نوع مقاله : مقاله پژوهشی
نویسندگان
1 محقق بخش آبیاری و فیزیک خاک، مؤسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران
2 گروه سازه‌های آبی، گروه علوم و مهندسی آب، دانشکده کشاورزی دانشگاه شهرکرد، شهرکرد، ایران.
3 دانشیار بخش آبیاری و فیزیک خاک، مؤسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران
4 استادیار بخش آبیاری و فیزیک خاک، موسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Appropriate estimation of reference evapotranspiration (ET0) has always been challengeas the fundamental parameter to estimate crop water requirement (ETc) in places with a data limitation forresearchers of soil and water resources.In this research, (ET0) had been estimated using the ERA5 reanalysis dataset and the by Penman–Monteith FAO-56 (PM). In the next step, the result was evaluated at the location of meteorological stations in the catchment of Karoon.Climatic data to compute the (ET0) from 26 synoptic meteorological stations of the basin and ERA5 dataset were obtained. Then, daily ET0 were calculated from 1390 to 1400.At first, variables including Tmax, Tmean, Tdew, Tmin, solar radiation, and wind speed were compared with the data of the meteorological station.The results showed that, the ERA5 dataset showed provide reliable temperature parameters and solar radiation estimates (i.e., normalized root mean square error (nRMSE) of < 30%)at the majority of cases. Although this dataset showed high nRMSE in all stations for wind speed values. These comparison between ET0 from observation and ERA5 dataset shown that at the 17 station from 26 station nRMSE less than 30 percent. Overall, the use of ERA5 dataset and estimation of ET0 in places that are faced with data scarcityfor decision- making in new planning can be a useful and reliable tool.
کلیدواژه‌ها [English]
Extended Abstract
Reference Evapotranspiration (ET0) is a complex hydrological variable that is defined by various climatic factors affecting water and energy balances. These balances are critical for determining crop water requirements and irrigation scheduling. The most common method for estimating ET0 is using meteorological data and applying the FAO Penman-Monteith equation. However, meteorological stations are often located at a distance away from agriculture areas, and may not provide accurate ET0 due to the conditions at specific locations. This has led to the development of various empirical methods for estimating ET0 based on rigorous climatic data. In places where climatic data is not readily available, the use of reanalysis datasets, such as ERA5, can provide a suitable alternative for ET0 estimation.
The objective of this study is to evaluate the meteorological data from the ERA5 dataset and compare the estimated ET0 values obtained from the weather station to those obtained from the reanalysis dataset.
For the purpose of this study, data related to ET0 estimation, such as minimum temperature (Tmin), maximum temperature (Tmax), average temperature (Tmean), dew point temperature (Tdewpoint), sunshine (SR), and average relative humidity (RHmean), were collected from 26 synoptic stations in the Karun basin over the period of 2010-2020. These data was then compared to the corresponding data from the ERA5 datasets. ET0 was estimated on a daily temporal resolution using the Penman-Monteith method from FAO 56, and the results were compared to the field measurements. Finally, the accuracy of the two methods for estimating ET0 was assessed using statistical indices, including nRMSE and rMBE.
The results of the comparison between the ERA5 dataset and the synoptic stations in the Karun basin showed that Tmax had an nRMSE of less than 30% in all stations, except for Safi Abad Dezful. Tmean had an nRMSE of more than 30% in Yasuj, Dehdz, and Farsan stations. Additionally, the variables of Tmin, Tdew, and U2 had high nRMSE values. The solar radiation variable showed an error of more than 30% in four stations, Gatvand, Shush, Azna, and Ahvaz, indicating a relatively good performance of this parameter. The evaluation of ET0 showed that in 9 out of 26 stations, the error was more than 30%. In other words, the ET0 estimated from the ERA5 dataset provided acceptable results in approximately two-thirds of the stations in the Karun catchment.
After evaluating the reference evapotranspiration and the key parameters affecting its estimation from the ERA5 dataset with the data from the synoptic stations in the Karun catchment, the results showed that the ERA5 dataset produced satisfactory results. However, the highest error was found to be related to the U2 values at the weather station locations. It is therefore suggested to use meteorological U2 values instead of wind values from the reanalysis dataset. If meteorological data is not available at the catchment scale, reanalysis datasets such as ERA5 can be implemented as a suitable alternative.
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