Modelgebaseerde analyse van de rivierwaterkwaliteit onder huidige en toekomstige klimaatcondities

Clean water is an increasing concern to our society because poor water quality both directly and indirectly causes many water-related diseases. It is necessary to assess river water quality under current and future climate conditions in any river basin management and planning. Physically-based mathematical water quality models are known as potentially effective tools to simulate the temporal and spatial variations of water quality variables along rivers. At the boundaries of river systems, these models require information that is typically estimated from limited data. Each model relies on specific sets of assumptions and equations to simulate the physico-biochemical processes, which affect its simulation results. Additionally, their long computing time poses many difficulties for applications that involve a large number of model iterations such as real-time control, optimization and uncertainty analysis. Within this context, this research has following 5 main objectives and steps: (i) developing and testing detailed physically-based river water quality models applying state-of-the-art simulation software, (ii) assessing the influence of model structure uncertainty on river water quality, (iii) developing and testing a surrogate, simplified conceptual model identified and calibrated to simulation results with the detailed models, (iv) analyzing the impacts of input estimations and other main types of uncertainties on model simulation results and (v) evaluating river water quality under current and future climate conditions based on model simulations. The latter two tasks become practically feasible thanks to the conceptual model developed. By means of these tasks, the applicability of the conceptual model will also be demonstrated. Two popular commercial software packages for river modelling, namely MIKE11 and InfoWorks RS, are selected as the physically-based reference models. The river water quality assessment is performed for the Molse Nete catchment in Belgium.Acknowledgements i Abstract iii Beknopte samenvatting vii Acronyms xi Table of contents xv List of Figures xix List of Tables xxiii 1 Introduction 1 1.1 Problem statement 1 1.2 State of the art 3 1.3 Objectives 12 1.4 Overview of chapters 13 2 Molse Neet catchment 17 2.1 General characteristics 17 2.2 Pollutant sources 20 3 Existing models and methods 23 3.1 Hydrological models 23 3.1.1 Probability Distribution Model 24 3.1.2 Generalized Hydrological Model 26 3.2 Hydrodynamic models 28 3.3 River water quality models 30 3.3.1 Advection and diffusion 31 3.3.2 Physico-biochemical transformation processes 32 3.4 Model inputs 42 3.4.1 Model input data 42 3.4.2 Model input estimation 43 3.5 Climate change tool and scenarios 48 3.6 POT extraction method 50 4 Development of a COnceptual RIver WAter Quality model (CORIWAQ) with flexible model structure 53 4.1 Introduction 53 4.2 Processes 54 4.2.1 Advection and diffusion 54 4.2.2 Physico-biochemical transformations 55 4.3 Calibration parameters 57 4.4 Implementation for MIKE 11 and InfoWorks RS 58 4.4.1 MIKE 11 58 4.4.2 InfoWorks RS 59 4.5 Performance evaluation 61 4.6 Results and discussions 62 4.6.1 Calibration results 63 4.6.2 Performance evaluation results 70 4.7 Conclusions 79 5 Seasonal variation of river bed roughness impacts on water level 83 5.1 Methodology 83 5.2 Results and discussions 87 5.2.1 MIKE 11 calibration roughness coefficient 88 5.2.2 InfoWorks RS time-varying roughness coefficient 93 5.3 Conclusions 96 6 Influence of model structure uncertainty on river water quality assessment 99 6.1 Methodology 99 6.2 Results and discussions 101 6.2.1 Graphical sensitivity analysis 102 6.2.2 Local sensitivity analysis 104 6.3 Conclusions 112 7 CORIWAQ input uncertainty analysis 115 7.1 Methodology 115 7.2 Results and discussions 120 7.2.1 Gap filling and stochastic modelling of input uncertainties 120 7.2.2 Sensitivity indices 128 7.2.3 Convergence 132 7.2.4 Contribution of input uncertainty to total model residuals 132 7.3 Conclusions 133 8 Climate change impacts on river water quality 137 8.1 Methodology 137 8.1.1 Propagation of climate change to river water quality input 137 8.1.2 Impacts of climate change on extreme flows and determinant concentrations 139 8.1.3 Evaluation of the input factors controlling the climatic changes 140 8.1.4 Sensitivity of the hydrological model calibration to the climate change impact assessment 141 8.2 Results and discussions 142 8.2.1 Propagation of climate change to river water quality input 143 8.2.2 Impacts of climate change on extreme flows and determinant concentrations 148 8.2.3 Evaluation of the input factors controlling the climatic changes 151 8.2.4 Sensitivity of the hydrological model calibration to the climate change impact assessment 152 8.3 Conclusions 155 9 Conclusions and perspectives 157 9.1 Contributions of the doctoral research 158 9.1.1 Quantitatively evaluate and compare the reference river WQ models and increase the insights in the river WQ drivers 158 9.1.2 Develop a river water quality conceptual model based on InfoWorks RS 160 9.1.3 Uncertainty analysis and assessment of climate change impacts on river water quality 160 9.2 Future research 162 9.2.1 Development of CORIWAQ 163 9.2.2 Improvement of the results 165 Bibliography 167 Curriculum Vitae 183 Publications by the author 185nrpages: 186status: publishe