Development and Calibration of Sentinel-2 Spectral Indices for Water Quality Parameter Estimation in Alqueva Reservoir, Southern Portugal.
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| Title: | Development and Calibration of Sentinel-2 Spectral Indices for Water Quality Parameter Estimation in Alqueva Reservoir, Southern Portugal. |
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| Authors: | Neves, Vítor H.1,2,3 (AUTHOR), Sánchez-Pérez, Lisette2,4 (AUTHOR), Antunes, Sara C.2,3 (AUTHOR), Pace, Giorgio4,5,6 (AUTHOR), Sòria-Perpinyà, Xavier4,5 (AUTHOR), Delegido, Jesús4,6 (AUTHOR) jesus.delegido@uv.es |
| Source: | Remote Sensing. Feb2026, Vol. 18 Issue 3, p469. 20p. |
| Subjects: | Total suspended solids, Chlorophyll, Remote sensing, Atmospheric effects on remote sensing, Water depth, Artificial satellites, Water quality |
| Geographic Terms: | Portugal |
| Abstract: | Highlights: Developed localized empirical models for Chl-a, TSS, and SDD using Sentinel-2. Nine years of in situ data enhanced model calibration and validation. C2RCC-COMPLEX achieved superior performance in Alqueva Reservoir. Satellite-derived maps reveal drought and post-winter water quality trends. Monitoring water quality in large reservoirs is essential yet challenging, particularly in regions with limited in situ coverage. This study presents a robust methodology for integrating a decade-long in situ dataset (2014–2022) with Sentinel-2 multispectral imagery to develop and validate localized algorithms for water quality assessment in the Alqueva Reservoir, the largest artificial lake in Western Europe. Three atmospheric correction algorithms (C2RCC, C2X, C2X-COMPLEX) were evaluated, with C2RCC-COMPLEX identified as the most suitable for capturing the reservoir's optical complexity, yielding the lowest RMSE for Total Suspended Solids (TSS: 2.4 g/m3) and Secchi Disk Depth (SDD: 0.85 m). Empirical models using Sentinel-2 bands 7 (783 nm), 6 (740 nm), and 8A (865 nm) demonstrated strong correlations (R2 ≈ 0.69–0.71) for Chlorophyll-a (Chl-a) with a range data of 0.1–65 mg/m3, TSS with a range data of 2–13.1 g/m3, and SDD with a range data of 0.4–8 m. Spatially explicit water quality maps illustrate the models' capacity to capture distinct gradients and seasonal dynamics, e.g., elevated Chl-a (>30 mg/m3) and TSS (>7.5 g/m3) in the reservoir's nutrient-rich northern section during drought (August 2022), and more uniform conditions following winter recovery (March 2019), with SDD exceeding 2 m near the dam. These results underscore the utility of Sentinel-2 for resolving spatial and temporal variability in optically complex inland waters. The proposed workflow offers a transferable, cost-effective framework for monitoring eutrophication risks and sediment dynamics under increasing hydrological variability. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: Developed localized empirical models for Chl-a, TSS, and SDD using Sentinel-2. Nine years of in situ data enhanced model calibration and validation. C2RCC-COMPLEX achieved superior performance in Alqueva Reservoir. Satellite-derived maps reveal drought and post-winter water quality trends. Monitoring water quality in large reservoirs is essential yet challenging, particularly in regions with limited in situ coverage. This study presents a robust methodology for integrating a decade-long in situ dataset (2014–2022) with Sentinel-2 multispectral imagery to develop and validate localized algorithms for water quality assessment in the Alqueva Reservoir, the largest artificial lake in Western Europe. Three atmospheric correction algorithms (C2RCC, C2X, C2X-COMPLEX) were evaluated, with C2RCC-COMPLEX identified as the most suitable for capturing the reservoir's optical complexity, yielding the lowest RMSE for Total Suspended Solids (TSS: 2.4 g/m3) and Secchi Disk Depth (SDD: 0.85 m). Empirical models using Sentinel-2 bands 7 (783 nm), 6 (740 nm), and 8A (865 nm) demonstrated strong correlations (R2 ≈ 0.69–0.71) for Chlorophyll-a (Chl-a) with a range data of 0.1–65 mg/m3, TSS with a range data of 2–13.1 g/m3, and SDD with a range data of 0.4–8 m. Spatially explicit water quality maps illustrate the models' capacity to capture distinct gradients and seasonal dynamics, e.g., elevated Chl-a (>30 mg/m3) and TSS (>7.5 g/m3) in the reservoir's nutrient-rich northern section during drought (August 2022), and more uniform conditions following winter recovery (March 2019), with SDD exceeding 2 m near the dam. These results underscore the utility of Sentinel-2 for resolving spatial and temporal variability in optically complex inland waters. The proposed workflow offers a transferable, cost-effective framework for monitoring eutrophication risks and sediment dynamics under increasing hydrological variability. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18030469 |
