Evaluation of Valiantzas’ Simplified Forms of the FAO-56 Penman-Monteith Reference Evapotranspiration Model in a Humid Climate

Authors

Koffi Djaman, Africa Rice CenterFollow
Daran Rudnick, University of Nebraska - LincolnFollow
Valere C. Mel, Africa Rice Center
Denis Mutiibwa, University of Nevada, Reno, Nevada
Lamine Diop, Universite Gaston BergerFollow
Mamadou Sall, Institut Senegalais de Recherches Agricoles, Centre de Saint Louis, Saint Louis, Sénégal
Isa Kabenge, Makerere University
Ansoumana Bodian, Université Gaston Berger (UGB), Saint Louis, Sénégal
Hossein Tabari, KU Leuven
Suat Irmak, University of Nebraska - LincolnFollow

Document Type

Article

Date of this Version

2017

Citation

Published in Journal of Irrigation and Drainage Engineering, 2017, 143(8): 06017005

DOI: 10.1061/(ASCE)IR.1943-4774.000119

Comments

Copyright © 2017 American Society of Civil Engineers. Used by permission.

Abstract

The unavailability of some meteorological variables, especially solar radiation and wind speed, is the main constraint for reference evapotranspiration (ETo) estimation using the standard United Nations Food and Agriculture Organization (FAO) Penman–Monteith (FAO-PM) equation in most developing countries. The application of ETo methods with fewer input requirements is necessary under limited climatic data conditions. The FAO-PM method under limited data conditions and nine of Valiantzas’ equations were evaluated for daily ETo estimation in a humid climate in Uganda. The FAO-PM method with missing relative humidity data performed very well across Uganda, whereas using the long-term local wind speed average values in place of missing wind speed data resulted in inaccurate ETo estimates. Under missing solar radiation measurements, the FAO-PM method showed different performances relative to the locations. When more than one climatic variable is missing, the FAO-PM method yielded poor ETo estimates compared to the FAO-PM method with full climatic data. The performance of Valiantzas’ equations depends on data requirements: the more meteorological inputs, the higher the ETo accuracy.