Obtaining estimation algorithms for water quality variables in the Jaguari-Jacarei Reservoir using Sentinel-2 images

Author(s)

Camargo, Zahia Catalina Merchan ; Soria-Perpinya, Xavier ; Pompeo, Marcelo ; Moschini-Carlos, Viviane ; Sendra, Maria Dolores

• Document type: Journal article
• Source: REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT; v. 36, p. 15-pg., 2024-09-12.

Abstract

Satellite images are essential tools for monitoring aquatic ecosystems and assessing water quality, as they enable the measurement of parameters such as chlorophyll-a (Chl-a) concentration, phycocyanin (PC), and cyanobacteria density. These indicators aid in evaluating eutrophication processes and detecting cyanobacteria in aquatic ecosystems. This study utilized field data and images captured by the Sentinel-2 sensor from 2015 to 2022 to investigate the Jaguari-Jacare & iacute; reservoirs (JAG-JAC). Two atmospheric corrections from the Case 2 Regional Coast Color (C2RCC) processor, namely C2X and C2XC, were applied, and algorithms were developed to estimate the parameters using both in situ data measurements and reflectance data extracted from the images. For Chl-a concentration, the dataset was divided into two blocks: one for model calibration (70% of the data) and the other for validation (30% of the data). As for PC, the entire dataset was utilized to calibrate the model, and validation was conducted through cross-validation using the Automated Radiative Transfer Model Operator (ARTMO) software. Cyanobacteria density was indirectly estimated from the Chl-a concentrations determined in the field samples, as these variables exhibited a strong correlation, also validating the model previously proposed for the Cantareira system for estimating cyanobacteria density from Chl-a data. Additionally, the automatic chlorophyll-a products (con_chla) derived from the C2X and C2XC processors were validated. The findings revealed that the C2X processor exhibited the greatest potential for estimating water quality parameters. It was observed that the most effective algorithms were derived using the R705/R665 band ratio for Chl-a and the R705/R490 ratio for PC. For cyanobacteria density, the optimal algorithm was established based on the relationship between cyanobacteria density and Chl-a using the data obtained in this study. (AU)

• FAPESP's process: 21/11283-0 - The problem of cyanobacteria in the Jaguari and Jacarei reservoirs (Cantareira System, SP, Brazil)
• Grantee: Viviane Moschini Carlos
• Support Opportunities: Regular Research Grants
• FAPESP's process: 20/11759-1 - A look at the quality of reservoir waters from 786 km of altitude: Sentinel 2 images
• Grantee: Marcelo Luiz Martins Pompêo
• Support Opportunities: Research Grants - Research Partnership for Technological Innovation - PITE
• FAPESP's process: 21/10637-2 - Multiple views on the sediment and water quality in the Barra Bonita Reservoir (São Paulo State): the weight of evidence
• Grantee: Marcelo Luiz Martins Pompêo
• Support Opportunities: Regular Research Grants