长江科学院院报 ›› 2023, Vol. 40 ›› Issue (11): 85-92.DOI: 10.11988/ckyyb.20220632

• 农业水利 • 上一篇    下一篇

基于云模型的云南参考作物蒸散量时空变化及影响因素分析

杨蕊, 王龙   

  1. 云南农业大学 水利学院,昆明 650201
  • 收稿日期:2022-06-06 修回日期:2022-08-06 出版日期:2023-11-01 发布日期:2023-11-09
  • 作者简介:杨蕊(1981-),女,云南泸西人,副教授,硕士,主要从事节水灌溉与水资源开发利用等研究。E-mail:yr199743@126.com
  • 基金资助:
    云南省教育厅科学研究基金项目(2019J0132)

Spatial and Temporal Variations and Influencing Factors of Evapotran- spiration of Reference Crop in Yunnan Province Based on Cloud Model

YANG Rui, WANG Long   

  1. College of Water Conservancy,Yunnan Agricultural University,Kunming 650201,China
  • Received:2022-06-06 Revised:2022-08-06 Published:2023-11-01 Online:2023-11-09

摘要: 云模型可定量描述参考作物蒸散量(ET0)的随机性和模糊性,基于云模型分析云南ET0的时空变化,结果可为云南农业灌溉、水旱灾害等研究提供参考。以云南省31个气象站1958—2013年的逐日气象资料为基础计算ET0,基于云模型并结合线性倾向、M-K趋势检验、偏相关分析等研究云南参考作物蒸散量及影响因素的变化特征。结果表明:1958—2013年,云南ET0在时间和空间上分布不均匀,空间分布较时间变化更不均匀且不稳定。56 a间ET0呈不显著增加趋势,2000年后ET0显著大幅增加且分布极不均匀极不稳定;春季ET0最大,冬季ET0最小,冬春ET0分散且不稳定;ET0呈“中高东西低、南多北少”的空间分布和“西增中东减”的变化规律,滇中高值区ET0变化不均匀且不稳定;湿度、日照时数和风速是影响ET0的主要因素。

关键词: 蒸散量, 参考作物, 影响因素, 时空变化, 云模型, 云南

Abstract: Cloud model offers a quantitative representation of the randomness and fuzziness associated with reference crop evapotranspiration (ET0). To provide valuable insights for agricultural irrigation, flood, and drought studies in Yunnan Province, we employed cloud model to analyze the spatiotemporal distribution of ET0 in the region based on daily meteorological data from 31 meteorological stations in Yunnan spanning the period from 1958 to 2013. ET0 was calculated and examined using linear trend, partial correlation analysis, and the M-K methods. Results revealed a lack of consistency in the homogeneity of the temporal-spatial distribution of ET0 in Yunnan. The temporal variation exhibited lower homogeneity and stability compared to the spatial distribution. Over the 56 years, no significant increasing trend in ET0 was observed. However, after the year 2000, a significant upward trend in ET0 became evident, accompanied by a decrease in homogeneity and stability. Seasonally, spring exhibited the highest ET0, while winter displayed the lowest values. Notably, ET0 distribution in winter and spring appeared uneven and unstable. Spatially, the middle and south region exhibited higher ET0 values than the eastern and western and northern areas. Further analysis highlighted an increasing trend in ET0 in western Yunnan, while the middle and eastern regions experienced a decrease. The high-value areas in central Yunnan exhibited uneven and unstable variations in ET0. Additionally, our analysis identified humidity, sunshine duration, and wind speed as the primary influencing factors on ET0.

Key words: evapotranspiration, reference crop, influencing factors, spatial and temporal variations, cloud model, Yunnan Province

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