基于小波分析的水稻生育期气象因子对产量的影响
|
摘要
为水稻产量趋势化及定量化预报提供依据,对水稻全生育期气象因子与产量的影响关系进行分析。提取1986—2015年间辽宁省水稻产量数据和同期时序气象数据,对水稻气象产量及同期时序气象因子进行连续小波分析,研究水稻气象产量、日照时数、日平均气温等气象因子的时序变化特征;分别利用相干小波分析和交叉小波分析方法,研究水稻气象产量与日照时数、日平均气温等气象因子的相互关系。结果表明:1)辽宁省水稻气象产量存在5~8年和2~3年的显著周期,自2001年之后,水稻在频率上的能量强弱分布不显著,表明气象产量连续丰年的周期在变长;2)对水稻生育期内的气象因子进行连续小波分析,其中除总降水量外,其他气象因子均都存在不同的显著周期。
By assessing the influence of the meteorological factors during the whole growth stage of rice on its yield, this study determined rice production trend, thus laying foundations for quantitatively forecasting rice yield. The influential factors on rice yield were identified based on the analysis of extracted rice yield data and the corresponding meteorological data from 1986 to 2015 in Liaoning Province. The continuous wavelet analysis was performed to evaluate the meteorological yield of rice and the meteorological factors during this period, which revealed the temporal variation patterns of meteorological factors such as rice meteorological yield,and daily average temperature and sunshine time. Cross wavelet analysis and wavelet coherence analysis were conducted to determine the relations between the meteorological yield of rice and meteorological factors such as daily average temperature and sunshine time.Results are as follows. Firstly, the meteorological yield of rice in Liaoning Province had significant cycles of 5—8 years and 2—3 years; since 2001, the meteorological yield of rice showed insignificant frequency distribution of energy intensity, indicating that the cycle of continuous years with high meteorological yield became longer. Secondly. continuous wavelet analysis was performed to assess the temporal variation patterns of total precipitation, sunshine hours, precipitation, average temperature, the difference in average temperature between day and night, the average of the lowest temperature, the highest temperature of everyday, relative humidity, and total wind speed in the reproductive period of rice; as a result, all these meteorological factors except total precipitation had significant cycles.
By assessing the influence of the meteorological factors during the whole growth stage of rice on its yield, this study determined rice production trend, thus laying foundations for quantitatively forecasting rice yield. The influential factors on rice yield were identified based on the analysis of extracted rice yield data and the corresponding meteorological data from 1986 to 2015 in Liaoning Province. The continuous wavelet analysis was performed to evaluate the meteorological yield of rice and the meteorological factors during this period, which revealed the temporal variation patterns of meteorological factors such as rice meteorological yield,and daily average temperature and sunshine time. Cross wavelet analysis and wavelet coherence analysis were conducted to determine the relations between the meteorological yield of rice and meteorological factors such as daily average temperature and sunshine time.Results are as follows. Firstly, the meteorological yield of rice in Liaoning Province had significant cycles of 5—8 years and 2—3 years; since 2001, the meteorological yield of rice showed insignificant frequency distribution of energy intensity, indicating that the cycle of continuous years with high meteorological yield became longer. Secondly. continuous wavelet analysis was performed to assess the temporal variation patterns of total precipitation, sunshine hours, precipitation, average temperature, the difference in average temperature between day and night, the average of the lowest temperature, the highest temperature of everyday, relative humidity, and total wind speed in the reproductive period of rice; as a result, all these meteorological factors except total precipitation had significant cycles.
引文
[1]陈柏林.气候对常德地区水稻产量的影响[J].气象学报,1983(4):452-459.
[2]涂悦贤.广东省水稻生产与农业气候的关系[J].热带地理,1989(2):108-116.
[3]许信旺,孙满英,方宇媛,等.安徽省气候变化对水稻生产的影响及应对[J].农业环境科学学报,2011,30(9):1755-1763.
[4]张宇,王馥棠.气候变暖对我国水稻生产可能影响的数值模拟试验研究[J].应用气象学报,1995(增刊1):19-25.
[5]沈陈华.气象因子对江苏省水稻单产的影响[J].生态学报,2015,35(12):4155-4167.
[6]唐余学,罗孳孳,范莉,等.基于关键气象因子的中稻单产动态预报[J].中国农业气象,2011,32(增刊1):140-143.
[7]GRINSTED A,MOORE J C,JEVREJEVA S.Application of the cross wavelet transform and wavelet coherence to geophysical time series[J].Nonlinear Processes in Geophysics,2004,11(5/6):561-566.
[8]陈涛,孙卫国,程炳岩.交叉小波变换在河南降水时频分析中的应用[J].南京气象学院学报,2002,25(5):685-692.
[9]LONNIE H,HUANG J P.Bivariate wavelet analysis of Asia monsoon and ENSO[J].Advances in Atmospheric Sciences,1996,13(3):299-312.
[10]魏中海,王建勇,夏宣炎.粮食产量预测的因子处理和建模方法[J].华中农业大学学报,2004,23(6):680-684.
[11]刘占明,陈子燊,路剑飞,等.广东北江流域降水时空分布及其与Nio3区SST相关性分析[J].自然资源学报,2013,28(5):786-798.
[12]余丹丹,张韧,洪梅,等.基于交叉小波与小波相干的西太平洋副高与东亚夏季风系统的关联性分析[J].南京气象学院学报,2007(6):755-769.
[13]TORRENCE C,COMPO G P.A practical guide to wavelet analysis[J].Bulletin of the American Meteorological Society,1998,79(1):61-78.
[14]徐科军,李永三.基于连续小波变换的功率谱估计方法[J].应用科学学报,2003,21(2):157-160.
[2]涂悦贤.广东省水稻生产与农业气候的关系[J].热带地理,1989(2):108-116.
[3]许信旺,孙满英,方宇媛,等.安徽省气候变化对水稻生产的影响及应对[J].农业环境科学学报,2011,30(9):1755-1763.
[4]张宇,王馥棠.气候变暖对我国水稻生产可能影响的数值模拟试验研究[J].应用气象学报,1995(增刊1):19-25.
[5]沈陈华.气象因子对江苏省水稻单产的影响[J].生态学报,2015,35(12):4155-4167.
[6]唐余学,罗孳孳,范莉,等.基于关键气象因子的中稻单产动态预报[J].中国农业气象,2011,32(增刊1):140-143.
[7]GRINSTED A,MOORE J C,JEVREJEVA S.Application of the cross wavelet transform and wavelet coherence to geophysical time series[J].Nonlinear Processes in Geophysics,2004,11(5/6):561-566.
[8]陈涛,孙卫国,程炳岩.交叉小波变换在河南降水时频分析中的应用[J].南京气象学院学报,2002,25(5):685-692.
[9]LONNIE H,HUANG J P.Bivariate wavelet analysis of Asia monsoon and ENSO[J].Advances in Atmospheric Sciences,1996,13(3):299-312.
[10]魏中海,王建勇,夏宣炎.粮食产量预测的因子处理和建模方法[J].华中农业大学学报,2004,23(6):680-684.
[11]刘占明,陈子燊,路剑飞,等.广东北江流域降水时空分布及其与Nio3区SST相关性分析[J].自然资源学报,2013,28(5):786-798.
[12]余丹丹,张韧,洪梅,等.基于交叉小波与小波相干的西太平洋副高与东亚夏季风系统的关联性分析[J].南京气象学院学报,2007(6):755-769.
[13]TORRENCE C,COMPO G P.A practical guide to wavelet analysis[J].Bulletin of the American Meteorological Society,1998,79(1):61-78.
[14]徐科军,李永三.基于连续小波变换的功率谱估计方法[J].应用科学学报,2003,21(2):157-160.