Abstract
Evapotranspiration can be considered as an indicator in evaluating the effects of climate change. It is the sole factor with the capability of concurrently balancing the ecosystem energy and water fluxes. Reference evapotranspiration (ETo) is the amount of water evaporated from reference crop that is affected by climatic parameters. The aim of this study was to assess ETo during the period of 2020–2049 in various climatic zones of Iran (including Tabriz, Bushehr, Isfahan, Sanandaj and Urmia). Climatic parameters including relative humidity, wind speed, Sunshine hours, atmospheric pressure, maximum and minimum temperatures were utilized for calculating ETo using FAO Penman–Monteith equation. The NCEP data and HADCM3 model data (under scenario A2 and B2) were used for prediction of future climatic parameters during 2020–2049. Statistical down scaling model was used as a hybrid regression model as well as a stochastic weather data generator. The course period was between 1986 and 2015 that was regarded for calibration and evaluation of the model. Subsequently, evapotranspiration was estimated using the model outputs in the FAO Penman–Monteith equation. Results indicated that the simulated data by the model has the same accuracy and validity under both scenarios A2 and B2. Results showed that in the studied areas, ETo tend to have an increasing trend in upcoming years. In scenario A2, ETo will increase about 16.81, 0.137, 17.52, 9.46 and 2.57 mm year−1 in Tabriz, Bushehr, Isfahan, Sanandaj and Urmia stations, respectively. Also our results represented that ETo will increase about 7.67, 6.52, 10.33, 7.73 and 1.99 mm year−1 in Tabriz, Bushehr, Isfahan, Sanandaj and Urmia stations, respectively based on the B2 scenario. Although no significant trend was observed in most of the climatic variables under A2 and B2 scenarios over the time period of 2020–2049, the ETo significantly increased during this period. Hence it could be concluded that ETo is a better indicator for describing the future climate change, compared to other climatic variables.
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