Remote sensing estimation of the concentration and sources of coloured dissolved organic matter based on MODIS: A case study of Erhai lake

Abstract

The use of satellite remote sensing to estimate coloured dissolved organic matter (CDOM) and identify its potential sources is important for monitoring lake water quality and implementing management strategies. In this study, taking Erhai Lake as an example and based on MODIS/Aqua satellite images and in-situ measured data, we used empirical and semi-empirical methods to develop algorithms for CDOM and the fluorescence index (FI370) from remote sensing reflectance (Rrs(λ)). The temporal and spatial distributions of the CDOM concentration and FI370 in Erhai Lake during 2013–2019 were retrieved. The results show the following. (1) The band ratio (Rrs(469)+Rrs(645))/Rrs(555) model could estimate the CDOM absorption coefficient at 412 nm (aCDOM(412)) (R2=0.507), and it was relatively stable. Using the band ratio Rrs(645)/Rrs(469) combined with the chlorophyll-a (Chl-a) APProach by ELimination (APPEL) model, a semi-empirical inversion model of FI370 performed with satisfactory accuracy (R2=0.550) and was more accurate than the empirical algorithm (R2=0.505). (2) During the period of 2013–2019, the CDOM concentration in Erhai Lake generally decreased from the northern to the central to the southern parts of the lake, and the CDOM concentration was higher in summer and autumn than in spring and winter. FI370 was higher in the northern and western coastal waters and lower in the central, southern and eastern parts of the lake. FI370 in autumn and winter was higher than that in spring and summer. CDOM was affected by both terrestrial and internal sources, and their relative contributions were not the same in different seasons. (3) For different Chl-a concentrations, different CDOM concentration models had better retrieval effects, i.e., Rrs(645))/Rrs(555) and (Rrs(469)+Rrs(645))/Rrs(555) had the best performance when Chl-a10 μg/L, respectively. The inversion models established in this study offer improved quantifications of the CDOM concentration and the FI370 in Erhai Lake, providing important support for monitoring water quality and implementing efficient management strategies.

Keywords

• CDOM
• Fluorescence index
• Empirical algorithm
• Semi-empirical algorithm
• Erhai Lake