English
引用本文:赵众,周密,张刘东,等.顾及“蒸发悖论”的洱海灌区逐日参考作物蒸散发预测[J].灌溉排水学报,0,():-.
zhaozhong,zhoumi,zhangliudong,et al.顾及“蒸发悖论”的洱海灌区逐日参考作物蒸散发预测[J].灌溉排水学报,0,():-.
【打印本页】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
过刊浏览    高级检索
本文已被:浏览 1591次   下载 0  
分享到: 微信 更多
顾及“蒸发悖论”的洱海灌区逐日参考作物蒸散发预测
赵众,周密,张刘东,等
1.云南农业大学;2.云南省水利水电勘测设计研究院
摘要:
【目的】蒸散发(ET)是区域水循环中最重要的水文过程之一,对短期参考作物蒸散发(ET0)的估算或准确测量具有重要的现实意义。【方法】本文以滇中高原上洱海湖滨灌区的大理气象站为例,探究“蒸发悖论”现象出现的时期,分别采用常规的概念统计模型如气象因子线性回归模型、蒸发皿折算系数Kp模型、气象因子+蒸发皿蒸发(Epan)多元回归模型,以及随机方法之Normal Copula模型等4种方法对逐日ET0进行预测对比,并以Penman Monteith公式计算所得的ET0为标准值进行对比。【结果】(1)在1954~2018年长时间序列上,大理站ET0和20cm蒸发皿蒸发量均呈下降趋势,但ET0的下降趋势更平缓,气温呈上升趋势,虽然在长时间序列上ET0和蒸发皿蒸发量有相同的变化趋势,但在年代际存在显著的差异性,1960s和2000s全年以及四季均出现“蒸发悖论”,1970s则是全年以及夏、秋、冬三季出现“蒸发悖论”,1990s仅夏季出现“蒸发悖论”,2010s秋季出现“蒸发悖论”;(2)在未出现“蒸发悖论”时期,加入Epan后的气象因子多元回归模型法(ET0,Epan+Metr)所得逐日ET0预测结果与标准值的误差最小,其次为单纯的气象因子多元线性回归模型法(ET0,Metr),最差为蒸发皿折算系数Kp模型法(ET0,Kp),以加入Epan后的气象因子多元回归模型(ET0,Epan+Metr)进行逐日ET0预测,相对误差(ERR)小于15%、20%、25%的样本数达到了79.18%~90.16%、89.32%~97.23%、94.79%~98.36%;【结论】出现“蒸发悖论”时,蒸发皿蒸发与ET0的变化趋势相反,只能采用Copula联合分布函数模型预测,构建T-Tmax二维Normal Copula模型的精度更高,ERR小于15%、20%、25%的样本数为73.70%~86.56%,82.51%~92.95%,89.89%~98.52%。
关键词:  参考作物蒸散发(ET0);蒸发皿蒸发量(Epan);Mann Kendall检验;多元回归;Copula联合分布函数;实时预测;洱海灌区
DOI:
分类号:S271
基金项目:云南省应用基础研究重点基金(2017FA022);国家自然科学基金项目(51669035);云南重点研发计划(科技入滇专项);云南省创新团队建设专项(2018HC024)
Prediction of daily reference evapotranspiration considering evaporation paradox phenomena in Erhai irrigated district
zhaozhong1, zhoumi2, zhangliudong1, gushixiang3, lijing1
1.Yunnan Agricultural University;2.Yunnan Institute for Investigation. Design and Research of Water Resources & Hydropower Engineering,;3.Yunnan Institute for Investigation. Design and Research of Water Resources & Hydropower Engineerin
Abstract:
【Objective】Evapotranspiration (ET) is one of the most important hydrological processes in the regional water cycle, which is of great practical significance for the estimation or accurate measurement of short-term reference crop evapotranspiration (ET0). 【Method】This paper takes Dali meteorological station in the upper Erhai Lake Irrigation Area of the central Yunnan Plateau as an example to analyze the period of "evaporation paradox" phenomenon, and uses conventional conceptual statistical models such as linear regression of meteorological factors, the pan conversion coefficient Kp model, the meteorological factor plus pan multiple regression model, and the normal copula model of the random method are used to predict and compare the daily ET0, and the ET0 calculated by penman Monteith formula is used as the standard value for comparative analysis. 【Result】(1) in the long time series from 1954 to 2018, the evaporation capacity of ET0 and 20cm evaporating dish all shows a downward trend, but the downward trend of ET0 is more gently, and the temperature shows an upward trend. Although the evaporation capacity of ET0 and evaporating dish has the same change trend in the long time series, there are different ages in the short time series, and "evaporation paradox" appears in the whole year and the four seasons of 1960s and 2000s.In 1970s, “evaporation paradox” appeared in the whole year, summer, autumn and winter, in 1990s, only in summer, and in 2010s, in autumn; (2) In the period of no "evaporation paradox", the error between daily ET0 prediction result and standard value is the smallest by adding Epan's multiple regression model (ET0, Epan + metr), followed by simple meteorological factor's multiple linear regression model (ET0, metr), and the worst is the pan conversion coefficient Kp model(ET0, Kp).Used to predict daily ET0 by adding Epan (ET0, EPAn + metr). the relative error ERR is less than 15%, 20%, 25% of the sample number is 79.18% - 90.16%, 89.32% - 97.23%, 94.79% - 98.36%;【Conclusion】When the "evaporation paradox" occurs, the change trend of evaporation plate is opposite to that of ET0, only copula joint distribution function model can be used to predict and build two-dimensional normal The accuracy of copula model is higher. The number of samples with err less than 15%, 20%, 25% is 73.70% - 86.56%, 82.51% - 92.95%, 89.89% - 98.52%.
Key words:  reference crop evapotranspiration(ET0);pan evaporation(Epan);Mann-Kendall test; Multi- linear regression; high-dimensional Copula function;Real –time forecast; Erhai irrigated district