A remote sensing algorithmic framework for characterizing chromophoric dissolved organic matter in lagoon-estuarine...

Area of Science:

• Environmental Science
• Remote Sensing
• Oceanography

Background:

• Chromophoric Dissolved Organic Matter (CDOM) is crucial for coastal biogeochemistry but its variability in dynamic estuarine systems is understudied.
• Estuarine systems exhibit significant seasonal and spatial variability, complicating CDOM monitoring.

Purpose of the Study:

• To develop and validate a remote sensing algorithmic framework for estimating CDOM optical properties in variable coastal lagoon-estuarine systems.
• To characterize CDOM variability and sources using a novel metric, the Normalized Spectral Slope Ratio (NSSR).

Main Methods:

• Utilized Sentinel-2 derived spectral remote sensing reflectance data.
• Integrated in situ spectral CDOM absorption data from Chilika Lagoon (2018-2019).
• Developed an optical framework to retrieve CDOM absorption coefficients, spectral slopes, and the NSSR.

Main Results:

• The framework successfully retrieved comprehensive CDOM optical properties.
• Observed a 36% increase in CDOM absorption post-Super Cyclone Amphan, linked to extreme precipitation and freshwater discharge.
• A 33% decrease in NSSR indicated an influx of terrestrial CDOM, altering the lagoon's biogeochemistry.

Conclusions:

• The developed framework effectively monitors CDOM dynamics and characterizes sources in coastal lagoons.
• Estuarine ecosystems are highly sensitive to extreme meteorological events, leading to significant biogeochemical shifts.
• The study highlights the utility of remote sensing for understanding estuarine responses to climate-related disturbances.