Augmenting estuary monitoring from space: New retrievals of fine-scale CDOM quality and DOC exchange

• New MSI and OLI algorithms are developed to retrieve CDOM, spectral slope, and DOC. • Random forest regression performed best, with R rs and month as input features. • Algorithms applied show strong urban estuary seasonality in CDOM amount and quality. • Post-storm and low-tide imagery highlight terrigenous and wastewater CDOM inputs. Fueled by both terrestrial and marine inputs, estuaries worldwide are important biogeochemical reactors, strongly susceptible to natural and anthropogenic, episodic, or compounding disturbances. Satellite sensors provide a unique vantage point to capture estuarine processes at scales not feasible with in situ sampling alone; yet, remote sensing retrievals of estuarine biogeochemical dynamics remain challenging. Here, we developed new algorithms for high spatial resolution satellite retrievals of colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC)—two key indicators of estuarine water quality and biogeochemical state. CDOM algorithms were optimized for Long Island Sound—one of the world’s most heavily urbanized estuaries—and included retrievals of CDOM absorption at 300 nm (a CDOM (300)), a proxy for CDOM amount, as well as absorption spectral slope in the 275–295 nm range (S 275-295 ), a proxy for CDOM quality. Algorithms were specifically designed for Sentinel-2A/2B MSI and Landsat-8/9 OLI, a constellation of high spatial resolution sensors that provides coverage of the most dynamic zones for estuary exchange. MSI and OLI a CDOM (300) and S 275-295 were most successfully retrieved using machine learning (ML) random forest regression, with the input features of remote sensing reflectance bands, band ratios, and month of acquisition. Satellite retrieval of DOC concentrations relied on a tight, widely applicable relationship between a CDOM (300) and S 275-295 . Timeseries generated for Long Island Sound, and its most impaired water quality region in the Western Narrows, revealed strong CDOM spatiotemporal dynamics associated with seasonal freshwater discharge, tidal wetland carbon export, recurring wastewater pollution, and episodic extreme events. Results highlight the value of these new ecosystem-scale observations for enhanced, sustainable estuarine management.

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Publication Details

Journal
International Journal of Applied Earth Observation and Geoinformation
Published
2025-02-20
DOI
https://doi.org/10.1016/j.jag.2025.104389
Citations
2
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
3.59

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article

Augmenting estuary monitoring from space: New retrievals of fine-scale CDOM quality and DOC exchange

Maria Tzortziou, Alana Menendez
2 citations
International Journal of Applied Earth Observation and Geoinformation
Marine and coastal ecosystems
3.59
article

Augmenting estuary monitoring from space: New retrievals of fine-scale CDOM quality and DOC exchange

Maria Tzortziou, Alana Menendez
article en
2 citations

Abstract

• New MSI and OLI algorithms are developed to retrieve CDOM, spectral slope, and DOC. • Random forest regression performed best, with R rs and month as input features. • Algorithms applied show strong urban estuary seasonality in CDOM amount and quality. • Post-storm and low-tide imagery highlight terrigenous and wastewater CDOM inputs. Fueled by both terrestrial and marine inputs, estuaries worldwide are important biogeochemical reactors, strongly susceptible to natural and anthropogenic, episodic, or compounding disturbances. Satellite sensors provide a unique vantage point to capture estuarine processes at scales not feasible with in situ sampling alone; yet, remote sensing retrievals of estuarine biogeochemical dynamics remain challenging. Here, we developed new algorithms for high spatial resolution satellite retrievals of colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC)—two key indicators of estuarine water quality and biogeochemical state. CDOM algorithms were optimized for Long Island Sound—one of the world’s most heavily urbanized estuaries—and included retrievals of CDOM absorption at 300 nm (a CDOM (300)), a proxy for CDOM amount, as well as absorption spectral slope in the 275–295 nm range (S 275-295 ), a proxy for CDOM quality. Algorithms were specifically designed for Sentinel-2A/2B MSI and Landsat-8/9 OLI, a constellation of high spatial resolution sensors that provides coverage of the most dynamic zones for estuary exchange. MSI and OLI a CDOM (300) and S 275-295 were most successfully retrieved using machine learning (ML) random forest regression, with the input features of remote sensing reflectance bands, band ratios, and month of acquisition. Satellite retrieval of DOC concentrations relied on a tight, widely applicable relationship between a CDOM (300) and S 275-295 . Timeseries generated for Long Island Sound, and its most impaired water quality region in the Western Narrows, revealed strong CDOM spatiotemporal dynamics associated with seasonal freshwater discharge, tidal wetland carbon export, recurring wastewater pollution, and episodic extreme events. Results highlight the value of these new ecosystem-scale observations for enhanced, sustainable estuarine management.

International Journal of Applied Earth Observation and GeoinformationVol. 137
The Graduate Center, CUNY (US), City University of New York (US)
National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, New York Sea Grant, State University of New York
Life below water, Climate action
Openalex Percentile: Top 10%
Marine and coastal ecosystems
3.59
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