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逐日参照腾发量预测的改进方法
引用本文:GU Shi-xiang,何大明,李远华,李靖.逐日参照腾发量预测的改进方法[J].水利学报,2005,36(11):1292-1297.
作者姓名:GU Shi-xiang  何大明  李远华  李靖
作者单位:1. 武汉大学,水利水电学院,湖北,武汉,430072;云南省水利水电勘测设计研究院,云南,昆明,650021
2. 云南大学,亚洲国际河流中心,云南,昆明,650091
3. 中国灌溉排水发展中心,北京,100053
4. 云南农业大学,水利水电与建筑学院,云南,昆明,650201
基金项目:国家重点基础研究发展规划(973计划)资助项目(2003CB415105);国家"十五"重点科技攻关计划项目(2002BA901A22);国家自然科学基金项目(40261001);云南省水资源综合规划专题研究(YSZY-2003-01)
摘    要:利用Penman Monteith方程计算并分析了山西洪洞、山东陡山、广西桂林、湖北漳河、云南景洪及昆明等国内6个不同经纬度和海拔站点16~31年不同长度系列的逐日ET0变化规律,将过去按旬统计的天气类型修正系数缩短到逐日,引入基于Zadeh算子的模糊隶属函数,进行天气类型修正系数的模糊集运算判别.改进的数学模型在昆明和景洪两个灌区分别用于2000年和1998年逐日ET0预测的结果表明,预测精度较此前的径向基函数法和年际均值校正法分别提高18.9%和10%以上.

关 键 词:参考作物腾发量  预测  数学模型  改进方法  低纬度高原
文章编号:0559-9350(2005)11-1292-06
收稿时间:2005-03-12
修稿时间:2005年3月12日

Improved method for daily evapotranspiration prediction
GU Shi-xiang,HE Da-ming,LI Yuan-hua,LI Jing.Improved method for daily evapotranspiration prediction[J].Journal of Hydraulic Engineering,2005,36(11):1292-1297.
Authors:GU Shi-xiang  HE Da-ming  LI Yuan-hua  LI Jing
Affiliation:1. Wuhan University, Wuhan 430072, China ; 2. Yunnan Institute of Water Resources and Hydropower Engineering Investigation, Design and Research, Kunming 650021, China 3. Yunnan University, Kunming 650091, China ; 4. National Center of Irrigation and Drainage Development, Beijing 100053, China ; 5. Yunnan Agriculture University, Kunming 650201, China
Abstract:The Penman-Monteith equation is applied to analyze the daily evapotranspiration ETo variation of 6 stations located at different longitudes and latitudes as well as different elevations based on the historical meteorological data. In the analysis, instead of 10 days as a period the weather classification correction coefficients in calculated according to the statistics based on every day, and a fuzzy subset based on the Zadeh operator is introduced to judge the fuzzy group calculation of daily weather classification correction coefficient. The modified prediction model has been successfully used to predict the ETo of Jinghong Irrigation District in 1998 and Dianchi Irrigation District in 2000. The result demonstrates the prediction precision of the proposed model is better than that of artificial neural network model using radial-basis function and experiential concept model.
Keywords:evapotranspiration  forecast  mathematical model  improved method  low latitude plateau
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