The Use of Sentinel-3/OLCI for Monitoring the Water Quality and Optical Water Types in the Largest Portuguese Reservoir

• Autor(a) principal: Rodrigues, Gonçalo
• Data de Publicação: 2022
• Outros Autores: Potes, Miguel, Penha, Alexandra, Costa, Maria João, Morais, Maria Manuela
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/32124; https://doi.org/Rodrigues, G.; Potes, M.; Penha, A.M.; Costa, M.J.; Morais, M.M. The Use of Sentinel-3/OLCI for Monitoring the Water Quality and Optical Water Types in the Largest Portuguese Reservoir. Remote Sens. 2022, 14, 2172. https://doi.org/10.3390/rs14092172; https://doi.org/10.3390/rs14092172
• topic: Alqueva reservoir; microalgae blooms

The Alqueva reservoir is essential for water supply in the Alentejo region (south of Portugal). Satellite data are essential to overcome the temporal and spatial limitations of in situ measurements, ensuring continuous and global water quality monitoring. Data between 2017 and 2020, obtained from OLCI (Ocean and Land Color Instrument) aboard Sentinel-3, were explored. Two different methods were used to assess the water quality in the reservoir: K-means to group reflectance spectra into different optical water types (OWT), and empirical algorithms to estimate water quality parameters. Spatial (in five different areas in the reservoir) and temporal (monthly) variations of OWT and water quality parameters were analyzed, namely, Secchi depth, water turbidity, chlorophyll a, and phycocyanin concentrations. One cluster has been identified representing the typical spectra of the presence of microalgae in the reservoir, mainly between July and October and more intense in the northern region of the Alqueva reservoir. An OWT type representing the area of the reservoir with the highest transparency and lowest chlorophyll a concentration was defined. The methodology proposed is suitable to continuously monitor the water quality of Alqueva reservoir, constituting a useful contribution to a potential early warning system for identification of critical areas corresponding to cyanobacterial algae blooms.