Estimating Water Transparency Using Sentinel-2 Images in a Shallow Hypertrophic Lagoon (The Albufera of Valencia, Spain)

Water transparency, a crucial environmental indicator, was assessed during fieldwork via Secchi disk depth (ZSD) measurements. Three optical models (R490/R560, R490/R705, and R560/R705) were explored to establish a robust algorithm for ZSD estimation. Through extensive field sampling and laboratory analyses, weekly data spanning 2018 to 2023 were collected, including water transparency, temperature, conductivity, and chlorophyll-a concentration. Remote sensing imagery from the Sentinel-2 mission was employed, and the images were processed using SNAP 9.0 software. The R560/R705 index, suitable for turbid lakes, proved to be the most optimal, with an R2 of 0.6149 in calibration and 0.916 during validation. In contrast, the R490/R705 and R490/R560 indices obtained R2 values of 0.2805 and 0.0043 respectively. The algorithm calibrated in the present study improved the pre-existing algorithm, with an NRMSE of 17.8% versus 20.7% of the previous one for estimating the Secchi disk depth in the Albufera de Valencia, highlighting the importance of developing specific algorithms for specific water body characteristics. The study contributes to improved water quality assessment and resource management, underscoring the value of remote sensing in environmental research.

Automated summary

Water transparency, a crucial environmental indicator, was assessed using the Secchi disk depth (ZSD) and three optical models were explored to establish a robust algorithm for ZSD estimation. The R560/R705 index was found to be the most optimal for turbid lakes. Remote sensing imagery from the Sentinel-2 mission was employed to validate the algorithm. The study contributes to improved water quality assessment and resource management.