1- Department of Range and Watershed Management Engineering, Faculty of Natural Resources, Lorestan University, Khorramabad, Iran, Haghizadeh.a@lu.ac.ir , Haghizadeh.a@lu.ac.ir
2- Department of Range and Watershed Management Engineering, Faculty of Natural Resources, Lorestan University, Khorramabad, Iran, nooraldin@gmail.com
3- Department of Range and Watershed Management Engineering, Faculty of Natural Resources, Lorestan University, Khorramabad, Iran, ghasemi.leila3103@gmail.com
4- Department of Climatology, Faculty of Geographical Sciences, Kharazmi University, Tehran, Iran, std_bosak.a.97@khu.ac.ir
2- Department of Range and Watershed Management Engineering, Faculty of Natural Resources, Lorestan University, Khorramabad, Iran, nooraldin@gmail.com
3- Department of Range and Watershed Management Engineering, Faculty of Natural Resources, Lorestan University, Khorramabad, Iran, ghasemi.leila3103@gmail.com
4- Department of Climatology, Faculty of Geographical Sciences, Kharazmi University, Tehran, Iran, std_bosak.a.97@khu.ac.ir
Abstract: (162 Views)
Evaporation is considered a critical factor in water balance systems, accounting for substantial water loss from lakes. With advancements in remote sensing technologies and computational algorithms, the estimation of evaporation from water surfaces has undergone significant transformation. This study employed the SEBAL algorithm within the Google Earth Engine platform to estimate evaporation from the Ayvashan Dam reservoir. Landsat 8 satellite imagery was processed in Google Earth Engine (GEE) to compute pixel-level evapotranspiration using the SEBAL algorithm. The results revealed that across all three study dates (10/07/2024, 04/08/2024, and 26/08/2024), the evaporation rate near the center of the dam reservoir was consistently higher than in peripheral areas. Furthermore, this study demonstrates that implementing the SEBAL algorithm in the Google Earth Engine platform maintains reasonable accuracy despite challenges such as limited access to pan evaporation data and the 11 km distance between the meteorological station and study area - a finding supported by statistical metrics (RMSE = 2.4 and Nash-Sutcliffe coefficient of 0.83). Calculated evaporation rates for July, August, and September were 9.15 mm, 12.7 mm, and 9.34 mm respectively, indicating substantial water loss from the reservoir. These findings underscore the algorithm's effectiveness in evaporation estimation even under constrained ground data conditions. Given that precipitation in the study area occurs primarily as short-term episodic events with predominantly dry conditions throughout the year, water conservation during arid periods becomes particularly crucial.
Keywords: Google Earth Engine (GEE), SEBAL Algorithm, Cloud Computing, Evaporation Modeling, Eyvashan Dam.
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This work is licensed under a Creative Commons — Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)