[1]何南腾,邹嘉南,郭文弟,等.阿克苏地区日蒸散量估算方法研究[J].气象研究与应用,2022,43(02):35-40.[doi:10.19849/j.cnki.CN45-1356/P.2022.2.06]
　He Nanteng,Zou Jianan,Guo Wendi,et al.Study on estimation method of daily evapotranspiration in Aksu Prefecture[J].Journal of Meteorological Research and Application,2022,43(02):35-40.[doi:10.19849/j.cnki.CN45-1356/P.2022.2.06]
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阿克苏地区日蒸散量估算方法研究()
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气象研究与应用[ISSN:1673-8411/CN:45-1356/P]

卷:
第43卷
期数:
2022年02期
页码:
35-40
栏目:
研究论文
出版日期:
2022-06-15

文章信息/Info

Title:
Study on estimation method of daily evapotranspiration in Aksu Prefecture
作者:
何南腾1;  邹嘉南1;  郭文弟2;  周笑迁1;  狄迪1
1. 南京信息工程大学中国气象局气溶胶与云降水重点开放实验室, 南京 210044;
2. 中国地质调查局西安矿产资源调查中心, 西安 710100
Author(s):
He Nanteng1;  Zou Jianan1;  Guo Wendi2;  Zhou Xiaoqian1;  Di Di1
1. Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2. Xi’an Center of Mineral Resources Survey, China Geological Survey, Xi’an 710100, China
关键词:
日蒸散量; Penman-Monteith公式; GRNN; BP
Keywords:
daily evapotranspiration; Penman-Monteith formula; GRNN; BP
分类号:
P426.2
DOI:
10.19849/j.cnki.CN45-1356/P.2022.2.06
摘要:
采用阿克苏地区2006-2015年日蒸散量数据和气象数据，对几种不同的日蒸散量估算方法进行评估与修正。结果表明，修正后的彭曼公式在阿克苏地区的适用性、准确性有所提高，均方根误差值由11.78减小到8.80；BP神经网络比GRNN神经网络估算效果好，前者Nash-Sutcliffe系数为-0.09、RMSE值为3.27，后者Nash-Sutcliffe系数为-0.44、RMSE值为3.34。研究成果可为极端干旱区的棉花等作物节水种植提供参考。
Abstract:
Based on the daily evapotranspiration data and meteorological data of Aksu from 2006 to 2015, several different estimation methods of daily evapotranspiration were evaluated and modified. The applicability and accuracy of the modified Penman-Monteith(PM) formula in Aksu are improved, and the root mean square error is reduced from 11.78 to 8.80. The BP neural network (Back Propagation Neural Network) has better estimation effect than the GRNN(General Regression Neural Network). The former has a Nash-Sutcliffe coefficient of -0.09 and an RMSE value of 3.27, while the latter has a Nash-Sutcliffe coefficient of -0.44 and an RMSE value of 3.34. The research results can provide references for water-saving planting of cotton and other crops in extremely arid regions.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2021-12-14。
基金项目:江苏省高等学校自然科学研究项目（21KJB170002）
作者简介:何南腾(2001-),男,学士,研究方向为颗粒物浓度反演。E-mail:201983300656@nuist.edu.cn
通讯作者:邹嘉南(1990-),男,博士,讲师,研究方向为气溶胶物理化学。E-mail:Zoujn16@nuist.edu.Cn
更新日期/Last Update: 1900-01-01