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Showing 2 results for Sebal Algorithm
Modeling Evaporation from Eyvashan Dam Lake: Implementing the SEBAL Algorithm and Cloud Computing on Google Earth Engine
Dr Ali Haghizadeh, Mr Nooraldin Moridi, Mrs Leila Ghasemi, Mrs Atefeh Bosak,
Volume 0, Issue 0 (3-1921)
Abstract
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.

Radiation balance and urban land use (case study: Kermanshah city)
Taher Safarrad, Mehran Mansourinia, Hersh Entezami,
Volume 19, Issue 53 (6-2019)
Abstract
Population growth and urbanization development are the main triggering factors of changes in urban land uses. These, in turn, result in changes in the components of radiation balance. The present study tries to analyze the role of urban land uses in radiation balance by calculating net radiation and its analysis. For this purpose, the Landsat 8 satellite image of 2016 was used. Characteristics of radiation flux including net radiation flux (RN), ground surface albedo (α), incoming longwave radiation (RL↓), incoming shortwave radiation (RS↓), outgoing longwave radiation (RL↑), and ground surface temperature were computed using Sebal algorithm.The values ​​of these components in different land uses (compressed residential, scattered residential, green area and wastelands) were analyzed using one-way analysis of variance (ANOVA) and Tukey’s test. The results of this study showed that the selected land uses have significant differences in the amount of radiation flux, therefore the wastelands are warmer than the residential areas by about 6 oC and the residential areas are warmer than the green areas by about 1.5 oC. The results also indicated that these differences are due to changes in output energy (α and RL↑), and any change in land use over time will ultimately lead to a change in the radiation balance and the temperature of those places, which this temperature increase, is different from the increase of the temperature due to global warming.

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This work is licensed under a Creative Commons — Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)