This study presents an systematic approach to water quality
assessment, hybrid modelling and decision support for
eutrophication management in deep reservoirs. It is found that
during the summer monsoon the catchment runoff into the Yongdam
reservoir induces a trandsfer of pollutants from a middle
stratified layer to the surface layer. Although the transport
mechanism limits nutrient accumulation on the bottom of the
reservoir, it also offers an opportunity for on-going algae
production in the surface water. Physically based modelling is used
to understand the process of micro-scale turbulent mixing and its
impact on the nutrient uptake by algae. Further, a data-driven
model using clustering and partial least squares regression which
uses results from a physically based model of the reservoir
successfully predicts Chlorophyll-a concentrations.
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