田俊武, 尚松浩, 孙丽艳, 温守光. 山西潇河灌区参考作物腾发量和降水的随机特性[J]. 农业工程学报, 2005, 21(10): 26-30.
    引用本文: 田俊武, 尚松浩, 孙丽艳, 温守光. 山西潇河灌区参考作物腾发量和降水的随机特性[J]. 农业工程学报, 2005, 21(10): 26-30.
    Tian Junwu, Shang Songhao, Sun Liyan, Wen Shouguang. Stochastic characters of reference evapotranspiration and precipitation of Xiaohe Irrigation Areas, Shanxi Province[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2005, 21(10): 26-30.
    Citation: Tian Junwu, Shang Songhao, Sun Liyan, Wen Shouguang. Stochastic characters of reference evapotranspiration and precipitation of Xiaohe Irrigation Areas, Shanxi Province[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2005, 21(10): 26-30.

    山西潇河灌区参考作物腾发量和降水的随机特性

    Stochastic characters of reference evapotranspiration and precipitation of Xiaohe Irrigation Areas, Shanxi Province

    • 摘要: 气象要素的随机变化对于农田水分的动态变化与优化调控具有重要影响。根据山西潇河灌区1978~2003年共26年的气象资料,利用FAO推荐的Penman-Monteith公式计算了逐旬的参考作物腾发量(ET0)。采用时间序列分析方法对ET0序列和降水(P)序列的随机特性进行了分析,并将以上序列分解为趋势项、周期项(包括均值和标准差)和平稳随机项。结果表明:近20多年来潇河灌区ET0序列具有递增趋势,而降水具有递减趋势,同时二序列存在负相关关系;去除趋势项的ET0和P序列的旬均值和标准差具有周期性变化的特征,可以用Fourier级数的二阶分量来描述;二序列的平稳随机成分可以用自回归模型来描述。以上结果可以进一步用于农田墒情的随机预报和作物灌溉制度的随机优化。

       

      Abstract: The stochastic characteristics of meteorological factors play important roles in the dynamic variation and optimal regulation of soil moisture. Using 26 years' meteorological data of Xiaohe Irrigation Area, Shanxi Province, reference evapotranspiration per 10 days was calculated with Penman-Monteith equation suggested by FAO. The stochastic characteristics of reference evapotranspiration series and precipitation series were analyzed by time series analysis method, and each series was decomposed to trend component, periodic component and stationary stochastic component. The results suggest that the reference evapotranspiration has an increasing trend, while the precipitation series has a decreasing trend in the recent over 20 years. These two series are negatively correlated. Their mean values and standard deviation can be expressed with the second order Fourier series, and their stochastic component can be expressed with autoregression models. These models can be further used in the stochastic forecasting of soil moisture and stochastic optimization of irrigation scheduling.

       

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