نوع مقاله : مقاله پژوهشی
نویسندگان
گروه مهندسی و مدیریت آب،دانشکده کشاورزی، دانشگاه تربیت مدرس، تهران، ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
This study evaluates the accuracy and performance of the FAO WaPOR version 2 model product for reference evapotranspiration (ET₀ WaPOR) in comparison with corresponding estimates derived from the FAO Penman-Monteith equation using meteorological station data across various climate zones in Iran. A total of 42 stations located in northern and northeastern provinces of the country, with recorded data from 2009 to 2022, were selected for the analysis. Comparisons were conducted at daily, dekadal, and monthly time scales. To assess the role of climate, regions were classified based on the UNEP aridity index. Furthermore, the impact of radiative and convective components on evapotranspiration estimation accuracy in the WaPOR model was investigated. Results showed that the WaPOR model performed well in arid and semi-arid climates, with an average R² of 0.91 and an average nRMSE of approximately 20%. In contrast, in humid and sub-humid climates, the R² and nRMSE were 0.83 and 26%, respectively. The model's bias was negative in arid climates and positive in humid ones, indicating overestimation under humid conditions. Additionally, the analysis of the radiative and convective contributions to evapotranspiration estimation revealed that model accuracy decreased with increasing radiative dominance, particularly in humid regions. Overall, the WaPOR model, based on remote sensing, can be considered a reliable tool for irrigation planning in arid and semi-arid regions, especially during the wheat growing season. However, its performance in humid climates requires further optimization.
کلیدواژهها [English]
Water is a fundamental agricultural input and the most limiting factor for production in arid and semi-arid regions. In Iran, with its diverse climatic zones, water resources are under increasing pressure due to population growth, reduced per capita water availability, and the intensification of agricultural activities. Inefficient water use and irrigation practices exacerbate these challenges, making it essential to optimize irrigation systems for sustainable water management. Reference evapotranspiration (ET₀) plays a critical role in estimating crop water requirements, influencing irrigation scheduling and water resource management. The FAO Penman-Monteith equation, widely recognized as the most accurate method for ET₀ estimation, requires extensive meteorological data that may not always be readily available. This limitation has led to the use of satellite-based data, such as those provided by the WaPOR platform, which offers free, daily ET₀ data with a 20 km spatial resolution since 2009. This study aims to assess the performance of WaPOR's ET₀ data by comparing it with ground-based measurements across various climatic zones in Iran, providing insights into its potential for improving water management in agriculture.
This study was conducted in six northern and northeastern provinces of Iran, including Gilan, Mazandaran, Golestan, Semnan, North Khorasan, and Razavi Khorasan, which have diverse climates and rainfall amounts. Meteorological data, including minimum and maximum temperature, relative humidity, wind speed, sunshine hours, and precipitation, were collected from 42 synoptic stations in the region over a 14-year period (2009–2022). The Aridity Index (AI) for each station was calculated using the FAO Penman-Monteith equation, and the climates were classified into humid, semi-humid, dry semi-humid, dry, and semi-arid categories. Additionally, reference evapotranspiration (ET₀ WaPOR) data from the WaPOR platform with a 20 km spatial resolution were obtained for further analysis. These data were extracted on a daily, ten-day, and monthly basis and compared with station data to assess the accuracy and performance of ET₀ WaPOR. To balance the results, four stations from each climate zone were selected and analyzed. Moreover, the radiative and convective components of ET₀ were calculated to distinguish between dry and humid climates. Finally, reference evapotranspiration (ET₀ WaPOR) data during the wheat and rice growing seasons were analyzed to evaluate the accuracy of the WaPOR model using four statistical indices, including (R²), (RMSE), (nRMSE), and (MBE).
The results of the study indicate that the performance of the ET₀ WaPOR product in estimating reference evapotranspiration (ET₀) is influenced by climatic conditions. At different time scales, especially the daily scale, the correlation between WaPOR data and station values is generally high, but this correlation is higher in dry climates compared to humid climates. In dry climates, the coefficient of determination (R²) was on average 0.86, and the nRMSE was around 25%, whereas in humid climates, these values decreased to 0.82 and 39%, respectively. These differences emphasize the importance of considering climatic characteristics when using remote sensing products. Additionally, the bias error analysis indicates that in humid climates, WaPOR tends to overestimate values, and this tendency increases with higher humidity in the climate.
The results of this study indicate that the WaPOR model performs better, especially in dry and semi-arid regions, and shows higher accuracy in estimating reference evapotranspiration (ET₀) at longer time scales, such as the monthly scale. This improved performance is due to the reduction of short-term fluctuations and sampling errors at larger time scales. However, in more humid climates, the WaPOR model requires further adjustments, as the correlation between satellite data and ground-based values decreases and errors increase. Specifically, in more humid climates with higher radiative flux, the model's accuracy decreases, whereas in drier climates with higher convective flux, the model's accuracy improves. These findings emphasize that the WaPOR model requires bias correction and model optimization in humid regions. Furthermore, the results suggest that for the effective use of WaPOR data in management and agricultural studies, emphasis on regional accuracy and bias correction is essential, especially in humid climates where overestimation tendencies exist. Ultimately, this research can serve as a foundation for designing more accurate models to predict evapotranspiration under different climatic conditions and demonstrates that the WaPOR model is a suitable tool for irrigation planning in dry and semi-arid regions, but requires further optimization in humid areas.
F.K: Data preparation and review, software programming, resource provision, results interpretation, writing the original draft, visualization, and project management. S.H.T: Methodology design, formal analysis and data investigation, final review. S.M.M: Results interpretation, review, and editing and supervision. H.S.M: Manuscript review, results interpretation.
Data is available on reasonable request from the authors.
This paper is published as part of a Master's thesis at Tarbiat Modares University, Iran. The authors would like to thank the Iranian Meteorological Organization for their valuable collaboration and support.
The authors declare that there is no conflict of interest regarding the publication of this manuscript. In addition, the ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, and redundancies have been fully observed by the authors.
The authors declare no conflict of interest.
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