There are many factors of uncertainty regarding the impact of climate change on reference evapotranspiration (ETo). The accuracy of the results is strictly related to these factors and ignoring any one of them reduces the precision of the results, and reduces their applicability for decision makers. In this study, the uncertainty related to two ETo models, the Hargreaves-Samani (HGS) and Artificial Neural Network (ANN), and two Atmosphere-Ocean General Circulation Models (AOGCMs), Hadley Centre Coupled Model, version 3 (HadCM3) climatic model and the Canadian Global Climate Model, version 3 (CGCM3) climatic model under climate change, was evaluated. The models predicted average temperature increases by 2010 to 2039 of 0.95 °C by the HadCM3 model and 1.13°C by the CGCM3 model under the A2 scenario relative to observed temperature. Accordingly, the models predicted average ETo would increase of 0.48, 0.60, 0.50 and 0.60 (mm/day) by 2010 to 2039 projected by four methods (by introducing the temperature of the HadCM3-A2 model and the CGCM3-A2 to ANN and HGS) relative to ETo of the observed period. The results showed that uncertainty of the AOGCMs is more than that of the ETo models applied in this study.
Uncertainty of climate change and its impact on reference evapotranspiration in Rasht City, Iran
Heerbod Jahanbani, Lee Teang Shui, Alireza Massah Bavani, Abdul Halim Ghazali; Uncertainty of climate change and its impact on reference evapotranspiration in Rasht City, Iran. Journal of Water and Climate Change 1 March 2011; 2 (1): 72–83. doi: https://doi.org/10.2166/wcc.2011.055
Download citation file: