Monitoring turbidity in a highly variable estuary using Sentinel 2-A/B for ecosystem management applications

The Guadalquivir estuary (southern Spain) occasionally experiences medium to high turbidity, reaching above 700 Formazin Nephelometric Unit (FNU) during extreme events, thus negatively influencing its nursery function and the estuarine community structure. Although several turbidity algorithms are available to monitor water quality, they are mainly developed for mapping turbidity ranges of 0-100 FNU. Thus, their use in a highly turbid region may not give accurate results, which is crucial for estuarine ecosystem management. To fill this gap, we developed a multi-conditional turbidity algorithm that can retrieve turbidity from 0 to 600 FNU using the Sentinel-2 red and red-edge bands. Four major steps are implemented: atmospheric and sun glint correction of the Level-1C Sentinel-2 data, spectral analysis for different water turbidity levels, regression modelling between in situ turbidity and remote sensing reflectance (Rrs) for algorithm development, and validation of the best-suited model. When turbidity was < 85 FNU, the Rrs increased firstly in the red wavelength (665 nm), but it saturated beyond a certain turbidity threshold (> 250 FNU). At this time, Rrs started to increase in the red-edge wavelength (704 nm). Considering this spectral behavior, our algorithm is designed to automatically select the most sensitive turbidity vs. Rrs, thus avoiding the saturation effects of the red bands at high turbidity levels. The model showed good agreement between the satellite derived turbidity and the in situ measurements with a correlation coefficient of 0.97, RMSE of 15.93 FNU, and a bias of 13.34 FNU. Turbidity maps derived using this algorithm can be used for routine turbidity monitoring and assessment of potential anthropogenic actions (e.g., dredging activities), thus helping the decision-makers and relevant stakeholders to protect coastal resources and human health.

This research was partly funded by grants RTI2018-098784-JI00 (Sen2Coast Project) and IJC2019-039382-I (Juan de la Cierva-Incorporación) from the MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. The research was also supported by the Andalusia Regional Government (PY20-00244), National Project OAPN (Observatorio TIAMAT, REF: 2715/2021) and the European Union-NextGenerationEU Agreement between MITECO, CSIC, AZTI, SOCIB, and the universities of Vigo and Cadiz, to promote research and generate scientific knowledge in the field of marine sustainability. Estuary monitoring and in situ data were provided by IFAPA-Junta de Andalucıá projects GUADALQUIVIR_LTER-PP.FEM. PPA201700.5 and GUADACONECT-PR.FEM.PPA201900.005, 75% co-funded by the European Maritime and Fisheries Fund (EMFF) 2014-2020. The three field campaigns were supported by the Spanish Ministerio de Ciencia e Innovación, the Agencia Estatal de Investigación, and the European Regional Development Fund in the frame of the Sen2Coast Project. MC is a PhD student at the University of Cadiz who is currently employed by the company Quasar Science Resources S.L. Consequently, MC is 50% funded by Quasar and 50% by the Industrial Doctorate Program of the Spanish Ministerio de Ciencia e Innovación (ref. DIN2020-010979/AEI/10.13039/501100011033). This work is part of MC’s PhD within the SIMBAD project (ref. QSR-ESABIC-2018-001, incubated by ESA-BIC Madrid region) and the University of Cadiz, and was partly supported by a grant funded by the European Commission under the Erasmus Mundus Joint Master Degree Programme in Water and Coastal Management (WACOMA; Project num. 586596-EPP-1-2017-1-IT-EPPKA1-JMD-MOB) and represents a contribution to CSIC Thematic Interdisciplinary Platform PTI TELEDETECT and PTI Oceans+.

The open access fee was co-funded by the QUALIFICA Project (QUAL21-0019, Junta de Andalucía).

Peer reviewed