Bio-geo-optical properties and remote sensing of CDOM in optically complex inland waters

Abstract

A substantial number of studies demonstrate the sensitivity of lakes to climate change and show that physical, chemical, and biological lake properties respond rapidly to climate-related changes. The indicators include variables such as temperature, dissolved organic carbon (DOC) or plankton composition. DOC is also known to play a primary role in protecting freshwater organisms from exposure to UV radiation and a big fraction of it is typically represented by dissolved organic matter (DOM). Moreover, the conservative properties between the coloured fraction of DOM (CDOM) and DOC, and the possibility of remotely estimating CDOM from space given its optical properties, makes it often used as a proxy for DOC. The development and validation of remote-sensing-based approaches for the retrieval of CDOM concentrations requires a comprehensive understanding of the sources and magnitude of variability in the optical properties of dissolved material within lakes. The present study aims to contribute with the knowledge of remote sensing of CDOM in inland water bodies with the specific objectives of characterising the link between CDOM absorption and DOC content in inland waters, investigating how changes in CDOM absorption can be used to infer information on its concentration, sources and decomposition and finally, to present an extensive CDOM algorithm validation exercise. The results of this Thesis indicate that the relationship between CDOM and DOC can vary remarkably. Strongest relationships have been found in waters with low anthropogenic influence, whereas waters more influenced by human activity present less clear linkages between the two parameters. As aromaticity increases in more productive waters we can then infer low CDOM to DOC relationships to them. 8 Remote-sensing models for DOC estimation based on the relationship between CDOM and DOC should therefore consider local variability and optical complexity, considering at least groups of water types according to their absorption features. In-lake spatial and seasonal variability in the quantity and quality of CDOM should also be taken into account. Photobleaching has been found to be a major factor controlling the in-lake transformation and degradation of CDOM, and a key process influencing the spatial structure CDOM throughout the system. These results also provide an insight on the potential contribution of wetlands to DOM and CDOM in lakes, not only in terms of the concentration of CDOM, but also in terms of its seasonality. All this leads to understand that CDOM content in complex inland waters usually present a wide range given their surrounding terrestrial characteristics and seasonal differences. The complexity of inland water bodies is currently a challenge to current remote sensing algorithms used to estimate parameters such as CDOM absorption (aCDOM). The accuracy of remote sensing-based retrievals of aCDOM at 440 nm (aCDOM (440)) can improve, mostly by targeting specific OWTs in algorithm development. For hypereutrophic waters with cyanobacterial blooms and abundant vegetation Blue-Green ratio based algorithms. For moderately productive waters with cyanobacteria presence, a double Blue-Green ratio based empirical algorithm is recommended. A double Blue-Green ratio and a Red-Green ratio for application in clear waters, turbid waters with high organic content, high productive waters with high cyanobacteria abundance and high reflectance at red/near-infrared spectral region. For waters high in CDOM, cyanobacteria presence and high absorption by NAP (Non-Algal Particles), a Green-Red ratio based algorithm. And finally, a semi analytic algorithm worked best for waters with high Rrs at short wavelengths.