Eco-Hydraulic Modelling of Eutrophication for Reservoir Management

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 transfer 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.

INTRODUCTION Man-Made Reservoir Characteristics of Reservoir Management Issues Framework of Reservoir Management Challenges Study Site Study Aim, Objective and Hypothesis Layout of the Thesis

RESERVOIR ECOSYSTEMS Physical Structure Abiotic and Biotic Structure Eutrophication

PHYSICAL PROCESSES OF RESERVOIRS Mixing Processes in a Reservoir Scales of Motions Navier-Stokes Equation Reynolds Time-Averaged Mean Flow and Transport Equations Turbulent Viscosity

PHYSICALLY BASED NUMERICAL MODELLING Equations for Physical Process Solution of Equations Methods of Time Variable Solutions Lake/Reservoir Modelling Instantiating Models

DATA-DRIVEN MODELLING Introduction Machine Learning Methods Application of DDM to Eco-Environment

CASE STUDY: DATA ACQUISITION AND ASSESSMENT Research Site Material and Methods Water Quality Assessment Algal Growth Potential Test Conclusion

CASE STUDY: CONSTRUCTION OF MODELS Outline of Case Study Eco-Hydrodynamic Modelling Data-Driven Modelling Hybrid Model Decision Support
CONCLUSIONS AND RECOMMENDATIONS Conclusions Recommendations for Future Research

AppendicesReferences