Utilizing Satellite Imagery to Map Lake Surface Temperature and Explore its Effect on Evaporation Rate

This study aims to map the Lake Surface Water Temperature (LSWT) for the northern part of Aswan High Dam Lake (AHDL) within the years 2018, 2019, and 2020; and detect the effect of the estimated LSWT on the evaporation rate. To achieve these objectives, firstly, the LSWT maps were created from the Landsat-8 satellite images, a widely and conventional used method. Moreover, the LSWT maps were also generated by Sentinel-3 Sea and Land Surface Temperature Radiometer (Sentinel-3/SLSTR) satellite images. The created temperature maps by Landsat-8 were used to assess the ones produced by Sentinel-3. Then the relationship between the Sentinel-3 derived LSWT and the estimated evaporation rate, provided by floating hydro-meteorological stations within AHDL and reported by annual reports of the Ministry of Water Resources and Irrigation (MWRI), was determined. After assessing, it was found that the convergence percentage between the estimated temperature values by the Sentinel-3 and those estimated by Landsat-8 (the reference values) ranges from 1.00% to 4.71%, which indicates that the estimated temperature values from both satellite images are very close. Therefore, it is possible to rely on the results of the created temperature maps for the study area by Sentinel-3. Additionally, the study revealed a direct relationship between the evaporation rate and the LSWT estimated by Sentinel-3 within the same year. However, the results demonstrated that changes in the evaporation rate vary from year to year, indicating that LSWT is not the sole factor influencing.

Authors

Institutions

Publication Details

Journal
Aswan University Journal of Environmental Studies
Published
2025-03-01
DOI
https://doi.org/10.21608/aujes.2025.328326.1296
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Utilizing Satellite Imagery to Map Lake Surface Temperature and Explore its Effect on Evaporation Rate

Mohamed Soliman, Mohamed Elsahabi, Mohamed Hussein
Aswan University Journal of Environmental Studies
Water Quality Monitoring Technologies
article

Utilizing Satellite Imagery to Map Lake Surface Temperature and Explore its Effect on Evaporation Rate

Mohamed Soliman, Mohamed Elsahabi, Mohamed Hussein
article en

Abstract

This study aims to map the Lake Surface Water Temperature (LSWT) for the northern part of Aswan High Dam Lake (AHDL) within the years 2018, 2019, and 2020; and detect the effect of the estimated LSWT on the evaporation rate. To achieve these objectives, firstly, the LSWT maps were created from the Landsat-8 satellite images, a widely and conventional used method. Moreover, the LSWT maps were also generated by Sentinel-3 Sea and Land Surface Temperature Radiometer (Sentinel-3/SLSTR) satellite images. The created temperature maps by Landsat-8 were used to assess the ones produced by Sentinel-3. Then the relationship between the Sentinel-3 derived LSWT and the estimated evaporation rate, provided by floating hydro-meteorological stations within AHDL and reported by annual reports of the Ministry of Water Resources and Irrigation (MWRI), was determined. After assessing, it was found that the convergence percentage between the estimated temperature values by the Sentinel-3 and those estimated by Landsat-8 (the reference values) ranges from 1.00% to 4.71%, which indicates that the estimated temperature values from both satellite images are very close. Therefore, it is possible to rely on the results of the created temperature maps for the study area by Sentinel-3. Additionally, the study revealed a direct relationship between the evaporation rate and the LSWT estimated by Sentinel-3 within the same year. However, the results demonstrated that changes in the evaporation rate vary from year to year, indicating that LSWT is not the sole factor influencing.

Aswan University Journal of Environmental StudiesVol. 6(1)
Aswan University (EG)
Climate action
Openalex Percentile: Top 93%
Water Quality Monitoring Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.