Long-term water quality monitoring using Sentinel-2 data, Głuszyńskie Lake case study

• Autorzy: Ciężkowski Wojciech , Frąk Magdalena , Kardel Ignacy , Kościelny Marcin , Chormański Jarosław

Identyfikatory

DOI

10.22630/srees.448

• Języki publikacji: EN

Abstrakty

EN

This study shows the results of long-term inland water monitoring using Sentinel-2 data for Głuszyńskie Lake in the years 2015–2022. Four water quality parameters: biological oxygen demand (BOD), dissolved organic carbon (DOC), chlorophyll concentration (CHL) and electrical conductivity (EC) were calculated according to formulas found in the literature. The results were validated based on measurements conducted in 2021 and 2022, where for BOD, DOC and CHL high determination coefficients (0.77 and 0.79) were observed, and the EC determination coefficient was equal to 0.45. The results show that empirical formulas can be used for qualitative analyses of inland water quality, while for quantitative analyses more extensive field work needs to be performed.

Słowa kluczowe

EN

sentinel-2; inland water; biological oxygen demand; BOD; dissolved organic carbon; DOC; electrical conductivity; EC; chlorophyll concentration; CHL

• Wydawca: Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
• Czasopismo: Przegląd Naukowy Inżynieria i Kształtowanie Środowiska
• Rocznik: 2022
• Tom: Vol. 31, No. 4
• Strony: 283--293
• Opis fizyczny: Bibliogr. 21 poz., rys., tab., wykr.

Twórcy

autor

Ciężkowski Wojciech

• Department of Remote Sensing and Environmental Assessment, Institute of Environmental Engineering, Warsaw University of Life Science – SGGW, Nowoursynowska 166, 02-787 Warsaw, Poland

• https://orcid.org/0000-0003-3777-6550+

autor

Frąk Magdalena

• Department of Remote Sensing and Environmental Assessment, Institute of Environmental Engineering, Warsaw University of Life Science – SGGW, Nowoursynowska 166, 02-787 Warsaw, Poland

• https://orcid.org/0000-0001-5737-1951+

autor

Kardel Ignacy

• Department of Hydrology, Meteorology and Water Management, Institute of Environmental Engineering, Warsaw University of Life Science – SGGW, Nowoursynowska 166, 02-787 Warsaw, Poland

• https://orcid.org/0000-0002-5425-6218

autor

Kościelny Marcin

• Air-Concept Ltd Co., Rynek 10, 88-150 Kruszwica, Poland

autor

Chormański Jarosław

• Department of Remote Sensing and Environmental Assessment, Institute of Environmental Engineering, Warsaw University of Life Science – SGGW, Nowoursynowska 166, 02-787 Warsaw, Poland

• https://orcid.org/0000-0002-3800-4205+

Bibliografia

• Abdelmalik, K. W. (2018). Role of statistical remote sensing for inland water quality parameters prediction. The Egyptian Journal of Remote Sensing and Space Science, 21 (2), 193-200.
• Brando, V. E. & Dekker, A. G. (2003). Satellite hyperspectral remote sensing for estimating estuarine and coastal water quality. IEEE Transactions on Geoscience and Remote Sensing, 41 (6), 1378-1387.
• Duan, W., He, B., Takara, K., Luo, P., Nover, D., Sahu, N. & Yamashiki, Y. (2013a). Spatiotemporal evaluation of water quality incidents in Japan between 1996 and 2007. Chemosphere, 93 (6), 946-953.
• Duan, W., Takara, K., He, B., Luo, P., Nover, D. & Yamashiki, Y. (2013b). Spatial and temporal trends in estimates of nutrient and suspended sediment loads in the Ishikari River, Japan, 1985 to 2010. Science of the Total Environment, 461, 499-508.
• Gholizadeh, M. H., Melesse, A. M. & Reddi, L. (2016). A comprehensive review on water quality parameters estimation using remote sensing techniques. Sensors, 16 (8), 1298.
• Giardino, C., Bresciani, M., Cazzaniga, I., Schenk, K., Rieger, P., Braga, F., Matta, E. & Brando, V. E. (2014). Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda. Sensors, 14 (12), 24116-24131.
• Gitelson, A. A., Dall’Olmo, G., Moses, W., Rundquist, D. C., Barrow, T., Fisher, T. R., Gurlin, D. & Holz, J. (2008). A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation. Remote Sensing of Environment, 112 (9), 3582-3593.
• Hadjimitsis, D. G. & Clayton, C. (2009). Assessment of temporal variations of water quality in inland water bodies using atmospheric corrected satellite remotely sensed image data. Environmental Monitoring and Assessment, 159 (1), 281-292.
• International Organization for Standardization [ISO] (1999). Water quality. Guidelines for the determination of total organic carbon (TOC) and dissolved organic carbon (DOC) (ISO 8245). Geneva.
• Kloiber, S. M., Brezonik, P. L., Olmanson, L. G. & Bauer, M. E. (2002). A procedure for regional lake water clarity assessment using Landsat multispectral data. Remote Sensing of Environment, 82 (1), 38-47.
• Mancino, G., Nolè, A., Urbano, V., Amato, M. & Ferrara, A. (2009). Assessing water quality by remote sensing in small lakes: the case study of Monticchio lakes in southern Italy. iForestBiogeosciences and Forestry, 2 (4), 154.
• Morel, A. & Prieur, L. (1977). Analysis of variations in ocean color 1. Limnology and Oceanography, 22 (4), 709-722.
• Osińska-Skotak, K. (2010). Metodyka wykorzystania super- i hiperspektralnych danych satelitarnych w analizie jakości wód śródlądowych [Methodology of using super- and hyperspectral satellite data for inland water quality analysis]. Prace Naukowe Politechniki Warszawskiej. Geodezja, 47, 3-153.
• Polski Komitet Normalizacyjny [PKN] (2002). Jakość wody. Pomiar parametrów biochemicznych. Spektrometryczne oznaczanie stężenia chlorofilu a (PN-ISO 10260). Warszawa.
• Potes, M., Rodrigues, G., Penha, A. M., Novais, M. H., Costa, M. J., Salgado, R. & Morais, M. M. (2018). Use of Sentinel 2 - MSI for water quality monitoring at Alqueva reservoir, Portugal. Proceedings of the International Association of Hydrological Sciences, 380, 73-79.
• R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Retrieved from: http://www.r-project.org/index.html [accessed: 28.11.2022].
• Ranghetti, L., Boschetti, M., Nutini, F. & Busetto, L. (2020). “sen2r”: an R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data. Computers & Geosciences, 139, 104473.
• Ritchie, J. C., Zimba, P. V. & Everitt, J. H. (2003). Remote sensing techniques to assess water quality. Photogrammetric Engineering & Remote Sensing, 69 (6), 695-704.
• Słapińska, M., Berezowski, T., Frąk, M. & Chormański, J. (2016). Retrieval of water quality algorithms from airborne HySpex camera for oxbow lakes in north-eastern Poland. In EGU General Assembly 2016, 17-22 April 2016 Vienna. Book of abstracts. Vol. 18, EPSC2016-14167.
• Ścisłowski, Ł., Państwowe Gospodarstwo Wodne Wody Polskie - KZGW, Wydział SIGW (10.03.2022). Wody Polskie - Baza WMS. ver. 1.0.1. QGIS Python Plugins Repository. Retrieved from: https://github.com/LScislowski/Wody_Polskie_Baza_WMS [accessed: 28.11.2022].
• U.S. Environmental Protection Agency [EPA] (1983). Total Organic Carbon. Method 415.1. (Combustion or Oxidation). In Methods for the Chemical Analysis of Water and Wastes (EPA/600/4-79/020). Cincinnati, OH. Retrieved from: https://www.wbdg.org/FFC/EPA/EPACRIT/epa600_4_79_020.pdf [accessed: 28.11.2022].

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)