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Quantum yield of fluorescence (ϕ F ) is key to interpret remote measurements of sun-induced fluorescence (SIF), and whether the SIF signal is governed by photochemical quenching (PQ) or non-photochemical quenching (NPQ). Disentangling PQ from NPQ allows using SIF estimates in various applications in aquatic optics. However, obtaining ϕ F is challenging due to its high temporal and physiological variability, and the combined measurements needed to enclose all relevant optical paths. In inland waters, this type of data is scarce and information on diurnal and seasonal ϕ F dynamics are almost unknown. Using an autonomous hyperspectral Thetis profiler in Lake Geneva, we demonstrate how to estimate ϕ F using an ensemble of in-situ measurements acquired between 2018 to 2021. We use vertical and temporal changes in retrieved ϕ F to determine NPQ and PQ conditions. We observed NPQ in 36% of the total daytime profiles used in the ϕ F analysis. While downwelling irradiance is a significant contributor to ϕ F , its role cannot be easily interpreted. Other factors such as phytoplankton photoregulation and assemblages also likely play significant roles in quenching mechanisms. We conclude that an adapted approach exploiting in-situ data is suitable to determine diurnal and seasonal NPQ occurrence, and helps develop future remote sensing algorithms.

Water-leaving radiance is subject to depth variability of the water constituents. The optical penetration depth is strongly dependent on the wavelength λ, which allows to retrieve a non-uniform vertical profile of an optically-active constituent CTSM(z) from remote-sensing reflectance Rrs(λ,Cz). We define the apparent particle concentration CTSM,app(λ) of a vertically homogeneous water column whose Rrs(λ,Cconst) matches Rrs(λ,Cz). Subsequently, we define a vertically-weighted averaged particle concentration CTSM,ave(λ), only dependent on CTSM(z), and retrieve CTSM(z) by minimizing the error between CTSM,app(λ) and CTSM,ave(λ) with genetic algorithms. We conclude that the retrieval is excellent if the sub-surface maximum lays close to the surface or the background concentration of CTSM(z) is low. Conversely, results worsen for opposite conditions, due to insufficient signal strength from superimposed sub-surface maxima.