.
[6]郭建平,田志会,张涓涓.东北地区玉米热量指数的预测模型研究.应用气象学报,2003,14(5):626-633.
[7]高晓容,王春乙,张继权,等.东北地区玉米主要气象灾害风险评价与区划.中国农业科学,2014,47(24):4805-4820.
[8]初征,郭建平.未来气候变化对东北玉米品种布局的影响.应用气象学报,2018,29(2):165-176.
[9]赵俊芳,杨晓光,刘志娟.气候变暖对东北三省春玉米严重低温冷害及种植布局的影响.生态学报,2009, 29(12):6544-6551.
[10]张梦婷,刘志娟,杨晓光,等.气候变化背景下中国主要作物农业气象灾害时空分布特征:东北春玉米延迟型冷害.中国农业气象,2016,37(5):599-610.
[11]朱红蕊,刘赫男,张洪玲,等.黑龙江省玉米低温冷害风险评估及预估.气候变化研究进展,2015,11(3):173-178.
[12]中国气象局.QX/167-2012.北方春玉米冷害评估技术规范.北京:气象出版社,2012.
[13]杜春英,姜丽霞,朱海霞,等.基于积温距平的玉米冷害动态评估及其与玉米产量的关系.灾害学,2016,31(4):42-48.
[14]侯琼,王海梅,云文丽.河套灌区玉米低温冷害监测评估指标的研究.干旱区资源与环境,2015,29(2):179-184.
[15]陈凯奇,米娜.辽宁省玉米低温冷害和霜冻灾害风险评估.气象与环境学报,2016,32(1):89-94.
[16]李蕊,郭建平.东北春玉米积温模型的改进与比较.应用气象学报,2017,28(6):678-689.
[17]李蕊,郭建平.东北春玉米非线性积温模型参数改进.应用气象学报,2018,29(2):154-164.
[18]唐余学,郭建平.我国东北地区玉米冷害风险评估.应用气象学报,2016,27(3):352-360.
[19]王春乙.东北地区农作物低温冷害研究.北京:气象出版社,2008.
[20]高素华.玉米延迟型低温冷害的动态监测.自然灾害学报,2003,12(2):117-121.
[21]刘布春,王石立,庄立伟,等.基于东北玉米区域动力模型的低温冷害预报应用研究.应用气象学报,2003,14(5):616-625.
[22]杨若子,周广胜.1961-2013年东北三省玉米低温冷害强度的时空分布特征.生态学报,2016,36(14):4386-4394.
[23]吕厚荃.中国主要农区重大农业气象灾害演变及其影响评估.北京:气象出版社,2011.
[24]蔡菁菁,王春乙,张继权.东北地区玉米不同生长阶段干旱冷害危险性评价.气象学报,2013,71(5):976-986.
[25]马树庆,刘玉英,王琪.玉米低温冷害动态评估和预测方法.应用生态学报,2006,17(10):1905-1910.
[26]李祎君,王春乙.东北地区玉米低温冷害综合指标研究.自然灾害学报,2007,16(6):15-20.
[27]温克刚.中国气象灾害大典(辽宁卷).北京:气象出版社,2005.
[28]温克刚.中国气象灾害大典(吉林卷).北京:气象出版社,2008.
[29]温克刚.中国气象灾害大典(黑龙江卷).北京:气象出版社,2007.
[30]中国气象局.中国气象灾害年鉴.北京:气象出版社,2005-2014.
[31] Massey E J. The Kolmogorov-Smirnov test of goodness of fit.J Am Stat Assoc,1951,46:68-78.
[32]霍治国,李世奎,王素艳,等.主要农业气象灾害风险评估技术及其应用研究.自然资源学报,2003,18(6):692-703.
[33]盛骤,谢式千,潘承毅.概率论与数理统计.北京:高等教育出版社,1989.
[34] Wu X,Wang P J,IIuo Z G. et al. Crop drought identification index for winter wheat based on evapotranspiration in the IIuang-IIuai-IIai Plain, China. Agriculture, Ecosystems and Environment, 2018,263:18-30.
[35]郭建平,庄立伟,陈玥熤.东北玉米热量指数预测方法研究(Ⅰ)——热量指数与玉米产量.灾害学,2009,24(4):6-10.
[36] Yang J Y,IIuo Z G,Wu L,et al. Indictor-based evaluation of spatiotemporal characteristics of rice flood in Southwest China. Agriculture, Ecosystems and Environment,2016,230:221-230.
[37]汪天颖,霍治国,李旭辉,等.基于生育时段的湖南省早稻洪涝等级指标及时空变化特征.生态学杂志,2016,35(3):709-718.
[38]张桂香,霍治国,杨建莹,等.江淮地区夏玉米涝渍灾害时空分布特征和风险分析.生态学杂志,2017,36(3):747-756.
[39]杨宏毅,霍治国,杨建莹,等.江汉和江南西部春玉米涝渍指标及风险评估.应用气象学报,2017,28(2):237-246.
[40]郭建平,马树庆.农作物低温冷害监测预测理论和实践.北京:气象出版社,2009.