Jung Eco-hydraulic Modelling of Eutrophication for Reservoir Management

Erscheinungsjahr 2011
ISBN: 978-0-203-09325-2
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 264 Seiten

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.

Autoren/Hrsg.

Jung, Nahm-chung

Fachgebiete

• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Wasserversorgung, Wasseraufbereitung
• Geowissenschaften Geographie | Raumplanung Geographie: Sachbuch, Reise
• Naturwissenschaften Biowissenschaften Biowissenschaften Ökologie
• Naturwissenschaften Biowissenschaften Biowissenschaften Biowissenschaften, Biologie: Sachbuch, Naturführer

Inhaltsverzeichnis

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

Appendices
References