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Thesis Advisor冯广龙 ; 赵成义
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Discipline水土保持与荒漠化防治
Keyword参考作物蒸散量 计算方法比较 模型预测
Abstract参考作物蒸散量是指假想的参照作物冠层的蒸发蒸腾速率。假想作物的高度为0.12m,固定的叶面阻力为70s/m,反射率为0.23,非常类似于表面开阔、高度一致、生长旺盛、完全覆盖地面而不缺水的绿色草地蒸发蒸腾量。参考作物蒸散量的精确估算不仅能够为制定作物灌溉制度和区域灌溉需水计划提供基本依据,同时也能够为提高农田水资源利用效率提供数据支撑。 本文利用塔里木灌区阿克苏站1989~2014年间的气象资料,分析了年际和月际气象因子和参考作物蒸散量的变化趋势。采用不同计算方法计算了参考作物蒸散量并以标准方法FAO-56 Penman-Montieth作为实际观测值对比分析了各种方法计算结果在塔里木灌区的适用性。分别运用BP神经网络模型、广义回归神经网络模型对塔里木灌区的参考作物蒸散量进行了预测。结果表明: (1)阿克苏站1989~1996年平均气温累积距平呈下降趋势,而1996~2014年年平均气温累积距平呈上升趋势;最高气温累积距平1989~1996年呈下降趋势,1997~2005年出现平缓波动的趋势,2006~2014年之间呈现上升的趋势;最低气温累积距平除1989、1996、2014三年外为负值,其它年份年最低气温均为正值;日照时数累积距平基本上以2年为周期先呈下降趋势,后呈上升趋势;风速累积距平1989~1997年呈上升趋势,1998~2004年呈下降趋势,2005~2014年呈上升趋势;年相对湿度累积距平1989~1994 年呈下降趋势,1995~2003呈上升趋势,2005~2014平缓波动趋势。 (2)阿克苏站1989~2014年3、4、6、8月份的平均气温气候倾向率为正值,其它月份均为负值。整体上看冬季呈下降趋势,春、夏、秋三季呈升趋势;月最高气温气候倾向率除1、2、9、11、12月份均为负值,其它月份均为正值;月最低气温1、2、5、7、11、12月份呈下降趋势,其它月份呈上升趋势。冬季基本呈下降趋势,春夏秋3季呈上升趋势;月日照时数气候倾向率除8、11月为负值,其它各月均为正值,表明各月日照时数均上升趋势;平均风速气候倾向率除2、8、11、12月份为正值外,其它月份均为负值。相对湿度气候倾向率除1、3、4、8月份为负值外,其它月份均为正值。 (3)1989~2014阿克苏站参考作物蒸散量随时间呈减少趋势,日照和风速是影响阿克苏站ET0长期趋势变化的主要气象要素。从季节上看,日照对春季、夏季ET0值影响最显著,相对湿度对秋季ET0影响最大,最高气温对冬季ET0影响较大。 (4)1972 Kimberly Penman的计算结果与标准方法的计算结果差异最小,其次是1948 Penman、1985 Hargreaves、FAO PPP-17 Penman、1957 Makkink、Priestley-Taylor,而FAO-24 Radiation的差异最大,精度最低。说明1972 Kimberly Penman在塔里木灌区的适用性较好,在估算塔里木盆灌区的参考作物蒸散量时,可选用1972 Kimberly Penman公式。 (5)输入因子为最高温度、最低温度、日照时数和日序数时BP神经网络模型和广义回归模型有较好的模拟效果。
Other AbstractThe increasingly highlighted contradiction of water supply and demand, serious waste of agricultural water and water pollution have become the bottleneck of agriculture sustainable development as well as the national economic development. These problems are the major strategic issues that can affect national security. Quite a long time in the future, China's water shortage problems have to be resolved through water conservation. Crop water requirement rules could provide strong fundamental theory supports and technique supports for the development of agricultural water-saving techniques.The amount of water required to compensate the evapotranspiration loss from the cropped field is defined as crop water requirement. Although the values for crop evaportranspiration and crop water requirement are identical,crop water requirement refers to the amount of water that needs to be supplied,while crop evaportranspiration refers to the amount of water that is lost through evaportranspiration. At present,crop evaportranspiration can be calculated by the equation ET=Kc * ET0. As a result, ET0 has become the key point to calculate the crop water requirement. In this paper, the inter-annual and inter-monthly variation trends of meteorological factors from 1989 to 2014 were analyzed using meteorological data observed by Aksu station in Tarim river basin. Eight alternative ET0 methods,the FAO-56 Penman-Monteith、 1972 Kimberly Penman、FAO PPP-17 Penman、FAO-24 Radiation、1985 Hargreaves、1948 Penman、Priestley-Taylor and 1957 Makkink were evaluated for application in oasis of the Traim Basin. Average monthly reference evapotranspiration in Aksu area were predicted by BP neural network and generalized regression neural network using meteorological data from 1989 to 2014. The results showed: (1)Accumulation of annual average temperature in Aksu were decreased from 1989 to 1996 and were increased from 1996 to 2014; Accumulation of annual maximum temperature were decreased from 1989 to 1996 and were incresed from 2006 to 2014,and showed a appear flat fluctuating trend from 1997 to 2005; Accumulation of annual minimum temperature were negative except the year of 1989,1996,2014 ; Accumulation of annual sunshine appeared to be a 2-year period prior downward trend; Accumulation of annual wind speed were incresed from 1989 to 1997 and 2005 to 2014,while were decreased from 1998 to 2004 ; Accumulation of annual relative humidity were decreased from 1989 to 1994 and increased from 1995 to 2003, and appeared to be a gentle fluctuation from 2005 to 2014. (2)The Rate changes of average temperature in March,April, June,August were positive from 1989 to 2014,while others are negative. Overall, The Rate changes of average temperature in winter was decreased, and were increased in spring, summer, autumn; The Rate changes of average monthly maximum temperature are positive in the month of January, February, September, November, December,others are negative; The Rate changes of average monthly minimum temperature were decreased in the month of January,February,May, July, November, December, others were increased. Winter substantially decreased, spring, summer and autumn are on the rise; The Rate changes of average monthly sunshine hours were negative in the month of August and November; The Rate changes of average wind speed are positive in February, August, November, December,other month were negative; The Rate changes of average relative humidity were negative in January,March,April, August the other months were negative. (3)Reference crop evapotranspiration in Aksu station tended to decrease with time from 1989 to 2014, sunshine and wind speed are the main meteorological factors that influence Reference crop evapotranspiration. Judging from the season, reference crop evapotranspirationthe was influenced most by sunshine in spring, by relative humidity in Autumn, by maximum temperature in winter. (4)1972 Kimberly Penman produced ET0 estimates which were very close to the results estimated by FAO-56 Penman-Monteith method in comparison with other methods, however, FAO-24 Radiation estimated ET0 which was very far from FAO-56 Penman-Monteith. 1972 Kimberly Penman can be used for the calculation of reference evapotranspiration in oasis of Traim Basin. (5)The BP model and generalized regression neural network model were suitable for forecasting ET0 when the input were highest temperature lowest temperature ,sunshine duration and days。
Subject Area水土保持与荒漠化防治
Document Type学位论文
Recommended Citation
GB/T 7714
高飞. 新疆塔里木灌区参考作物蒸散量计算与预测研究[D]. 北京. 中国科学院大学,2015.
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