A transferable bio-optical model for quantification of inland water caynobacterial pigments

Abstract

Cyanobacterial blooms are currently one of the most important issues faced by environmental agencies, water authorities and public health organizations. Remote sensing provides an advanced approach to monitor cyanobacteria by detecting and quantifying chlorophyll-a (Chl-a) and phycocaynin (PC). In this thesis, an analytical bio-optical model, more typically applied to ocean waters, was modified to accommodate the complexity of inland waters. The newly developed models work well to estimate inherent optical properties, including absorption and backscattering coefficients, in eight different study sites distributed around the globe. Based on derived absorption coefficients, Chl-a and PC concentrations were accurately retrieved for data sets collected annually from 2006 to 2010, and the estimation accuracy exceeded that of currently used algorithms. An important advantage of the model is that low concentrations of Chl-a and PC can be predicted more accurately, enabling early warning of cyanobacterial blooms. In addition, the results also indicated good spatial and temporal transferability of the algorithms, since no specific calibration procedures were required for data sets collected in a different sites and seasons. The compatibility of the newly developed algorithm with MERIS spectra provides the possibility for routine surveillance of cyanobacterial growth in inland waters.