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Assessing Water Quality Parameters in Burullus Lake Using Sentinel-2 Satellite Images

  • HYDROCHEMISTRY, HYDROBIOLOGY, ECOLOGICAL ASPECTS
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Abstract

Burullus lake is one of the coastal lakes in northern Egypt. Burullus lake is connected to seven drains through its western, eastern, and southern shores. The discharge of untreated wastewater (domestic, industrial, and agricultural) from these drains caused degradation for the water quality of the lake. Therefore, it is needed to develop a methodology to monitor water quality parameters at a low cost. This study is a trial to estimate water quality parameters from remote sensing data (reflectance data) by developing statistical regression models. Sentinel-2 reflectance data are compared to field measurements. The field measurements include transparency (SDT), chlorophyll-a concentration (Chl-a), total nitrogen (TN), total phosphorus (TP), and salinity. The coefficient of determination (R2) and normalized root mean square error (NRMSE) are calculated to evaluate the goodness of fit between field measurements and reflectance values. The results show that the optimum bands and bands ratios to estimate SDT, Chl-a, TN, TP, and Salinity are B6/B7, B7/B8, B8A, B8/B3, and B3/B8, respectively. The developed regression model is acceptable to be used for detecting water parameters and the produced R2 and NRMSE are within the range from 0.52 to 0.83 and from 0.12 to 0.34, respectively. The distribution maps of water quality parameters were built using the regression equations by writing these equations in the raster calculator as raster calculation expression. The results of this study show that both optical and non-optical water quality parameters are reasonably correlated with Sentinel-2 reflectance data as a low-cost data source.

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ACKNOWLEDGMENTS

The first author would like to thank the Egyptian Ministry of Higher Education (MoHE) for granting him the Post-Doctoral Scholarship. Also, thanks and gratitude for Tokyo Institute of Technology for their support and for offering the tools needed for this research. Also, thanks and gratitude for the Academy of Scientific Research and Technology (ASRT) of Egypt and the Italian National Research Council (CNR) in the framework of the bilateral CNR-ASRT project for their technical support.

Funding

The Egyptian Ministry of Higher Education (MoHE) has awarded a Postdoctoral Scholarship for the corresponding author to carry out this study. The corresponding author was hosted by Tokyo Institute of Technology as a visiting fellow, providing support and tools for this research.

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Authors and Affiliations

  1. Faculty of Engineering, Aswan University, Aswan, Egypt

    Hickmat Hossen

  2. Faculty of Engineering, Assiut University, Assiut, Egypt

    Wael Elham Mahmod

  3. Faculty of Engineering, Zagazig University, Zagazig, Egypt

    Abdelazim Negm

  4. School of Environment and Society, Tokyo Institute of Technology, Tokyo, Japan

    Takashi Nakamura

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  1. Hickmat Hossen
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  2. Wael Elham Mahmod
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  3. Abdelazim Negm
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  4. Takashi Nakamura
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Contributions

Hickmat Hossen (first author) is the author of the main idea of this paper and who obtained water quality data. Wael Mahmod (second author) participated in developing statistical models and reviewing the research. Abdelazim Negm (third author) is the author of the idea of using the Sentinel-2 satellite image and also contributed to the review of the research results. Takashi Nakamura (fourth author) is the author of the idea of creating the water quality distribution maps by written the regression equations as a raster calculator expressions in a raster calculator and also contributed to the review of the research results. All authors read and approved the final manuscript.

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Correspondence to Hickmat Hossen.

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All data generated or analysed during this study are included in this published article.

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Hossen, H., Mahmod, W.E., Negm, A. et al. Assessing Water Quality Parameters in Burullus Lake Using Sentinel-2 Satellite Images. Water Resour 49, 321–331 (2022). https://doi.org/10.1134/S0097807822020087

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