Climate Change Research

Climate Change Research

Reference Evapotranspiration Dynamics Under the Shadow of Atmospheric Dryness: A Multidimensional Assessment of Empirical Methods in a Semi-Arid Region

Document Type : Original Article

Authors
1 Professor, Department of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources. Gorgan, Iran
2 Ph.D. Candidate in Irrigation and Drainage, Department of Water Engineering, Sari Agricultural Sciences and Natural Resources University. Sari, Iran,
3 Postdoctoral Researcher, Department of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources. Gorgan, Iran
4 Associate Professor, Department of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources. Gorgan, Iran
5 Assistant Professor, Department of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources. Gorgan, Iran
10.30488/ccr.2026.598895.1357
Abstract
Accurate estimation of reference evapotranspiration (ET₀) is essential for effective water resources management, particularly under changing climatic conditions. This study evaluates the performance of 14 empirical methods for estimating ET₀ against the standard FAO Penman–Monteith (PM-FAO56) method and investigates their temporal variations at the Hashemabad synoptic station in Golestan Province, Iran. For this purpose, descriptive statistics, distribution analysis, Pearson’s correlation coefficient, and time-series analyses based on the Mann–Kendall, Sen’s slope, and Pettitt tests were employed. The results showed that the ABT method performed well in terms of the similarity of its estimated mean and distribution characteristics to those of PM-FAO56. The ROM method exhibited the highest temporal correlation with PM-FAO56 (r = 0.848), whereas PAP showed relatively good agreement and error characteristics, with a higher Lin’s concordance correlation coefficient (LinCCC = 0.702), low bias (−14.64 mm), and the lowest RMSE (105.05 mm). In contrast, BC substantially overestimated, while MAK considerably underestimated. Trend analysis showed that all ET₀ series increased significantly at the 5% significance level, with the highest Sen’s slope for PM-FAO56 (11.7 mm year⁻¹). The Pettitt test also identified significant change points for most methods in 1997, 1999, and 2011. The co-occurrence of these changes with increases in temperature, solar radiation, and wind speed, along with a decrease in mean relative humidity, indicates substantial changes in the climatic conditions associated with evaporative demand at the study station. These findings highlight the importance of a multi-criteria evaluation of ET₀ estimation methods; however, the generalization of the results to other regions requires independent temporal and spatial validation.
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