Algal blooms plague freshwaters across the globe, as increased nutrient loads lead to eutrophication of inland waters and the presence of potentially harmful cyanobacteria. In this context, remote sensing is a valuable approach to monitor water quality over broad temporal and spatial scales. However, there remain several challenges to the accurate retrieval of water quality parameters, and the research in this thesis investigates these in an optically complex lake (Lake Balaton, Hungary). This study found that bulk and specific inherent optical properties [(S)IOPs] showed significant spatial variability over the trophic gradient in Lake Balaton. The relationships between (S)IOPs and biogeochemical parameters differed from those reported in ocean and coastal waters due to the high proportion of particulate inorganic matter (PIM). Furthermore, wind-driven resuspension of mineral sediments attributed a high proportion of total attenuation to particulate scattering and increased the mean refractive index (n̅p) of the particle assemblage. Phytoplankton pigment concentrations [chlorophyll-a (Chl-a) and phycocyanin (PC)] were also accurately retrieved from a times series of satellite data over Lake Balaton using semi-analytical algorithms. Conincident (S)IOP data allowed for investigation of the errors within these algorithms, indicating overestimation of phytoplankton absorption [aph(665)] and underestimation of the Chl-a specific absorption coefficient [a*ph(665)]. Finally, Chl-a concentrations were accurately retrieved in a multiscale remote sensing study using the Normalized Difference Chlorophyll Index (NDCI), indicating hyperspectral data is not necessary to retrieve accurate pigment concentrations but does capture the subtle heterogeneity of phytoplankton spatial distribution. The results of this thesis provide a positive outlook for the future of inland water remote sensing, particularly in light of contemporary satellite instruments with continued or improved radiometric, spectral, spatial and temporal coverage. Furthermore, the value of coincident (S)IOP data is highlighted and contributes towards the improvement of remote sensing pigment retrieval in optically complex waters.

<p>This thesis presents predictive models for important variables concerning eutrophication effects in lakes. The keystone is a dynamic phosphorus model based on ordinary differential equations. By calculating mass fluxes of phosphorus into, within and out from a lake, the concentrations of different forms of phosphorus in different compartments of the lake are estimated.</p><p>The dynamic phosphorus model is critically tested and several improvements are presented, including two new compartments for colloidal phosphorus, a sub-model for suspended particulate matter (SPM) and new algorithms for lake outflow, water mixing, diffusion, water content and organic content of accumulation sediments are implemented. Predictions with the new version show good agreement against empirical data in five tested lakes.</p><p>The sub-model for SPM uses the same driving variables as the basic phosphorus model, so the inclusion of this model as a sub-model does not require any additional variables. The model for SPM may also be used as a separate model giving monthly predictions of suspended particulate matter in two water compartments and one compartment with SPM available for resuspension in ET-sediments.</p><p>Empirical data from Lake Erken (Sweden) and Lake Balaton (Hungary) are used to evaluate the variability in settling velocity of SPM. It is found that the variability is substantial and may be accounted for by using a dimensionless moderator for SPM concentration. Empirical data from accumulation area sediments in Lake Erken are used to develop a model for the dynamics of phosphorus sedimentation, burial and diffusion in the sediments. The model is shown to provide reasonable monthly predictions of four functional forms of phosphorus at different sediment depths.</p><p>Simulations with the lake phosphorus model using two different climate scenarios indicate that lakes may respond very differently to climate change depending on their physical character. Lake Erken, with a water retention time of 7 years, appears to be much more sensitive than two basins of Lake Mälaren (Sweden) with substantially shorter retention times. The implication would be that in eutrophic lakes with long water retention times, eutrophication problems may become serious if the future becomes warmer. This will be important in contexts of lake management when remedial measures against lake eutrophication have to be taken.</p>

This thesis presents predictive models for important variables concerning eutrophication effects in lakes. The keystone is a dynamic phosphorus model based on ordinary differential equations. By calculating mass fluxes of phosphorus into, within and out from a lake, the concentrations of different forms of phosphorus in different compartments of the lake are estimated. The dynamic phosphorus model is critically tested and several improvements are presented, including two new compartments for colloidal phosphorus, a sub-model for suspended particulate matter (SPM) and new algorithms for lake outflow, water mixing, diffusion, water content and organic content of accumulation sediments are implemented. Predictions with the new version show good agreement against empirical data in five tested lakes. The sub-model for SPM uses the same driving variables as the basic phosphorus model, so the inclusion of this model as a sub-model does not require any additional variables. The model for SPM may also be used as a separate model giving monthly predictions of suspended particulate matter in two water compartments and one compartment with SPM available for resuspension in ET-sediments. Empirical data from Lake Erken (Sweden) and Lake Balaton (Hungary) are used to evaluate the variability in settling velocity of SPM. It is found that the variability is substantial and may be accounted for by using a dimensionless moderator for SPM concentration. Empirical data from accumulation area sediments in Lake Erken are used to develop a model for the dynamics of phosphorus sedimentation, burial and diffusion in the sediments. The model is shown to provide reasonable monthly predictions of four functional forms of phosphorus at different sediment depths. Simulations with the lake phosphorus model using two different climate scenarios indicate that lakes may respond very differently to climate change depending on their physical character. Lake Erken, with a water retention time of 7 years, appears to be much more sensitive than two basins of Lake Mälaren (Sweden) with substantially shorter retention times. The implication would be that in eutrophic lakes with long water retention times, eutrophication problems may become serious if the future becomes warmer. This will be important in contexts of lake management when remedial measures against lake eutrophication have to be taken.