Chlorophyll-a concentration estimation using three difference bio-optical algorithms, including a correction for the low-concentration range: the case of the Yiam reservoir, Korea

Abstract

ABSTRACTBio-optical algorithms have been applied to monitor water quality in surface water systems. Empirical algorithms have been applied to estimate the chlorophyll-a (chl-a) concentrations. However, the performance of each algorithm severely degrades at concentrations notably lower than 10 mg m−3. This could be attributed to the chl-a specific absorption coefficient that became less consistent at low chl-a concentrations. Nonetheless, no effort has been made in previous studies to correct existing algorithms. In this study, we propose a correction approach to improve their performance for chl-a estimation in Yiam reservoir, Korea. Estimated chl-a concentrations of the algorithms improved after applying the correction process proposed in this study; Nash–Sutcliffe efficiency values increased from 53% to 65% and root mean square error decreased from 39% to 43%, respectively. Further research is needed to verify the correction approaches for different years or study sites.