Limnetica 39

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Monitoring water transparency of a hypertrophic lake (the Albufera of València) using multitemporal sentinel-2 satellite images

Xavier Sòria-Perpinyà, Esther Patricia Urrego, Marcela Pereira-Sandoval, Antonio Ruiz-Verdú, Juan M. Soria, Jesús Delegido, Eduardo Vicente and José Moreno
2020
39
1
373-386
DOI: 
10.23818/limn.39.24

The Albufera of València has been a hypertrophic lake since the 1970s. Extensive efforts to revert the system to a clear water state, such as wastewater treatment and green filters construction, have not yielded the desired results; Albufera is still qualified as “bad” according to the Spanish Water Framework Directive implementation. Currently, the lake requires constant monitoring, and water transparency, measured by Secchi disc depth (SDD), is a key parameter for evaluating water quality. Remote sensing offers substantial advantages over traditional monitoring methods such as SDD because it allows the quality of the surface waters to be continuously monitored. This work aimed to calibrate and validate an algorithm for SDD retrieval from Sentinel-2 (S2) (A and B) satellites with multispectral instrument (MSI) sensors (13 bands) from 404 nm to 2200 nm, spatial resolutions of 10, 20 and 60 m and a temporal frequency of 5 days (revisit at the equator)-values previously unattainable from open access images. The study was carried out with images from 2016 and 2017; only 40 of the 81 images of the Albufera captured by the S2 satellites could be used, mainly due to the presence of clouds. Once the images were downloaded, they were processed using SNAP 5 software. Images were then atmospherically corrected using the Sen2Cor tool, and the lake’s SDD was estimated using the developed algorithm. The estimated SDD data were validated against field samples; a total of 20 sampling campaigns were carried out to measure the SDD, and 114 samples were taken. Chlorophyll a concentrations from each sample point were also measured to allow for better data interpretation; hydrological, precipitation and wind data were also collected. The algorithm model’s calibration showed its robustness with an R2 of 0.673 using 79 samples. Validation of the algorithm’s accuracy using 35 samples produced a low root mean squared error of 0.06 m, indicating a perfect fit between the predicted and observed data. Interpretation of thematic maps showed that SDD temporal variations follow an annual bimodal pattern where the increase of SDD is determined by a significant increase in water renewal. The retrieval algorithm to estimate the SDD from S2 satellite images is accurate and appropriate to use within a protocol whose main purpose is to monitor the ecological status of the Albufera of València.

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