Performance Assessment of Remote Sensing and Empirical Evaporation Models in Lake Urmia

Authors
H. Khaleghi 1
M. Rahimzadegan 2
1 M.Sc. Graduate of Water Resources Engineering and Management Department, Faculty of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran.
2 Associate professor, Water Resources Engineering and Management Department, Faculty of Civil Engineering, K. N. Toosi University of Technology
Abstract
Evaporation serves as a significant factor in the hydrological deficit experienced by Lake Urmia, thereby exerting a vital influence on its overall water equilibrium. The evolution of satellite sensor technology has facilitated the acquisition of a comprehensive range of satellite imagery, underscoring the necessity for meticulous evaluation in the assessment of lake evaporation. This research endeavor is designed to quantify daily evaporation rates from Lake Urmia through the integration of Landsat 8 and 9 imagery from the year 2022, while concurrently assessing the efficacy of physical, empirical, and remote sensing methodologies. A comprehensive analysis was conducted on a total of 21 satellite images, wherein the FAO56-PM, Priestley-Taylor, and Hargreaves-Samani models, in conjunction with the remote sensing techniques of the Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration at High Resolution and with Internalized Calibration (METRIC), were executed within the Google Earth Engine (GEE) framework. The resultant model outputs were corroborated against pan evaporation data obtained from the Urmia meteorological station, which served as the reference ground truth dataset. The analysis indicated that SEBAL, when utilized without a correction factor, exhibited superior accuracy, achieving a Root Mean Square Error (RMSE) of 0.83 mm/day and a Nash-Sutcliffe Efficiency (NSE) value of 0.48. Upon the implementation of a correction factor, the FAO56-PM model produced optimal outcomes, with an RMSE of 1.04 mm/day and an NSE of 0.18. In summary, SEBAL surpassed the performance of the other models, attributable to its dependence on satellite-derived imagery. Moreover, the amalgamation of satellite data with empirical modeling approaches holds significant potential for enhancing water resource management strategies within the context of Lake Urmia.

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The Journal of Spatial Planning and Geomatics
Volume 29, Issue 1
March 2025
Pages 1-23