Abstract
An evaporation study was conducted at Van Lake, one of the largest soda lakes on Earth, which is located on a high plateau in the Eastern Anatolia region of Turkey. Evaporation on a daily basis for the Gevaş station located at the southeastern shore of the lake was calculated using the Bowen ratio energy budget (BREB), Priestley–Taylor, deBruin–Keijman, Penman, and deBruin methods. The calculated evaporation values were then compared and tested with previously calculated and measured evaporation rates. Compared with available measured evaporation data, the best evaporation estimations (within ±0.5 mm/day) were made by the BREB method. The BREB calculations made in this study were statistically significant at the confidence level of 99.9 % for estimation of evaporation at the Gevaş station. Relationships between the calculated BREB evaporations and historical climatic records were also examined to propose a new empirical equation for evaporation estimation for the case of Lake Van. The best regression equation with a coefficient of determination (R 2) of 0.9399 was found between BREB evaporation values and incoming solar radiation (Q s) values. A power regression model proposed to estimate daily evaporation rates from Q s values was statistically significant at the confidence level of 99.9 %. Additionally, a few regression models were also examined to predict the surface water temperature of Lake Van from recorded air temperature. The highest coefficient of determination (0.974) and moderate standard error (3.12 °C) values were obtained from a polynomial air–water temperature model. Estimated lake water temperatures using the polynomial model were within ±10 % of observed lake water temperatures.
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The authors are grateful and thank the Turkish State Meteorological Service (DMI) for providing the meteorological data. We acknowledge the anonymous reviewers for their careful reading of our manuscript and for their valuable comments and suggestions.
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Aydin, H., Karakuş, H. Estimation of evaporation for Lake Van. Environ Earth Sci 75, 1275 (2016). https://doi.org/10.1007/s12665-016-6077-4
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DOI: https://doi.org/10.1007/s12665-016-6077-4