Turbidity and Secchi disc depth with Sentinel-2 in different trophic status reservoirs at the Comunidad Valenciana
DOI:
https://doi.org/10.4995/raet.2019.12603Keywords:
Sentinel-2, eutrophication, Secchi disk, turbidity, Júcar basin reservoirsAbstract
Transparency or turbidity is one of the main indicators in studies of water quality using remote sensing. Transparency can be measured in situ through the Secchi disc depth (SD), and turbidity using a turbidimeter. In recent decades, different relationships between bands from different remote sensing sensors have been used for the estimation of these variables. In this paper, several indices and spectral bands have been calibrated in order to estimate transparency from Sentinel-2 (S2) images from field data, obtained throughout 2017 and 2018 in Júcar basin reservoirs with a great variety of trophic states. Three atmospheric correction methods developed for waters have been applied to the S2 level L1C images taken at the same day as the field data: Polymer, C2RCC and C2X. From the spectra obtained from S2 and the SD field data, it has been found that the smallest error is obtained with the images atmospherically corrected with Polymer and a potential adjustment of the reflectivities’ ratio of the blue and green bands (R490/R560), which allow the estimation of SD with a relative error of 13%. Also the C2X method presents good adjustment with the same bands ratio, although with a greater error, while the correction C2RCC shows the worst correlation. The relationship between SD (in m) and turbidity (in NTU) has also been obtained, which provides an operational method for estimating turbidity with S2. The relationship for the different reservoirs between SD and chlorophyll-a concentration, suspended solids and dissolved organic matter, is also shown.
Downloads
References
Alikas, K., Kratzer, S. 2017. Improved retrieval of Secchi depth for optically-complex waters using remote sensing data. Ecological indicators, 77, 218- 227. https://doi.org/10.1016/j.ecolind.2017.02.007
Ansper, A., Alikas, K. 2019. Retrieval of Chlorophyll-a from Sentinel-2 MSI Data for the European Union Water Framework Directive Reporting Purposes. Remote Sensing, 11, 64. https://doi.org/10.3390/rs11010064
APHA, 1992. Standard methods for the examination of water and wastewater. 18th edition. American Public Health Association. Washington D.C., USA. 1105 pp.
Baughman, C.A., Jones, B.M., Bartz, K.K., Young, D.B., Zimmerman, C.E. 2015. Reconstructing Turbidity in a Glacially Influenced Lake Using the Landsat TM and ETM+ Surface Reflectance Climate Data Record Archive, Lake Clark, Alaska. Remote Sensing, 7, 13692-13710. https://doi.org/10.3390/rs71013692
Brockmann, C., Doerffer, R., Peters, M., Kerstin, S., Embacher, S., Ruescas, A. 2016. Evolution of the C2RCC neural network for Sentinel 2 and 3 for the retrieval of ocean colour products in normal and extreme optically complex waters. In Proceedings of the “ESA Living Planet Symposium 2016”, Prague, Czech Republic, 9-13 May 2016.
Delegido, J., Urrego, P., Ruiz-Verdú, A., PereiraSandoval, M., Vicente, E., Sòria-Perpinyà, X., Soria, J.M., Moreno, J. 2019. Transparencia de diferentes embalses de la cuenca del Júcar con imágenes Sentinel-2. XVIII Congreso de la Asociación Española de Teledetección. Valladolid, 24-27 septiembre 2019.
Doron, M., Babin, M., Mangin, A., Hembise, O. 2007. Estimation of light penetration, and horizontal and vertical visibility in oceanic and coastal waters from surface reflectance. J. Geophys. Res., 112, C06003. https://doi.org/10.1029/2006JC004007
Gholizadeh, M.H., Melesse, A.M., Reddi, L. 2016. A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques. Sensors, 16(8), E1298. https://doi.org/10.3390/s16081298
Jeffrey, S.T., Humphrey, G.F. 1975. New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochem. Physiol. Pflanz., 167, 191-194. https://doi.org/10.1016/S0015-3796(17)30778-3
Khorram, S., Cheshire, H., Geraci, A.L., Rosa, G.L., 1991. Water quality mapping of Augusta Bay, Italy from Landsat-TM data. Int. J. Remote Sens., 12(4), 803- 808. https://doi.org/10.1080/01431169108929696
Koponen, S., Pulliainen, J., Kallio, K., Hallikainen, M. 2002, Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data. Remote Sensing of Environment, 79, 51-59. https://doi.org/10.1016/S0034-4257(01)00238-3
Korshin, G.V., Li, C.W., Benjamin, M.M. 1997. Monitoring the properties of natural organic matter through UV spectroscopy: A consistent theory. Water Research, 31, 1787-1795. https://doi.org/10.1016/S0043-1354(97)00006-7
Kratzer, S., Brockmann, C., Moore, G. 2008. Using MERIS full resolution data to monitor coastal waters – A case study from Himmerfjärden, a fjordlike bay in the northwestern Baltic Sea. Remote Sensing of Environment, 112(5), 2284-2300. https://doi.org/10.1016/j.rse.2007.10.006
Lee, Z., Shang, S., Hu, C., Du, K., Weidemann, A., Hou, W., Lin, J., Lin, G. 2016. Secchi disk depth: a new theory and mechanistic model for underwater visibility. Remote Sens. Environ., 169, 139-149. https://doi.org/10.1016/j.rse.2015.08.002
Matthews, M.W. 2011. A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters. International Journal of Remote Sensing, 32(21), 6855-6899. https://doi.org/10.1080/01431161.2010.512947
Mosquera, A., Torres, J.M., González-Vilas, L., Martínez-Iglesias, G., Pazos, Y. 2006. Estudio de una floración tóxica de Pseudonitzschias sp. en las costas de Galicia usando una imagen MERIS y datos in situ. Revista de Teledetección, 25, 75-79. Disponible en: http://www.aet.org.es/revistas/revista25/AET25- 15.pdf. Último acceso: Diciembre de 2019.
Mueller, J. L. 2000. SeaWiFS algorithm for the diffuse attenuation coefficient, K (490), using water-leaving radiances at 490 and 555 nm. SeaWiFS Postlaunch Calibration and Validation Analyses, part 3, edited by S. B. Hooker, pp. 24–27, NASA Goddard Space Flight Center.
Page, B., Kumar, A., Mishra, D. 2018. A novel crosssatellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom. Int. J. Appl. Earth Obs. Geoinf., 66, 68-81. https://doi.org/10.1016/j.jag.2017.11.003
Page, B., Olmanson, L., Mishra, D. 2019. A harmonized image processing workflow using Sentinel-2/MSI and Landsat-8/OLI for mapping water clarity in optically variable lake systems. Remote Sens. Environ., 231, 111284. https://doi.org/10.1016/j.rse.2019.111284
Pahlevan, N., Chittimalli, S., Balasubramanian, S., Vellucci, V. 2019. Sentinel2/Landsat8 product consistency and implications for monitoring aquatic systems. Remote Sens. Environ., 220, 19-29. https://doi.org/10.1016/j.rse.2018.10.027
Pereira-Sandoval, M., Ruescas, A.B., Urrego, P., Delegido, J., Ruiz-Verdú, A, Tenjo, C., SoriaPerpinyà, X., Vicente, E, Soria, J., Peña, R., Moreno, J. 2018. Evaluación de métodos de corrección atmosférica sobre imágenes Sentinel2-MSI en aguas continentales. XVIII Simposio Internacional SELPER y Sistemas de Información Espacial, Noviembre de 2018, La Habana, Cuba.
Pereira-Sandoval, M., Urrego, P., Ruiz-Verdú, A., Tenjo, C., Delegido, J., Soria-Perpinyà, X., Vicente, E., Soria, J., Moreno, J. 2019a. Calibration and validation of algorithms for the estimation of chlorophyll-a concentration and Secchi depth in inland waters with Sentinel-2. Limnetica, 38(1), 471- 487. https://doi.org/10.1109/IGARSS.2018.8517371
Pereira-Sandoval, M., Ruescas, A., Urrego, P., RuizVerdú, A., Delegido, J., Tenjo, C, Soria-Perpinyà, X., Vicente, E., Soria, J., Moreno, J. 2019b. Evaluation of Atmospheric Correction Algorithms over Spanish Inland Waters for Sentinel-2 Multi Spectral Imagery Data. Remote Sensing, 11, 1469. https://doi.org/10.3390/rs11121469
Shoaf, W.T., Lium, B.W. 1976. Improved extraction of chlorophyll a and b from algae using dimethyl sulphoxide. Limnol. Oceanogr., 21, 926-928. https://doi.org/10.4319/lo.1976.21.6.0926
Soria, X., Vicente, E., Durán, C., Soria, J.M., Peña, R. 2017. Uso de imágenes Landsat-8 para la estimación de la profundidad del disco de Secchi en aguas continentales. XVII Congreso de la Asociación Española de Teledetección. pp. 293-296. Murcia 3-7 octubre 2017.
Sòria-Perpinyà, X., Urrego, P., Pereira-Sandoval, M., Ruiz-Verdú, A., Peña, R., Soria, J.M., Delegido, J., Vicente, E., Moreno, J. 2019. Monitoring the ecological state of a hypertrophic lake (Albufera of València, Spain) using multitemporal Sentinel-2 images. Limnetica, 38(1), 457-469. https://doi.org/10.23818/limn.38.26
Steinmetz, F., Deschamps, P.Y., Ramon, D. 2011. Atmospheric correction in presence of sun glint: Application to MERIS. Optics Express, 19(10), 9783-800. https://doi.org/10.1364/OE.19.009783
Toming, K., Kutser, T., Laas, A., Sepp, M., Paavel, B., Nõges, T. 2016. First experiences in mapping lake water quality parameters with Sentinel-2 MSI imagery. Remote Sens., 8, 640. https://doi.org/10.3390/rs8080640
Tyler, A.N., Hunter, P.D., Spyrakos, E., Groom, S., Constantinescu, A.M., Kitchen, J. 2016. Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters. Sci. Total Environ., 572, 1307-1321. https://doi.org/10.1016/j.scitotenv.2016.01.020
Zhao, D., Cai, Y., Jiang, H., Xu, D., Zhang, W., An, S. 2011. Estimation of water clarity in Taihu Lake and surrounding rivers using Landsat imagery. Advances in Water Resources, 34(2), 165-173. https://doi.org/10.1016/j.advwatres.2010.08.010
Downloads
Published
Issue
Section
License
This journal is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
