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Remote Sensing of Chlorophyll a and Temperature to Support Algal Bloom Monitoring in Blue Mesa Reservoir, Colorado.

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Title: Remote Sensing of Chlorophyll a and Temperature to Support Algal Bloom Monitoring in Blue Mesa Reservoir, Colorado.
Authors: King, Tyler V.1 (AUTHOR) tvking@usgs.gov, Bean, Robert A.2 (AUTHOR), Walton‐Day, Katherine2 (AUTHOR), Mast, M. Alisa2 (AUTHOR), Gohring, Evan J.2 (AUTHOR), Gidley, Rachel G.2 (AUTHOR), Day, Natalie K.2 (AUTHOR), Gibney, Nicole D.3 (AUTHOR)
Source: Journal of the American Water Resources Association. Aug2025, Vol. 61 Issue 4, p1-19. 19p.
Subjects: Chlorophyll, Water temperature, Remote sensing, Machine learning, Reservoir ecology, Remote-sensing images
Geographic Terms: Colorado
Abstract: We present methods to reconstruct historical chlorophyll a and surface water temperatures from satellite‐based remote sensing products for Blue Mesa Reservoir, Colorado, to support algal bloom monitoring. A machine learning model was trained to construct chlorophyll a concentrations from Sentinel‐2 satellite imagery and in situ measurements of chlorophyll a concentrations (out of bag RMSE = 1.9 μg/L, R2 = 0.63) and reconstruct summertime chlorophyll a concentrations over the entire reservoir from 2016 through 2023. Concurrently, we developed an approach to retrieve remotely sensed water temperatures from the Landsat collection 2 provisional surface temperature product (MAE = 0.6°C) and reconstructed summertime surface water temperature records from 2000 through 2023. Finally, we demonstrate how the reconstructed chlorophyll a and temperature records can yield insight on reservoir dynamics. The chlorophyll a records indicate that algal blooms have a consistent spatial pattern across multiple years, initiating in the eastern end of the reservoir and spreading to the west over time. Water temperatures increased at a linearized rate of 0.3°C per decade from 2000 through 2023 and were inversely proportional to reservoir water surface elevation. Finally, mean summer remotely sensed chlorophyll a concentration had a moderately positive correlation with mean summer remotely sensed water temperature. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:We present methods to reconstruct historical chlorophyll a and surface water temperatures from satellite‐based remote sensing products for Blue Mesa Reservoir, Colorado, to support algal bloom monitoring. A machine learning model was trained to construct chlorophyll a concentrations from Sentinel‐2 satellite imagery and in situ measurements of chlorophyll a concentrations (out of bag RMSE = 1.9 μg/L, R2 = 0.63) and reconstruct summertime chlorophyll a concentrations over the entire reservoir from 2016 through 2023. Concurrently, we developed an approach to retrieve remotely sensed water temperatures from the Landsat collection 2 provisional surface temperature product (MAE = 0.6°C) and reconstructed summertime surface water temperature records from 2000 through 2023. Finally, we demonstrate how the reconstructed chlorophyll a and temperature records can yield insight on reservoir dynamics. The chlorophyll a records indicate that algal blooms have a consistent spatial pattern across multiple years, initiating in the eastern end of the reservoir and spreading to the west over time. Water temperatures increased at a linearized rate of 0.3°C per decade from 2000 through 2023 and were inversely proportional to reservoir water surface elevation. Finally, mean summer remotely sensed chlorophyll a concentration had a moderately positive correlation with mean summer remotely sensed water temperature. [ABSTRACT FROM AUTHOR]
ISSN:1093474X
DOI:10.1111/1752-1688.70038