Remote Sensing of Water Quality in Aquatic Systems

Remote sensing techniques have transformed water quality monitoring by enabling spatially continuous and frequent observations of physical, chemical and biological parameters across lakes, rivers, reservoirs and coastal zones. Multispectral and hyperspectral satellite sensors measure reflected radiance in discrete and contiguous bands, which can be inverted to estimate concentrations of chlorophyll-a, suspended particulate matter, coloured dissolved organic matter and other constituents. Advances in atmospheric correction and sun-glint removal have improved data quality in optically complex (“Case II”) waters, while machine-learning algorithms and uncertainty quantification frameworks now provide robust retrievals with confidence bounds. Long-term records from platforms such as MODIS, Landsat, Sentinel-2 and ocean-colour sensors have elucidated global patterns of eutrophication, sediment transport and harmful algal blooms. Integration of satellite products with in situ measurements and biogeochemical models supports ecosystem assessment, early warning for cyanobacterial blooms, and adaptive management of water resources. These capabilities inform policy decisions, guide conservation efforts and enhance our understanding of aquatic systems under changing climatic and anthropogenic pressures.

Research from Nature Portfolio

Recent studies have leveraged decade-long satellite archives to quantify phytoplankton biomass and surface bloom dynamics in large freshwater systems. One foundational work developed an empirical model for estimating chlorophyll-a concentrations in a eutrophic lake using a calibrated ocean-colour sensor, yielding a continuous time series from 2003 to 2013. Analysis revealed spatial heterogeneity in bloom intensity and demonstrated that air temperature and phosphorus inputs are primary controls on annual algal variability, while wind speed and atmospheric pressure modulate surface bloom formation. This research underpins strategies for monitoring nutrient-driven algal dynamics and informs adaptive management of inland waters.

Remote Sensing of Water Quality in Aquatic Systems publication trend

The graph below shows the total number of articles in remote sensing of water quality in aquatic systems across all publications each year (not limited to Nature Index journals).

Technical terms

Chlorophyll-a: A photosynthetic pigment found in phytoplankton used as an indicator of algal biomass and primary productivity.

Remote Sensing Reflectance (Rrs): The ratio of water-leaving radiance to downwelling irradiance, used to retrieve water-quality constituents from satellite imagery.

Trophic State Index (TSI): A numerical scale that classifies water bodies based on nutrient levels and algal biomass, indicating oligotrophic to hypereutrophic conditions.

Cyanobacterial Surface Bloom: A dense aggregation of cyanobacteria at the water surface, often visible via distinct spectral signatures in satellite data.

Atmospheric Correction: The process of removing atmospheric effects, such as scattering and absorption, from satellite signals to accurately derive water-leaving reflectance.

References

1. Per-Pixel Uncertainty Quantification and Reporting for Satellite-Derived Chlorophyll-a Estimates via Mixture Density Networks. IEEE Transactions on Geoscience and Remote Sensing (2023).
2. Remote sensing of water colour in small southeastern Australian waterbodies. Journal of Environmental Management (2024).
3. A dataset of trophic state index for nation-scale lakes in China from 40-year Landsat observations. Scientific Data (2024).
4. Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands.. Optics Express (2010).
5. Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths. Remote Sensing (2009).
6. Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data?successes and challenges. Environmental Research Letters (2009).
7. Satellite Ocean Colour: Current Status and Future Perspective. Frontiers in Marine Science (2019).
8. Long-term MODIS observations of cyanobacterial dynamics in Lake Taihu: Responses to nutrient enrichment and meteorological factors. Scientific Reports (2017).