Abstract
Receiving water quality simulation in highly urbanised areas requires the integration of several processes occurring at different space-time scales. These integrated catchment models deliver results with a significant uncertainty level associated. Still, uncertainty analysis is seldom applied in practice and the relative contribution of the individual model elements is poorly understood. Often the available methods are applied to relatively small systems or individual sub-systems, due to limitations in organisational and computational resources. Consequently this work presents an uncertainty propagation and decomposition scheme of an integrated water quality modelling study for the evaluation of dissolved oxygen dynamics in a large-scale urbanised river catchment in the Netherlands. Forward propagation of the measured and elicited uncertainty input-parametric distributions was proposed and contrasted with monitoring data series. Prior ranges for river water quality-quantity parameters lead to high uncertainty in dissolved oxygen predictions, thus the need for formal calibration to adapt to the local dynamics is highlighted. After inferring the river process parameters with system measurements of flow and dissolved oxygen, combined sewer overflow pollution loads became the dominant uncertainty source along with rainfall variability. As a result, insights gained in this paper can help in planning and directing further monitoring and modelling efforts in the system. When comparing these modelling results to existing national guidelines it is shown that the commonly used concentration-duration-frequency tables should not be the only metric used to select mitigation alternatives and may need to be adapted in order to cope with uncertainties.
Highlights
Meeting the established environmental regulations (e.g. The Water Framework Directive, 2000/60/EC 200) of the European Union) is still a challenge in many densely urbanised catchments, as it often requires the implementation of intensive investment and regulatory plans
The proposed model structure captures the flow dynamics in the river submodel, which are mainly driven by the baseflow inputs from the rural hydrology and the discharges from the WWTP (c.a. 40e50% of baseflow during summer) reasonably well (Nash-Sutcliffe efficiency of 0.82e0.86 at the inferred and validation series respectively)
This study presents an uncertainty analysis scheme of a largescale integrated catchment model
Summary
Meeting the established environmental regulations (e.g. The Water Framework Directive, 2000/60/EC 200) of the European Union) is still a challenge in many densely urbanised catchments, as it often requires the implementation of intensive investment and regulatory plans (i.e. infrastructure construction, control systems or user limitations). Integrated Catchment Modelling (ICM) has become an essential tool in the water quality management process over the last decades (Andres-Domenech et al, 2010; Langeveld et al, 2013b; Willems and Berlamont, 2002). ICMs are, by definition, abstractions of highly complex water systems, usually constituted by the joint modelling of two or more subsystems of the urban water system (Keupers and Willems, 2017; Rauch et al, 2002). This often involves the joint simulation of sewer hydrodynamics, wastewater treatment processes, rural hydrology and river physical-biochemical dynamics (Benedetti et al, 2013a). The stepwise process of abstraction from reality to model representation with its necessary simplifications and idealisations of the real systems includes the unavoidable occurrence of uncertainties (Muschalla et al, 2009)
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