Evaluation of applicability of three evapotranspiration models using meteorological data

被引:0
|
作者
Han, Song-Jun [1 ]
Hu, He-Ping [1 ]
Tian, Fu-Qiang [1 ]
机构
[1] Tsinghua University, Beijing 100084, China
来源
关键词
Meteorology;
D O I
暂无
中图分类号
学科分类号
摘要
The applicability of three models used to estimate the evapotranspiration based on general meteorological data is analyzed. The models include the advection-aridity (AA) model, Granger model and the improved Penman-Monteith model proposed by Katerji and Perrier, namely P-M-Katerji model. The dimensionless analysis method is applied, by which the ratio of actual evapotranspiration to Penman potential evapotranspiration is expressed as a function of the proportion of the radiation term in Penman potential evapotranspiration. The three models use different functions, and the applicability of each model is analyzed according to the characteristics of the functions respectively. It is found that the AA model is applicable to the environment which is neither extreme dry nor extreme wet, it underestimates the actual evapotranspiration under dry conditions but overestimates under wet conditions. The Granger model is applicable to the conditions with a wide range of evapotranspiration ratio, and it is approximately equivalent to the AA model under ordinary wet condition. The simulation result of the P-M-Katerji model is not very good if the variation range of evapotrnaspiration is wide. The validity of the analysis result is verified by a case study.
引用
收藏
页码:75 / 81
相关论文
共 50 条
  • [21] Evaluation of reference evapotranspiration models using single crop coefficient method and lysimeter data
    Kumar, Rohitashw
    Kumar, Mukesh
    INDIAN JOURNAL OF AGRICULTURAL SCIENCES, 2017, 87 (03): : 350 - 354
  • [22] Applicability assessment of five evapotranspiration models based on lysimeter data from a bioretention system
    Zhang, Wenlong
    Yang, Moyuan
    Zhang, Shouhong
    Yu, Lei
    Zhao, Fei
    Chen, Duwei
    Yang, Simin
    Li, Hualin
    Zhang, Sunxun
    Li, Ruixian
    Zhang, Jianjun
    ECOLOGICAL ENGINEERING, 2023, 194
  • [23] Estimation of Reference Crop Evapotranspiration with Three Different Machine Learning Models and Limited Meteorological Variables
    Yong, Stephen Luo Sheng
    Ng, Jing Lin
    Huang, Yuk Feng
    Ang, Chun Kit
    AGRONOMY-BASEL, 2023, 13 (04):
  • [24] PERFORMANCE EVALUATION OF ARTIFICIAL NEURAL NETWORKS IN ESTIMATING REFERENCE EVAPOTRANSPIRATION WITH MINIMAL METEOROLOGICAL DATA
    Diamantopoulou, M. J.
    Georgiou, P. E.
    Papamichail, D. M.
    GLOBAL NEST JOURNAL, 2011, 13 (01): : 18 - 27
  • [25] Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China
    Fan, Junliang
    Yue, Wenjun
    Wu, Lifeng
    Zhang, Fucang
    Cai, Huanjie
    Wang, Xiukang
    Lu, Xianghui
    Xiang, Youzhen
    AGRICULTURAL AND FOREST METEOROLOGY, 2018, 263 : 225 - 241
  • [26] Applicability of different models of reference crops evapotranspiration in China
    Wang, Xi
    Wang, Honglei
    Jia, Fangfang
    Wang, Xiuru
    Nature Environment and Pollution Technology, 2014, 13 (02) : 289 - 296
  • [27] Comparative analysis of advanced deep learning models for predicting evapotranspiration based on meteorological data in bangladesh
    Paul, Sourov
    Farzana, Syeda Zehan
    Das, Saikat
    Das, Pobithra
    Kashem, Abul
    Environmental Science and Pollution Research, 2024, 31 (50) : 60041 - 60064
  • [28] Comparison of CLDAS and Machine Learning Models for Reference Evapotranspiration Estimation under Limited Meteorological Data
    Qian, Long
    Wu, Lifeng
    Liu, Xiaogang
    Cui, Yaokui
    Wang, Yongwen
    SUSTAINABILITY, 2022, 14 (21)
  • [29] Estimation of daily potato crop evapotranspiration using three different machine learning algorithms and four scenarios of available meteorological data
    Yamac, Sevim Seda
    Todorovic, Mladen
    AGRICULTURAL WATER MANAGEMENT, 2020, 228
  • [30] Evaluation on applicability of daily solar radiation model in Northwest China based on meteorological data
    Zhang Q.
    Cui N.
    Feng Y.
    Jia Y.
    Li C.
    Gong D.
    Hu X.
    Cui, Ningbo (cuiningbo@126.com), 2018, Chinese Society of Agricultural Engineering (34): : 189 - 196