| 引用本文: | 刘静霞,蒙 强,曹志翔,等.基于云模型的西藏高原灌区参考作物蒸散量时间变化特征与影响因子研究[J].灌溉排水学报,2021,(5):134-144. |
| LIU Jingxia,MENG Qiang,CAO Zhixiang,et al.基于云模型的西藏高原灌区参考作物蒸散量时间变化特征与影响因子研究[J].灌溉排水学报,2021,(5):134-144. |
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| 摘要: |
| 【目的】研究气候变化背景下西藏高原灌区参考作物蒸散量（ET0）时间变化特征及其影响因子。【方法】根据1991—2016年满拉、墨达、江北3个灌区的逐日气象数据，利用FAO推荐的Penman-Monteith模型计算ET0，并依靠M-K检验、云模型对3个灌区的ET0及气象因子在时间尺度上的变化趋势及其分布的均匀性和稳定性进行了研究；同时，采用通径分析对影响ET0的气象因子进行了探讨。【结果】1991—2016年江北、墨达灌区年ET0分别以27.97、6.41 mm/(10 a)的倾向率逐渐递减，其中仅江北灌区变化趋势显著；满拉灌区年ET0以9.99 mm/(10 a)的倾向率逐渐递增，但变化趋势不显著。云模型结果表明，江北灌区年ET0分布的均匀性及稳定性最高，墨达灌区最差。季节尺度上，3个灌区ET0均呈夏季＞春季＞秋季＞冬季的分布特点，且冬春季ET0分布的均匀性及稳定性最高，夏秋季较低。月尺度上，ET0呈单峰形分布，其中1月ET0分布最稳定，5月最差。通径分析表明，各气象因子均对ET0变化产生影响且不同灌区中影响ET0的主要气象因子存在差异。平均相对湿度为直接影响满拉、墨达灌区ET0变化最显著的气象因子；平均风速为直接影响江北灌区ET0变化最显著的气象因子；平均相对湿度为间接影响江北、满拉灌区ET0变化的最显著的气象因子；日照时间为间接影响墨达灌区ET0变化的最显著的气象因子。【结论】1991—2016年江北灌区年ET0分布的均匀性及稳定性较高并在年际间以27.97 mm/(10 a)倾向率显著下降。平均风速、平均相对湿度是影响江北、满拉、墨达灌区年ET0变化的主要气象因子。 |
| 关键词: 参考作物蒸散量；云模型；变化特征；气象因子；西藏 |
| DOI：10.13522/j.cnki.ggps.2020189 |
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| Using Cloud Model to Analyze Spatiotemporal Variation of Reference Evapotranspiration and Its Determinants in Tableland Irrigation District in Tibet |
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LIU Jingxia, MENG Qiang, CAO Zhixiang*, LI Yuqing, ZHANG Wenxian
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Water Conservancy Project and Civil Engineering College, Tibet Agriculture and Animal Husbandry University, Linzhi 860000, China
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| Abstract: |
| 【Background and objective】The response of the reference evapotranspiration (ET0) to climate change and its underlying determinants has attracted increased interest over the past decade, but there is a lack of knowledge about how ET0 in Tibet has changed. This paper is to plug this gap.【Method】ET0 in three irrigation districts, Manla, Moda and Jiangbei, was calculated using the Penman-Monteith equation recommended by FAO based on long-term meteorological data measured from each district. Conversion from quantitative ET0 to qualitative description of ET0 was calculated using the cloud model, from which the homogeneity and stability indexes were used to analyze the temporal variation of ET0 as well as its contributing factors. We also analyzed the meteorological factors that affect ET0 most in the three irrigation districts using the path coefficient analysis.【Result】Annual ET0 in Jiangbei and Moda had been in decrease from 1991 to 2016 at an average rate of 27.97 mm/(10a) and 6.41 mm/(10a) respectively, but increased in Moda at an average rate of 9.99 mm/(10a) though not at significant level. The annual ET0 was most temporally uniform and stable in Jiangbei, and least in Moda. Seasonally, the magnitude of ET0 was ranked in the order of summer > spring > autumn > winter in all three irrigation districts. ET0 was most temporal uniform and stable in winter and spring, and least in summer and autumn. Monthly, ET0 peaked in summer and it was most temporally stable in January, and least in May. Path coefficient analysis showed that ET0 was affected by several meteorological factors, and their significance varied between districts. Average relative humidity directly affected ET0 in Manla and Moda most, while average wind speed directly affected ET0 in Jiangbei more than other factors. Daily sunshine had an indirect effect on ET0 in Moda. 【Conclusion】ET0 in Jiangbei had been in decline since 1991 at an average rate 27.97 mm/(10a) despite being most temporally stable and uniform. Wind speed and average relative humidity were the main factors affecting ET0 in all three irrigation districts. |
| Key words: reference crop evapotranspiration; cloud model; meteorological factors; irrigation district; Tibet |
