Estimating evapotranspiration (ET), the main water output flux within basins, is an important step in assessing hydrological changes and water availability. However, direct measurements of ET are challenging, especially for large regions. Global products now provide gridded estimates of ET at different temporal resolution, each with its own method of estimating ET based on various data sources. This study investigates the differences between ERA5, GLEAM, and GLDAS datasets of estimated ET at gridded points across Iran, and their accuracy in comparison with reference ET. The spatial and temporal discrepancies between datasets are identified, as well as their co-variation with forcing variables. The ET reference values used to check the accuracy of the datasets were based on the water balance (ET_wb) from Iran’s main basins, and co-variation of estimated errors for each product with forcing drivers of ET. The results indicate that ET_ERA5 provides higher base average values and lower maximum annual average values than ET_GLEAM. Temporal changes at the annual scale are similar for GLEAM, ERA5, and GLDAS datasets, but differences at seasonal and monthly time scales are identified. Some discrepancies are also recorded in ET spatial distribution, but generally, all datasets provide similarities, e.g., for humid regions basins. ET_ERA5 has a higher correlation with available energy than available water, while ET_GLEAM has higher correlation with available water, and ET_GLDAS does not correlate with none of these drivers. Based on the comparison of ET_ERA5 and ET_GLEAM with ET_wb, both have similar errors in spatial distribution, while ET_GLDAS provided over and under estimations in northern and southern basins, respectively, compared to them (ET_ERA5 and ET_GLEAM). All three datasets provide better ET estimates (values closer to ET_WB) in hyper-arid and arid regions from central to eastern Iran than in the humid areas. Thus, the GLEAM, ERA5, and GLDAS datasets are more suitable for estimating ET for arid rather than humid basins in Iran.

中文翻译：

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伊朗全球网格状蒸发蒸腾数据集的时空评估

估算蒸散量（ET）是流域内的主要出水通量，是评估水文变化和可用水量的重要步骤。但是，直接测量ET具有挑战性，特别是对于大区域。现在，全球产品在不同的时间分辨率下提供了ET的网格化估计，每种方法都有其自己的基于各种数据源的ET估计方法。这项研究调查了伊朗各地网格点的估计​​ET的ERA5，GLEAM和GLDAS数据集之间的差异，以及与参考ET相比其准确性。确定数据集之间的时空差异，以及它们与强迫变量的协方差。用于检查数据集准确性的ET参考值基于水平衡（ET _wb），并强制使用ET来驱动每种产品的估计误差的协变。结果表明，与ET _GLEAM相比，ET _ERA5提供了更高的基本平均值和更低的最大年平均值。对于GLEAM，ERA5和GLDAS数据集，年度尺度上的时间变化是相似的，但是可以确定季节性和每月尺度上的差异。ET空间分布中也记录了一些差异，但是通常，所有数据集都提供相似性，例如，对于潮湿地区的盆地。ET _ERA5与可用能量的相关性高于可用水，而ET _GLEAM与可用水的相关性更高，而ET _GLDAS与这些驱动程序都不相关。根据ET _ERA5和ET _GLEAM与ET _wb的比较，两者在空间分布上都有相似的误差，而ET _GLDAS分别提供了北部和南部盆地的_高估和_低估（ET _ERA5和ET _GLEAM）。在伊朗中部和东部的干旱和干旱地区，这三个数据集都比潮湿地区提供了更好的ET估计（值更接近ET _WB）。因此，GLEAM，ERA5和GLDAS数据集更适合于估算伊朗干旱而不是潮湿盆地的ET。