Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters

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Abstract

The high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.

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Watanabe, F., Alcântara, E., Imai, N., Rodrigues, T., & Bernardo, N. (2018). Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters. Remote Sensing, 10(2). https://doi.org/10.3390/rs10020227

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