Evaluating River Water Quality Modelling Uncertainties at Multiple Time and Space Scales
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Department of Civil and Structural Engineering Evaluating River Water Quality Modelling Uncertainties at Multiple Time and Space Scales By Vivian Veronica Camacho Suarez Submitted in part fulfilment of the Degree of Doctor of Philosophy in the Faculty of Engineering, University of Sheffield. March 2020 To my son Rafael, Eres el motorcito de mi vida Abstract Maintaining healthy river ecosystems is crucial for sustaining human needs and biodiversity. Therefore, accurately assessing the ecological status of river systems and their response to short and long-term pollution events is paramount. Water quality modelling is a useful tool for gaining a better understanding of the river system and for simulating conditions that may not be obtained by field monitoring. Environmental models can be highly unreliable due to our limited knowledge of environmental systems, the difficulty of mathematically and physically representing these systems, and limitations to the data used to develop, calibrate and run these models. The extensive range of physical, biochemical and ecological processes within river systems is represented by a wide variety of models: from simpler one-dimensional advection dispersion equation (1D ADE) models to complex eutrophication models. Gaining an understanding of uncertainties within catchment water quality models across different spatial and temporal scales for the evaluation and regulation of water compliance is still required. Thus, this thesis work 1) evaluates the impact of parameter uncertainty from the longitudinal dispersion coefficient on the one-dimensional advection-dispersion model and water quality compliance at the reach scale and sub-hourly scale, 2) evaluates the impact of input data uncertainty and the representation of ecological processes on an integrated catchment water quality model, and 3) evaluates the impact of one-dimensional model structures on water quality regulation. Findings from this thesis stress the importance of longitudinal mixing specifically in the sub daily time scales and in-between 10s of meters to 100s of meters. After the sub daily time scale, other biological and ecological processes become more important than longitudinal mixing for representing the seasonal dynamics of dissolved oxygen (DO). The thorough representation of the dominant ecological processes assists in obtaining accurate seasonal patterns even under input data variability. Furthermore, the use of incorrect model structures for water quality evaluation and regulation leads to considerable sources of uncertainty when applying duration over threshold regulation within the first 100s of meters and sub hourly time scale. Keywords: Integrated water quality modelling, uncertainty analysis, longitudinal dispersion, water quality processes, ecological modelling I Acknowledgement My deepest gratitude goes to my Supervisors Dr James Shucksmith and Dr Alma Schellart. I am forever thankful not only for their continuous academic guidance, but also, for providing a supportive work environment throughout my PhD. I would also like to thank Dr Will Shepherd, Dr Simon Tait, Dr Wernher Brevis, for their continuous academic and administrative support. Thank you very much to those who helped me during my secondments: Dr Hans Korving, Dr Jeroen Langeveld, Bob Brederveld, Marieke Fennema, Antonio Moreno, Dr Lutz Breuer, Dr Philipp Kraft and Carla Camargos. My thanks to: my parents Humberto and Ilse, who have gone to great lengths to always support my personal and professional development, to my colleagues and friends Ambuj, Mano and Ana Paula for always being there, to my family and friends from all over the world. Thank you very much to the examiners Dr Andrea Marion and Dr Ann Van Griensven for their insightful comments. Last but not least, a million thanks to my beloved husband, Dr Gareth Bird for all the patience, support and love throughout this process. This PhD research was conducted as part of the Marie Curie ITN – Quantifying Uncertainty in Integrated Catchment Studies (QUICS) project. This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 607000. II Table of Contents Abstract ............................................................................................................ I Acknowledgement ........................................................................................... II 1. Introduction .............................................................................................. 1 1.1 Background and motivation......................................................................................... 1 1.2 Contributions and thesis structure .............................................................................. 4 2. Literature review ....................................................................................... 5 2.1 River water quality processes ...................................................................................... 5 2.1.1 Physical Processes ................................................................................. 5 2.1.2 Biochemical reactions ........................................................................... 8 2.2 River Water Quality Modelling .................................................................................. 10 2.2.1 Space and time scales in water quality modelling ............................... 11 2.2.2 Physical pollutant behaviour ............................................................... 11 2.2.3 Biochemical models and ecological modelling .................................... 18 2.2.4 Water quality modelling software ....................................................... 19 2.3 Water Quality Regulation .......................................................................................... 21 2.4 Sources of Uncertainty .............................................................................................. 22 2.4.1 Structural uncertainty ......................................................................... 23 2.4.2 Parameter uncertainty ........................................................................ 24 2.4.1 Input Data Uncertainty ........................................................................ 26 2.5 Concluding Remarks .................................................................................................. 27 3. Thesis Aim and Objectives ....................................................................... 30 3.1 Specific Objectives ..................................................................................................... 30 4. Quantifying the Impact of Uncertainty within the Longitudinal Dispersion Coefficient on Concentration Dynamics and Regulatory Compliance in Rivers . 31 4.1 Introduction ............................................................................................................... 31 4.2 Evaluation of methodologies to estimate dispersion coefficient in rivers ................. 35 4.3 Methodology for Uncertainty Propagation ............................................................... 41 4.3.1 Uncertainty Quantification Results ..................................................... 45 4.4 Impact of dispersion coefficient uncertainty on concentration-duration threshold based standards ................................................................................................................... 48 4.4.1 Duration over Threshold Analysis Results ........................................... 51 4.5 Discussion .................................................................................................................. 55 4.6 Conclusion ................................................................................................................. 57 References ............................................................................................................................ 59 5. Evaluation of a coupled hydrodynamic-closed ecological cycle approach for modelling dissolved oxygen in surface waters ................................................ 64 5.1 Introduction ............................................................................................................... 64 5.2 Methodology ............................................................................................................. 68 5.2.1 Study Area Description ........................................................................ 68 5.2.2 Rainfall-Runoff Modelling .................................................................... 69 III 5.2.3 Hydrodynamic Modelling .................................................................... 70 5.2.4 Water Quality Modelling ..................................................................... 71 5.3 Results ....................................................................................................................... 76 5.3.1 Evaluation of combined modelling approach ...................................... 76 5.3.2 Input Boundaries Sensitivity Analysis on Dissolved Oxygen Concentrations 78 5.3.3 Dominant Processes in Oxygen Production and Consumption ........... 81 5.4 Discussion .................................................................................................................. 85 5.5 Conclusion ................................................................................................................. 88 References ...........................................................................................................................