Evaluation of Changes in Reference Evapotranspiration in Iran Over the Last Decades

IntroductionToday, one of the biggest challenges for mankind is the lack of water resources in the world. This is one of the limiting factors for agricultural development in Iran in recent years. Identifying and estimating reference evapotranspiration (ET0) can help make decisions to plan and mitigate the use of water resources and appropriate management methods in the country. Thus, one of the ways to reduce water losses in the fields is good irrigation planning, which is based on accurate estimation of the water requirements of plants and ET0. The aim of this research is to evaluate the ET0 changes using temperature and radiation methods, statistical tests such as Man-Kendall, Sen’s slope analysis in Iran over the last decades. Material and MethodsIn the current research, primary evaluation of data, such as sorting, etc., was conducted in the desired ET0 calculation format. For the classification of weather station climate, annual precipitation and temperature data from 1976 to 2020 were used. To estimate ET0, maximum temperature (°C), minimum temperature (°C), average relative humidity (%), wind speed (m/s), and sunshine hour (h) were used on a monthly time scale. The Koppen-Geiger climate classification method was used to classify the meteorological stations studied. For estimating monthly and annual ET0, the methods such as FAO Penman-Monteith (FAO PM), Hargreaves-Samani (H-S), and Priestley Taylor (PT) were used. Then, an attempt was made to introduce the appropriate model for each climate by using the results of ET0 estimation using RMSE and MAE. ET0 maps were produced with more accuracy based on the results of the RMSE. Among different geostatistical interpolation methods, the Kriging method worked better than the other methods, which was used as the superior interpolation method. The Mann-Kendall non-parametric test was used to detect the trend of time series. To examine the trend slope in the ET0 time series, the  non-parametric Sen's slope method was used. For qualitative analysis of the ET0 trend, the innovative ITA trend was used for all three methods on a yearly basis Results and DiscussionIn this research, the station climate classification results show that climate varieties in Iran are high and can be divided into seven different climates. According to the RMSE and MAE statistical evaluations, the H-S method in semi-desert climates, dry and cold steppe, dry desert, temperate with dry summers, very hot semi-desert and snowy climates; and PT method in dry desert climates, moderate with dry summers, semi-desert, and very hot semi-desert were recognized as superior methods. In the temperate and rainy climate zone of Bandar Anzali, the H-S, and in Rasht, the PT methods were evaluated as suitable methods. Based on the monthly ET0 estimation, the amount of ET0 is significantly reduced in the northwestern, western and northeastern regions during the winter season. In winter, ET0 decreases as a result of increased air moisture. In the spring season, the amount of ET0 declined in the northern latitudes. The onset of convective spring rains in the northern latitudes of the country is one of the reasons behind this reduction in ET0 in these areas. During the summer season, regions in the upper latitudes have a lower ET0 because of their lower temperature than southern latitudes. In the autumn, there is a lower ET0 in the northern latitudes than in the southern regions of the country. Trend analysis shows that with the exception of the Arak station with an ET0 downward trend in April, most ET0 time series have a positive trend in the rest of the stations. Sanandaj is the only station that has a downward trend in ET0 in November. An increasing trend is observed in most of the studied stations, but in some other stations such as Arak and Sanandaj, a downward trend in the Reference Evapotranspiration may be observed. Finally, the results of the Innovative Trend Analysis (ITA) showed an upward trend in the amount of ET0 in both high and low areas in all seasons. This shows the increase of the long-term ET0 trend, indicating the increase in water requirements for plants in Iran. In the present study, climatic data from 40 stations from 1976 to 2020 were used to estimate ET0 in Iran. The Koppen- Geiger method was also used to classify the weather stations into the seven climates classes. The FAO PM, H-S, and PT models were used to estimate monthly and annually ET0. To choose the appropriate method of estimating ET0 in each climate zones; the H-S and PT methods were compared with the FAO PM method, and validated using RMSE and MAE statistics. Due to the involvement of various processes in ET0 changes, the best estimation method differs between stations. In this research, the H-S method was more compatible than the PT method at most of the stations.  Results have been presented as monthly and annual zoning maps. The zoning results of the three ET0 calculation methods mentioned showed that changes in climatic elements in different regions and periods have different effects on the ET0 value. The trend in ET0 changes using the Mann-Kendall test showed that the ET0 data at most stations have an increasing slope. Only two stations (Arak representing the top stations and Sanandaj representing the bottom station) have a decreasing slope. Based on the results of the ET0 time series analysis using ITA, the ET0 trend increased at all stations representative of the high and low elevation zones. Overall results show that TE0 has increased in most parts of the country, resulting in increased water requirements for plants. In the absence of effective management, Iran will face a serious water crisis in the future.