Multsch, S., Exbrayat, J.F., Kirk, M., Viner, N.R., Frede, H.G. and Breuer, L. (2015) Reduction of Predictive Uncertainty in Estimating Irrigation Water Requirement through Multi-Model Ensembles and Ensemble Averaging. Geoscientific Model Development, 8, 1233-1244.
https://doi.org/10.5194/gmd-8-1233-2015

has been cited by the following article:

• TITLE: Evaluation of Eleven Reference Evapotranspiration Models in Semiarid Conditions

  AUTHORS: Koffi Djaman, Komlan Koudahe, Christopher Oluwakunmi Akinbile, Suat Irmak

  KEYWORDS: Reference Evapotranspiration, Semiarid and Arid Climate, Mali

  JOURNAL NAME: Journal of Water Resource and Protection, Vol.9 No.12, November 29, 2017

  ABSTRACT: The objectives of this study were to evaluate the performance of the FAO Penman Monteith reference evapotranspiration model under limited data and some mine temperature methods of reference evapotranspiration (ETo) under the semiarid and arid conditions in Mali. The results showed that under limited data conditions, the FAO-PM equation achieved accurate estimation of daily ETo when solar radiation, relative humidity, and wind speed are lacking individually with root mean squared errors (RMSE) averaging 0.52, 0.56 and 0.62 mm/day, respectively. Much more accurate ETo was estimated under relative humidity and wind speed missing data conditions with RMSE varying from 0.20 to 0.58 mm/day and average RE, MBE and MAE of 6.7%, -0.25 mm/day and 0.30 mm/day. The Jensen-Haise equation systematically overestimated ETo while the Hansen, Christiansen, and Irmak, and the two Tabari’s equations underestimated ETo at all weather stations. The Abtew equation showed the best performance among the selected ETo equations.