中国农业气象

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黑龙港流域参考作物蒸散量的时序变化和分形特征

李春友;张劲松;孟平;黄辉;高峻;   

  1. 河北农业大学;中国林业科学研究院林业研究所/国家林业局林木培育重点实验室;
  • 出版日期:2011-02-10 发布日期:2011-02-10
  • 基金资助:
    中央级公益性院所基金课题(CAFYBB2007038);; 科技部社会公益性研究项目(2004DIB4J167)

Study on Temporal Variation and Fractal Characteristics of Reference Crop Evapotranspiration in the Heilonggang Basin

LI Chun-you 1,2,ZHANG Jin-song2,MENG Ping2,Huang Hui2,Gao Jun2(1.Agricultural University of Hebei,Baoding 071001,China;2.Research Institute of Forestry,CAF/Key Laboratory of Forestry Silviculture of the State Forestry Administration,Beijing 100091)   

  • Online:2011-02-10 Published:2011-02-10

摘要: 利用位于黑龙港流域的武强、深泽、饶阳、晋州、献县5站1957-2009年日最高气温、日平均气温、日最低气温、日平均相对湿度、日平均风速、日照时数资料,采用Penman-Monteith算法,计算各站不同时间尺度ET0,采用线性趋势分析法分析其趋势倾向,并应用滑动R/S分析方法研究该流域不同时间尺度ET0时间序列的分形特征。线性趋势分析显示,各站历史上自1957年以来的ET0年总值的气候倾向率在-33.81~-10.79mm.10a-1,即均呈下降趋势,但变化倾向率不同;各月ET0倾向率在-11.27~2.02mm.10a-1,大多数为负值,其中5、6月份各站的下降趋势最大;春、夏、秋、冬季ET0倾向率为-15.87~1.30mm.10a-1,且夏季各站之间的差异较大,尤以饶阳站与其他4站间的差异最大。气候要素倾向率的对比分析表明,5站参考作物蒸散量总体下降趋势的基本特征主要是由于风速下降、日照时数减少、日最高最低气温上升造成的;5、6月份下降趋势明显则主要是由于风速下降、日照时数减少、日平均气温上升减缓、相对湿度上升明显造成的;饶阳站与其他4站差异较大的主要原因在于2、3、11、12月风速下降和日照时数减少以及日最高最低气温上升趋势减缓、相对湿度和气压下降明显,以致这些月份的ET0倾向率大于0,形成秋季和冬季ET0倾向率大于0,年尺度ET0年际变化下降趋势不明显。R/S分析结果显示,5站全年和各季ET0时间序列的Hurst指数均大于0.5,相关系数均在0.98以上,分维数均小于1.5,说明各站全年和各季节ET0时间序列变化趋势在未来一段时间内具有持续性,即ET0在未来将呈较明显的下降趋势,这种趋势在除饶阳外的其他站月均有不同程度的表现。

关键词: 黑龙港流域, 参考作物蒸散, 时间序列, 气候倾向率, 分形特征

Abstract: Based on the daily data of mean temperature,maximum temperature,minimum temperature,relative humidity,wind velocity,sunshine hours and atmospheric pressure from 1957 to 2009 on five weather stations-Wuqiang,Shenze,Raoyang,Jinzhou and Xianxian in Heilonggang basin,the reference crop evapotranspiration of each station for different time scales was estimated by Penman-Monteith method.The change trend of ET0was analyzed by linear trend analysis method,and the fractal characteristics of time series for ET0 in the basin was studied by sliding R/S analysis method.The linear trend analysis indicated that the climate tendency ratio of annual ET0of every station over the years in the history since 1957 was between-33.81~-10.79 mm per 10 years,which all were in a decreasing trend,but presented great difference between each station;the monthly climate tendency ratio was between-11.27~2.02 mm per 10 years,most of it was under 0,the lowest monthly climate tendency ratio was in May and June in each station;the climate tendency ratio of each season was between-15.87~1.3 mm per 10 years,the ratio was the difference between each station in summer,and there was the maximum difference between Raoyang and other stations in summer.The comparative analysis of climate tendency ratio for meteorological factors showed the main reason which resulted in the decreasing trend of ET0 in the basin were the decreasing of wind speed and sunshine hours,and the increasing of daily maximum and minimum temperature;the main reason which resulted in the evident decreasing trend of ET0 in May and June were the decreasing of wind speed and sunshine hours,the slower increasing of daily mean temperature,and the evident increasing of relative humidity;the main reason which resulted in great difference between Raoyang and other four stations for ET0 change trend were the slower decreasing of wind speed and sunshine hours,the slower increasing of daily maximum and minimum temperature,the evident decreasing of relative humidity and atmospheric pressure in February,March,November and December,which causing the increasing trend of monthly ET0 in these months and the slower decreasing trend of annual ET0.The result of R/S analysis showed that over the year and in each season,the Hurst indexes in each station were greater than 0.5,the correlation coefficient were greater than 0.98,and the fractal dimensions were less than 1.5.This suggested that the time series for ET0 of the year and each season have a sustainability,ET0 in the future would decrease,and the decreasing trend also exists in monthly ET0 in other stations except for Raoyang.

Key words: Heilonggang basin, Heilonggang basin, Reference crop evapotranspiration, Time series, Climate tendency ratio, Fractal features