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The proper evaluation of evapotranspiration is essential in food security investigation, farm management, pollution detection, irrigation scheduling, nutrient flows, carbon balance as well as hydrologic modeling, especially in arid environments. To achieve sustainable development and to ensure water supply, especially in arid environments, irrigation experts need tools to estimate reference evapotranspiration on a large scale. In this study, the monthly reference evapotranspiration was estimated by three different regression models including the multivariate fractional polynomial (MFP), robust regression, and Bayesian regression in Ardestan, Esfahan, and Kashan. The results were compared with Food and Agriculture Organization (FAO)-Penman-Monteith (FAO-PM) to select the best model. The results show that at a monthly scale, all models provided a closer agreement with the calculated values for FAO-PM (R 2 [ 0.95 and RMSE \ 12.07 mm month-1). However, the MFP model gives better estimates than the other two models for estimating reference evapotranspiration at all stations.

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Understanding the trends of reference evapotranspiration (ETo) and its influential meteorological variables due to climate change is required for studying the hydrological cycle, vegetation restoration, and regional agricultural production. Although several studies have evaluated these trends, they suffer from a number of drawbacks: (1) they used data series of less than 50 years; (2) they evaluated the individual impact of a few climatic variables on ETo, and thus could not represent the interactive effects of all forces driving trends of ETo; (3) they mostly studied trends of ETo and meteorological variables in similar climate regions; (4) they often did not eliminate the impact of serial correlations on the trends of ETo and meteorological variables; and finally (5) they did not study the extremum values of meteorological variables and ETo. This study overcame the abovementioned shortcomings by (1) analyzing the 50-year (1961–2010) annual trends of ETo and 12 meteorological variables from 18 study sites in contrasting climate types in Iran, (2) removing the effect of serial correlations on the trends analysis via the trend-free pre-whitening approach, (3) determining the most important meteorological variables that control the variations of ETo, and (4) evaluating the coincidence of annual extremum values of meteorological variables and ETo. The results showed that ETo and several meteorological variables (namely wind speed, vapor pressure deficit, cloudy days, minimum relative humidity, and mean, maximum and minimum air temperature) had significant trends at the confidence level of 95% in more than 50% of the study sites. These significant trends were indicative of climate change in many regions of Iran. It was also found that the wind speed (WS) had the most significant influence on the trend of ETo in most of the study sites, especially in the years with extremum values of ETo. In 83.3% of the study sites (i.e., all arid, Mediterranean and humid regions and 66.7% of semiarid regions), both ETo and WS reached their extremum values in the same year. The significant changes in ETo due to WS and other meteorological variables have made it necessary to optimize cropping patterns in Iran.

One of the basic objectives of sustainable agriculture is the efficient use of available inputs and resources. Hence, energy use was evaluated in the present study for the cultivation and the greenhouse gas emissions in the main horticultural crops and paddy in Tajan. The required data were collected through relying on subjective and objective methods such as questionnaries and field data recorded in Tajan plain in the period of 2020–2022. The maximum input energy was reported 64,867.5 MJ/ha for the cultivation of rice, and the minimum amount of input energy belonging to pear cultivation was 30,982.95 MJ/ha. Similarly, the highest amount of output energy was recorded 86,401 MJ/ha for the cultivation of rice crops, and the lowest amount of output energy was 30,400 MJ/ha in the cultivation of pomegranate. The results taken from the GHG index and the global warming potential indicated that the products including paddy (2726.19 kg CO2/ha), apple (2681.6 kg CO2/ha) and citrus (2545.3 kg CO2/ha) had the highest impact on pollution and greenhouse gas emissions. Subsequently, according to the data regarding the cultivation percentage of each crop, it was found out that paddy crop had the largest share of potential impact on global warming (72,789,535.76 kg CO2) in Tajan plain. Therefore, the production of products with incredibly high water consumption as well as great use of chemical fertilizers and old high-working hour machines have greater share in energy consumption and global heating potential in comparison to the other indices.

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