Lagoons and coastal ecosystems in tropical regions are increasingly subjected to strong anthropogenic pressures, making water quality monitoring particularly crucial. Colored Dissolved Organic Matter (CDOM) is a key indicator of water quality due to its influence on optical properties and biogeochemical processes. This study aims to assess the contribution of remote sensing to the estimation of CDOM in the Adjin Lagoon, located in southeastern C？te d’Ivoire. Multispectral Sentinel-2 images covering the period 2018-2024, processed using the Case 2 Regional CoastColour (C2RCC) algorithm adapted for optically complex waters, were combined with in situ measurements collected in June 2024 to analyze the spatio-temporal variability of CDOM and its relationship with chlorophyll-a. The results reveal marked seasonal variations in CDOM and chlorophyll concentrations. Chlorophyll peaks observed in January, May, and October are associated with phytoplankton blooms driven by favorable light and nutrient conditions, whereas CDOM concentrations are mainly controlled by terrestrial inputs, with maximum values recorded during the rainy season, particularly in August (0.86 m？1). The correlation between CDOM and chlorophyll is weak and positive (r = 0.27), indicating partially independent dynamics. Validation using in situ data shows excellent agreement with satellite-derived estimates, with a negligible difference of approximately 0.02 m？1, confirming the reliability of remote sensing for CDOM assessment in tropical lagoon environments. This study highlights the potential of remote sensing for monitoring lagoon water quality and provides useful insights for the sustainable management of coastal ecosystems in C？te d’Ivoire.
References
[1]
Davies-Vollum, K.S., Koomson, D. and Raha, D. (2024) Coastal Lagoons of West Africa: A Scoping Study of Environmental Status and Management Challenges. AnthropoceneCoasts, 7, Article No. 7. https://doi.org/10.1007/s44218-024-00039-9
[2]
Siegel, D.A., Maritorena, S., Nelson, N.B., Hansell, D.A. and Lorenzi‐Kayser, M. (2002) Global Distribution and Dynamics of Colored Dissolved and Detrital Organic Materials. JournalofGeophysicalResearch: Oceans, 107, 21-1-21-14. https://doi.org/10.1029/2001jc000965
[3]
Gholizadeh, M., Melesse, A. and Reddi, L. (2016) A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques. Sensors, 16, Article 1298. https://doi.org/10.3390/s16081298
[4]
Chaouachi, B., Ben Hassine, O.K. and Lemoalle, J. (2001) Variations des teneurs en chlorophylle a et en sels nutritifs dans la lagune de l’Ichkeul. Bulletin de l’Institut National des Sciences et Technologies de la Mer (INSTM), 28, 105-111.
[5]
Babin, M., Stramski, D., Ferrari, G.M., Claustre, H., Bricaud, A., Obolensky, G., et al. (2003) Variations in the Light Absorption Coefficients of Phytoplankton, Nonalgal Particles, and Dissolved Organic Matter in Coastal Waters around Europe. JournalofGeophysicalResearch: Oceans, 108, Article 3211. https://doi.org/10.1029/2001jc000882
[6]
Asmala, E., Massicotte, P. and Carstensen, J. (2021) Identification of Dissolved Organic Matter Size Components in Freshwater and Marine Environments. LimnologyandOceanography, 66, 1381-1393. https://doi.org/10.1002/lno.11692
[7]
Corredor, J., Morell, J., López, J., Armstrong, R., Dieppa, A., Cabanillas, C., et al. (2003) Remote Continental Forcing of Phytoplankton Biogeochemistry: Observations across the “Caribbean-Atlantic Front”. Geophysical Research Letters, 30, 1-4. https://doi.org/10.1029/2003gl018193
[8]
Bergamaschi, B.A., Tsamakis, E., Keil, R.G., Eglinton, T.I., Montlu？on, D.B. and Hedges, J.I. (1997) The Effect of Grain Size and Surface Area on Organic Matter, Lignin and Carbohydrate Concentration, and Molecular Compositions in Peru Margin Sediments. GeochimicaetCosmochimicaActa, 61, 1247-1260. https://doi.org/10.1016/s0016-7037(96)00394-8
[9]
Stedmon, C.A. and Markager, S. (2005) Tracing the Production and Degradation of Autochthonous Fractions of Dissolved Organic Matter by Fluorescence Analysis. LimnologyandOceanography, 50, 1415-1426. https://doi.org/10.4319/lo.2005.50.5.1415
[10]
Pahlevan, N., Sarkar, S., Franz, B.A., Balasubramanian, S.V. and He, J. (2017) Sentinel-2 Multispectral Instrument (MSI) Data Processing for Aquatic Science Applications: Demonstrations and Validations. RemoteSensingofEnvironment, 201, 47-56. https://doi.org/10.1016/j.rse.2017.08.033
