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This study presents a systematic approach to water quality assessment, hybrid modelling, and decision support for eutrophication management in deep reservoirs. The author uses physically based modelling to understand the process of micro-scale turbulent mixing and its impact on the nutrient uptake by algae. He also delineates how 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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