Evaporation plays a key role in the water balance of hypersaline lakes, where high Total Dissolved Solids (TDS) concentrations considerably impact evaporation rates. In this study, a novel Evaporation Factor based on TDS (EF-TDS) was introduced to improve evaporation estimates from hypersaline water bodies. Lake Urmia, one of the world’s largest hypersaline lakes, located in northwestern Iran, was selected as the case study. The Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), along with the FAO56-PM, Priestley-Taylor, and Hargreaves-Samani models, were evaluated. Additionally, the Bowen-Ratio Energy Balance (BREB) and Penman Salinity models were implemented for comparison. To implement these models, satellite data, including 30 Landsat 8 Operational Land Imager (OLI) images and 76 Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2013 to 2015, were processed using the Google Earth Engine (GEE) platform. In-situ measurements from a saline evaporation pan and a modified FAO56-PM model were employed to validate the results. The findings showed that, without considering TDS, all models overestimated evaporation, while METRIC outperformed other models with a Nash-Sutcliffe Efficiency (NSE) of 0.88 compared to the modified FAO56-PM model. However, after applying EF-TDS, remarkable improvements were observed across the models, with the Priestley-Taylor model achieving the highest performance (NSE = 0.90). Moreover, EF-TDS outperformed the method of reducing vapor pressure in evaporation models. This study demonstrates the importance of accounting for TDS in evaporation models, particularly for hypersaline lakes, and highlights the effectiveness of EF-TDS in improving the accuracy of evaporation estimates.

中文翻译：

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使用基于总溶解固体的因子改进高盐水体的蒸发估计


蒸发在高盐湖的水平衡中起着关键作用，其中高总溶解固体 （TDS） 浓度会对蒸发速率产生重大影响。在这项研究中，引入了一种基于 TDS 的新型蒸发因子 （EF-TDS） 来改进高盐水体的蒸发估计。位于伊朗西北部的世界上最大的高盐湖之一乌尔米亚湖被选为案例研究。评估了土地表面能量平衡算法 （SEBAL） 和高分辨率蒸散映射与内部校准 （METRIC） 以及 FAO56-PM、Priestley-Taylor 和 Hargreaves-Samani 模型。此外，还实施了 Bowen-Ratio Energy Balance （BREB） 和 Penman Salinity 模型进行比较。为了实现这些模型，使用 Google Earth Engine （GEE） 平台处理了卫星数据，包括 2013 年至 2015 年的 30 张 Landsat 8 Operational Land Imager （OLI） 图像和 76 张中分辨率成像光谱仪 （MODIS） 图像。采用盐水蒸发盘和改进的 FAO56-PM 模型的原位测量来验证结果。结果表明，在不考虑 TDS 的情况下，所有模型都高估了蒸发量，而与改进的 FAO56-PM 模型相比，METRIC 的表现优于其他模型，Nash-Sutcliffe 效率 （NSE） 为 0.88。然而，在应用 EF-TDS 后，观察到所有模型都有显著的改进，其中 Priestley-Taylor 模型实现了最高性能 （NSE = 0.90）。此外，EF-TDS 的性能优于蒸发模型中降低蒸气压的方法。 本研究证明了在蒸发模型中考虑 TDS 的重要性，特别是对于高盐湖，并强调了 EF-TDS 在提高蒸发估计准确性方面的有效性。