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Sun-induced fluorescence (SIF) emission can be used as a proxy for chlorophyll-a concentration (chl a) and as an indicator of phytoplankton physiological status. However, retrieving and interpreting the SIF signal is challenging due to physiological factors, optical properties of the atmosphere and the water body, instrumental effects, and assumptions inherent to retrieval schemes. Due to the complexity of factors determining SIF occurrence, lack of measurement protocols and few studies on retrieval methods, its exploitation remains limited, especially in lakes.
To address some of these challenges, we assess SIF estimate sensitivity to quantum yield of fluorescence (φF). Often assumed constant, φF exhibits a diel cycle related to light stress, which impacts the interpretation of fluorescence signals. Determining φF allows us to estimate and predict SIF diurnal variability, evaluate how this variability impacts chl a estimates, and gain insight into photosynthetic activity of the phytoplankton community. We address the dynamics of φF by using high-frequency optical measurements in Lake Geneva. From this dataset, we are able to calculate φF, infer the strata where non-photochemical quenching occurs and how this affects the SIF signal detected above water. We compare chl a estimates obtained from fluorescence and absorption measurements to assess at which conditions fluorescence-derived estimates are underestimated, and at which conditions saturation irradiance for photosynthesis is reached.
The increasing availability of hyperspectral satellite data could improve SIF retrieval since algorithms utilizing contiguous bands can be implemented. Subsequently, an improved retrieval scheme will allow for better φF estimation. An upcoming satellite mission from ESA, the Fluorescence Explorer,designed to measure terrestrial SIF globally, can potentially be used in aquatic environments.
Through this study, we demonstrate how hyperspectral measurements improve SIF signal interpretation by understanding φF dynamics. Despite using in-situ data, our findings can also contribute to the evaluation of SIF estimates from hyperspectral satellite data.
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