Abstract

With the rapid development of the economy in recent years, massive algal (blue-green algae in particular) blooms have often observed in Chinese eutrophic lakes. The concentration of the cyanobacterial pigment phycocyanin (PC), an accessory pigment unique to freshwater blue-green algae, is often used as a quantitative indicator of blue-green algae in eutrophic inland waters. The purpose of this study was to evaluate the semi-analytic PC retrieval algorithm proposed by Simis et al. and to explore the potential to improve this PC algorithm so that it is more suitable for eutrophic lakes, such as Taihu Lake. In this paper, we recalculated the correction coefficients γ and δ to calculate the absorptions of chlorophyll-a at 665nm and the absorptions of phycocyanin at 620nm in terms of in situ measurements and observed that the values of these coefficients differed from the values used by Simis et al. and Randolph et al. The two coefficients are site dependent due to the different bio-optical properties of lakes. We also observed that the specific PC absorption at 620nm apc*(620) decreases exponentially with an increase in PC concentrations. Therefore, a non-linear power–function of apc*(620), instead of a constant value of apc*(620) as used by Simis et al., was proposed for our improved PC retrieval algorithm in Taihu Lake, yielding a squared correlation coefficient (R2) of 0.55 and a root mean square error (RMSE) of 58.89μg/L. Compared with the original PC retrieval algorithm by Simis et al., the improved retrieval algorithm has generally superior performance. In evaluating the limitation of the PC retrieval algorithms, we observed that the ratio of the total suspended solids to phycocyanin can be used as a primary measure for retrieval performance. Validation in Dianchi Lake and an error analysis proved that the improved PC algorithm has a better universality and is more suitable for eutrophic lakes with higher PC concentrations.

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