Evaluation of solar radiation estimation methods for reference evapotranspiration estimation in Canada

被引:31
|
作者
Aladenola, Olanike O. [1 ]
Madramootoo, Chandra A. [1 ]
机构
[1] McGill Univ, Dept Bioresource Engn, Ste Anne De Bellevue, PQ H9X 3V9, Canada
关键词
PREDICTION; MODELS;
D O I
10.1007/s00704-013-1070-2
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The accuracy of nine solar radiation (R-s) estimation models and their effects on reference evapotranspiration (ETo) were evaluated using data from eight meteorological stations in Canada. The R-s estimation models were FAO recommended Angstrom-Prescott (A-P) coefficients, locally calibrated A-P coefficients, Hargreaves and Samani (H-S) (1982), Annandale et al., (2002), Allen (1995), Self-Calibrating (S-C, Allen, 1997), Samani (2000), Mahmood and Hubbard (M-H) (2002), and Bristow and Campbell (B-C) (1984). The estimated R-s values were then compared to measured R-s to check the appropriateness of these models at the study locations. Based on root mean square error (RMSE), mean bias error (MBE) and modelling efficiency (ME) ranking, calibrated A-P coefficients performed better than all other methods. The calibrated H-S method (using new K-RS 0.15) estimated R-s more accurately than FAO-56 recommended A-P in Elora, and Winnipeg. The RMSE of the calibrated H-S method ranged between 1-6% and the RMSE of the calibrated and FAO recommended Angstrom-Prescott (A-P) methods ranged between 1-9%. The models with the least accuracy at the eight locations are the Mahmood & Hubbard (2002) and Self-Calibrating models. The percent deviation in ETo calculated with estimated R-s was reduced by about 50% as compared to deviation in measured versus estimated R-s.
引用
收藏
页码:377 / 385
页数:9
相关论文
共 50 条
  • [1] Calibration and Evaluation of Alternative Methods for Reliable Estimation of Reference Evapotranspiration in South Korea
    Kim, Chul-Gyum
    Lee, Jeongwoo
    Lee, Jeong-Eun
    Chung, Il-Moon
    WATER, 2024, 16 (17)
  • [2] Estimation methods to define reference evapotranspiration: a comparative perspective
    Pinos, Juan
    WATER PRACTICE AND TECHNOLOGY, 2022, 17 (04) : 940 - 948
  • [3] ESTIMATION METHODS OF REFERENCE EVAPOTRANSPIRATION (ETo) FOR UBERLANDIA -MG
    de lacerda, Zilda C.
    Turco, Jose E. P.
    ENGENHARIA AGRICOLA, 2015, 35 (01): : 27 - 38
  • [4] Evaluation and calibration of simple methods for daily reference evapotranspiration estimation in humid East China
    Xu, Junzeng
    Peng, Shizhang
    Ding, Jiali
    Wei, Qi
    Yu, Yanmei
    ARCHIVES OF AGRONOMY AND SOIL SCIENCE, 2013, 59 (06) : 845 - 858
  • [5] Adapting estimation methods of daily solar radiation for crop modelling applications in Canada
    Qian, Budong
    Jing, Qi
    Zhang, Xuebin
    Shang, Jiali
    Liu, Jiangui
    Wan, Hui
    Dong, Taifeng
    De Jong, Reinder
    CANADIAN JOURNAL OF SOIL SCIENCE, 2019, 99 (04) : 533 - 547
  • [6] Assessment of reference evapotranspiration estimation methods in controlled greenhouse conditions
    Rahimikhoob, Hadisseh
    Sohrabi, Teymour
    Delshad, Mojtaba
    IRRIGATION SCIENCE, 2020, 38 (04) : 389 - 400
  • [7] Improved reference evapotranspiration methods for regional irrigation water demand estimation
    Su, Qiong
    Singh, Vijay P.
    Karthikeyan, Raghupathy
    AGRICULTURAL WATER MANAGEMENT, 2022, 274
  • [8] Alternative methods of estimation of reference evapotranspiration in the Yauri station - Cusco, Peru
    Lujano, Apolinario
    Quispe, Jose P.
    Lujano, Efrain
    REVISTA INVESTIGACIONES ALTOANDINAS-JOURNAL OF HIGH ANDEAN RESEARCH, 2019, 21 (03): : 215 - 224
  • [9] Estimation of solar radiation using modern methods
    Karaman, Omer Ali
    Agir, Tuba Tanyildizi
    Arsel, Ismail
    ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (02) : 2447 - 2455
  • [10] Using support vector machine to deal with the missing of solar radiation data in daily reference evapotranspiration estimation in China
    Chen, Shang
    He, Chuan
    Huang, Zhuo
    Xu, Xijuan
    Jiang, Tengcong
    He, Zhihao
    Liu, Jiandong
    Su, Baofeng
    Feng, Hao
    Yu, Qiang
    He, Jianqiang
    AGRICULTURAL AND FOREST METEOROLOGY, 2022, 316